Journal articles: 'Game; Memory; Algorithms'

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Bosansky, B., C. Kiekintveld, V. Lisy, and M. Pechoucek. "An Exact Double-Oracle Algorithm for Zero-Sum Extensive-Form Games with Imperfect Information." Journal of Artificial Intelligence Research 51 (December 30, 2014): 829–66. http://dx.doi.org/10.1613/jair.4477.

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Developing scalable solution algorithms is one of the central problems in computational game theory. We present an iterative algorithm for computing an exact Nash equilibrium for two-player zero-sum extensive-form games with imperfect information. Our approach combines two key elements: (1) the compact sequence-form representation of extensive-form games and (2) the algorithmic framework of double-oracle methods. The main idea of our algorithm is to restrict the game by allowing the players to play only selected sequences of available actions. After solving the restricted game, new sequences are added by finding best responses to the current solution using fast algorithms. We experimentally evaluate our algorithm on a set of games inspired by patrolling scenarios, board, and card games. The results show significant runtime improvements in games admitting an equilibrium with small support, and substantial improvement in memory use even on games with large support. The improvement in memory use is particularly important because it allows our algorithm to solve much larger game instances than existing linear programming methods. Our main contributions include (1) a generic sequence-form double-oracle algorithm for solving zero-sum extensive-form games; (2) fast methods for maintaining a valid restricted game model when adding new sequences; (3) a search algorithm and pruning methods for computing best-response sequences; (4) theoretical guarantees about the convergence of the algorithm to a Nash equilibrium; (5) experimental analysis of our algorithm on several games, including an approximate version of the algorithm.

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Bulitko, V., Y. Björnsson, and R. Lawrence. "Case-Based Subgoaling in Real-Time Heuristic Search for Video Game Pathfinding." Journal of Artificial Intelligence Research 39 (September 29, 2010): 269–300. http://dx.doi.org/10.1613/jair.3076.

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Real-time heuristic search algorithms satisfy a constant bound on the amount of planning per action, independent of problem size. As a result, they scale up well as problems become larger. This property would make them well suited for video games where Artificial Intelligence controlled agents must react quickly to user commands and to other agents' actions. On the downside, real-time search algorithms employ learning methods that frequently lead to poor solution quality and cause the agent to appear irrational by re-visiting the same problem states repeatedly. The situation changed recently with a new algorithm, D LRTA*, which attempted to eliminate learning by automatically selecting subgoals. D LRTA* is well poised for video games, except it has a complex and memory-demanding pre-computation phase during which it builds a database of subgoals. In this paper, we propose a simpler and more memory-efficient way of pre-computing subgoals thereby eliminating the main obstacle to applying state-of-the-art real-time search methods in video games. The new algorithm solves a number of randomly chosen problems off-line, compresses the solutions into a series of subgoals and stores them in a database. When presented with a novel problem on-line, it queries the database for the most similar previously solved case and uses its subgoals to solve the problem. In the domain of pathfinding on four large video game maps, the new algorithm delivers solutions eight times better while using 57 times less memory and requiring 14% less pre-computation time.

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Hasanudin, Muhaimin, Turki Salim, and Arkan Nur Robby. "RANCANG BANGUN APLIKASI GAME PUZZLE BERBASIS ANDROID MENGGUNAKAN ALGORITMA DECISION TREE." Journal CERITA 3, no. 2 (August 1, 2017): 171–80. http://dx.doi.org/10.33050/cerita.v3i2.654.

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The development of games today is very rapid and has become part of the lifestyle. A puzzle game is an application that can be used to hone thinking and memory skills where users have to find a way out and collect special items that have been provided at every level of the game . The player must collect all the white orb in each level to get the key to move to the next level but the player will be confronted by the constraints on how to find the key and retrieve it . The game is designed using decision tree and game algorithms designed using Game Maker Studio that is applied to Android devices.

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Pratiwi, Heny, Ita Arfyanti, and M. Za’iem Sururi. "Membangun Game Edutainment “Pengenalan Komputer” Menggunakan Shuffle Random (SR) Dan Finite State Machine (FSM) Untuk Anak Tunagrahita Ringan." J-SAKTI (Jurnal Sains Komputer dan Informatika) 3, no. 2 (September 13, 2019): 307. http://dx.doi.org/10.30645/j-sakti.v3i2.149.

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Research to build an Edutainment Game "Introduction to Computers" for mild retarded children is a study designed for teachers to deliver material to special school students (SLB) with special needs such as children with visual impairment, hearing impairment, mental retardation, intellectual disability, autism and blindness. . In this game the player will be presented with a variety of learning menus about "Computer Devices" and a game menu consisting of a guessing picture quiz to train memory, then there are typing games and labyrinth games to develop motor movements and increase students' responses and interests. Shuffle and Finite State Machine randomization algorithms will be applied in this study, with the aim of arranging the image position to be randomized in the learning menu and typing games as well as randomizing the position of the main characters and enemies in the labyrinth game made in three levels. This is done to improve students' learning and curiosity. The technology applied in this research is intelligent agent (intelligent system) which has a game agent character that will accompany children to learn and play.

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Yun, Heuijee, and Daejin Park. "Virtualization of Self-Driving Algorithms by Interoperating Embedded Controllers on a Game Engine for a Digital Twining Autonomous Vehicle." Electronics 10, no. 17 (August 30, 2021): 2102. http://dx.doi.org/10.3390/electronics10172102.

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Computer simulation based on digital twin is an essential process when designing self-driving cars. However, designing a simulation program that is exactly equivalent to real phenomena can be arduous and cost-ineffective because too many things must be implemented. In this paper, we propose the method using the online game GTA5 (Grand Theft Auto5), as a groundwork for autonomous vehicle simulation. As GTA5 has a variety of well-implemented objects, people, and roads, it can be considered a suitable tool for simulation. By using OpenCV (Open source computer vision) to capture the GTA5 game screen and analyzing images with YOLO (You Only Look Once) and TensorFlow based on Python, we can build a quite accurate object recognition system. This can lead to writing of algorithms for object avoidance and lane recognition. Once these algorithms have been completed, vehicles in GTA5 can be controlled through codes composed of the basic functions of autonomous driving, such as collision avoidance and lane-departure prevention. In addition, the algorithm tested with GTA5 has been implemented with a programmable RC car (Radio control car), DonkeyCar, to increase reliability. By testing those algorithms, we can ensure that the algorithms can be conducted in real time and they cost low power and low memory size. Therefore, we have found a way to approach digital twin technology one step more easily.

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Kitakoshi, Daisuke, Ryo Hanada, Keitarou Iwata, and Masato Suzuki. "Cognitive Training System for Dementia Prevention Using Memory Game Based on the Concept of Human-Agent Interaction." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 6 (November 20, 2015): 727–37. http://dx.doi.org/10.20965/jaciii.2015.p0727.

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This paper describes a cognitive training system to help older adults to stimulate and maintain their cognitive functions based on a memory game implemented on a tablet device. In this system, a software agent incorporated into the tablet device performs dialogic interactions with users based on the concept of human-agent interaction (HAI) to (i) reduce their psychological resistance to the system; (ii) maintain their interest in the game; and (iii) improve the motivation for users to play the game long term. The difficulty level of the game is adjusted through reinforcement learning algorithms depending on the proficiency of respective users. Several experiments and subjective evaluations by older adults were conducted to evaluate the basic characteristics of the system, and to investigate the impact of the system on cognitive function. The ultimate goal of the proposed system is to establish an environment in which users can continuously engage in dementia-prevention activities without getting bored.

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Fortuna RGP, Putrie, and Ahmaddul Hadi. "RANCANG BANGUN APLIKASI BELAJAR PEMROGRAMAN DENGAN GAME EDUCATION PADA SMARTPHONE BERBASIS ANDROID." Voteteknika (Vocational Teknik Elektronika dan Informatika) 7, no. 3 (July 10, 2019): 30. http://dx.doi.org/10.24036/voteteknika.v7i3.105086.

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Programming is a vocational subject in the Vocational School majoring in Software Engineering and Electronics. Programming is classified as a subject that is less desirable and difficult for students, because these subjects are not graphically based and students do not understand the basic structure of the program. And less Affective use of conventional learning resources as the main source of the learning. With the existence of smartphones can be used as an additional source in the world of education. One of them is the use of smartphones as learning media. The purpose of this study is to produce learning media that can help teachers and students in the learning process by loading educational games that can attract students' interest in learning. This application is made using the System Development Life Cycle (SDLC) Prototype method, using an Android-based java programming language, by applying game education algorithms and word game genres where players must arrange random letters into coherent sentences, the random letters will be matched with the answers stored in the database to be the correct answer. The content in the application is the 2013 curriculum syllabus. The material consists of RPP and teaching materials for each basic competency. Ebooks, articles and videos that discuss basic programming. Evaluation is a practice question to measure the level of understanding of students and quiz games in the form of stacking words to train students' memory about basic programming.Keywords: Android, Programming, Game education. word game

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Kim, Sungwook. "Cooperative Game-Based Virtual Machine Resource Allocation Algorithms in Cloud Data Centers." Mobile Information Systems 2020 (March 16, 2020): 1–11. http://dx.doi.org/10.1155/2020/9840198.

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With the growing demand of cloud services, cloud data centers (CDCs) can provide flexible resource provisioning in order to accommodate the workload demand. In CDCs, the virtual machine (VM) resource allocation problem is an important and challenging issue to provide efficient infrastructure services. In this paper, we propose a unified resource allocation scheme for VMs in the CDC system. To provide a fair-efficient solution, we concentrate on the basic concept of Shapley value and adopt its variations to effectively allocate CDC resources. Based on the characteristics of value solutions, we develop novel CPU, memory, storage, and bandwidth resource allocation algorithms. To practically implement our algorithms, application types are assumed as cooperative game players, and different value solutions are applied to optimize the resource utilization. Therefore, our four resource allocation algorithms are jointly combined as a novel fourfold game model and take various benefits in a rational way through the cascade interactions while solving comprehensively some control issues. To ensure the growing demand of cloud services, this feature can leverage the full synergy of different value solutions. To check the effectiveness and superiority of our proposed scheme, we conduct extensive simulations. The simulation results show that our algorithms have significant performance improvement compared to the existing state-of-the-art protocols. Finally, we summarize our cooperative game-based approach and discuss possible major research issues for the future challenges about the cloud-assisted DC resource allocation paradigm.

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Kodynets, Anatolii, and Arsen Murashko. "Video game in the system of intellectual property: the concept and features of legal protection." Theory and Practice of Intellectual Property, no. 3 (September 7, 2021): 57–66. http://dx.doi.org/10.33731/32021.239584.

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Keywords: video game, intellectual property law, computer program, software, digitalinformation, electronic information, multimedia work, audiovisual work The article is devoted to thestudy of the legal understanding of video games as an object of intellectual propertyrights. The author concludes that video games constitute digital information, whichgreatly facilitates their development, however, complicates the protection of intellectualproperty rights. There is a contradictory connection between the concepts of«electronic (digital) information», «audiovisual work», «computer program» and «literarywork», which establishes some uncertainty in the protection of video games,namely, what should be understood by these concepts in terms of law.The author found that the use of the latest technologies to improve the visual componentbrings the video game even closer to the game audiovisual object, which increasesthe complexity of the process of protection of intellectual property rights. However, thecurrent situation with the use of the term «computer program» in the context of protectionof intellectual property rights to video games does not cover all features of the latter,covering only the main program among the software recording and operation of thegame, such as audiovisual content. Therefore, there is a need to use the generalized conceptof «software» as opposed to the narrower concept of «computer program». In thiscase, in the absence of at least one of the characteristics of the multimedia work, the computerprogram should be referred to the scope of legal regulation of software.The author proposed to understand the video game as object of intellectual propertylaw in the following manner: multimedia work expressed in the form of digital(electronic) information, the principle of which is determined by the algorithms of thesoftware provided for installation in the memory of computer devices.In general, the digital nature of video games presupposes a revision of existing approachesto the protection of intellectual property rights, which may be aimed atweakening the regulatory function of the law where it is possible to regulate the relationshipby more flexible means.

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Gallardo, J. E., C. Cotta, and A. J. Fernández. "Solving Weighted Constraint Satisfaction Problems with Memetic/Exact Hybrid Algorithms." Journal of Artificial Intelligence Research 35 (July 28, 2009): 533–55. http://dx.doi.org/10.1613/jair.2770.

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A weighted constraint satisfaction problem (WCSP) is a constraint satisfaction problem in which preferences among solutions can be expressed. Bucket elimination is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply bucket elimination is too high, a heuristic method based on it (denominated mini-buckets) can be used to calculate bounds for the optimal solution. Nevertheless, the curse of dimensionality makes these techniques impractical on large scale problems. In response to this situation, we present a memetic algorithm for WCSPs in which bucket elimination is used as a mechanism for recombining solutions, providing the best possible child from the parental set. Subsequently, a multi-level model in which this exact/metaheuristic hybrid is further hybridized with branch-and-bound techniques and mini-buckets is studied. As a case study, we have applied these algorithms to the resolution of the maximum density still life problem, a hard constraint optimization problem based on Conway's game of life. The resulting algorithm consistently finds optimal patterns for up to date solved instances in less time than current approaches. Moreover, it is shown that this proposal provides new best known solutions for very large instances.

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Valladares-Rodriguez, Sonia, Manuel J. Fernández-Iglesias, Luis Anido-Rifón, David Facal, and Roberto Pérez-Rodríguez. "Episodix: a serious game to detect cognitive impairment in senior adults. A psychometric study." PeerJ 6 (September 5, 2018): e5478. http://dx.doi.org/10.7717/peerj.5478.

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Introduction Assessment of episodic memory is traditionally used to evaluate potential cognitive impairments in senior adults. The present article discusses the capabilities of Episodix, a game to assess the aforementioned cognitive area, as a valid tool to discriminate among mild cognitive impairment (MCI), Alzheimer’s disease (AD) and healthy individuals (HC); that is, it studies the game’s psychometric validity study to assess cognitive impairment. Materials and Methods After a preliminary study, a new pilot study, statistically significant for the Galician population, was carried out from a cross-sectional sample of senior adults as target users. A total of 64 individuals (28 HC, 16 MCI, 20 AD) completed the experiment from an initial sample of 74. Participants were administered a collection of classical pen-and-paper tests and interacted with the games developed. A total of six machine learning classification techniques were applied and four relevant performance metrics were computed to assess the classification power of the tool according to participants’ cognitive status. Results According to the classification performance metrics computed, the best classification result is obtained using the Extra Trees Classifier (F1 = 0.97 and Cohen’s kappa coefficient = 0.97). Precision and recall values are also high, above 0.9 for all cognitive groups. Moreover, according to the standard interpretation of Cohen’s kappa index, classification is almost perfect (i.e., 0.81–1.00) for the complete dataset for all algorithms. Limitations Weaknesses (e.g., accessibility, sample size or speed of stimuli) detected during the preliminary study were addressed and solved. Nevertheless, additional research is needed to improve the resolution of the game for the identification of specific cognitive impairments, as well as to achieve a complete validation of the psychometric properties of the digital game. Conclusion Promising results obtained about psychometric validity of Episodix, represent a relevant step ahead towards the introduction of serious games and machine learning in regular clinical practice for detecting MCI or AD. However, more research is needed to explore the introduction of item response theory in this game and to obtain the required normative data for clinical validity.

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Neider, Daniel, Alexander Weinert, and Martin Zimmermann. "Synthesizing optimally resilient controllers." Acta Informatica 57, no. 1-2 (October 31, 2019): 195–221. http://dx.doi.org/10.1007/s00236-019-00345-7.

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Abstract Recently, Dallal, Neider, and Tabuada studied a generalization of the classical game-theoretic model used in program synthesis, which additionally accounts for unmodeled intermittent disturbances. In this extended framework, one is interested in computing optimally resilient strategies, i.e., strategies that are resilient against as many disturbances as possible. Dallal, Neider, and Tabuada showed how to compute such strategies for safety specifications. In this work, we compute optimally resilient strategies for a much wider range of winning conditions and show that they do not require more memory than winning strategies in the classical model. Our algorithms only have a polynomial overhead in comparison to the ones computing winning strategies. In particular, for parity conditions, optimally resilient strategies are positional and can be computed in quasipolynomial time.

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Liang, Shuang, and Yang Li. "Using Camshift and Kalman Algorithm to Trajectory Characteristic Matching of Basketball Players." Complexity 2021 (June 16, 2021): 1–11. http://dx.doi.org/10.1155/2021/4728814.

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Because of its unique charm, sports video is widely welcomed by the public in today’s society. Therefore, the analysis and research of sports game video data have high practical significance and commercial value. Taking a basketball game video as an example, this paper studies the tracking feature matching of basketball players’ detection, recognition, and prediction in the game video. This paper is divided into four parts to improve the application of the interactive multimodel algorithm to track characteristic matching: moving object detection, recognition, basketball track characteristic matching, and player track characteristic matching. The main work and research results of each part are as follows: firstly, the improved K-means clustering algorithm is used to segment the golf field area; then, HSV is combined with the RGB Fujian value method to eliminate the field area; at last, straight field lines were extracted by Hough transform, and elliptical field lines were extracted by curve fitting, and the field lines were eliminated to realize the detection of moving objects. Seven normalized Hu invariant moments are used as the target features to realize the recognition of moving targets. By obtaining the feature distance between the sample and the template, the category of the sample is judged, which has a good robustness. The Kalman filter is used to match the characteristics of the basketball trajectory. Aiming at the occlusion of basketball, the least square method was used to fit the basketball trajectory, and the basketball position was predicted at the occlusion moment, which realized the occlusion trajectory matching. The matching of players’ track characteristics is realized by the CamShift algorithm based on the color model, which makes full use of players’ color information and realizes real-time performance. In order to solve the problem of occlusion between players in the track feature matching, CamShift and Kalman algorithms were used to determine the occlusion factor through the search window and then weighted Kalman and CamShift according to the occlusion degree to get the track feature matching result. The experimental results show that the detection time is greatly shortened, the memory space occupied is small, and the effect is very ideal.

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Liu, Man, Hongjun Zhang, Wenning Hao, Xiuli Qi, Kai Cheng, Dawei Jin, and Xinliang Feng. "Introduction of a new dataset and method for location predicting based on deep learning in wargame." Journal of Intelligent & Fuzzy Systems 40, no. 5 (April 22, 2021): 9259–75. http://dx.doi.org/10.3233/jifs-201726.

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It is a challenge for existing artificial intelligence algorithms to deal with incomplete information of computer tactical wargames in military research, and one effective method is to take advantage of game replays based on data mining or supervised learning. However, the open source datasets of wargame replays are extremely rare, which obstruct the development of research on computer wargames. In this paper, a data set of wargame replays is opened for predicting algorithm on the condition of incomplete information, to be specific, we propose the dataset processing method for deep learning and an network model for enemy locations predicting. We first introduce the criteria and methods of data preprocessing, parsing and feature extraction, then the training set and test set for deep learning are predefined. Furthermore, we have designed a newly specific network model for enemy locations predicting, including multi-head input, multi-head output, CNN and GRU layers to deal with the multi-agent and long-term memory problems. The experimental results demonstrate that our method achieves good performance of 84.9% on top-50 accuracy. Finally, we open source the data set and methods on https://github.com/daman043/AAGWS-Wargame-master.

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You, Shixun, Ming Diao, and Lipeng Gao. "Completing Explorer Games with a Deep Reinforcement Learning Framework Based on Behavior Angle Navigation." Electronics 8, no. 5 (May 25, 2019): 576. http://dx.doi.org/10.3390/electronics8050576.

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In cognitive electronic warfare, when a typical combat vehicle, such as an unmanned combat air vehicle (UCAV), uses radar sensors to explore an unknown space, the target-searching fails due to an inefficient servoing/tracking system. Thus, to solve this problem, we developed an autonomous reasoning search method that can generate efficient decision-making actions and guide the UCAV as early as possible to the target area. For high-dimensional continuous action space, the UCAV’s maneuvering strategies are subject to certain physical constraints. We first record the path histories of the UCAV as a sample set of supervised experiments and then construct a grid cell network using long short-term memory (LSTM) to generate a new displacement prediction to replace the target location estimation. Finally, we enable a variety of continuous-control-based deep reinforcement learning algorithms to output optimal/sub-optimal decision-making actions. All these tasks are performed in a three-dimensional target-searching simulator, i.e., the Explorer game. Please note that we use the behavior angle (BHA) for the first time as the main factor of the reward-shaping of the deep reinforcement learning framework and successfully make the trained UCAV achieve a 99.96% target destruction rate, i.e., the game win rate, in a 0.1 s operating cycle.

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Nesterenko, Konstantin, and Bohdan Zhurakovskyi. "IMAGE CONVERTER BASED ON BLOCK COMPRESSION ALGORITHMS OF DXT1, DXT3 AND DXT5 TEXTURES." Cybersecurity: Education, Science, Technique 12, no. 4 (June 24, 2021): 69–84. http://dx.doi.org/10.28925/2663-4023.2021.12.6984.

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This article analyzes the existing applications that implement block texture compression algorithms. Based on it, the most optimal variant of technical implementation is introduced. A set of technologies for the implementation of the prototype is selected and substantiated and its architecture is developed on the basis of the principles that ensure the maximum extensibility and purity of the code. With the development of technology and the integration of computerized systems into all possible areas of human activity, more and more software with three-dimensional graphics is being used. Such programs have long since ceased to be used only in the entertainment field for tasks such as computer game development or special effects for cinema. Now with their help doctors can plan the most complex operations, architects check the developed plans of constructions and engineers to model prototypes without use of any materials. On the one hand, such a rapid increase can be explained by the increase in the power of components for personal computers. For example, modern graphics processors, which play a key role in the operation of graphics software, have become much faster in recent decades and have increased their memory hundreds of times. However, no matter how many resources the system has, the question of their efficient use still remains. It is to solve this problem that block texture compression algorithms have been created. In fact, they made it possible to create effective software when computer resources were still quite limited. And with increasing resources allowed to develop software with an incredible level of detail of the models, which led to its active implementation in such demanding areas as medicine, construction and more. The end result of this work is a developed application that takes into account the modern needs of the user. During the development, the most modern technologies were used for the highest speed and relevance of the application. The main advantages and disadvantages of existing solutions were also taken into account during the development. The capabilities of the system were tested using manual testing on a local machine.

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Noori, Azad, and Farzad Moradi. "Simulation and Comparison of Efficency in Pathfinding algorithms in Games." Ciência e Natura 37 (December 19, 2015): 230. http://dx.doi.org/10.5902/2179460x20778.

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There are several routes to go from point A to point B in many computer games and computer player have to choose the best route. To do this, the pathfinding algorithms is used. Currently, several algorithms have been proposed for routing in games so that the general challenges of them is high consumption of memory and a long Execution time. Due to these problems, the development and introduction of new algorithms will be continued. At the first part of this article, in addition to basic and important used algorithms, the new algorithm BIDDFS is introduced.In the second part, these algorithms in the various modes, are simulated on 2D-Grid, and compared based on their efficency (memory consumption and execution time) , Simulated algorithms include: Dijkstra, Iddfs, Biddfs, Bfs (Breadth), Greedy Best First Search, Ida*, A*, Jump point search, HPA*.

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Krawiec, Krzysztof, Wojciech Jaśkowski, and Marcin Szubert. "Evolving small-board Go players using coevolutionary temporal difference learning with archives." International Journal of Applied Mathematics and Computer Science 21, no. 4 (December 1, 2011): 717–31. http://dx.doi.org/10.2478/v10006-011-0057-3.

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Evolving small-board Go players using coevolutionary temporal difference learning with archivesWe apply Coevolutionary Temporal Difference Learning (CTDL) to learn small-board Go strategies represented as weighted piece counters. CTDL is a randomized learning technique which interweaves two search processes that operate in the intra-game and inter-game mode. Intra-game learning is driven by gradient-descent Temporal Difference Learning (TDL), a reinforcement learning method that updates the board evaluation function according to differences observed between its values for consecutively visited game states. For the inter-game learning component, we provide a coevolutionary algorithm that maintains a sample of strategies and uses the outcomes of games played between them to iteratively modify the probability distribution, according to which new strategies are generated and added to the sample. We analyze CTDL's sensitivity to all important parameters, including the trace decay constant that controls the lookahead horizon of TDL, and the relative intensity of intra-game and inter-game learning. We also investigate how the presence of memory (an archive) affects the search performance, and find out that the archived approach is superior to other techniques considered here and produces strategies that outperform a handcrafted weighted piece counter strategy and simple liberty-based heuristics. This encouraging result can be potentially generalized not only to other strategy representations used for small-board Go, but also to various games and a broader class of problems, because CTDL is generic and does not rely on any problem-specific knowledge.

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Kovalova, Оlena. "STIMULATION OF COGNITIVE FUNCTIONS OF PSYCHE BY MEANS OF ONLINE GAMES." Science and Education 2020, no. 4 (December 2020): 66–76. http://dx.doi.org/10.24195/2414-4665-2020-4-9.

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The article presents the results of testing of the developed online-training of cognitive functions of the brain, which was implemented on a separately created game platform using a set of specially developed games. The proposed results reveal the theoretical justification of the cognitive functions, which are selected for training: memory, thinking, attention, imagination, perception. The characteristics of each cognitive function to be stimulated in the conditions of online games are highlighted. We described the algorithm for games evaluating according to certain cognitive functions and their characteristics. An analysis of the effectiveness of evaluation is given. The results of completing by players of game sessions balanced on the chosen cognitive functions are described. A comparison of the effectiveness of stimulation of different cognitive functions depending on the motivation and choice of players is presented. The aim of the study was to evaluate the effectiveness of online games in activation and stimulation of the cognitive functions of the human psyche. The research methods were based on our own developed algorithm for training success estimation, analysis of the results of online games, methods of mathematical statistics. The results of the study are presented on the basis of approbation of the developed training, conducted during two years. The analysis of the implementation of the training revealed the dependence of the effectiveness of stimulation of cognitive functions on the motivation and choice of the player. It is shown that when training on a balanced set of games, where all cognitive functions are present in equal shares, the effectiveness of training is not uniform and not balanced. It is investigated that the effectiveness of training depends on the quality of the game's effect on cognitive function. In order to take into account this quality of influence, all games were divided into two classes: actively shaping and passively stimulating. The distribution of games by classes was experimentally confirmed. A generalized analysis of the game sessions of all players for six months revealed cognitive functions which for the most players were better developed and more stimulated.

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WALSH, KYLE, and BIKRAMJIT BANERJEE. "FAST A* WITH ITERATIVE RESOLUTION FOR NAVIGATION." International Journal on Artificial Intelligence Tools 19, no. 01 (February 2010): 101–19. http://dx.doi.org/10.1142/s0218213010000054.

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We argue that A*, the popular technique for path-finding for NPCs in games, suffers from three limitations that are pertinent to game worlds: (a) the grid maps often restrict the optimality of the paths, (b) A* paths exhibit wall-hugging behavior, and (c) optimal paths are more predictable. We present a new algorithm, VRA*, that varies map-resolution as needed, and repeatedly calls A*. We also present an extension of an existing post-smoothing technique, and show that these two techniques together produce more realistic looking paths than A*, that overcome the above limitations, while using significantly less memory and time than A*.

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Liu, Lu-Ping, and Wen-Sheng Jia. "An Intelligent Algorithm for Solving the Efficient Nash Equilibrium of a Single-Leader Multi-Follower Game." Mathematics 9, no. 5 (February 24, 2021): 454. http://dx.doi.org/10.3390/math9050454.

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This aim of this paper is to provide the immune particle swarm optimization (IPSO) algorithm for solving the single-leader–multi-follower game (SLMFG). Through cooperating with the particle swarm optimization (PSO) algorithm and an immune memory mechanism, the IPSO algorithm is designed. Furthermore, we define the efficient Nash equilibrium from the perspective of mathematical economics, which maximizes social welfare and further refines the number of Nash equilibria. In the end, numerical experiments show that the IPSO algorithm has fast convergence speed and high effectiveness.

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TAN, Jian, Guoqiang JIANG, and Zuogong WANG. "Evolutionary game of information sharing on supply chain network based on memory genetic algorithm." Journal Européen des Systèmes Automatisés 50, no. 4-6 (December 28, 2017): 507–19. http://dx.doi.org/10.3166/jesa.50.507-519.

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Kim, Jangsaeng, Dongseok Kwon, Sung Yun Woo, Won-Mook Kang, Soochang Lee, Seongbin Oh, Chul-Heung Kim, Jong-Ho Bae, Byung-Gook Park, and Jong-Ho Lee. "On-chip trainable hardware-based deep Q-networks approximating a backpropagation algorithm." Neural Computing and Applications 33, no. 15 (February 10, 2021): 9391–402. http://dx.doi.org/10.1007/s00521-021-05699-z.

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AbstractReinforcement learning (RL) using deep Q-networks (DQNs) has shown performance beyond the human level in a number of complex problems. In addition, many studies have focused on bio-inspired hardware-based spiking neural networks (SNNs) given the capabilities of these technologies to realize both parallel operation and low power consumption. Here, we propose an on-chip training method for DQNs applicable to hardware-based SNNs. Because the conventional backpropagation (BP) algorithm is approximated, a performance evaluation based on two simple games shows that the proposed system achieves performance similar to that of a software-based system. The proposed training method can minimize memory usage and reduce power consumption and area occupation levels. In particular, for simple problems, the memory dependency can be significantly reduced given that high performance is achieved without using replay memory. Furthermore, we investigate the effect of the nonlinearity characteristics and two types of variation of non-ideal synaptic devices on the performance outcomes. In this work, thin-film transistor (TFT)-type flash memory cells are used as synaptic devices. A simulation is also conducted using fully connected neural network with non-leaky integrated-and-fire (I&F) neurons. The proposed system shows strong immunity to device variations because an on-chip training scheme is adopted.

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Watanabe, Takuji, Kazuteru Miyazaki, and Hiroaki Kobayashi. "A New Improved Penalty Avoiding Rational Policy Making Algorithm for Keepaway with Continuous State Spaces." Journal of Advanced Computational Intelligence and Intelligent Informatics 13, no. 6 (November 20, 2009): 675–82. http://dx.doi.org/10.20965/jaciii.2009.p0675.

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The penalty avoiding rational policy making algorithm (PARP) [1] previously improved to save memory and cope with uncertainty, i.e., IPARP [2], requires that states be discretized in real environments with continuous state spaces, using function approximation or some other method. Especially, in PARP, a method that discretizes state using a basis functions is known [3]. Because this creates a new basis function based on the current input and its next observation, however, an unsuitable basis function may be generated in some asynchronous multiagent environments. We therefore propose a uniform basis function and range extent of the basis function is estimated before learning. We show the effectiveness of our proposal using a soccer game task called “Keepaway.”

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Rawat, Danda B., and Sachin Shetty. "Game Theoretic Cloud-Assisted Opportunistic Spectrum Access in Cognitive Radio Networks." International Journal of Grid and High Performance Computing 8, no. 2 (April 2016): 94–110. http://dx.doi.org/10.4018/ijghpc.2016040106.

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Opportunistic Spectrum Access (OSA) in a Cognitive Radio Network (CRN) is regarded as emerging technology for utilizing the scarce Radio Frequency (RF) spectrum by allowing unlicensed secondary users (SUs) to access licensed spectrum without creating harmful interference to primary users (PUs). The SUs are considerably constrained by their limited power, memory and computational capacity when they have to make decision about spectrum sensing for wide band regime and OSA. The SUs in CRN have the potential to mitigate these constraints by leveraging the vast storage and computational capacity of cloud computing approaches. In this paper, the authors investigate a game theoretic approach for opportunistic spectrum access in cognitive networks. The proposed algorithm leverages the geo-locations of both SUs and spectrum opportunities to facilitate OSA to SUs. The active SUs using game theory adapt their transmit powers in a distributed manner based on the estimated average packet-error rate while satisfying the Quality-of-Service (QoS) in terms of signal-to-interference-noise-ratio (SINR). Furthermore, to control greedy SUs in distributed power control game, the authors introduce a manager/leader through a Stackelberg power adaptation game. The performance of the proposed approaches is investigated using numerical results obtained from simulations.

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Zhao, Yu, Jifeng Guo, Chengchao Bai, and Hongxing Zheng. "Reinforcement Learning-Based Collision Avoidance Guidance Algorithm for Fixed-Wing UAVs." Complexity 2021 (January 16, 2021): 1–12. http://dx.doi.org/10.1155/2021/8818013.

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A deep reinforcement learning-based computational guidance method is presented, which is used to identify and resolve the problem of collision avoidance for a variable number of fixed-wing UAVs in limited airspace. The cooperative guidance process is first analyzed for multiple aircraft by formulating flight scenarios using multiagent Markov game theory and solving it by machine learning algorithm. Furthermore, a self-learning framework is established by using the actor-critic model, which is proposed to train collision avoidance decision-making neural networks. To achieve higher scalability, the neural network is customized to incorporate long short-term memory networks, and a coordination strategy is given. Additionally, a simulator suitable for multiagent high-density route scene is designed for validation, in which all UAVs run the proposed algorithm onboard. Simulated experiment results from several case studies show that the real-time guidance algorithm can reduce the collision probability of multiple UAVs in flight effectively even with a large number of aircraft.

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Mozaffari, Ahmad. "Synchronous self-learning Pareto strategy." International Journal of Intelligent Computing and Cybernetics 11, no. 2 (June 11, 2018): 197–233. http://dx.doi.org/10.1108/ijicc-05-2017-0050.

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Purpose In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue. Design/methodology/approach A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front. Findings To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems. Originality/value To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.

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Hong, Xijun. "Basketball Data Analysis Using Spark Framework and K-Means Algorithm." Journal of Healthcare Engineering 2021 (July 27, 2021): 1–7. http://dx.doi.org/10.1155/2021/6393560.

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With the rapid development, different information relating to sports may now be recorded forms of useful big data through wearable and sensing technology. Big data technology has become a pressing challenge to tackle in the present basketball training, which improves the effect of baseball analysis. In this study, we propose the Spark framework based on in-memory computing for big data processing. First, we use a new swarm intelligence optimization cuckoo search algorithm because the algorithm has fewer parameters, powerful global search ability, and support of fast convergence. Second, we apply the traditional K-clustering algorithm to improve the final output using clustering means in Spark distributed environment. Last, we examine the aspects that could lead to high-pressure game circumstances to study professional athletes’ defensive performance. Both recruiters and trainers may use our technique to better understand essential player’s qualities and eventually, to assess and improve a team’s performance. The experimental findings reveal that the suggested approach outperforms previous methods in terms of clustering performance and practical utility. It has the greatest influence on the shooting training impact when moving, yielding complimentary outcomes in the training effect.

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Park, Seung-Min, Kwang-Eun Ko, Junheong Park, and Kwee-Bo Sim. "Game model-based co-evolutionary algorithm with non-dominated memory and Euclidean distance selection mechanisms for multi-objective optimization." International Journal of Control, Automation and Systems 9, no. 5 (October 2011): 924–32. http://dx.doi.org/10.1007/s12555-011-0513-8.

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Sandanayake, Priyath T., and Diane J. Cook. "ONASI: Online Agent Modeling Using a Scalable Markov Model." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 05 (August 2003): 757–79. http://dx.doi.org/10.1142/s0218001403002642.

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Human and software agents exhibit regularities in their activities. We describe our ONASI algorithm, which derives a Markov model from such observed regularities, and dynamically scales the model through merging and splitting of states. ONASI uses this model to predict the agent's next action. We evaluate ONASI's predictive accuracy on a dataset of Wumpus World games, and demonstrate from this approach that the model can correctly predict the agent's next action with adjustable computation and memory resources. These predictions can be used to imitate, assist or obstruct an agent.

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Ferrarini, Luca, Baldur van Lew, Johan H. C. Reiber, Claudia Gandin, Lucia Galluzzo, Emanuele Scafato, Giovanni B. Frisoni, Julien Milles, and Michela Pievani. "Hippocampal atrophy in people with memory deficits: results from the population-based IPREA study." International Psychogeriatrics 26, no. 7 (February 13, 2014): 1067–81. http://dx.doi.org/10.1017/s1041610213002627.

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ABSTRACTBackground:Clinical studies have shown that hippocampal atrophy is present before dementia in people with memory deficits and can predict dementia development. The question remains whether this association holds in the general population. This is of interest for the possible use of hippocampal atrophy to screen population for preventive interventions. The aim of this study was to assess hippocampal volume and shape abnormalities in elderly adults with memory deficits in a cross-sectional population-based study.Methods:We included individuals participating in the Italian Project on the Epidemiology of Alzheimer Disease (IPREA) study: 75 cognitively normal individuals (HC), 31 individuals with memory deficits (MEM), and 31 individuals with memory deficits not otherwise specified (MEMnos). Hippocampal volumes and shape were extracted through manual tracing and the growing and adaptive meshes (GAMEs) shape-modeling algorithm. We investigated between-group differences in hippocampal volume and shape, and correlations with memory deficits.Results:In MEM participants, hippocampal volumes were significantly smaller than in HC and were mildly associated with worse memory scores. Memory-associated shape changes mapped to the anterior hippocampus. Shape-based analysis detected no significant difference between MEM and HC, while MEMnos showed shape changes in the posterior hippocampus compared with HC and MEM groups.Conclusions:These findings support the discriminant validity of hippocampal volumetry as a biomarker of memory impairment in the general population. The detection of shape changes in MEMnos but not in MEM participants suggests that shape-based biomarkers might lack sensitivity to detect Alzheimer's-like pathology in the general population.

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Hazarika, Jupitara, Piyush Kant, Rajdeep Dasgupta, and Shahedul Haque Laskar. "EEG Wavelet Coherence Based Analysis of Neural Connectivity in Action Video Game Players in Attention Inhibition and Short-term Memoryretention Task." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 12, no. 4 (August 23, 2019): 324–38. http://dx.doi.org/10.2174/2352096511666180821111536.

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Background: The involvement in action video gaming alters the cognitive abilities and hence affects the neural functionality. Electroencephalogram (EEG) favorably provides the measure. Wavelet coherence, which is a wavelet transform based feature that provides useful information regarding synchronized activity between two signals. It does not depend on the stationarity of the signal and hence very much relevant for non-stationary EEG application. Methods: We aimed to examine how the task-related synchronization pattern of action video game players (AVGPs) differs from non-AVGPs. EEG data were collected from thirty-five young and healthy male participants while performing an attention inhibition task and a visuospatial short-term memory-retention task. The sub-frequency components, theta, alpha, beta and gamma bands of EEG were extracted using Discrete wavelet transform (DWT). The intra and inter-hemispheric coherence in EEG sub-frequency bands were assessed as a feature for the analysis. Results: Theta, alpha, beta and gamma coherence has shown a significant difference (p<0.05) between AVGPs and non-AVGPs in both the visuo-spatial tasks in intra and inter-hemispheric functionality. More than 90% classification accuracies are achieved with ANFIS algorithm. Results also indicate that frontoparietal connectivity is significantly improved in AVGPs in both the visual sensory tasks considered. Conclusion: These EEG based analysis reports enhanced neural communication with improved attention inhibition and short-term memory retention in AVGPs. Result also established the Wavelet coherence as an effective tool in understanding the neural communication among different brain locations.

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Moll, Maximilian, and Leonhard Kunczik. "Comparing quantum hybrid reinforcement learning to classical methods." Human-Intelligent Systems Integration 3, no. 1 (March 2021): 15–23. http://dx.doi.org/10.1007/s42454-021-00025-3.

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AbstractIn recent history, reinforcement learning (RL) proved its capability by solving complex decision problems by mastering several games. Increased computational power and the advances in approximation with neural networks (NN) paved the path to RL’s successful applications. Even though RL can tackle more complex problems nowadays, it still relies on computational power and runtime. Quantum computing promises to solve these issues by its capability to encode information and the potential quadratic speedup in runtime. We compare tabular Q-learning and Q-learning using either a quantum or a classical approximation architecture on the frozen lake problem. Furthermore, the three algorithms are analyzed in terms of iterations until convergence to the optimal behavior, memory usage, and runtime. Within the paper, NNs are utilized for approximation in the classical domain, while in the quantum domain variational quantum circuits, as a quantum hybrid approximation method, have been used. Our simulations show that a quantum approximator is beneficial in terms of memory usage and provides a better sample complexity than NNs; however, it still lacks the computational speed to be competitive.

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Soboleva, Elena V., Ekaterina P. Kirillova, Denis E. Lomakin, and Dmitry N. Gribkov. "Formation of computational thinking skills in the development of computer games for educational purposes." Perspectives of Science and Education 49, no. 1 (March 1, 2021): 464–77. http://dx.doi.org/10.32744/pse.2021.1.32.

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The problem and the aim of the study. The problem, to be solved by the study, is proper to the need to expand the goals of the education system, to update tools and methods based on digital technologies, that promote the activation of a sequence of images from a person's memory, formulate a problem, and compose an effective solution algorithm. For the formation of the relevant skills that determine the essence of special computational thinking, the authors propose to include in the educational and cognitive activities of students the practice of developing game educational spaces using digital gamification resources. Research methods. To obtain theoretical generalizations was used the analysis of scientific works on the problem of defining the phenomenon of "computational thinking", the apply of digital resources of gamification in teaching. The HTML 5 language as a software implementation tool was used. The study involved 26 bachelors of the Institute of Mathematics, Informatics and Physics in the direction 01.03.02 Applied Mathematics and Informatics and 13 students in the direction 44.04.01 Pedagogical education (master's level) of Vyatka State University. The experiment used the Student's t-test. Results. The authors clarify the essence of the concept of "computational thinking", includes a system of actions for activating patterns from human memory, connections between them; problem statement into account the uncertainty of the future; drawing up an effective solution algorithm using digital technology tools. The authors described directions of educational and cognitive activities, based on the principles of gamification: obtaining relevant information on advanced technological developments; problem statement and modeling; creation of your own software product. The effectiveness of the proposed approach was assessed and statistically significant differences in qualitative changes in temp> tcrit were revealed at α = 0.05 (8,2> 2,06). In conclusion the authors generalized the conditions that influence the formation of computational thinking: obtaining relevant scientific and theoretical facts, patterns, information on innovative methods and tools; reasoned choice, effective implementation at a high technical level; analysis of the result and its practical application.

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Pavlovskaya, V. A. "FEATURES OF COGNITIVE STYLES IN THE CHESS GAME." Scientific Notes of V.I. Vernadsky Crimean Federal University. Sociology. Pedagogy. Psychology 6(72), no. 3 (2020): 115–26. http://dx.doi.org/10.37279/2413-1709-2020-6-3-115-126.

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The article discusses various approaches to understanding the essence of cognitive styles, and provides a description of the most common types of cognitive styles. In the modern situation of the existence of various types of information influences on the emotional and volitional sphere of preschool and primary school children, problems of low motivation for any type of activity, poor memory, perception disorders are found. Сhess is a means of constructively solving these problems. From the set of cognitive styles studied in the scientific environment, 10 types were selected, namely, utility / gender independence, narrowness / breadth in the range of equivalence, rigidity/flexibility, narrowness/breadth of the category, tolerance to unrealistic experience, narrowness/breadth of the category, focusing/scanning control, smoothing/sharpening, impulsiveness/reflexivity, cognitive simplicity/complexity, concreteness/abstraction. Definitions of each of the indicated cognitive styles and their hypothetical relationship with the checkmate game are given. Based on the fact that chess is an intellectual activity that includes cognitive processes, some psychological features of the chess game are described and designated, hypothetically associated with a specific type of cognitive style. The author emphasizes that in the organization and effectiveness of learning chess, as well as other types of educational activity, a large role is played by such cognitive style as impulsivity/reflexivity and field-dependence/field-independence, as well as the development of mobility and flexibility of the cognitive style, namely, the ability to switch from one style parameter to another at the necessary moment of the game. Some problems in the study of cognitive styles are identified. Most research focuses on the study of utility and differentiation, which is not a comprehensive study of cognitive styles. The nature of cognitive styles is not fully understood. It is also unclear the specific age characteristic of the formation and manifestation of a particular cognitive style in a particular person. The article reveals the concept of chess success as the ability to focus on a group of breakout pieces, creating three levels of significance of the pieces on the Board and distributing the controlled fields of the Board into two levels: significant and insignificant. Some stylistic features of the checkmate game of such world Champions as Botvinnik, Tal, and Petrosyan are described. It is concluded that chess is a means of versatile development of the child. This is a universal discipline of the game character, aimed at fostering a common culture. Chess affects the development of external and internal speech, combinatorial and logical thinking, will, vital activity, criticality, the ability to self-analysis and self-assessment, self-education. The review suggests that in teaching children, among other things, it is advisable to use the following algorithm: to determine the child’s cognitive styles and the degree of their rootedness (formation) in cognitive processes; to identify fragments (components) of learning chess most associated with the advantages of a particular cognitive style and take this connection into account; to train or develop children’s cognitive mobility, i.e. the ability to switch from one style to another if necessary.

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Harabor, Daniel Damir, Alban Grastien, Dindar Öz, and Vural Aksakalli. "Optimal Any-Angle Pathfinding In Practice." Journal of Artificial Intelligence Research 56 (May 26, 2016): 89–118. http://dx.doi.org/10.1613/jair.5007.

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Any-angle pathfinding is a fundamental problem in robotics and computer games. The goal is to find a shortest path between a pair of points on a grid map such that the path is not artificially constrained to the points of the grid. Prior research has focused on approximate online solutions. A number of exact methods exist but they all require super-linear space and pre-processing time. In this study, we describe Anya: a new and optimal any-angle pathfinding algorithm. Where other works find approximate any-angle paths by searching over individual points from the grid, Anya finds optimal paths by searching over sets of states represented as intervals. Each interval is identified on-the-fly. From each interval Anya selects a single representative point that it uses to compute an admissible cost estimate for the entire set. Anya always returns an optimal path if one exists. Moreover it does so without any offline pre-processing or the introduction of additional memory overheads. In a range of empirical comparisons we show that Anya is competitive with several recent (sub-optimal) online and pre-processing based techniques and is up to an order of magnitude faster than the most common benchmark algorithm, a grid-based implementation of A*.

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Fadeev, Pavel V. "Sports Victories as a Value Uniting Russians (Through the Example of the Sochi 2014 Winter Olympics)." Sociologicheskaja nauka i social naja praktika 8, no. 1 (2020): 120–30. http://dx.doi.org/10.19181/snsp.2020.8.1.7099.

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Based on research performed by the Russian Public Opinion Research Center and the Russian Society of Sociologists, the mechanism for identifying Russian society under the influence of the victory of the Russian national team at the Olympic Games in Sochi in 2014 is analyzed. An algorithm for identifying Russians under the influence of athletes’ successes in a stable sequence is described: from individual emotional reflection to gaining a united motivation toward improvement of the existing world order. An analysis of the secondary data of the sociological centers suggests that the influence of sports victories on the identification of Russians is neither episodic in nature, nor based on individual and collective emotions, but, on the contrary, is a kind of “building material” that strengthens the unity of the people. Every victory of Russian athletes in prestigious competitions is tied in the common historical memory of people to the past successes and achievements of the people. Thus, the successes of athletes contribute to the unity of all citizens of Russia.

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Moskalenko, Olga Valentinovna. "PROBLEMS OF PSYCHO DIDACTICS IN UNIVERSITY AND POSSIBLE WAYS OF THEIR SOLUTION." SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference 1 (May 26, 2017): 305. http://dx.doi.org/10.17770/sie2017vol1.2273.

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This article is devoted to the study of two main problems – whom and how to teach in a university. Theoretical analysis substantiated the thesis that the inefficiency of teaching students is connected directly with the lack of teachers’ knowledge about psychological peculiarities of modern student community. Accordingly, the research shows the contrariety between this age and forms of its appearance as one of students’ specifics. One of main consequences of those problems is the genesis and development of student infantilism, which has such essential characteristics: ambivalence, motivational stimulating force, behavioral form, protracted nature of infantilism and its extending, possibility of its overcoming and correction. The particular research set effective algorithm and the program of psychological correction of student’s infantilism while obtaining higher education. The second problem is devoted to the necessity of using teaching psycho didactical methods to create conditions for personal cognitive development. Theoretical analysis and empiric research identified the method system to develop cognitive process: for memory – enlarging didactic units as factors for systematizing learning materials and students’ knowledge; attention – improving individual controlled work of students; information representation – text manipulation and multimedia didactics; feelings – emotional and willful control, decision taking ability logic development; imagination – didactical games.

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Oliveira, J., R. Brito, P. Lopes, L. Rodelo, L. Pinto, D. Morais, and P. Gamito. "Evaluation of Cognitive Functions through the Systemic Lisbon Battery: Normative Data." Methods of Information in Medicine 55, no. 01 (2016): 93–97. http://dx.doi.org/10.3414/me14-02-0021.

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SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Methodologies, Models and Algorithms for Patients Rehabilitation”. Background: ICT is an emerging alternative to paper-and-pencil tests for the assessment of cognitive functions, allowing for the monitoring of participants’ behavior while they perform simulations of instrumental activi -ties of daily life (IADLs) in a virtual reality (VR) scenario. This requires normative values for each VR task, so that deviations to normality can be identified as indicators of cognitive impairment. Objectives: To identify normative data for several IADL tasks that are available on the Systemic Lisbon Battery (SLB). Methods: Fifty-nine participants performed a series of VR tasks that require the use of the memory and executive function dimensions of cognitive functionality. Results: Normative data for the different subsets and total score of the SLB, based on proportion of correct hits per execution time, were identified. Age and experience with video games affect (respectively, negatively and positively) performance on the SLB and should be taken into account in assessment; on the other hand, gender and education do not. Conclusions: Overall results suggest that the SLB may be useful to assess cognitive functioning during the execution of activities of daily living, but larger studies and with clinical samples are needed.

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Khan, Murad, Junho Seo, and Dongkyun Kim. "Towards Energy Efficient Home Automation: A Deep Learning Approach." Sensors 20, no. 24 (December 15, 2020): 7187. http://dx.doi.org/10.3390/s20247187.

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Home Automation Systems (HAS) attracted much attention during the last decade due to the developments in new wireless technologies, such as Bluetooth 4.0, 5G, WiFi 6, etc. In order to enable automation as a service in smart homes, a number of challenges must be addressed, such as fulfilling the electrical energy demands, scheduling the operational time of appliances, applying machine learning models in real-time, optimal human appliances interaction, etc. In order to address the aforementioned challenges and control the wastage of energy due to the lifestyle of the home users, we propose a system for automatically controlling the energy consumption by employing machine and deep learning techniques to smart home networks. The proposed system works in three phases, (1) feature extraction and classification based on 1-dimensional Deep Convolutional Neural Network (1D-DCNN) which extract important energy patterns from the historic energy data, (2) a load forecasting system based on Long-short Term Memory (LSTM) is proposed to forecast the load based on the extracted features in phase 1 and (3) a scheduling algorithm based on the forecasted data obtained from phase 2 is designed to schedule the operational time of smart home appliances. The proposed scheme efficiently automates the smart home appliances to consume less energy while adapting to the lifestyle of smart home users. The validation of the proposed scheme is tested with a number of simulation scenarios incorporating datasets from authentic data sources. The simulation results show that the proposed smart home automation system can be a game-changer in fulfilling the energy demands of the home users without installing renewable and other energy sources in the future.

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Zhang, Hongjie, Cheng Qu, Jindou Zhang, and Jing Li. "Self-Adaptive Priority Correction for Prioritized Experience Replay." Applied Sciences 10, no. 19 (October 2, 2020): 6925. http://dx.doi.org/10.3390/app10196925.

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Deep Reinforcement Learning (DRL) is a promising approach for general artificial intelligence. However, most DRL methods suffer from the problem of data inefficiency. To alleviate this problem, DeepMind proposed Prioritized Experience Replay (PER). Though PER improves data utilization, the priorities of most samples in its Experience Memory (EM) are out of date, as only the priorities of a small part of the data are updated while the Q network parameters are updated. Consequently, the difference between storage and real priority distributions gradually increases, which will introduce bias into the gradients of Deep Q-Learning (DQL) and make the DQL update toward a non-ideal direction. In this work, we propose a novel self-adaptive priority correction algorithm named Importance-PER (Imp-PER) to fix the update deviation. Specifically, we predict the sum of real Temporal-Difference error (TD-error) of all data in EM. Data are corrected by an importance weight, which is estimated by the predicted sum and the real TD-error calculated by the latest agent. To control the unbounded importance weight, we use truncated importance sampling with a self-adaptive truncation threshold. The conducted experiments on various games of Atari 2600 with Double Deep Q-Network and MuJoCo with Deep Deterministic Policy Gradient demonstrate that Imp-PER improves the data utilization and final policy quality on discrete states and continuous states tasks without increasing the computational cost.

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Petrova-Antonova, Dessislava, Ivaylo Spasov, Yanita Petkova, Ilina Manova, and Sylvia Ilieva. "CogniSoft: A Platform for the Automation of Cognitive Assessment and Rehabilitation of Multiple Sclerosis." Computers 9, no. 4 (November 16, 2020): 93. http://dx.doi.org/10.3390/computers9040093.

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Cognitive disorders remain a major cause of disability in Multiple Sclerosis (MS). They lead to unemployment, the need for daily assistance, and a poor quality of life. The understanding of the origin, factors, processes, and consequences of cognitive disfunction is key to its prevention, early diagnosis, and rehabilitation. The neuropsychological testing and continuous monitoring of cognitive status as part of the overall evaluation of patients with MS in parallel with clinical and paraclinical examinations are highly recommended. In order to improve health and disease understanding, a close linkage between fundamental, clinical, epidemiological, and socio-economic research is required. The effective sharing of data, standardized data processing, and the linkage of such data with large-scale cohort studies is a prerequisite for the translation of research findings into the clinical setting. In this context, this paper proposes a software platform for the cognitive assessment and rehabilitation of patients with MS called CogniSoft. The platform automates the Beck Depression Inventory (BDI-II) test and diagnostic tests for the evaluation of memory and executive functions based on the nature of Brief International Cognitive Assessment for MS (BICAMS), as well as implementing a set of games for cognitive rehabilitation based on BICAMS. The software architecture, core modules, and technologies used for their implementation are presented. Special attention is given to the development of cognitive tests for diagnostics and rehabilitation. Their automation enables better perception, avoids bias as a result of conducting the classic paper tests of various neurophysiologists, provides easy administration, and allows data collection in a uniform manner, which further enables analysis using statistical and machine learning algorithms. The CogniSoft platform is registered as medical software by the Bulgarian Drug Agency and it is currently deployed in the Neurological Clinic of the National Hospital of Cardiology in Sofia, Bulgaria. The first experiments prove the feasibility of the platform, showing that it saves time and financial resources while providing subjectivity in the interpretation of the cognitive test results.

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Buchok, Lianna. "V. Telychko’s “Children’s Album” as an example of the modern tonal image of the world: peculiarities of the musical vocabulary and melodic ideas." Problems of Interaction Between Arts, Pedagogy and the Theory and Practice of Education 49, no. 49 (September 15, 2018): 70–84. http://dx.doi.org/10.34064/khnum2-49.05.

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Background. The beginning of the development of musical art in Transcarpathia dates back to the end of the nineteenth century and lasts during the first third of the twentieth century. First of all, it was an interest in the genre of choral music (a synthetic genre based on the merging of the Word and Music), which fully corresponded to the enlightened spirit of life of the Transcarpathians under the political conditions of that time. And only in the second half of the twentieth century intensive blossoming of the varieties of instrumental (kind of «pure») music with its conceptually most complex types of creative thinking and adaptation to the methods of style transformation takes place. The piano music, one of the most abstract forms of the creative process, has revealed its peculiarities in this process. However, the researchers virtually never paid attention to piano pieces for children, which are naturally inferior by their practically necessary and didactically appropriate visual simplicity of musical vocabulary to the works of the so-called large genre. In addition, historically, the creative work of Transcarpathian composers has been considered only as a product of a purely regional significance. Therefore, it is important that the piano works of Transcarpathian composers for children should also be considered in the context of such integrity as the Intentional period of the music history, which has been defined as non-classical and at the same time permeated with the idea of global cultural synthesis Objectives. The essence of the tasks and the purpose is to present the "Child Album" by V. Telychko (the first in Transcarpathia sample of the genre of children’s musical album, 2016) as an example of the creation of the modern intonational image of the world - in its associative diversity and intentionality. Methods. A selection of research methods, namely, analytical (analysis and synthesis, induction and deduction, systematization, classification and generalization), comparative, systemic, phenomenological, functional, has been used in view of the holistic approach – in the spirit of spiritual development of the world. In this regard, the interpretive potential of the concepts of the intonational model and the modal nature of musical themes as types of thinking by sound images is considered methodologically appropriate: both purposefully focus attention of the recipient on the sound «body» and the intonational "soul" of the musical matter in the integrity of the creative idea of the work, and also is didactically productive in terms of comprehension of the architectonics of the world of music as a world of musical ideas. Results. V. Telichko’s "Children’s Album" is a cyclic structure of the linear/plot type, where step-by-step compositional and dramaturgical organization of the whole ensures the principle of successive naming of new, but equal in figurative semantic content pieces. At the same time, it will be superfluous to reflect on the fact that the structure of cycles such as "album" is rarely evaluated as such that it is actually "filled in" (for example, with memorable photos or pictures), and only since then its "white" (from alba) of the blank/empty sheets is filled in with the semantics and the logic of placement of fixed events, phenomena, impressions, etc in a certain order. Against the background of such reflection the memory recalls such "albums" of romantics: all of them are based on the logic of the course of a day lived by a child (for example, P. I. Tchaikovsky). V. Telichko’s principle of collecting pieces "into the album" has such a life-justifiable logic – the gradual flow of events of the day, embodied in a child’s only perception of the world and itself. The semantic code of the composer’s plan is referenced in his dedication: "I devote my love to grandchildren Angelina and Anna" - expressing love for grandchildren, admiring their fantasy and energy, caring for the formation of their worldview on a certain system of values (family, native land, diversity of traditions of the countries of the world , historical memory): the pieces "Morning", "My Mother", "Our Grandmother" represent an idea of an ingenuous and happy feeling of a child in the family; "Anna’s Teddy-Bear", "Angelina’s Hobbyhorse" and "Angelina’s Waltz " represent a lively imagination of children, each of them having a favorite game "theme"; the plays "About Transcarpathia", "Kolomyika", "Tropotyanka", "Long road" and "It’s raining" are outlined by the situation of instructive stories of grandfather about the regionally formed traditions of the Transcarpathians, their spirit and uneasy destiny; while the pieces "On Scotland", "On Slovakia" and "On Japan" outline the interests of somewhat different cognitive significance - the intention to comprehend a certain national "otherness", which has its own color of its culture; in the end, "A Lullaby for Anna" creates, so to say, a backlash against the grand finale-prologue, consisting of the pieces "On Austria" (the cultural center of the European musical classicism) and "On Romania" (regionally closest to Transcarpathia country). Another signifying circumstance of the idea and plan of the cycle refers to the types of performances and personification of images, both as members of the family circle and as a certain social unity: in addition to the versions of solo performance, in a considerable number of plays there is ensemble performance in four and six hands; at the same time, each of the parts is composed as a certain texture layer, which in aggregate (duo, terzetto) gives the effect of an "orchestral" score. However, the most important thing is that for the instrumentalist performer, and for the listener or analyst (who is also a "listener"), the "Children’s Album" by V. Telichko is a test of the ability to perceive musical vocabulary in the form of a certain sound form/idea with which it is necessary to have a relationship according to the algorithm of personal identification. On the one hand, in the musical text there is an opportunity to recognize the classical models of musical vocabulary (cantilena, recitation, motility, general forms of motion, signaling, sound illustration); and on the other - due to the constructive interference of the classical techniques of the creation of musical matter (emancipated dissonance, the non-systemic character of the tonality, etc.) the meanings are accumulated. Another important component of the composer’s plan is to introduce a purely methodical (level of methodical reception) task of developing the technology of the game on the piano into the original sound form/idea, which first of all requires a skillful usage of all the fingers. Conclusions. As a research material the "Children’s Album" by a contemporary composer from Transcarpathia, V. Telichko provides several important and mutually perceptible scientific tasks directly related to musicology and pedagogical practice: testing of the theoretically updated analytical apparatus for tracking the intonational field of music and its thoughts and comprehension of the didactically expedient implementation of its results in the educational sphere; in particular, in terms of the prospective guideline for the development of musicality (a high measure of the ability to self-identification with the musical image) and the piano skills of a child musician.

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Khelifi, Meriem, Mohand Yazid Saidi, and Saadi Boudjit. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. 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Alqahtani, Sarra, and Rose Gamble. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. 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J. 2(3), 153-159 (2017); View Description A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017); View Description Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor Martin F. Pico, Eduardo J. Adam Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017); View Description Development and Validation of a Heat Pump System Model Using Artificial Neural Network Nabil Nassif, Jordan Gooden Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017); View Description Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017); View Description Kinect-Based Moving Human Tracking System with Obstacle Avoidance Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017); View Description A security approach based on honeypots: Protecting Online Social network from malicious profiles Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017); View Description Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC) Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017); View Description Enabling Toy Vehicles Interaction With Visible Light Communication (VLC) M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017); View Description Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices Mahmut Ün, Manolya Ün Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017); View Description Fire extinguishing system in large underground garages Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017); View Description Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017); View Description Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017); View Description Magnetically Levitated and Guided Systems Florian Puci, Miroslav Husak Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017); View Description Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks Minh T. Nguyen Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017); View Description Validity and efficiency of conformal anomaly detection on big distributed data Ilia Nouretdinov Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017); View Description S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency Juma Mary Atieno, Xuliang Zhang, HE Song Bai Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017); View Description Synthesis of Important Design Criteria for Future Vehicle Electric System Lisa Braun, Eric Sax Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017); View Description Gestural Interaction for Virtual Reality Environments through Data Gloves G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017); View Description Solving the Capacitated Network Design Problem in Two Steps Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017); View Description A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks Mohammad Nurul Afsar Shaon, Ken Ferens Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017); View Description Real Time Advanced Clustering System Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017); View Description Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors Khalid Al-Mutib, Foudil Abdessemed Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017); View Description Validity of Mind Monitoring System as a Mental Health Indicator using Voice Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017); View Description The Model of Adaptive Learning Objects for virtual environments instanced by the competencies Carlos Guevara, Jose Aguilar, Alexandra González-Eras Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017); View Description An Overview of Traceability: Towards a general multi-domain model Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017); View Description L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits Yasushi Itoh, Hiroaki Takagi Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017); View Description Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017); View Description Secure Path Selection under Random Fading Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017); View Description Security in SWIPT with Power Splitting Eavesdropper Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017); View Description Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017); View Description Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems Hanene Medhaffar, Moez Feki, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017); View Description Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017); View Description Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid Turgay Yalcin, Muammer Ozdemir Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017); View Description A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017); View Description Service Productivity and Complexity in Medical Rescue Services Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017); View Description Principal Component Analysis Application on Flavonoids Characterization Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017); View Description A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017); View Description Verifying the Detection Results of Impersonation Attacks in Service Clouds." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (May 2017): 449–59. http://dx.doi.org/10.25046/aj020358.

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47

Abdelhedi, Fatma, and Nabil Derbel. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017); View Description Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017); View Description A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management Indranil Nath Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017); View Description Feedback device of temperature sensation for a myoelectric prosthetic hand Yuki Ueda, Chiharu Ishii Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017); View Description Deep venous thrombus characterization: ultrasonography, elastography and scattering operator Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017); View Description Improving customs’ border control by creating a reference database of cargo inspection X-ray images Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017); View Description Aviation Navigation with Use of Polarimetric Technologies Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017); View Description Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki Adv. Sci. Technol. Eng. Syst. J. 2(3), 73-81 (2017); View Description Singular Integral Equations in Electromagnetic Waves Reflection Modeling A. S. Ilinskiy, T. N. Galishnikova Adv. Sci. Technol. Eng. Syst. J. 2(3), 82-87 (2017); View Description Methodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives. Fabian Bustamante, Walter Fuertes, Paul Diaz, Theofilos Toulqueridis Adv. Sci. Technol. Eng. Syst. J. 2(3), 88-99 (2017); View Description Dependence-Based Segmentation Approach for Detecting Morpheme Boundaries Ahmed Khorsi, Abeer Alsheddi Adv. Sci. Technol. Eng. Syst. J. 2(3), 100-110 (2017); View Description Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language Soufiane Farrah, Hanane El Manssouri, Ziyati Elhoussaine, Mohamed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 111-115 (2017); View Description Medical imbalanced data classification Sara Belarouci, Mohammed Amine Chikh Adv. Sci. Technol. Eng. Syst. J. 2(3), 116-124 (2017); View Description ADOxx Modelling Method Conceptualization Environment Nesat Efendioglu, Robert Woitsch, Wilfrid Utz, Damiano Falcioni Adv. Sci. Technol. Eng. Syst. J. 2(3), 125-136 (2017); View Description GPSR+Predict: An Enhancement for GPSR to Make Smart Routing Decision by Anticipating Movement of Vehicles in VANETs Zineb Squalli Houssaini, Imane Zaimi, Mohammed Oumsis, Saïd El Alaoui Ouatik Adv. Sci. Technol. Eng. Syst. J. 2(3), 137-146 (2017); View Description Optimal Synthesis of Universal Space Vector Digital Algorithm for Matrix Converters Adrian Popovici, Mircea Băbăiţă, Petru Papazian Adv. Sci. Technol. Eng. Syst. J. 2(3), 147-152 (2017); View Description Control design for axial flux permanent magnet synchronous motor which operates above the nominal speed Xuan Minh Tran, Nhu Hien Nguyen, Quoc Tuan Duong Adv. Sci. Technol. Eng. Syst. J. 2(3), 153-159 (2017); View Description A synchronizing second order sliding mode control applied to decentralized time delayed multi−agent robotic systems: Stability Proof Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 160-170 (2017); View Description Fault Diagnosis and Tolerant Control Using Observer Banks Applied to Continuous Stirred Tank Reactor Martin F. Pico, Eduardo J. Adam Adv. Sci. Technol. Eng. Syst. J. 2(3), 171-181 (2017); View Description Development and Validation of a Heat Pump System Model Using Artificial Neural Network Nabil Nassif, Jordan Gooden Adv. Sci. Technol. Eng. Syst. J. 2(3), 182-185 (2017); View Description Assessment of the usefulness and appeal of stigma-stop by psychology students: a serious game designed to reduce the stigma of mental illness Adolfo J. Cangas, Noelia Navarro, Juan J. Ojeda, Diego Cangas, Jose A. Piedra, José Gallego Adv. Sci. Technol. Eng. Syst. J. 2(3), 186-190 (2017); View Description Kinect-Based Moving Human Tracking System with Obstacle Avoidance Abdel Mehsen Ahmad, Zouhair Bazzal, Hiba Al Youssef Adv. Sci. Technol. Eng. Syst. J. 2(3), 191-197 (2017); View Description A security approach based on honeypots: Protecting Online Social network from malicious profiles Fatna Elmendili, Nisrine Maqran, Younes El Bouzekri El Idrissi, Habiba Chaoui Adv. Sci. Technol. Eng. Syst. J. 2(3), 198-204 (2017); View Description Pulse Generator for Ultrasonic Piezoelectric Transducer Arrays Based on a Programmable System-on-Chip (PSoC) Pedro Acevedo, Martín Fuentes, Joel Durán, Mónica Vázquez, Carlos Díaz Adv. Sci. Technol. Eng. Syst. J. 2(3), 205-209 (2017); View Description Enabling Toy Vehicles Interaction With Visible Light Communication (VLC) M. A. Ilyas, M. B. Othman, S. M. Shah, Mas Fawzi Adv. Sci. Technol. Eng. Syst. J. 2(3), 210-216 (2017); View Description Analysis of Fractional-Order 2xn RLC Networks by Transmission Matrices Mahmut Ün, Manolya Ün Adv. Sci. Technol. Eng. Syst. J. 2(3), 217-220 (2017); View Description Fire extinguishing system in large underground garages Ivan Antonov, Rositsa Velichkova, Svetlin Antonov, Kamen Grozdanov, Milka Uzunova, Ikram El Abbassi Adv. Sci. Technol. Eng. Syst. J. 2(3), 221-226 (2017); View Description Directional Antenna Modulation Technique using A Two-Element Frequency Diverse Array Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 227-232 (2017); View Description Classifying region of interests from mammograms with breast cancer into BIRADS using Artificial Neural Networks Estefanía D. Avalos-Rivera, Alberto de J. Pastrana-Palma Adv. Sci. Technol. Eng. Syst. J. 2(3), 233-240 (2017); View Description Magnetically Levitated and Guided Systems Florian Puci, Miroslav Husak Adv. Sci. Technol. Eng. Syst. J. 2(3), 241-244 (2017); View Description Energy-Efficient Mobile Sensing in Distributed Multi-Agent Sensor Networks Minh T. Nguyen Adv. Sci. Technol. Eng. Syst. J. 2(3), 245-253 (2017); View Description Validity and efficiency of conformal anomaly detection on big distributed data Ilia Nouretdinov Adv. Sci. Technol. Eng. Syst. J. 2(3), 254-267 (2017); View Description S-Parameters Optimization in both Segmented and Unsegmented Insulated TSV upto 40GHz Frequency Juma Mary Atieno, Xuliang Zhang, HE Song Bai Adv. Sci. Technol. Eng. Syst. J. 2(3), 268-276 (2017); View Description Synthesis of Important Design Criteria for Future Vehicle Electric System Lisa Braun, Eric Sax Adv. Sci. Technol. Eng. Syst. J. 2(3), 277-283 (2017); View Description Gestural Interaction for Virtual Reality Environments through Data Gloves G. Rodriguez, N. Jofre, Y. Alvarado, J. Fernández, R. Guerrero Adv. Sci. Technol. Eng. Syst. J. 2(3), 284-290 (2017); View Description Solving the Capacitated Network Design Problem in Two Steps Meriem Khelifi, Mohand Yazid Saidi, Saadi Boudjit Adv. Sci. Technol. Eng. Syst. J. 2(3), 291-301 (2017); View Description A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks Mohammad Nurul Afsar Shaon, Ken Ferens Adv. Sci. Technol. Eng. Syst. J. 2(3), 302-320 (2017); View Description Real Time Advanced Clustering System Giuseppe Spampinato, Arcangelo Ranieri Bruna, Salvatore Curti, Viviana D’Alto Adv. Sci. Technol. Eng. Syst. J. 2(3), 321-326 (2017); View Description Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors Khalid Al-Mutib, Foudil Abdessemed Adv. Sci. Technol. Eng. Syst. J. 2(3), 327-337 (2017); View Description Validity of Mind Monitoring System as a Mental Health Indicator using Voice Naoki Hagiwara, Yasuhiro Omiya, Shuji Shinohara, Mitsuteru Nakamura, Masakazu Higuchi, Shunji Mitsuyoshi, Hideo Yasunaga, Shinichi Tokuno Adv. Sci. Technol. Eng. Syst. J. 2(3), 338-344 (2017); View Description The Model of Adaptive Learning Objects for virtual environments instanced by the competencies Carlos Guevara, Jose Aguilar, Alexandra González-Eras Adv. Sci. Technol. Eng. Syst. J. 2(3), 345-355 (2017); View Description An Overview of Traceability: Towards a general multi-domain model Kamal Souali, Othmane Rahmaoui, Mohammed Ouzzif Adv. Sci. Technol. Eng. Syst. J. 2(3), 356-361 (2017); View Description L-Band SiGe HBT Active Differential Equalizers with Variable, Positive or Negative Gain Slopes Using Dual-Resonant RLC Circuits Yasushi Itoh, Hiroaki Takagi Adv. Sci. Technol. Eng. Syst. J. 2(3), 362-368 (2017); View Description Moving Towards Reliability-Centred Management of Energy, Power and Transportation Assets Kang Seng Seow, Loc K. Nguyen, Kelvin Tan, Kees-Jan Van Oeveren Adv. Sci. Technol. Eng. Syst. J. 2(3), 369-375 (2017); View Description Secure Path Selection under Random Fading Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 376-383 (2017); View Description Security in SWIPT with Power Splitting Eavesdropper Furqan Jameel, Faisal, M Asif Ali Haider, Amir Aziz Butt Adv. Sci. Technol. Eng. Syst. J. 2(3), 384-388 (2017); View Description Performance Analysis of Phased Array and Frequency Diverse Array Radar Ambiguity Functions Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 389-394 (2017); View Description Adaptive Discrete-time Fuzzy Sliding Mode Control For a Class of Chaotic Systems Hanene Medhaffar, Moez Feki, Nabil Derbel Adv. Sci. Technol. Eng. Syst. J. 2(3), 395-400 (2017); View Description Fault Tolerant Inverter Topology for the Sustainable Drive of an Electrical Helicopter Igor Bolvashenkov, Jörg Kammermann, Taha Lahlou, Hans-Georg Herzog Adv. Sci. Technol. Eng. Syst. J. 2(3), 401-411 (2017); View Description Computational Intelligence Methods for Identifying Voltage Sag in Smart Grid Turgay Yalcin, Muammer Ozdemir Adv. Sci. Technol. Eng. Syst. J. 2(3), 412-419 (2017); View Description A Highly-Secured Arithmetic Hiding cum Look-Up Table (AHLUT) based S-Box for AES-128 Implementation Ali Akbar Pammu, Kwen-Siong Chong, Bah-Hwee Gwee Adv. Sci. Technol. Eng. Syst. J. 2(3), 420-426 (2017); View Description Service Productivity and Complexity in Medical Rescue Services Markus Harlacher, Andreas Petz, Philipp Przybysz, Olivia Chaillié, Susanne Mütze-Niewöhner Adv. Sci. Technol. Eng. Syst. J. 2(3), 427-434 (2017); View Description Principal Component Analysis Application on Flavonoids Characterization Che Hafizah Che Noh, Nor Fadhillah Mohamed Azmin, Azura Amid Adv. Sci. Technol. Eng. Syst. J. 2(3), 435-440 (2017); View Description A Reconfigurable Metal-Plasma Yagi-Yuda Antenna for Microwave Applications Giulia Mansutti, Davide Melazzi, Antonio-Daniele Capobianco Adv. Sci. Technol. Eng. Syst. J. 2(3), 441-448 (2017); View Description Verifying the Detection Results of Impersonation Attacks in Service Clouds Sarra Alqahtani, Rose Gamble Adv. Sci. Technol. Eng. Syst. J. 2(3), 449-459 (2017); View Description Image Segmentation Using Fuzzy Inference System on YCbCr Color Model Alvaro Anzueto-Rios, Jose Antonio Moreno-Cadenas, Felipe Gómez-Castañeda, Sergio Garduza-Gonzalez Adv. Sci. Technol. Eng. Syst. J. 2(3), 460-468 (2017); View Description Segmented and Detailed Visualization of Anatomical Structures based on Augmented Reality for Health Education and Knowledge Discovery Isabel Cristina Siqueira da Silva, Gerson Klein, Denise Munchen Brandão Adv. Sci. Technol. Eng. Syst. J. 2(3), 469-478 (2017); View Description Intrusion detection in cloud computing based attack patterns and risk assessment Ben Charhi Youssef, Mannane Nada, Bendriss Elmehdi, Regragui Boubker Adv. Sci. Technol. Eng. Syst. J. 2(3), 479-484 (2017); View Description Optimal Sizing and Control Strategy of renewable hybrid systems PV-Diesel Generator-Battery: application to the case of Djanet city of Algeria Adel Yahiaoui, Khelifa Benmansour, Mohamed Tadjine Adv. Sci. Technol. Eng. Syst. J. 2(3), 485-491 (2017); View Description RFID Antenna Near-field Characterization Using a New 3D Magnetic Field Probe Kassem Jomaa, Fabien Ndagijimana, Hussam Ayad, Majida Fadlallah, Jalal Jomaah Adv. Sci. Technol. Eng. Syst. J. 2(3), 492-497 (2017); View Description Design, Fabrication and Testing of a Dual-Range XY Micro-Motion Stage Driven by Voice Coil Actuators Xavier Herpe, Matthew Dunnigan, Xianwen Kong Adv. Sci. Technol. Eng. Syst. J. 2(3), 498-504 (2017); View Description Self-Organizing Map based Feature Learning in Bio-Signal Processing Marwa Farouk Ibrahim Ibrahim, Adel Ali Al-Jumaily Adv. Sci. Technol. Eng. Syst. J. 2(3), 505-512 (2017); View Description A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances." Advances in Science, Technology and Engineering Systems Journal 2, no. 3 (June 2016): 513–19. http://dx.doi.org/10.25046/aj020366.

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48

Biran, Yahav, George Collins, Borky John M, and Joel Dubow. "Volume 2, Issue 3, Special issue on Recent Advances in Engineering Systems (Published Papers) Articles Transmit / Received Beamforming for Frequency Diverse Array with Symmetrical frequency offsets Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 1-6 (2017); View Description Detailed Analysis of Amplitude and Slope Diffraction Coefficients for knife-edge structure in S-UTD-CH Model Eray Arik, Mehmet Baris Tabakcioglu Adv. Sci. Technol. Eng. Syst. J. 2(3), 7-11 (2017); View Description Applications of Case Based Organizational Memory Supported by the PAbMM Architecture Martín, María de los Ángeles, Diván, Mario José Adv. Sci. Technol. Eng. Syst. J. 2(3), 12-23 (2017); View Description Low Probability of Interception Beampattern Using Frequency Diverse Array Antenna Shaddrack Yaw Nusenu Adv. Sci. Technol. Eng. Syst. J. 2(3), 24-29 (2017); View Description Zero Trust Cloud Networks using Transport Access Control and High Availability Optical Bypass Switching Casimer DeCusatis, Piradon Liengtiraphan, Anthony Sager Adv. Sci. Technol. Eng. Syst. J. 2(3), 30-35 (2017); View Description A Derived Metrics as a Measurement to Support Efficient Requirements Analysis and Release Management Indranil Nath Adv. Sci. Technol. Eng. Syst. J. 2(3), 36-40 (2017); View Description Feedback device of temperature sensation for a myoelectric prosthetic hand Yuki Ueda, Chiharu Ishii Adv. Sci. Technol. Eng. Syst. J. 2(3), 41-40 (2017); View Description Deep venous thrombus characterization: ultrasonography, elastography and scattering operator Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier Adv. Sci. Technol. Eng. Syst. J. 2(3), 48-59 (2017); View Description Improving customs’ border control by creating a reference database of cargo inspection X-ray images Selina Kolokytha, Alexander Flisch, Thomas Lüthi, Mathieu Plamondon, Adrian Schwaninger, Wicher Vasser, Diana Hardmeier, Marius Costin, Caroline Vienne, Frank Sukowski, Ulf Hassler, Irène Dorion, Najib Gadi, Serge Maitrejean, Abraham Marciano, Andrea Canonica, Eric Rochat, Ger Koomen, Micha Slegt Adv. Sci. Technol. Eng. Syst. J. 2(3), 60-66 (2017); View Description Aviation Navigation with Use of Polarimetric Technologies Arsen Klochan, Ali Al-Ammouri, Viktor Romanenko, Vladimir Tronko Adv. Sci. Technol. Eng. Syst. J. 2(3), 67-72 (2017); View Description Optimization of Multi-standard Transmitter Architecture Using Single-Double Conversion Technique Used for Rescue Operations Riadh Essaadali, Said Aliouane, Chokri Jebali and Ammar Kouki Adv. Sci. Technol. Eng. Syst. 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Gong, Zhenying, Tao Wang, Zhen Zhao, Xin Liu, and Yina Guo. "Accuracy electroencephalography classification by a regularized long short-term memory network." Journal of Vibration and Control, April 16, 2021, 107754632110093. http://dx.doi.org/10.1177/10775463211009373.

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The motor-based brain–computer interface is widely used in the exoskeleton reconstruction of patients with muscle weakness and to enhance the operating experience of somatosensory game customers through the combination of actions and electroencephalography signals. However, the recognition algorithms in traditional motor-based brain–computer interfaces have problems such as “brain–computer interface blindness” (recognition accuracy is less than 70%) and “one person one model.” In this study, a regularized long short-term memory algorithm and a hardware platform for gesture recognition by using the motor-based brain–computer interface are proposed. Experimental results show that the gesture recognition accuracy rate based on the motor brain–computer interface is up to 95.69%, which is significantly better than that of other algorithms. The proposed model enhances the applicability and generalization ability of the brain–computer interface, for which the practicability and effectiveness are verified.

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Cheng, Wei. "Translation and Big Data Technology: Challenges and Implications." Lebende Sprachen 62, no. 2 (January 11, 2017). http://dx.doi.org/10.1515/les-2017-0019.

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AbstractIn China, a growing market for language service along and rapidly-developing technology have ushered in a new wave of T&I software development. Despite translation tools’ wide range of applications and the current explosion of AI, translation memory and translation tools’ machine learning algorithms are far from satisfactory in providing language solutions. Unfortunately, an overreliance on technology has reduced some translators to machine operators or post-editors, as their traditional skills of critical thinking, analysis, and aesthetic pursuit have declined. By analyzing cases where machine translation gave incorrect suggestions, this article aims to explore the relationship between emerging technology and traditional professionalism in T&I. The author believes that technology and professionalism are not in a zero-sum game; technology does not deprive translators of job opportunities, but rather their analytical skills, critical thinking and aesthetic pursuits. While technology is going to streamline the more basic and repetitive aspects of translation work, in-depth cultural exchanges and communication will only be achievable by professional translators.

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Journal articles on the topic 'Game; Memory; Algorithms'

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