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Osamy, Walid, Ahmed M. Khedr, Ahmed A. El-Sawy, Ahmed Salim e Dilna Vijayan. "IPDCA: Intelligent Proficient Data Collection Approach for IoT-Enabled Wireless Sensor Networks in Smart Environments". Electronics 10, n.º 9 (22 de abril de 2021): 997. http://dx.doi.org/10.3390/electronics10090997.
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The Internet of Things (IoT) enables the interrelation of physical things and devices that can be accessed through the internet and it simply forms a single integrated network of various things. An IoT-facilitated smart city scenario spans several sectors, such as industrial applications, public transportation, smart grid, emergency services, health care, etc. In this paper, we propose an Intelligent Proficient Data Collection Approach (IPDCA) to deliver public data in a large-scale smart city set-up. IPDCA utilizes public vehicles as the mobile data collectors (D-collectors) that read (or collect) data from multiple Access Points (APs) and send them back to the central Base Station (BS). Moreover, IPDCA adopts a modified Bat algorithm for path finding of D-collectors, where we extend the Bat algorithm to solve our discrete optimization problem. Besides, for selecting D-collectors in smart city settings, we use a multi-objective fitness function that considers the count, travelled distance, and storage of D-collectors to ensure optimal use of resources. Efficiency of the proposed mechanism is proved through simulations.
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Senagi, Kennedy, e Henri E. Z. Tonnang. "A Novel Tightly Coupled Information System for Research Data Management". Electronics 11, n.º 19 (5 de outubro de 2022): 3196. http://dx.doi.org/10.3390/electronics11193196.
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Most research projects are data driven. However, many organizations lack proper information systems (IS) for managing data, that is, planning, collecting, analyzing, storing, archiving, and sharing for use and re-use. Many research institutions have disparate and fragmented data that make it difficult to uphold the FAIR (findable, accessible, interoperable, and reusable) data management principles. At the same time, there is minimal practice of open and reproducible science. To solve these challenges, we designed and implemented an IS architecture for research data management. Through it, we have a centralized platform for research data management. The IS has several software components that are configured and unified to communicate and share data. The software components are, namely, common ontology, data management plan, data collectors, and the data warehouse. Results show that the IS components have gained global traction, 56.3% of the total web hits came from news users, and 259 projects had metadata (and 17 of those also had data resources). Moreover, the IS aligned the institution’s scientific data resources to universal standards such as the FAIR principles of data management and at the same time showcased open data, open science, and reproducible science. Ultimately, the architecture can be adopted by other organizations to manage research data.
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Ahmed, Wasim, e Sergej Lugovic. "Social media analytics: analysis and visualisation of news diffusion using NodeXL". Online Information Review 43, n.º 1 (11 de fevereiro de 2019): 149–60. http://dx.doi.org/10.1108/oir-03-2018-0093.
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Purpose The purpose of this paper is to provide an overview of NodeXL in the context of news diffusion. Journalists often include a social media dimension in their stories but lack the tools to get digital photos of the virtual crowds about which they write. NodeXL is an easy to use tool for collecting, analysing, visualising and reporting on the patterns found in collections of connections in streams of social media. With a network map patterns emerge that highlight key people, groups, divisions and bridges, themes and related resources. Design/methodology/approach This study conducts a literature review of previous empirical work which has utilised NodeXL and highlights the potential of NodeXL to provide network insights of virtual crowds during emerging news events. It then develops a number of guidelines which can be utilised by news media teams to measure and map information diffusion during emerging news events. Findings One emergent software application known as NodeXL has allowed journalists to take “group photos” of the connections among a group of users on social media. It was found that a diverse range of disciplines utilise NodeXL in academic research. Furthermore, based on the features of NodeXL, a number of guidelines were developed which provide insight into how to measure and map emerging news events on Twitter. Social implications With a set of social media network images a journalist can cover a set of social media content streams and quickly grasp “situational awareness” of the shape of the crowd. Since social media popular support is often cited but not documented, NodeXL social media network maps can help journalists quickly document the social landscape utilising an innovative approach. Originality/value This is the first empirical study to review literature on NodeXL, and to provide insight into the value of network visualisations and analytics for the news media domain. Moreover, it is the first empirical study to develop guidelines that will act as a valuable resource for newsrooms looking to acquire insight into emerging news events from the stream of social media posts. In the era of fake news and automated accounts, i.e., bots the ability to highlight opinion leaders and ascertain their allegiances will be of importance in today’s news climate.
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Mardianto, Is, Dedy Sugiarto e Krisna Aditama Ashari. "The Elastic Stack Ability Test To Monitor Slowloris Attack on Digital Ocean Server". Ultimatics : Jurnal Teknik Informatika 13, n.º 2 (23 de janeiro de 2022): 120–26. http://dx.doi.org/10.31937/ti.v13i2.2209.
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Servers have a central role in computer network. The server is in charge of serving user requests with various types of services. Every server activity in handling these things will generate different types of logs. Information from this large amount of logs is often ignored and has not been widely used as material for analyzing the performance of the server itself. In this study, Elastic Stack is functioned as a system that handles upstream to downstream processes starting from collection, transformation, and storage as well as graphical visualization of the Nginx web server given an attack scenario in the form of massive incoming connection requests and server login access attempts. The Elastic Stack components used as log collectors are Filebeat and Metricbeat for system metric data. For testing attacks using the Slowloris tool which will consume web server resources. The results of the research that have been carried out are when there are 500 incoming connections, the web server can serve requests normally, at 1000 connections there are some packets that are not served, the server becomes unable to access when it reaches a total of 2000 incoming connections. Metric data in the form of CPU Usage and Memory Usage are affected, although not significantly. Identification of IP Address shows the source of the attack comes from Singapore, according to the domicile of the attacker's computer. All access data in the form of username, time, origin of region trying to enter the server are recorded by the system.
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Hamby, Rogan, e Andrea Buntz Neiman. "A tiny library with a million volumes: Open-source resource sharing with fulfillment interlibrary loan (ILL)". Information Services & Use 43, n.º 3-4 (15 de dezembro de 2023): 285–88. http://dx.doi.org/10.3233/isu-230222.
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his paper is based upon a lightning talk given at the NISO Plus conference on February 14, 2023 and it describes interlibrary Loan syste4m, Fulfillment, developed by the Equinox Open Library Initiative. A thriving resource-sharing consortium allows libraries to offer broader and deeper opportunities for individual learning and greater community equity. It unlocks access to additional copies beyond what an owning library has available, along with a broad range of content owned within the network, which provides a diverse collection for library users. Providing access to such a rich network of resources is the goal of Fulfillment, an open-source resource sharing system which breaks down barriers to sharing collections.
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Sulistyo, Wahyu Djoko, Wahyudi Deny Yudo, Jalani Azmi Bin Muhamad @Md., Putra Candra Kurnia e Hartono. "The Effectiveness of Laboratory Digitalization for 21st Century Learning". International Journal of Interactive Mobile Technologies (iJIM) 18, n.º 04 (27 de fevereiro de 2024): 48–64. http://dx.doi.org/10.3991/ijim.v18i04.46353.
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Learning resources are crucial and strategic elements that impact the accessibility of easy, fast, accurate, and affordable information in the era of Society 5.0. Learning resources must be adaptable to technological advancements. The history laboratory is a learning resource that must be transformed and adapted to address the aforementioned needs and problems as a solution. The extensive collection of owned items has the potential to support this. This paper describes the creation of a digital laboratory by utilizing collections from the UM History Department. The research employed the Research and Development (R&D) method, utilizing the ADDIE model, which includes the stages of analysis, design, development, implementation, and evaluation. The study presents findings on the importance of digitizing laboratories as educational resources and digital laboratory products for the UM History Department. This digital laboratory product consists of several features, including an e-book (book catalog), an e-repository (final project catalog), an e-museum (museology collection catalog), tool lending, and graduate assessment. The results of the validation and implementation tests demonstrate that the criteria are highly valid and extremely effective. These results demonstrate that the digital laboratory serves as a more effective and efficient learning resource that is easily accessible and usable for civil society 5.0.
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Garrido-Muñoz , Ismael, Arturo Montejo-Ráez , Fernando Martínez-Santiago e L. Alfonso Ureña-López . "A Survey on Bias in Deep NLP". Applied Sciences 11, n.º 7 (2 de abril de 2021): 3184. http://dx.doi.org/10.3390/app11073184.
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Deep neural networks are hegemonic approaches to many machine learning areas, including natural language processing (NLP). Thanks to the availability of large corpora collections and the capability of deep architectures to shape internal language mechanisms in self-supervised learning processes (also known as “pre-training”), versatile and performing models are released continuously for every new network design. These networks, somehow, learn a probability distribution of words and relations across the training collection used, inheriting the potential flaws, inconsistencies and biases contained in such a collection. As pre-trained models have been found to be very useful approaches to transfer learning, dealing with bias has become a relevant issue in this new scenario. We introduce bias in a formal way and explore how it has been treated in several networks, in terms of detection and correction. In addition, available resources are identified and a strategy to deal with bias in deep NLP is proposed.
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Kiejziewicz, Agnieszka. "Kolekcjonowanie popkultury. Kilka słów o archiwizacji anime i japońskich filmowych memorabiliach". Studia Filmoznawcze 42 (1 de agosto de 2022): 5–16. http://dx.doi.org/10.19195/0860-116x.42.1.
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The presented article concerns the issue of collecting film memorabilia, with a particular emphasis on the Japanese artefacts related to anime production. Beginning with a brief introduction to the differences between collections and archives, the author aims to present the current state of research on the categorization of popular culture memorabilia. The following parts of the article underline the importance of considering Japanese post-animation products as historical resources. Regarding the ways of presentation of selected works in galleries, the author provides such case-study examples of exhibitions as A World Is Born: The Emerging Arts and Designs in 1980s Japanese Animation (Singapore 2018, Stockholm 2019) and Proto Anime Cut — Spaces and Visions in Japanese Animation (International, 2011–2012). A significant part of the article is devoted to the description and analysis of the presence of Japanese anime memorabilia in European and Polish collections, which shows the rapid development of interest in collecting popular culture.
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Meelen, Marieke, Élie Roux e Nathan Hill. "Optimisation of the Largest Annotated Tibetan Corpus Combining Rule-based, Memory-based, and Deep-learning Methods". ACM Transactions on Asian and Low-Resource Language Information Processing 20, n.º 1 (abril de 2021): 1–11. http://dx.doi.org/10.1145/3409488.
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This article presents a pipeline that converts collections of Tibetan documents in plain text or XML into a fully segmented and POS-tagged corpus. We apply the pipeline to the large extent collection of the Buddhist Digital Resource Center. The semi-supervised methods presented here not only result in a new and improved version of the largest annotated Tibetan corpus to date, the integration of rule-based, memory-based, and neural-network methods also serves as a good example of how to overcome challenges of under-researched languages. The end-to-end accuracy of our entire automatic pipeline of 91.99% is high enough to make the resulting corpus a useful resource for both linguists and scholars of Tibetan studies.
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Ally, Juma. "Group-Based Data Offloading Techniques Assisted by D2D Communication in 5G Mobile Network". Tanzania Journal of Engineering and Technology 41, n.º 2 (30 de junho de 2022): 52–69. http://dx.doi.org/10.52339/tjet.v41i2.778.
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Machine type communication devices proposed as one of the substantial data collections in the 5G of wireless networks. However, the existing mobile communication network is not designed to handle massive access from the MTC devices instead of human type communication. In this context, we propose the device-to-device communication assisted a mobile terminal (smartphone) on data computing, focusing on data generated from a correlated source of machine type communication devices. We consider the scenario that the MTC devices after collecting the data will transmit to a smartphone for computing. With the limitation of computing resources at the smartphone, some data are offloaded to the nearby mobile edge-computing server. By adopting the sensing capability on MTC devices, we use a power exponential function to compute a correlation coefficient existing between the devices. Then we propose two grouping techniques K-Means and hierarchical clustering to combine only the MTC devices, which are spatially correlated. Based on this framework, we compare the energy consumption when all data processed locally at a smartphone or remotely at mobile edge computing server with optimal solution obtained by exhaustive search method. The results illustrated that; the proposed grouping technique reduce the energy consumption at a smartphone while satisfying a required completion time.
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Mikheeva, Vitalina Vladimirovna. "The use of Internet resources in historical research". Genesis: исторические исследования, n.º 3 (março de 2024): 152–65. http://dx.doi.org/10.25136/2409-868x.2024.3.70031.
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Computer technology has long been an integral part of our lives. The information resource of mankind is constantly growing, being updated and replenished, and benefits professionals of any specialization. Currently, the Internet has turned into a vast information space, into an immeasurable repository. In this repository, information of various kinds (scientific, business, educational, text, audio and video information) is publicly available and is constantly being enriched, there are virtual archives, libraries, and news feeds. The worldwide information network has connected not only individual researchers, but also numerous scientific organizations around the world. The object of the research is the analysis of Internet resources and the application of their potential in the field of historical knowledge. The subject of the research is the analysis of the Internet as a modern information environment of historical science, the use of Internet capabilities in historical research, as well as in historical education. The following methods were used in writing the work: historicism, historical-comparative, historical-genetic. This made it possible to discover potential Internet resources in the field of historical research. When writing the work, the author conducted a study, during which more than 300 sites and Web pages on the history of Russia and world history, located on various servers, were analyzed. The author gave a description of the main groups of sources represented on the Internet, and proposed his own classification of professional resources. He also focused on the characteristics of resources created by Academic organizations, the search for special articles and books, historical multimedia resources, collections of encyclopedias and dictionaries, anthologies, the use of blogs and forums, as well as file-sharing networks to search for historical information. Internet bibliographic resources, electronic catalogs, and meta-search bibliographic systems are also highlighted. Special attention is paid to the methods of more effective search for historical information, a new search concept is proposed.
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Pisarenko, I. V., K. N. Alekseev e A. K. Melnikov. "RESOURCE-INDEPENDENT REPRESENTATION OF SORTING NETWORKS IN Set@l PROGRAMMING LANGUAGE". Vestnik komp'iuternykh i informatsionnykh tekhnologii, n.º 185 (novembro de 2019): 53–60. http://dx.doi.org/10.14489/vkit.2019.11.pp.053-060.
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The development of scalable parallel programs for high-performance computer systems with reconfigurable and hybrid architectures is an important problem in the field of modern supercomputer engineering. Resource-independent applied software in the high-level COLAMO programming language describes only the limited number of the algorithm implementations for some configurations due to the inductive principle of the information graph forming. However, the creation of efficient resource-independent parallel software requires programming tool that supports both induction and reduction of calculations. To solve the problem, we propose the application of the Set@l programming language based on the aspect-oriented programming paradigm and set-theoretical code representation. According to the aspect-oriented concept, Set@l describes an algorithm for the problem solution and its parallelizing and other implementation features as separated program modules – source code and various aspects. The programming language being considered has much in common with traditional set-theory-based languages such as SETL, SETLX and SETL2, but Set@l introduces the essential classification of collections by parallelism, definiteness, orderliness and other criteria. In contrast to the high-level COLAMO programming language, Set@l specifies the full information graph of a computational problem in the absolutely parallel form and describes the reduction principles for all configurations of a computer system as independent aspects of a program. In this paper, we demonstrate that the aspect-oriented sorting program in the Set@l language defines different types of quadratic sorting networks and various methods of their partition and reduction.
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Wang, Qian, Chun Yan Yang e Chang Qing Cui. "The Research of Distributed Computer Network Technology Based on Web". Applied Mechanics and Materials 631-632 (setembro de 2014): 985–88. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.985.
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With the rapid development of network technology, network scale, the increasing complexity, traditional centralized network data collecting the methods already cannot adapt to this situation, a web-based distributed computing structure because of its many advantages are widely used. This paper proposes a construct Web application framework of distributed application system, combination of Web technology and the SNMP network management technology. Thereby, it can maintain the increasingly huge network system, ensure that all the good operation of the network resources, the management of the convenient and easy to use network resources.
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Rincon-Quintero, A. D., C. L. Sandoval-Rodriguez, C. A. Angulo-Julio, O. Lengerke, A. J. Rodriguez-Nieves e N. Y. Castillo-Leon. "A parabolic solar collector for harnessing solar energy in Bucaramanga, Colombia". Sustainable Engineering and Innovation 5, n.º 2 (11 de dezembro de 2023): 151–60. http://dx.doi.org/10.37868/sei.v5i2.id228.
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In this work, a solar energy collection system based on a parabolic solar collector adjusted to the conditions and availability of energy was designed to examine this type of collection device and evaluate the energy potential when installed in an educational institution. To do this, data from the historical series of solar radiation compiled by the POWER project (Prediction of Worldwide Energy Resources) were analyzed and compared with data from the Institute of Hydrology, Meteorology and Environmental Studies in Colombia (IDEAM).
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Korobtseva, N., L. Karshakova e M. Obetkovskaya. "Development of Digital Show Methodology". Bulletin of Science and Practice 10, n.º 5 (15 de maio de 2024): 408–16. http://dx.doi.org/10.33619/2414-2948/102/51.
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The article proposes a method for creating a digital display of a clothing collection using modern information technologies. The authors analyzed technologies that can be used to display the collection in a digital environment. Particular attention is paid to 3D modeling and animation, as well as the integration of virtual models and scenes into videos. An algorithm is proposed that includes the stages of creating the image of the collection and selecting avatars, animation of the process of passing models in designed clothes across the stage in three-dimensional space. The purpose of this work is to consider the features of using neural networks for generating images, online resources and three graphic editors: a general-purpose 3D editor Blender, a 3D editor for designing and visualizing clothing Clo3D and a program for color correction, editing and video processing DaVinci Resolve. The main task was to study the possibilities of these technological solutions for creating motion design for a virtual fashion show of a clothing collection. Development algorithms are described at different stages: from searching for an artistic image using neural networks and digital design to developing animation design and video post-processing. The research materials contribute to understanding the possibilities of digital design in the field of fashion. The described tools allow you to create realistic clothing models, demonstrate animation and fabric simulation, and present collections in a dynamic format. In conclusion, recommendations are offered for the use of computer graphics for the effective development of virtual screenings. The article is intended for specialists in the field of costume and fashion design, computer graphics, virtual reality, as well as for anyone interested in innovative approaches to the organization and presentation of digital products.
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Choi e Yi. "Neighbor Discovery Optimization for Big Data Analysis in Low-Power, Low-Cost Communication Networks". Symmetry 11, n.º 7 (26 de junho de 2019): 836. http://dx.doi.org/10.3390/sym11070836.
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Big data analysis generally consists of the gathering and processing of raw data and producing meaningful information from this data. These days, large collections of sensors, smart phones, and electronic devices are all connected in the network. One of the primary features of these devices is low-power consumption and low cost. Power consumption is one of the important research concerns in low-power, low-cost communication networks such as sensor networks. A primary feature of sensor networks is a distributed and autonomous system. Therefore, all network devices in this type of network maintain the network connectivity by themselves using limited energy resources. When they are deployed in the area of interest, the first step for neighbor discovery involves the identification of neighboring nodes for connection and communication. Most wireless sensors utilize a power-saving mechanism by powering on the system if it is off, and vice versa. The neighbor discovery process becomes a power-consuming task if two neighboring nodes do not know when their partner wakes up and sleeps. In this paper, we consider the optimization of the neighbor discovery to reduce the power consumption in wireless sensor networks and propose an energy-efficient neighbor discovery scheme by adapting symmetric block designs, combining block designs, and utilizing the concept of activating nodes based on the multiples of a specific number. The performance evaluation demonstrates that the proposed neighbor discovery algorithm outperforms other competitive approaches by analyzing the wasted awakening slots numerically.
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Pandolfo, Laura, e Luca Pulina. "Building the Semantic Layer of the Józef Piłsudski Digital Archive With an Ontology-Based Approach". International Journal on Semantic Web and Information Systems 17, n.º 4 (outubro de 2021): 1–21. http://dx.doi.org/10.4018/ijswis.2021100101.
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Using semantic web technologies is becoming an efficient way to overcome metadata storage and data integration problems in digital archives, thus enhancing the accuracy of the search process and leading to the retrieval of more relevant results. In this paper, the results of the implementation of the semantic layer of the Józef Piłsudski Institute of America digital archive are presented. In order to represent and integrate data about the archival collections housed by the institute, the authors developed arkivo, an ontology that accommodates the archival description of records but also provides a reference schema for publishing linked data. The authors describe the application of arkivo to the digitized archival collections of the institute, with emphasis on how these resources have been linked to external datasets in the linked data cloud. They also show the results of an experiment focused on the query answering task involving a state-of-the-art triple store system. The dataset related to the Piłsudski Institute archival collections has been made available for ontology benchmarking purposes.
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Oriekhova, Svetlana, e Nataliia Lynska. "Application of cloud technologies in the system of information and communication activities of libraries". Bulletin of Mariupol State University. Series: Philosophy, culture studies, sociology 9, n.º 18 (2019): 71–76. http://dx.doi.org/10.34079/2226-2849-2019-9-18-71-76.
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The use of libraries’modern cloud technologies in information and communication activity is analyzed. It is considered the problems of cloud technologies implementation in libraries documentation and information circulation. of Advantages and disadvantages of cloud service’simplementation are revealed. Authors outlined transition prospects in the future to the cloud network and cloud technologies’use in library activity. Cloud service providers allow us to lease computing power and disk space online. Clouds are physically located in data centers - buildings that house powerful computers that are connected by a single network. Such unified computers also contain the virtual servers that are required for cloud services to work. It has been found that for libraries as social institutions that are unable to acquire and administer their own data warehouses, the use of cloud technologies is a unique opportunity to improve their work. The use of cloud technology in libraries helps to save money on acquiring a fleet of computers and licensed software. Book collections are successfully stored in large amounts on "clouds", which significantly unloads the work of local library networks, an automated library information system and its own server. Cloud services include those that are used to learn how to work with web services and standard documents. In particular, the Microsoft 365 cloud platform provides the opportunity to practice known office applications through a web browser. It includes e-mail and calendars, standard Office applications. Security is achieved through One Drive backup and two-factor authentication with face or fingerprint recognition or PIN to further protect files. Given the complexity of using security tools in cloud repositories, digital literacy plays an important role in effective communication for library users and their employees. It is resoluted that cloud services giveto library staff additional opportunities for organizing management activities. This includes, in particular, multimedia web resource services use (photo services - Picasa, Panoramio; video services – Youtubevideo, geoservices - Google maps; workflow - Slideshare, Google Docs, SkyDrive, etc.), which are free to usefor any user so we can freelystore and use image, audio and video resources. These systems can be used in management practice not only as a source of accumulation of multimedia educational web resources, but also as a system of storing library video, photo and audio archives, as well as improving the processes of information service for readers in libraries.
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Hidayatulloh, Syarif, e Wahyudin Wahyudin. "Perancangan Wide Area Network (WAN) Dengan Teknologi Virtual Private Network (VPN)". Jurnal Teknik Komputer 5, n.º 1 (6 de fevereiro de 2019): 7–14. http://dx.doi.org/10.31294/jtk.v5i1.4552.
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The use of information technology and its use in collecting and processing data into information that is useful in decision making will play a role in determining the success of an organization or company in the future. This happened to PT. Jasa Cendekia Indonesia, the computer network that is owned has not met the needs of its employees. A good computer network is one that can serve sharing resources, data security, resources more efficiently and up-to-date information. Basically if a company can hold a computer network that serves the above for employees, of course it will make it easier for employees to do the work and improve the standards of the company itself. The proposed network built by the author for PT. Indonesian Scholar Services is a computer network built with Virtual Private Network technology. Because companies that have communication between the head office and branches that are good and safe, will be the capital for their companies in facing challenges in the era of globalization. Communication that is connected to a fast and secure computer network will make it easier for a company to supervise the activities of its company.
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Shen, Qianhe. "Detecting Collectable Resources on Computer Game Based on the Neural Network". Highlights in Science, Engineering and Technology 34 (28 de fevereiro de 2023): 226–31. http://dx.doi.org/10.54097/hset.v34i.5476.
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Image recognition and classification were put in used in many places in recent years thanks to the great progress in machine learning and neural networks. However, seldom evidence indicate applications of image recognition in computer games. Since games are gradually becoming part of peoples life, it is the time to put the focus on those who are unable to enjoy this entertainment. Nowadays computer games often include the element of collecting e.g. (materials or treasure). A program that could automatically mark those collectable objects would significantly improve the gaming experience for those who have disability in their eyes. In this work the game Destiny 2 was used for training and testing and training model chose was Yolov5. 1,500 of images were put into the data set and trained with 350 epochs. The model eventually achieved 0.82 in precision, 0.96 in recall and 0.91 in F1. It also gets the average mAP value of 0.93. These results can strongly prove that this model has the potential to be used in real scenarios.
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Pathak, Vinay, Karan Singh, Radha Raman Chandan, Sachin Kumar Gupta, Manoj Kumar, Shashi Bhushan e Sujith Jayaprakash. "Efficient Compression Sensing Mechanism Based WBAN System Using Blockchain". Security and Communication Networks 2023 (11 de maio de 2023): 1–12. http://dx.doi.org/10.1155/2023/8468745.
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The hybrid wireless sensor network is made up of Wireless Body Area Network (WBAN). Generally, many hospitals use cellular networks to support telemedicine. To provide the treatment to the patient on time, for this, an early diagnosis is required, for treatment. With the help of WBANs, collections and transmissions of essential biomedical data to monitor human health becomes easy. Compressor Sensing (CS) is an emerging signal compression/acquisition methodology that offers a protruding alternative to traditional signal acquisition. The proposed mechanism reduces message exchange overhead and enhances trust value estimation via response time and computational resources. It reduces cost and makes the system affordable to the patient. According to the results, the proposed scheme in terms of Compression Ratio (CR) is 18.18% to 88.11% better as compared to existing schemes. Also in terms of Percentage Root-Mean-Squared Difference (PRD) value, the proposed scheme is 18.18% to 34.21% better than with respect to existing schemes. The consensus for any new block is achieved in 24% less time than the Proof-of-Work (PoW) approach. The shallow CPU usage is required for the leader election mechanism. CPU utilization while the experiment lies in the range of 0.9% and 14%. While simulating a one-hour duration, the peak CPU utilization is 21%.
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Liu, Han. "Resource Mining Algorithm and IoT Applications for Career Literacy Oriented Civics Courses". Wireless Communications and Mobile Computing 2022 (7 de setembro de 2022): 1–15. http://dx.doi.org/10.1155/2022/2957193.
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The importance of vocational efficiency has gradually grown in stature as a result of rapid population expansion, rapid urbanization, rising competitiveness in the labor market, and the growing requirement for specialist workforce. Around the world, there are several overarching trends in vocational education and training, including increased use of technology, increased relevance of information and communications systems and changes in country demographics. The main aim of this paper is to discuss a resource mining algorithm for vocational literacy-oriented civics courses. The exploratory data comes from a nearby vocational database partitioned into three segments: a record database, a data database, and a video database. The data sublibrary stores data like word-related types, collections, characters, archives, and photographs, though the video sublibrary stores general media data from the play. Indexes for both the data and video sublibraries can be found in the index sublibrary. In our proposed strategy for gathering vocational literacy resources on an organization stage, we have consolidated RFID remote sensor innovation with a remote organization convention stack. We utilized QGA to order the vocational literacy resources on the organization stage in light of the discoveries of the resource assortment. Besides, in the stage’s vocational literacy materials, we joined the fluffy property highlight ID strategy with the semantic affiliation elements of successive examples. The trial results show that this approach outflanks customary techniques as far as resource mining time, mining result breadth, and mining result exactness, demonstrating that this strategy has useful application esteem.
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Lazim Lafta, Ali, e Ayad I. Abdulsada. "SMPP-CBIR: shorted and mixed aggregated image features for privacy-preserving content-based image retrieval". Bulletin of Electrical Engineering and Informatics 11, n.º 5 (1 de outubro de 2022): 2930–37. http://dx.doi.org/10.11591/eei.v11i5.4323.
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Thanks to recent breakthroughs in photographic and digital technology, enormous amounts of image data are generated daily. Many content-based image retrieval (CBIR) systems have been developed for searching image collections. However, these systems need more computer and storage resources that can be met by cloud servers, since they supply a lot of processing power at a reasonable price. The protection of users' personal information is a worry for image owners since cloud services are not exactly trustworthy. In this paper, we suggest and put into practice a CBIR (SMPP-CBIR) technique for searching and retrieving ciphertext information that protects security. Asymmetric scalar-product-preserving encryption process (ASPE) is used to preserve aggregated mixed feature vectors while still enabling computation between them to describe the related picture collection. The k-means clustering algorithm is used to recursively arrange all encrypted attributes into a tree index in order to speed up search times. The findings show that SMPP-CBIR is more scalable, more precise, and faster in indexing and retrieval than earlier systems.
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Wang, Bin. "Study on Changes of College English Teaching Method and Redefinition of Teachers’ Roles in the Computer Network Environment". International Journal of Emerging Technologies in Learning (iJET) 12, n.º 08 (1 de agosto de 2017): 137. http://dx.doi.org/10.3991/ijet.v12i08.7138.
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Through interviews and induction, this paper attempts to discuss the importance of college English teaching methods in the teaching process under the network context and point out issues like teachers’ inadequate awareness and abilities of collecting network resources and information and insufficient background monitoring on students’ study activities. Based on this, this paper proposes that college English teachers should free their minds, change their views and improve their network operation skills to know more about students’ study activities and update their knowledge bases to improve their own quality so as to redefine their roles under the network context.
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Alusi, G. H., A. C. Tan, J. C. Campos, A. Linney e A. Wright. "Tele-education: The virtual medical laboratory". Journal of Telemedicine and Telecare 3, n.º 1_suppl (junho de 1997): 79–81. http://dx.doi.org/10.1258/1357633971930481.
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The virtual medical laboratory (VML) was conceived to provide an Internet-accessible resource, offering access for clinicians and scientists to an invaluable data archive at the Institute of Laryngology and Otology, London. The Institute is home to the largest collection of temporal bone, laryngeal, skull and sinus sections in Europe. The skull and sinus collections include an extensive section consisting of animal material. These were contributions from zoos around the world. Over the last 50 years, samples have been carefully sectioned and stained by specialized technicians to produce histology slices of most regions of the head and neck. The aim of the project is to create a virtual medical laboratory, which will provide access to archived histological material as well as computerized tomography and magnetic resonance data. Central to this aim is the reconstruction of the internal anatomy of the temporal bone from two-dimensional histology slices, to create three-dimensional views that can be used for anatomical simulation and surgical training in otolaryngology. State-of-the-art three-dimensional reconstruction and rendering technology allows us to develop such a model. Computer-generated simulation could be made available to all hospitals in which otolaryngology is practised, via digital communication networks. We aim to develop core technology in our own specialty that is applicable to other fields of higher education, which have not been exposed to such modern teaching modalities. This has the potential to become an invaluable teaching resource for anatomists, surgeons and other scientists.
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Федотов, Анатолий Михайлович, e Юлия Викторовна Леонова. "Requirements for the prototype of the information resources management system in distributed information systems for the support of scientific research". Вычислительные технологии, n.º 5(23) (2 de novembro de 2018): 82–109. http://dx.doi.org/10.25743/ict.2018.23.5.008.
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Описаны технологические подходы, применяемые для создания распределенных информационных систем поддержки научных исследований. Рассмотрены архитектурные решения, разработанные для создания таких систем и принципы интеграции этих систем с внешними источниками. Определены функциональные требования к модели такой информационной системы, которые обусловлены, во-первых, информационными потребностями исследователей, а во-вторых, необходимостью обеспечения надежного и долговременного хранения информации. Рассмотрены правила представления и преобразования метаданных. Описан и реализован прототип такой системы. The article addresses the description of technological approaches used to create distributed information systems for supporting scientific research. We describe the developed architectural solutions which are intended to create such systems and the principles for integrating of these systems with the external sources. The functional requirements for the model of such an information system are determined. These requirements are determined, firstly, by the information needs of researchers, and secondly, by ensuring a reliable and long-term storage of information. The considered model of SIS is implemented in the form of a prototype of the Electronic Library Management System (ELMS IRIS). ELMS IRIS operates with electronic collections. The electronic collection is considered as a set of information objects, united on a semantic basis and having the same structure (data schema). An ELMS allows to work with two types of collections which are the catalogs and the thesauri. The rules of representation and transformation of metadata are discussed. In order to organize metadata exchange between repositories and a metadata server (as well as with other systems with an extended profile), a special service is created that converts metadata from the internal schema into other metadata schemes. The OAI-PMH service is implemented, which periodically synchronizes the metadata of the repository and the metadata server in accordance with the schedule in batch mode. To fill the “Main metadata catalog”, in accordance with the metadata schemas created, managed dictionaries are used from the reference support block. To ensure data interoperability, the application server based on ZooPARK-ZS is also implemented, which provides access to system metadata via Z39.50 and SRW/SRU protocols. The developed model can be used as a model of the system for working with documents related to scientific and educational activities, since it solves the main tasks for these systems which are to provide a system for reliable long-term storage of digital (electronic) documents while preserving all the semantic and functional characteristics of source documents as well as ensuring “transparent” search and access of users to documents. These actions are necessary both for familiarization and for the analysis of the facts contained therein; and organization of collection of information on remote digital repositories supporting protocols OAI-PMH, SRW/SRU, Z39.50.
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Xu, Xiaolong, Zijie Fang, Lianyong Qi, Xuyun Zhang, Qiang He e Xiaokang Zhou. "TripRes". ACM Transactions on Multimedia Computing, Communications, and Applications 17, n.º 2 (junho de 2021): 1–21. http://dx.doi.org/10.1145/3401979.
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The Internet of Vehicles (IoV) connects vehicles, roadside units (RSUs) and other intelligent objects, enabling data sharing among them, thereby improving the efficiency of urban traffic and safety. Currently, collections of multimedia content, generated by multimedia surveillance equipment, vehicles, and so on, are transmitted to edge servers for implementation, because edge computing is a formidable paradigm for accommodating multimedia services with low-latency resource provisioning. However, the uneven or discrete distribution of the traffic flow covered by edge servers negatively affects the service performance (e.g., overload and underload) of edge servers in multimedia IoV systems. Therefore, how to accurately schedule and dynamically reserve proper numbers of resources for multimedia services in edge servers is still challenging. To address this challenge, a traffic flow prediction driven resource reservation method, called TripRes, is developed in this article. Specifically, the city map is divided into different regions, and the edge servers in a region are treated as a “big edge server” to simplify the complex distribution of edge servers. Then, future traffic flows are predicted using the deep spatiotemporal residual network (ST-ResNet), and future traffic flows are used to estimate the amount of multimedia services each region needs to offload to the edge servers. With the number of services to be offloaded in each region, their offloading destinations are determined through latency-sensitive transmission path selection. Finally, the performance of TripRes is evaluated using real-world big data with over 100M multimedia surveillance records from RSUs in Nanjing China.
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Silva-Blancas, Victor Hugo, Hugo Jiménez-Hernández, Ana Marcela Herrera-Navarro, José M. Álvarez-Alvarado, Diana Margarita Córdova-Esparza e Juvenal Rodríguez-Reséndiz. "A Clustering and PL/SQL-Based Method for Assessing MLP-Kmeans Modeling". Computers 13, n.º 6 (9 de junho de 2024): 149. http://dx.doi.org/10.3390/computers13060149.
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With new high-performance server technology in data centers and bunkers, optimizing search engines to process time and resource consumption efficiently is necessary. The database query system, upheld by the standard SQL language, has maintained the same functional design since the advent of PL/SQL. This situation is caused by recent research focused on computer resource management, encryption, and security rather than improving data mining based on AI tools, machine learning (ML), and artificial neural networks (ANNs). This work presents a projected methodology integrating a multilayer perceptron (MLP) with Kmeans. This methodology is compared with traditional PL/SQL tools and aims to improve the database response time while outlining future advantages for ML and Kmeans in data processing. We propose a new corollary: hk→H=SSE(C),wherek>0and∃X, executed on application software querying data collections with more than 306 thousand records. This study produced a comparative table between PL/SQL and MLP-Kmeans based on three hypotheses: line query, group query, and total query. The results show that line query increased to 9 ms, group query increased from 88 to 2460 ms, and total query from 13 to 279 ms. Testing one methodology against the other not only shows the incremental fatigue and time consumption that training brings to database query but also that the complexity of the use of a neural network is capable of producing more precision results than the simple use of PL/SQL instructions, and this will be more important in the future for domain-specific problems.
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Singal, TL, e Rajvir Singh. "EVOLVING FRAMEWORK FOR IOT-BASED ENERGY EFFICIENT WIRELESS SENSOR NETWORKS FOR HEALTHCARE SERVICES". International Journal of Engineering Applied Sciences and Technology 7, n.º 3 (1 de julho de 2022): 296–305. http://dx.doi.org/10.33564/ijeast.2022.v07i03.042.
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The Internet-of-Things (IoT) is a system of interrelated computing devices having unique identifiers that enables to transfer data over a network without requiring human-to-computer or human-to-human interaction. With the rapid growth in embedded wireless computing devices with high-speed internet connectivity, the Wireless Sensor Networks (WSNs) for healthcare applications comprises of interconnected several tinypowered, wearable, wireless bio-sensors to provide an effective way of collecting vital health-related data. The emerging paradigm of IoT in smart healthcare system requires a specialized secure framework in order to enable real-time health monitoring, reliable diagnostics, effective treatment processes, and many other related aspects of healthcare system. In this paper, various aspects of energy consumption in IoT-based framework of WSNs for healthcare services are discussed. The framework for IoTbased healthcare network cater to upgraded microcontrollers, IoT gateway devices, various wireless and web technologies for IoT, variety of bio-sensors and data collectors, and secure communication protocols. Techniques to optimize the energy consumption in WSNs have been presented leading to energy efficient framework for WSNs suitable for healthcare systems.
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Dong, Rui. "An Effective Quantum Genetic Algorithm Based on Drama Resource Mining Using Wireless Sensing Technology". Scientific Programming 2021 (24 de junho de 2021): 1–12. http://dx.doi.org/10.1155/2021/4122372.
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Wireless sensor technology has penetrated various domains of today’s life and plays a vital role in the advanced technology. Numerous researchers have combined this outstanding technology with other fields such as resource mining, industry, healthcare, automobile system, gaming industry, and dramas. However, in traditional resource mining, long mining time leads to incomplete mining results along with low accuracy. In order to improve the effect of resource mining, we have proposed an effective Quantum Generic Algorithm (QGA) based on drama resource mining by using wireless sensor technology. In our proposed scheme, we have combined the RFID technology of wireless sensor with wireless network protocol stack for the purpose of collecting drama resources on the network platform. We have classified the drama resources on the network platform by using QGA based on the results of resources collection. Additionally, we have mined the semantic association features of frequent patterns of the drama resources on the platform and combined with the fuzzy attribute feature detection method. The experimental results show that this method is superior to the traditional methods in terms of resource mining time, mining results’ comprehensiveness, and mining results’ accuracy, which shows that this method has practical application value.
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Bilyk, Iryna I. "Crowdfunding platforms as a tool for additional financing of non-profit organizations". Socio-Economic Problems of the Modern Period of Ukraine, n.º 4(156) (2022): 3–6. http://dx.doi.org/10.36818/2071-4653-2022-4-1.
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The article analyzes crowdfunding as the method of innovative solutions outsourcing as well as the main tool of fundraising for non-profit organizations in terms of developing IT technologies and global access to Internet networks. Crowdfunding opens prospects for non-profit organizations in the mobilization of tangible and intangible resources under the circumstances of rapidly growing competitive markets. The development of information technologies and computer networks gives an opportunity to create new forms of financing as well as promote projects that allow connecting with like-minded people around the world. Moreover, it facilitates fundraising coordination. Crowdfunding, due to its online form, conducts its activities through social network sites and specialized crowdfunding platforms. The latter gives its users an opportunity to carry out financial collections in order to cover the budget of the corresponding project. Such ideas of financing are based on the presentation of the beneficiary’s project and idea to Internet users via one of the crowdfunding platforms, where the amount needed is indicated for the implementation of the project and the duration of the collection. The phenomenon of crowdfunding platforms is considered as fundraising for projects, which are performed by non-profit organizations due to a big number of payments from donors interested in a project. In other words, it is a form of financing of different types of projects by both local and global communities using advertising and specialized Internet portals. Crowdfunding platforms, as the new alternative of financing for non-profit organizations, can be used in many different ways, however, not all companies, as well as projects, fit into that. Fundamental principles of crowdfunding include openness, accessibility, progressiveness, and truthfulness of the information. The situation in the Ukrainian market of crowdfunding platforms was investigated and some of its functioning attributes were revealed: crowdfunding, if used strategically, helps non-profit organizations reach interaction, informs about jobs, shares messages about the organization, and expands a donor base in order to increase general funding. Therefore, non-profit organizations which activities are related to crowdfunding win due to popularization, advocacy, and increasing trust in crowdfunding platforms. It serves as a fundraising method for a wide range of stakeholders, including beneficiaries, board members, employees, and donors.
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Barkalov, Alexander, Larysa Titarenko e Małgorzata Mazurkiewicz. "Reducing Hardware in LUT-Based Mealy FSMs with Encoded Collections of Outputs". Electronics 11, n.º 20 (19 de outubro de 2022): 3389. http://dx.doi.org/10.3390/electronics11203389.
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A method is proposed that is focused on reducing the chip area occupied by logic elements creating the circuit of Mealy finite state machines (FSMs). The proposed method is aimed at FSM circuits implemented with internal resources of field-programmable gate arrays (FPGA). The required chip area is estimated by the number of look-up table (LUT) elements in a particular circuit. The method is based on mutual application of two methods of structural decomposition. The first of them is based on dividing the set of outputs and using unitary-maximum encoding of collections of FSM outputs. The second method is based on dividing the set of states by classes of compatible states. The optimization is achieved by replacing the maximum binary state codes by two-part codes proposed in this article. Each two-part state code consists of a code of a class including a particular state and a maximum binary code of this state inside a particular class. The proposed approach leads to three-level LUT-based Mealy FSM circuits. The first logic level generates three types of partial functions: unitary encoded outputs, variables encoding collections of outputs, and input memory functions. Each partial function is represented by a circuit including a single LUT. The LUTs from the second logic level generate final values of these functions. The LUTs from the third level implement outputs using collections of outputs. An example of synthesis applying the proposed method is discussed. The experiments were conducted using standard benchmark FSMs. Their results showed significant improving of the area occupied by an FSM circuit. The LUT count decreased on average by 9.49%. The positive side effect of the proposed method was increasing the value of the maximum operating frequency (on average, by 8.73%). The proposed method is advisable to use if a single-level LUT-based implementation of the FSM circuit is impossible.
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Gan, Keng Hoon, e Keat Keong Phang. "Finding target and constraint concepts for XML query construction". International Journal of Web Information Systems 11, n.º 4 (16 de novembro de 2015): 468–90. http://dx.doi.org/10.1108/ijwis-04-2015-0017.
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Purpose – This paper aims to focus on automatic selection of two important structural concepts required in an XML query, namely, target and constraint concepts, when given a keywords query. Due to the diversities of concepts used in XML resources, it is not easy to select a correct concept when constructing an XML query. Design/methodology/approach – In this paper, a Context-based Term Weighting model that performs term weighting based on part of documents. Each part represents a specific context, thus offering better capturing of concept and term relationship. For query time analysis, a Query Context Graph and two algorithms, namely, Select Target and Constraint (QC) and Select Target and Constraint (QCAS) are proposed to find the concepts for constructing XML query. Findings – Evaluations were performed using structured document for conference domain. For constraint concept selection, the approach CTX+TW achieved better result than its baseline, NCTX, when search term has ambiguous meanings by using context-based scoring for the concepts. CTX+TW also shows its stability on various scoring models like BM25, TFIEF and LM. For target concept selection, CTX+TW outperforms the standard baseline, SLCA, whereas it also records higher coverage than FCA, when structural keywords are used in query. Originality/value – The idea behind this approach is to capture the concepts required for term interpretation based on parts of the collections rather than the entire collection. This allows better selection of concepts, especially when a structured XML document consists many different types of information.
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Zheng, Jia, e Wei Hong. "Construction of Knowledge Graph of 3D Clothing Design Resources Based on Multimodal Clustering Network". Computational Intelligence and Neuroscience 2022 (2 de junho de 2022): 1–12. http://dx.doi.org/10.1155/2022/1168012.
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The construction of 3D design model is a hotspot of applied research in the fields of clothing functional design system teaching and display. The simple 3D clothing visualization postprocessing lacks interactive functions, which is a hot issue that needs to be solved urgently at present. Based on analyzing the existing clothing modeling technology, template technology, and fusion technology, and based on the multimodal clustering network theory, this paper proposes a 3D clothing design resource knowledge graph modeling method with multiple fusion of features and templates. The position of each joint point is converted into the coordinate system centered on the torso point in advance and normalized to avoid the problem that the relative position of the camera and the collector cannot be determined, and the shape of different collectors is different. The paper provides a multimodal clustering network intelligence method, illustrates the interoperability of users switching between different design networks in the seamless connection movement, and combines the hybrid intelligence algorithm with the fuzzy logic interpretation algorithm to solve the problems in the field of 3D clothing design service quality. During the simulation process, the research scheme builds a logical multimodal clustering network framework, which integrates compatibility access and global access partition fusion of style templates to achieve information extraction of clothing parts. The experimental results show that the realistic 3D clothing modeling can be achieved by layering the 3D clothing map, contour features, clothing size features, and color texture features with the modeling template. The developed ActiveX control is mounted on MSN, and the system is compatible. The performance and integration rate reached 77.1% and 89.7%, respectively, which effectively strengthened the practical role of the 3D clothing design system.
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Dyanto, Dyanto, e David Humala Sitorus. "Pengaruh Motivasi, Komunikasi, Dan Stres Kerja Terhadap Kepuasan Kerja Karyawan Bravo Engineering". Jesya 6, n.º 1 (19 de setembro de 2022): 92–101. http://dx.doi.org/10.36778/jesya.v6i1.876.
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Human resources management is all activity relate to the recognitions of the importance’s of work motivations which will affects communications on employees job satisfactions and minimized the occurrence of works stress problems for employees. , utilizing function and activities that ensuring that human resources are utilizing effective and or for the benefit of individuals, companies and society. This studies aims to determined the effects of motivations, communications and works stress on job satisfactions of employees of PT Bravo Engineering Batam. This researches designed using researches designed and quantitatives researches methods. The data collections techniques is by distributed questionnaires to 115 respondents. The results of this studies indicated that motivation, communication and work stress partial and simultant has a significants effects on employee job satisfactions. The results of the coefficient of determination test indicate that motivation, communication and work stress affect job satisfaction by 51,3 percent, while the rest is influenced by other variables not examined in this study.
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Telgkamp, Michael, Dirk Koschützki, Henning Schwöbbermeyer e Falk Schreiber. "Community-based Linking of Biological Network Resources: Databases, Formats and Tools". Journal of Integrative Bioinformatics 4, n.º 3 (1 de dezembro de 2007): 135–46. http://dx.doi.org/10.1515/jib-2007-71.
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Summary The analysis of biological networks is increasingly important in the life sciences and in particular in systems biology. Computer-based analysis tools are exploited for the investigation of these networks. However, to find relevant data sources can be a time-consuming task, access to information changes, frequently it is not obvious to a user which tools can be used in combination with specific data sources, and network data is often not available in a format directly usable by analysis tools.To assist in collecting information about biological network data sources, and to help in investigating possible combinations of data sources and analysis software, we created BiNCo-wiki. BiNCo-wiki is a wiki system that stores information related to biological networks and allows all users to add or modify this information in an easy way. The collaborative character of a wiki system supports easy sharing of information and allows the community-based extension of the information already stored in BiNCo-wiki. We describe the general structure and functionality of the system and its initial content. BiNCo-wiki is accessible, free of charge, at http://pgrc.ipk-gatersleben.de/BiNCO-wiki.
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Roy, Satyaki, Preetam Ghosh, Nirnay Ghosh e Sajal K. Das. "Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey". ACM Computing Surveys 54, n.º 8 (30 de novembro de 2022): 1–36. http://dx.doi.org/10.1145/3468266.
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The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.
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Roy, Satyaki, Preetam Ghosh, Nirnay Ghosh e Sajal K. Das. "Transcriptional Regulatory Network Topology with Applications to Bio-inspired Networking: A Survey". ACM Computing Surveys 54, n.º 8 (30 de novembro de 2022): 1–36. http://dx.doi.org/10.1145/3468266.
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The advent of the edge computing network paradigm places the computational and storage resources away from the data centers and closer to the edge of the network largely comprising the heterogeneous IoT devices collecting huge volumes of data. This paradigm has led to considerable improvement in network latency and bandwidth usage over the traditional cloud-centric paradigm. However, the next generation networks continue to be stymied by their inability to achieve adaptive, energy-efficient, timely data transfer in a dynamic and failure-prone environment—the very optimization challenges that are dealt with by biological networks as a consequence of millions of years of evolution. The transcriptional regulatory network (TRN) is a biological network whose innate topological robustness is a function of its underlying graph topology. In this article, we survey these properties of TRN and the metrics derived therefrom that lend themselves to the design of smart networking protocols and architectures. We then review a body of literature on bio-inspired networking solutions that leverage the stated properties of TRN. Finally, we present a vision for specific aspects of TRNs that may inspire future research directions in the fields of large-scale social and communication networks.
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Shao, Lei, Nan Liu e Hai Bin Zuo. "The Computer Control System of Heat Exchange Station Based on Wireless Remote Monitoring of GPRS-Internet". Applied Mechanics and Materials 391 (setembro de 2013): 493–96. http://dx.doi.org/10.4028/www.scientific.net/amm.391.493.
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Usually the heat exchange station mainly adopts human monitoring which does not only waste human resources but also has many hidden dangers. On some control parameter adjustment, manual adjustment has a certain deviation and it is difficult to achieve the ideal running effect. The paper uses PIC single chip microcomputer as the controller core and transmits the collecting data to the monitoring center through GPRS - Internet network. This real-time monitoring system can effectively solve the problem of uneven heating caused by artificial regulate and achieve long-distance wireless remote monitoring and automatic temperature adjustment. It also has the certain energy-saving effect.
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Demianenko, V. B. "Trends in the use of cloud computing technologies to create personalized learning trajectories for students of the Minor Academy of Sciences of Ukraine". CTE Workshop Proceedings 1 (21 de março de 2013): 84–86. http://dx.doi.org/10.55056/cte.139.
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In recent years, reform trends have been noticeable in the system of extracurricular education: the goal is to create a new system of education that promotes personal professional self-determination of children, their adaptation to life in a dynamic information society, development of creative abilities, and involvement in culture. Personality-oriented education is not the formation of a personality with predetermined properties, but the creation of favorable conditions for the full identification and development of personal functions of the student. Among the most fruitful applications of the computer Y. I. Mashbitz notes the importance of implementing problem-based learning; forming creative thinking of schoolchildren, their readiness for creative work. M.I. Zhaldak stresses that the use of ICTs in the learning process "should not be concerned only with the study of certain curriculum material, but above all with the all-round and harmonious development of students' personalities, their creative abilities". V. Yu. Bykov notes that in recent years, further dynamic development acquire means and technologies of information and communication networks, in particular, the Internet, forming a computer and technological platform of the educational environment of modern education, especially open. On this basis, the subject-technological organization of information educational space is carried out, the processes of accumulation and storage of various subject collections of electronic computing resources are put in order, equal access to them for students is provided, ICT-support of learning processes, scientific research and education management is significantly improved.
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Et. al., Vigneshwari K,. "Genetic Algorithm Based Fuzzy Local Informationc-Means (Gaflicm) Clustering Algorithm And Hybrid Kernel Convolution Neural Network (Hkcnn) With Distributed Processing Framework For Brain Mri Images". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, n.º 10 (28 de abril de 2021): 5639–56. http://dx.doi.org/10.17762/turcomat.v12i10.5375.
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Cancer is the large important origin of casualty in today world. Among many cancers, brain cancer has been becomes one of the lowest living rate. It is formed based on the brain tumor. However brain tumors are able to have diverse categories based on their shape, texture, and position. Appropriate identification and retrieval of the tumor types create potential the doctor to compose the right cure option and assist keep the patient's life. Image processing has gained wide attention in medical analysis and health in recently. In general image processing methods, brain Magnetic Resonance Imaging (MRI) image collections cannot be processed efficiently on one computer due to large collection sizes and high computational costs. Hence, parallel computing and distributed system has been performed increasingly for brain MRI images in recently. In this paper, a novel Medical Image Cloud Processing (MICP) based distributed processing framework is proposed for brain MRI images by lesser computational time. In this work, image preprocessing is done by using the Adaptive Median Filtering (AMF) and image enhancement by Histogram Equalization (HE). The proposed MICP framework includes of Static Medical Image Cloud Processing (SMICP) and Dynamic Medical Image Cloud Processing (DMICP). In MICP framework, SMICP consists of two methods called Pure-Image and Big-Image. These methods are integrated to Genetic Algorithm based Fuzzy Local Information C-Means-MapReduce (GAFLICM-MR) algorithm to attain more optimized design and higher effectiveness. The core design of GAFLICM-MR framework is to make use of the rich computing resources given by means of the distributed system consequently as to apply efficient parallel processing. GAFLICM algorithm is also used as brain tumor segmentation in MRI images. In MICP framework, DMICP is developed via a parallel processing process of the distributed system. For retrieval and detection of brain Magnetic MRIimages into normal and tumor, Hybrid Kernel Convolution Neural Network (HKCNN) is developed in this work. Finally the results of the HKCNN classifier are compared to other previous works like precision, recall, f-measure, accuracy, time and memory.
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Moscicka, Albina. "“GEOHeritage” - GIS Based Application for Movable Heritage". Geoinformatics FCE CTU 6 (21 de dezembro de 2011): 228–32. http://dx.doi.org/10.14311/gi.6.28.
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The paper will present the results of a research project „A methodology for mapping movable heritage”. This project, financed by the Polish Ministry of Science and Higher Education in 2008-2010, was realized by the Institute of Geodesy and Cartography in cooperation with the Research and Academic Computer Network (portal Polska.pl), the Central Archives of Historical Records and Department of Art History of the Wroclaw University. The idea of the project was to simplify access to digital movable cultural heritage by the use of spatial information. The main aspect of the project was to use a Geographic Information System (GIS) - as a technology and as a tool - to integrate different digital collections, present their content in one space and provide online access to them from one common level – from an online map. The essence of the research was to present on the online map movable monument as multi-spatial object. The base of this assumption is that most of monuments, especially movable ones, can have several places in the geographical space that are connected with them (several various space relations). As a rule archival documents were created in one place, describe the other, today can be kept in places far away from the place they were prepared, and what more the parts of the same collection can be kept in different archives. Moreover, one single document can be connected or have relations (typological, thematically, temporal, spatial) with other relations to the same or the other one. The reason for it is that documents concerning various places are housed in the same archive, various documents can present the same place or the place of creating particular document can be the place of housing another. In the project the basic source material was digital collections of original records. Their metadata defined in the international standards of monuments’ description were used for connecting digital monuments with the geographic space. With the use of these standards, the Internet application for presenting cultural heritage on the map was developed. It can be found at www.GEOHeritage.polska.pl (Polish version) and www.GEOHeritage.poland.pl (English version). The application is based on the Geographic Information System (GIS), and its functionality is mainly the elements of selecting the resources, presenting the documents on the map in different ways and finding their images. The paper will present methodological solutions necessary for building on-line map of movable heritage together with the functionality of the application.
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Kolovou, Lamprini T., e Constantine A. Chassomeris. "Information and e-learning services for the efficient management of allergy and asthma, employing an integrated environment monitoring network". Journal of Telecommunications and Information Technology, n.º 4 (30 de dezembro de 2005): 73–83. http://dx.doi.org/10.26636/jtit.2005.4.342.
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In this paper we present a distributed telematic platform which is implemented to support health information management and innovative services to people suffering from allergies, asthma and rhinitis. The developed system establishes a trans-European information network offering specialized services to health professionals, patients and the public, by collecting, processing and distributing specialized data and informational content. An integrated monitoring and reporting system of aero-allergens is used to collect Pan-European environmental data and produce allergy maps, forecasting and danger level alerts. Informational content and e-learning resources are also consolidated and combined with personalized health management services. Through the created network, health information is supplied to sufferers via WWW and SMS technologies, and informational and learning resources are offered to health professionals. Sets of services were implemented in pilot form and offered to real users for testing purposes. The results were encouraging towards expansion to fully blown service at a Pan-European level.
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Botchkaryov, A. "METHOD FOR DECENTRALIZED CONTROL OF ADAPTIVE DATA COLLECTION PROCESSES IN AUTONOMOUS DISTRIBUTED SYSTEMS". Computer systems and network 5, n.º 1 (16 de dezembro de 2023): 8–19. http://dx.doi.org/10.23939/csn2023.01.008.
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The problem of monitoring a computer network under conditions of limitations on the use of system resources and high requirements for the survivability of the monitoring system has been considered. An autonomous decentralized computer network monitoring system has been developed, consisting of a team of software agents. Each agent can operate in two modes: main mode and monitoring system management console mode. In the main mode, the agent collects information about the computer network. In management console mode, the agent provides the user with access to information collected by all agents and allows the user to execute commands to manage the monitoring system. The developed monitoring system allows you to obtain more reliable information about the operation of the network with greater efficiency under the conditions of limitations on the use of system resources specified by the user. The autonomous monitoring system is created on the basis of the concept of multi-agent systems, within which a software agent of the system has some initiative for planning and implementing monitoring scenarios. The operation of software agents implements methods for organizing adaptive processes for collecting information using the principles of self-organization and the concept of structural adaptation. A decentralized software architecture for an autonomous monitoring system without a control center has been proposed. This ensures high reliability and survivability of the monitoring system. The software architecture of the autonomous monitoring system implements the SMA application software interface and the corresponding software library, which allows you to collect statistical data on the operation of the computer network and its nodes. The implementation of a software agent and a management console for an autonomous computer network monitoring system has been considered. Key words: computer network monitoring, autonomous system, decentralized control, software agent
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Rogachev, Aleksey, e Tamara Mazaeva. "Neural Network Algorithms and Methods for Monitoring the Psychological State of Society During Epidemics". BIO Web of Conferences 29 (2021): 01008. http://dx.doi.org/10.1051/bioconf/20212901008.
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The article presents the issue of monitoring the sociopsychological state of society in the period of epidemics by means of neural network algorithms and methods. Publications of sociologists, psychologists, and philologists, who have created a number of methods for in-depth analysis of emotions and tonality of texts in the Internet media, including cognitive and interpretive decoding, are devoted to substantiating approaches and methods for studying the content of Internet content. The purpose of the study is to substantiate the methods and computer tools for studying the socio-psychological state of society in crisis situations, in particular epidemics, based on neural network technologies based on Internet resources. The article considers methodological approaches and particular methods of their computer implementation. It is shown that for the computer analysis of the psychological state of society in the context of the epidemic, it is necessary to adapt the methodology for designing neural network technologies, as well as systems for collecting and textual analysis of the content of electronic and Internet resources. An effective approach to creating such systems is embedding, which uses a dense vector representation of tokens in a multidimensional space, the dimension of which should be selected experimentally in the process of training and testing the developed artificial neural networks (ANN). For contextual neural network analysis, a multiclass-oriented ANN with regularization layers of the form “SpatialDropout1D”can be used. The neural network architecture can be built on fully connected layers with an activation function of the “ReLU” type. The scientific and applied significance of the results of neural network analysis based on Internet resources is the possibility of obtaining classified assessments and segmentation of target information about the psychological state of society during periods of epidemics. This information can be used to effectively counter information threats to society.
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Yi-Wei Ma, Yi-Wei Ma, Jiann-Liang Chen Yi-Wei Ma, Yu-Liang Tang Jiann-Liang Chen e Kuan-Hung Lai Yu-Liang Tang. "Towards Adaptive Network Resource Orchestration for Cognitive Radio Networks". 網際網路技術學刊 23, n.º 5 (setembro de 2022): 1087–97. http://dx.doi.org/10.53106/160792642022092305017.
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<p>This work proposes an adaptive resource orchestration system for a Wireless Local Area Network (WLAN) that is based on the operating principle of Cognitive Radio (CR) technology. By collecting environmental parameters, including the retransmission rate and the channel occupancy rate, the proposed system has “knowledge” of overall transmission behavior and can regulate transmission resources. An Adaptive Connection Assignment (ACA) mechanism is proposed for end devices; it find out target end devices with poor transmission performance, analyzes their alternative Access Point (AP) availability and causes them to change connections to improve transmission performance. An Adaptive Channel Utilization (ACU) mechanism is designed for APs to identify a target AP that is suffering from interference, to analyze its alternative channel availability and to require it to change its working channel to improve transmission efficiency. Results of simulations of various scenarios indicate that the throughput of end devices is increased by 15 to 24%, the throughput of APs is increased by 6 to 47% and the retransmission rate of APs is reduced by 0.4 to 5.3%.</p> <p> </p>
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Kumar, Sanjeev, e Nandini Dutta. "Weaving a knowledge tapestry of traditional crafts for modern fashion designers: an Indian experience". Art Libraries Journal 36, n.º 2 (2011): 17–24. http://dx.doi.org/10.1017/s0307472200016874.
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Design innovations in India’s fashion products result from a fusion of modern technologies and traditional craft skills. This paper highlights the role of the National Resource Centre and the network of resource centres of the National Institute of Fashion Technology in collecting and preserving heritage resources using computer technology. Plans for a National Design Repository and for Shilpakala Jnana Kosha, a digital repository for the tacit craft knowledge of artisans, share the objectives of preserving endangered traditional skills, supporting a process of revival and optimising the use of traditional crafts in contemporary fashion design.
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Xu, Lijuan, e Lihong Zhang. "Construction of the Rule of Law System of Marine Ecological Environment Protection under the Background of Wireless Network Information Fusion". Wireless Communications and Mobile Computing 2021 (15 de outubro de 2021): 1–12. http://dx.doi.org/10.1155/2021/1611707.
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With the rapid development of my country’s marine economy, human society is demanding more and more marine resources and space, resulting in serious damage to the marine ecological environment. In order to protect the marine ecology and improve the sustainable development of marine resources, this paper studies the legal system of marine ecological environmental protection based on the background of wireless network information fusion. By studying the status quo of several well-known marine ports and ecological environment in China, building a wireless network information fusion platform, integrating wireless network information into marine ecological surveys, collecting data through WSN nodes, and comparing wireless network information fusion with traditional methods, the efficiency of marine ecological environmental protection and the identification of marine pollution methods in different periods of time coordinate the rapid economic development and build a sustainable marine ecology. The results of the study found that the monitoring efficiency based on wireless network information fusion is more than 25% higher than the traditional monitoring method, and the recognition efficiency after 3 months is still more than 20% higher than the traditional method. This shows that information fusion in wireless networks can play a key role in the construction of a legal system for marine ecological and environmental protection.
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Zamani, Hamed. "Neural models for information retrieval without labeled data". ACM SIGIR Forum 53, n.º 2 (dezembro de 2019): 104–5. http://dx.doi.org/10.1145/3458553.3458569.
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Recent developments of machine learning models, and in particular deep neural networks, have yielded significant improvements on several computer vision, natural language processing, and speech recognition tasks. Progress with information retrieval (IR) tasks has been slower, however, due to the lack of large-scale training data as well as neural network models specifically designed for effective information retrieval [9]. In this dissertation, we address these two issues by introducing task-specific neural network architectures for a set of IR tasks and proposing novel unsupervised or weakly supervised solutions for training the models. The proposed learning solutions do not require labeled training data. Instead, in our weak supervision approach, neural models are trained on a large set of noisy and biased training data obtained from external resources, existing models, or heuristics. We first introduce relevance-based embedding models [3] that learn distributed representations for words and queries. We show that the learned representations can be effectively employed for a set of IR tasks, including query expansion, pseudo-relevance feedback, and query classification [1, 2]. We further propose a standalone learning to rank model based on deep neural networks [5, 8]. Our model learns a sparse representation for queries and documents. This enables us to perform efficient retrieval by constructing an inverted index in the learned semantic space. Our model outperforms state-of-the-art retrieval models, while performing as efficiently as term matching retrieval models. We additionally propose a neural network framework for predicting the performance of a retrieval model for a given query [7]. Inspired by existing query performance prediction models, our framework integrates several information sources, such as retrieval score distribution and term distribution in the top retrieved documents. This leads to state-of-the-art results for the performance prediction task on various standard collections. We finally bridge the gap between retrieval and recommendation models, as the two key components in most information systems. Search and recommendation often share the same goal: helping people get the information they need at the right time. Therefore, joint modeling and optimization of search engines and recommender systems could potentially benefit both systems [4]. In more detail, we introduce a retrieval model that is trained using user-item interaction (e.g., recommendation data), with no need to query-document relevance information for training [6]. Our solutions and findings in this dissertation smooth the path towards learning efficient and effective models for various information retrieval and related tasks, especially when large-scale training data is not available.
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Dai, Xianlong, Guang Cheng, Ziyang Yu, Ruixing Zhu e Yali Yuan. "MSLCFinder: An Algorithm in Limited Resources Environment for Finding Top-k Elephant Flows". Applied Sciences 13, n.º 1 (31 de dezembro de 2022): 575. http://dx.doi.org/10.3390/app13010575.
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Encrypted traffic accounts for 95% of the total traffic in the backbone network environment with Tbps bandwidth. As network traffic becomes more and more encrypted and link rates increase in modern networks, the measurement of encrypted traffic relies more on collecting and analyzing massive network traffic data that can be separated from the support of high-speed network traffic measurement technology. Finding top-k elephant flows is a critical task with many applications in congestion control, anomaly detection, and traffic engineering. Owing to this, designing accurate and fast algorithms for online identification of elephant flows becomes more and more challenging. Existing methods either use large-size counters, i.e., 20 bit, to prevent overflows when recording flow sizes or require significant space overhead to measure the sizes of all flows. Thus, we adopt a novel strategy, called count-with-uth-level-sampling, in this paper, to find top-k elephant flows in limited resource environments. Moreover, the proposed algorithm, called MSLCFinder, incurs lightweight counter and uth-level multi-sampling with small, constant processing for millions of flows. Experimental results show that MSLCFinder can achieve more than 97% precision with an extremely limited hardware resource. Compared to the state-of-the-art, our method realizes the statistics and filtering of millions of data streams with less memory.