Journal articles on the topic 'Communication Complexity Scale'
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Brady, Nancy C., Kandace Fleming, Kathy Thiemann-Bourque, Lesley Olswang, Patricia Dowden, Muriel D. Saunders, and Janet Marquis. "Development of the Communication Complexity Scale." American Journal of Speech-Language Pathology 21, no. 1 (February 2012): 16–28. http://dx.doi.org/10.1044/1058-0360(2011/10-0099).
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Brady, Nancy C., Kandace Fleming, Rebecca Swinburne Romine, Alison Holbrook, Kristen Muller, and Connie Kasari. "Concurrent Validity and Reliability for the Communication Complexity Scale." American Journal of Speech-Language Pathology 27, no. 1 (February 6, 2018): 237–46. http://dx.doi.org/10.1044/2017_ajslp-17-0106.
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Purpose The Communication Complexity Scale (CCS; Brady et al., 2012) was created to fill a void in measures of expressive communication skills in individuals who communicate primarily with presymbolic or early symbolic means. CCS scores reflect expressive communication observed during interactive communication contexts. Method Two studies were completed to examine the reliability and validity of the revised CCS scores. Participants in both studies had minimal verbal skills (i.e., produced less than 20 functional words). Study 1 examined interobserver agreement, test–retest reliability, and concurrent validity for 239 participants with intellectual disabilities between the ages of 3–66 years, assessed with the protocol developed at the University of Kansas (KU CCS). CCS scores were compared with scores from the Vineland Adaptive Behavior Scales–Second Edition (Sparrow, Cicchetti, & Balla, 2005) and the Communication Matrix (Rowland & Fried-Oken, 2010). Study 2 examined the reliability and concurrent validity for CCS scores derived from 110 children (chronological age = 3–9) with autism from diverse backgrounds. These children were assessed with the Early Social Communication Scale (Mundy et al., 2003). CCS scores were compared with rates of communication derived from the Early Social Communication Scale. Results CCS scores were moderately correlated with scores from existing measures of early communication. In addition, CCS scores from different raters were reliable, and test–retest scores were highly similar. Conclusions These findings support the validity and reliability of the CCS when used with individuals across a wide range of ages and with various types of disabilities. The CCS can be used in research and clinical practice to describe extant communication levels in individuals with minimal verbal skills.
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Atwood, Erin, Nancy C. Brady, and Amy Esplund. "Measuring Early Communication in Spanish Speaking Children: The Communication Complexity Scale in Peru." International Journal of Speech & Language Pathology and Audiology 3, no. 1 (April 30, 2015): 9–19. http://dx.doi.org/10.12970/2311-1917.2015.03.01.2.
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Qian, Kun, Wen-Qin Wang, and Huaizong Shao. "Low-Complexity Transmit Antenna Selection and Beamforming for Large-Scale MIMO Communications." International Journal of Antennas and Propagation 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/159375.
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Transmit antenna selection plays an important role in large-scale multiple-input multiple-output (MIMO) communications, but optimal large-scale MIMO antenna selection is a technical challenge. Exhaustive search is often employed in antenna selection, but it cannot be efficiently implemented in large-scale MIMO communication systems due to its prohibitive high computation complexity. This paper proposes a low-complexity interactive multiple-parameter optimization method for joint transmit antenna selection and beamforming in large-scale MIMO communication systems. The objective is to jointly maximize the channel outrage capacity and signal-to-noise (SNR) performance and minimize the mean square error in transmit antenna selection and minimum variance distortionless response (MVDR) beamforming without exhaustive search. The effectiveness of all the proposed methods is verified by extensive simulation results. It is shown that the required antenna selection processing time of the proposed method does not increase along with the increase of selected antennas, but the computation complexity of conventional exhaustive search method will significantly increase when large-scale antennas are employed in the system. This is particularly useful in antenna selection for large-scale MIMO communication systems.
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Brady, Nancy C., Rebecca E. Swinburne Romine, Alison Holbrook, Kandace K. Fleming, and Connie Kasari. "Measuring Change in the Communication Skills of Children With Autism Spectrum Disorder Using the Communication Complexity Scale." American Journal on Intellectual and Developmental Disabilities 125, no. 6 (November 1, 2020): 481–92. http://dx.doi.org/10.1352/1944-7558-125.6.481.
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Abstract Changes in minimal verbal communication by children with autism spectrum disorder (ASD) were measured with the Communication Complexity Scale (CCS) and other communication assessments. The CCS measures complexity of preverbal and beginning verbal communication used to communicate behavior regulation and joint attention. The purpose was to investigate if the CCS was responsive to changes associated with a behavioral intervention aimed at improving communication skills. Changes were detected with CCS scores, rates of initiating joint attention, and the Mullen Scales of Early Learning (MSEL) Expressive Language subscale. Significant changes in CCS scores were also detected for a subgroup of participants who did not show significant changes on the MSEL Expressive Language subscale, demonstrating that CCS scores are sensitive to changes associated with a behavioral intervention.
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Pandurangan, Gopal, Peter Robinson, and Michele Scquizzato. "On the Distributed Complexity of Large-Scale Graph Computations." ACM Transactions on Parallel Computing 8, no. 2 (June 30, 2021): 1–28. http://dx.doi.org/10.1145/3460900.
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Motivated by the increasing need to understand the distributed algorithmic foundations of large-scale graph computations, we study some fundamental graph problems in a message-passing model for distributed computing where k ≥ 2 machines jointly perform computations on graphs with n nodes (typically, n >> k). The input graph is assumed to be initially randomly partitioned among the k machines, a common implementation in many real-world systems. Communication is point-to-point, and the goal is to minimize the number of communication rounds of the computation. Our main contribution is the General Lower Bound Theorem , a theorem that can be used to show non-trivial lower bounds on the round complexity of distributed large-scale data computations. This result is established via an information-theoretic approach that relates the round complexity to the minimal amount of information required by machines to solve the problem. Our approach is generic, and this theorem can be used in a “cookbook” fashion to show distributed lower bounds for several problems, including non-graph problems. We present two applications by showing (almost) tight lower bounds on the round complexity of two fundamental graph problems, namely, PageRank computation and triangle enumeration . These applications show that our approach can yield lower bounds for problems where the application of communication complexity techniques seems not obvious or gives weak bounds, including and especially under a stochastic partition of the input. We then present distributed algorithms for PageRank and triangle enumeration with a round complexity that (almost) matches the respective lower bounds; these algorithms exhibit a round complexity that scales superlinearly in k , improving significantly over previous results [Klauck et al., SODA 2015]. Specifically, we show the following results: PageRank: We show a lower bound of Ὼ(n/k 2 ) rounds and present a distributed algorithm that computes an approximation of the PageRank of all the nodes of a graph in Õ(n/k 2 ) rounds. Triangle enumeration: We show that there exist graphs with m edges where any distributed algorithm requires Ὼ(m/k 5/3 ) rounds. This result also implies the first non-trivial lower bound of Ὼ(n 1/3 ) rounds for the congested clique model, which is tight up to logarithmic factors. We then present a distributed algorithm that enumerates all the triangles of a graph in Õ(m/k 5/3 + n/k 4/3 ) rounds.
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Zhang, Bo, Yu Fei Wang, Tao Zhang, and Yuan Yuan Ma. "A Key Management Scheme for Smart Grid Wireless Terminals." Applied Mechanics and Materials 442 (October 2013): 501–6. http://dx.doi.org/10.4028/www.scientific.net/amm.442.501.
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With the large-scale construction of smart grid, smart grid terminals widely using wireless access technology to communicate to the power systems. For ensuring the communication security, pair-wise key pre-distribution scheme is widely used, however, which introduces the complexity of key management, and insufficient security problems. According to the smart grid terminals wireless communication features, proposes an intelligent grid wireless terminal online key management scheme, which is based on the t rank binary symmetric polynomial and fully homomorphic encryption algorithm. This scheme make the communication key could be established with a few parameters between the communicating parties, which reduces the complexity of key predistribution and the amount of calculation. Moreover, the whole process of the key generation is encrypted by fully homomorphic encryption algorithm, effectively enhances the security of the scheme.
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Fleming, Kandace K., and Nancy C. Brady. "Task and Participant Variables Predict Communication Complexity Scale (CCS) Scores: Closer Examination of the CCS." American Journal on Intellectual and Developmental Disabilities 124, no. 6 (November 1, 2019): 483–96. http://dx.doi.org/10.1352/1944-7558-124.6.483.
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Abstract Communication Complexity Scale (CCS) scores for 269 minimally verbal participants were examined to determine if communicator behavior and task and communicator characteristics were related to scores in a manner consistent with theoretical and research evidence expectations. Each participant completed an interactive assessment with 6 joint attention tasks and 6 behavior regulation tasks. Caregivers completed the Vineland Adaptive Behavior Scales II. Results indicated (a) joint attention tasks yielded lower scores than behavior regulation tasks, (b) older participants had lower scores, (c) individuals with autism spectrum disorder scored more similarly than those without, (d) the difference between joint attention and behavior regulation scores was greater for the autism spectrum disorder group, and (e) adaptive behavior was significantly positively related to complexity scores.
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Cakir, I., H. D. Kaya, I. Dikmen, G. Atasoy, and M. T. Birgonul. "An Exploratory Study on Communication Complexity in Mega Construction Projects." IOP Conference Series: Earth and Environmental Science 1101, no. 4 (November 1, 2022): 042045. http://dx.doi.org/10.1088/1755-1315/1101/4/042045.
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Abstract Complexity is the property of a project that makes it difficult to understand, foresee and control its behaviour due to interrelatedness between various project attributes such as tasks, parties, disciplines, and interfaces. Project complexity is an inherent part of mega construction projects due to their large scale, long period, the multiplicity of disciplines, the high number of stakeholders, multi-nationality, and high level of public attention, as well as political interest. This paper depicts findings of a research project that aims to identify characteristics of and factors that contribute to project complexity by referring to the experiences of professionals involved in mega construction projects. For this purpose, data has been collected by interviewing 18 participants from 11 mega construction projects. Communication complexity, which reflects the amount of distributed communication channels between various stakeholders, has been identified as one of the major drivers of project complexity in megaprojects. Based on literature and semi-structured interview findings, a causal structure to represent communication complexity comprising of three components, which are; project, stakeholders, and communication management, was developed. The causal map, which represents the opinions of a limited number of experts, cannot be generalised; however, it can provide useful insights about drivers of communication complexity that can be used to develop strategies to manage complexity.
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Nikodem, Maciej, Mariusz Slabicki, and Marek Bawiec. "Efficient Communication Scheme for Bluetooth Low Energy in Large Scale Applications." Sensors 20, no. 21 (November 8, 2020): 6371. http://dx.doi.org/10.3390/s20216371.
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The use of Bluetooth Low Energy (BLE) in the Internet-of-Things (IoT) applications has become widespread and popular. This has resulted in the increased number of deployed BLE devices. To ensure energy efficiency, applications use connectionless communication where nodes broadcast information using advertisement messages. As the BLE devices compete for access to spectrum, collisions are inevitable and methods that improve device coexistence are required. This paper proposes a connectionless communication scheme for BLE that improves communication efficiency in IoT applications where a large number of BLE nodes operate in the same area and communicate simultaneously to a central server. The proposed scheme is based on an active scanning mode and is compared with a typical application where passive scanning mode is used. The evaluation is based on numerical simulations and real-life evaluation of a network containing 150 devices. The presented scheme significantly reduces the number of messages transmitted by each node and decreases packet loss ratio. It also improves the energy efficiency and preserves the battery of BLE nodes as they transmit fewer radio messages and effectively spent less time actively communicating. The proposed connectionless BLE communication scheme can be applied to a large variety of IoT applications improving their performance and coexistence with other devices operating in the 2.4 GHz band. Additionally, the implementation complexity and costs of the proposed communication scheme are negligible.
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Mohammad Othman, Saman, and Salah Mohammed Salih. "Complexity of Mental Representation: A Cognitive Pragmatics Perspective." Journal of University of Raparin 8, no. 3 (September 29, 2021): 464–79. http://dx.doi.org/10.26750/vol(8).no(3).paper22.
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This article attempts to elucidate the meaning construction process, mental states and mental relations, communicative intentions, and action plans and thereby to explore the complexity of mental representations from a purely cognitive pragmatics perspective. It also attempts to reevaluate the violations of cooperative principle and maxims.
Cooperation, mental states and intentionality are the three basic tools for any communication process. Mental states are either conscious or unconscious. They are emotional and cognitive which include common attention, shared belief, and consciousness. Three different types of beliefs are differentiated: individual, common and shared. Intentionality is the relationship between mental acts and the external world. Every mental phenomenon has content and it is directed at an object. Two fundamental distinct meanings are attributed to the concept of intentionality: direction and deliberateness. Intentionality can be conceived of through communicative intentions and action plans.
The main concepts of communication, namely, cooperation, sharedness and intentionality are indispensable concepts to understand the process of comprehension and reconstruction of response in communication. Without rich shared knowledge, the inferential chain in non-standard communication becomes lengthy and laborious. Other possibilities arise due to the absence of the fundamental concepts, one of which is failure of communication. Any mental process can be envisaged in terms of steps starting with the expression of an act, moving through speaker meaning, to the communicative effect, then to the reaction it creates and finally the production of overt communicative response.
The paper examines the scale of complexity of mental representation and shows the underlying processes required in meaning construction. Additionally, the difference between standard and non-standard communication is presented in terms of complexity of inferential processes needed for each two different cases in communication.
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Shen, Shuheng, Yifei Cheng, Jingchang Liu, and Linli Xu. "STL-SGD: Speeding Up Local SGD with Stagewise Communication Period." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 11 (May 18, 2021): 9576–84. http://dx.doi.org/10.1609/aaai.v35i11.17153.
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Distributed parallel stochastic gradient descent algorithms are workhorses for large scale machine learning tasks. Among them, local stochastic gradient descent (Local SGD) has attracted significant attention due to its low communication complexity. Previous studies prove that the communication complexity of Local SGD with a fixed or an adaptive communication period is in the order of O (N3/2 T1/2) and O (N3/4 T3/4) when the data distributions on clients are identical (IID) or otherwise (Non-IID), where N is the number of clients and T is the number of iterations. In this paper, to accelerate the convergence by reducing the communication complexity, we propose STagewise Local SGD (STL-SGD), which increases the communication period gradually along with decreasing learning rate. We prove that STL-SGD can keep the same convergence rate and linear speedup as mini-batch SGD. In addition, as the benefit of increasing the communication period, when the objective is strongly convex or satisfies the Polyak-Lojasiewicz condition, the communication complexity of STL-SGD is O (N log T ) and O (N1/2 T1/2) for the IID case and the Non-IID case respectively, achieving significant improvements over Local SGD. Experiments on both convex and non-convex problems demonstrate the superior performance of STL-SGD.
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Galih, Savitri, ., and . "Low Complexity Interference Alignment for Distributed Large-Scale MIMO Hardware Architecture and Implementation for 5G Communication." International Journal of Engineering & Technology 7, no. 4.33 (December 9, 2018): 208. http://dx.doi.org/10.14419/ijet.v7i4.33.23561.
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Massive MIMO or Large Scale MIMO is a promising solution for achieving superior data rates in 5G communication systems. However, it has limitation in term of scalability and coverage for users that has highly spatial separation. Distributed massive MIMO is expected to enhance these drawbacks. One main problem arises in this scheme is the MIMO interference channel condition that can be copied by interference alignment algorithm. The main consideration for interference alignment algorithm in distributed Massive MIMO is to achieve low complexity precoding to eliminate interference channel condition and to design efficient hardware architecture for its implementation. Previous research regarding IA for Distributed Massive MIMO indicate that the complexity issues is still not widely discussed. This paper proposed the low complexity IA scheme for large scale MIMO system based on limited interferer and the implementation of low cost interference alignment and wireless synchronization for distributed MIMO using software defined radio hardware. From the simulation result, it shows that limited interferer IA algorithm achieve acceptable BER performance, i.e. in order of 10-3. The hardware implementation of the IA precoding matrix computation is also discussed. Based on the experiment, it is show that the proposed algorithm and architecture achieved higher hardware performance compared to the linear IA.
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Liu, Hai Long, and Yan Wang. "The Application Research in the Coal Mine on Chirp-UWB Wireless Communication Technology." Advanced Materials Research 1079-1080 (December 2014): 787–90. http://dx.doi.org/10.4028/www.scientific.net/amr.1079-1080.787.
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With the rapid development of wireless network technology, according to the actual need, the computer network group network type and each node has different function, so that the computer network system has node complexity, structure complexity and various other complexities. For these reasons, the large scale computer network can be treated and researched abstractly as specific Chirp-UWB network. Therefore, to keep up with the trend of technology progress by means of computer wireless technology, aided design of wireless communication system, it is quite necessary for the implementation of computer management of production safety.
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Carpentier, Sarah M., Sylvain Moreno, and Anthony R. McIntosh. "Short-term Music Training Enhances Complex, Distributed Neural Communication during Music and Linguistic Tasks." Journal of Cognitive Neuroscience 28, no. 10 (October 2016): 1603–12. http://dx.doi.org/10.1162/jocn_a_00988.
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Musical training is frequently associated with benefits to linguistic abilities, and recent focus has been placed on possible benefits of bilingualism to lifelong executive functions; however, the neural mechanisms for such effects are unclear. The aim of this study was to gain better understanding of the whole-brain functional effects of music and second-language training that could support such previously observed cognitive transfer effects. We conducted a 28-day longitudinal study of monolingual English-speaking 4- to 6-year-old children randomly selected to receive daily music or French language training, excluding weekends. Children completed passive EEG music note and French vowel auditory oddball detection tasks before and after training. Brain signal complexity was measured on source waveforms at multiple temporal scales as an index of neural information processing and network communication load. Comparing pretraining with posttraining, musical training was associated with increased EEG complexity at coarse temporal scales during the music and French vowel tasks in widely distributed cortical regions. Conversely, very minimal decreases in complexity at fine scales and trends toward coarse-scale increases were displayed after French training during the tasks. Spectral analysis failed to distinguish between training types and found overall theta (3.5–7.5 Hz) power increases after all training forms, with spatially fewer decreases in power at higher frequencies (>10 Hz). These findings demonstrate that musical training increased diversity of brain network states to support domain-specific music skill acquisition and music-to-language transfer effects.
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Hahn, Michael, Dan Jurafsky, and Richard Futrell. "Universals of word order reflect optimization of grammars for efficient communication." Proceedings of the National Academy of Sciences 117, no. 5 (January 21, 2020): 2347–53. http://dx.doi.org/10.1073/pnas.1910923117.
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The universal properties of human languages have been the subject of intense study across the language sciences. We report computational and corpus evidence for the hypothesis that a prominent subset of these universal properties—those related to word order—result from a process of optimization for efficient communication among humans, trading off the need to reduce complexity with the need to reduce ambiguity. We formalize these two pressures with information-theoretic and neural-network models of complexity and ambiguity and simulate grammars with optimized word-order parameters on large-scale data from 51 languages. Evolution of grammars toward efficiency results in word-order patterns that predict a large subset of the major word-order correlations across languages.
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Tian, Min, Jie Zhou, and Xin Lv. "An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks." Journal of Sensors 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/4839090.
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Large-scale wireless sensor networks consist of a large number of tiny sensors that have sensing, computation, wireless communication, and free-infrastructure abilities. The low-energy clustering scheme is usually designed for large-scale wireless sensor networks to improve the communication energy efficiency. However, the low-energy clustering problem can be formulated as a nonlinear mixed integer combinatorial optimization problem. In this paper, we propose a low-energy clustering approach based on improved niche chaotic genetic algorithm (INCGA) for minimizing the communication energy consumption. We formulate our objective function to minimize the communication energy consumption under multiple constraints. Although suboptimal for LSWSN systems, simulation results show that the proposed INCGA algorithm allows to reduce the communication energy consumption with lower complexity compared to the QEA (quantum evolutionary algorithm) and PSO (particle swarm optimization) approaches.
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Jiang, Weihua, Xiaoyu Yang, Feng Tong, Yijun Yang, and Tianhua Zhou. "A Low-Complexity Underwater Acoustic Coherent Communication System for Small AUV." Remote Sensing 14, no. 14 (July 15, 2022): 3405. http://dx.doi.org/10.3390/rs14143405.
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While underwater acoustic (UWA) communication offers a practical way to establish a wireless link with underwater vehicles, designing a UWA communication system onboard a small autonomous underwater vehicle (AUV) still poses significant challenges. As the adoption of the low-complexity, robust noncoherent communication technology is limited by low bandwidth efficiency and a low data rate, coherent UWA communication requires Doppler mitigation and channel equalization measures to achieve a relatively high data rate in a moving state. Due to the strict constraints of a small-scale AUV in terms of resources and energy consumption, it is not appropriate to use high-complexity Doppler/multipath compensation technology from the prospect of system implementation. In this paper, an efficient and low-complexity UWA differential binary phase-shift keying (DBPSK) system onboard a small AUV is proposed by simplifying the Doppler and multipath compensation. Specifically, for Doppler, the delay of the adjacent DBPSK symbols is calculated according to the Doppler estimate to facilitate delay-tuning Doppler correction. For multipath, low-complexity LMS channel equalization is incorporated with error correction coding to enable multipath mitigation. With a simple structure and low computational complexity, the proposed scheme facilitates the practical hardware implementation and system integration in the small AUV platform. The numerical simulations are conducted to assess the validity of the proposed scheme under different channel conditions and the effectiveness of the proposed scheme is further verified by two UWA communication field tests, which are performed at a practical shallow water sea and lake, respectively.
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Kusumawaty, Ira, Yunike Yunike, and Sujati Ni Ketut. "Relationship between Assertive Communication and Cyber-bullying in Adolescents." Jurnal Kedokteran Brawijaya 31, no. 4 (August 31, 2021): 7. http://dx.doi.org/10.21776/ub.jkb.2021.031.04.7.
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<p>The mandatory use of online facilities during the Covid-19 period has a great opportunity to increase the problem of cyber bullying at all levels of education. The concept of assertiveness cannot be separated from cyber bullying and it is known that communicating assertively can prevent cyber bullying even though it is difficult to implement. The complexity of the psychological problems of victims of cyber bullying requires comprehensive management. This analytical descriptive study with a cross sectional approach aims to analyze the relationship between assertive communication and cyber bullying by involving 151 student participants and high school students in Palembang. The data was collected using an assertive scale and a cyber-bullying scale, which was distributed online using a Google form. From Kendall's tau-b statistical test, it is known that there is a relationship between assertive communication and cyber bullying (p=0.026). It is recommended that the education sector implement self-awareness, empathy, assertive communication and conflict resolution training to prevent the increasing number of cyber bullying's victim. The academic and managerial sectors are expected to facilitate promotion through educational media about using online facilities intelligently by respecting human dignity.</p>
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Sun, Zhuo, Jia Hou, Siyuan Liu, Sese Wang, and Xuantong Chen. "Low Complexity Cyclic Feature Recovery Based on Compressed Sampling." International Journal of Distributed Sensor Networks 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/946457.
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To extract statistic features of communication signal from compressive samples, such as cyclostationary property, full-scale signal reconstruction is not actually necessary or somehow expensive. However, direct reconstruction of cyclic feature may not be practical due to the relative high processing complexity. In this paper, we propose a new cyclic feature recovery approach based on the reconstruction of autocorrelation sequence from sub-Nyquist samples, which can reduce the computation complexity and memory consumption significantly, while the recovery performance remains well in the same compressive ratio. Through theoretical analyses and simulations, we conducted to show and verify our statements and conclusions.
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Liu, Yanmei, Binghan Zheng, and Hao Zhou. "Measuring the difficulty of text translation." Target. International Journal of Translation Studies 31, no. 1 (2019): 125–49. http://dx.doi.org/10.1075/target.18036.zhe.
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Abstract This paper explores the impact of text complexity on translators’ subjective perception of translation difficulty and on their cognitive load. Twenty-six MA translation students from a UK university were asked to translate three English texts with different complexity into Chinese. Their eye movements were recorded by an eye-tracker, and their cognitive load was self-assessed with a Likert scale before translation and NASA-TLX scales after translation. The results show that: (i) the intrinsic complexity measured by readability, word frequency and non-literalness was in line with the results received from informants’ subjective assessment of translation difficulty; (ii) moderate and positive correlations existed between most items in the self-assessments and the indicator (fixation and saccade durations) obtained by the eye-tracking measurements; and (iii) the informants’ cognitive load as indicated by fixation and saccade durations (but not for pupil size) increased significantly in two of the three texts along with the increase in source text complexity.
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Pesce, Emanuele, and Giovanni Montana. "Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication." Machine Learning 109, no. 9-10 (January 23, 2020): 1727–47. http://dx.doi.org/10.1007/s10994-019-05864-5.
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Abstract Deep reinforcement learning algorithms have recently been used to train multiple interacting agents in a centralised manner whilst keeping their execution decentralised. When the agents can only acquire partial observations and are faced with tasks requiring coordination and synchronisation skills, inter-agent communication plays an essential role. In this work, we propose a framework for multi-agent training using deep deterministic policy gradients that enables concurrent, end-to-end learning of an explicit communication protocol through a memory device. During training, the agents learn to perform read and write operations enabling them to infer a shared representation of the world. We empirically demonstrate that concurrent learning of the communication device and individual policies can improve inter-agent coordination and performance in small-scale systems. Our experimental results show that the proposed method achieves superior performance in scenarios with up to six agents. We illustrate how different communication patterns can emerge on six different tasks of increasing complexity. Furthermore, we study the effects of corrupting the communication channel, provide a visualisation of the time-varying memory content as the underlying task is being solved and validate the building blocks of the proposed memory device through ablation studies.
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Teodorescu, Bianca, and Mihaela Gabriela Păun. "A Fly over the Barriers of Communication." International Letters of Social and Humanistic Sciences 39 (September 2014): 85–91. http://dx.doi.org/10.18052/www.scipress.com/ilshs.39.85.
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Communication has a number of features: unites people to send messages. In the process of communication exists different types of communication based on verbal and non-verbal actions. The process of communication occurs in a psychological, social, cultural and physical space. Another important feature about this process, is that the communication is characterized also through dynamism; it consists in the evolution and change of persons that are involved. The quality and quantity of the information theoretical substantiate the value. Any classification of the information is based on two existing forms: scale and complexity. The structure of communication and information is defined in theories and is redefined through analogy and generalization in science. Knowledge the object of communication means to understand how the process of communication is released.
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Mochinski, Marcos Alberto, Marina Luísa de Souza Carrasco Vieira, Mauricio Biczkowski, Ivan Jorge Chueiri, Edgar Jamhour, Voldi Costa Zambenedetti, Marcelo Eduardo Pellenz, and Fabrício Enembreck. "Towards an Efficient Method for Large-Scale Wi-SUN-Enabled AMI Network Planning." Sensors 22, no. 23 (November 23, 2022): 9105. http://dx.doi.org/10.3390/s22239105.
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In a smart grid communication network, positioning key devices (routers and gateways) is an NP-Hard problem as the number of candidate topologies grows exponentially according to the number of poles and smart meters. The different terrain profiles impose distinct communication losses between a smart meter and a key device position. Additionally, the communication topology must consider the position of previously installed distribution automation devices (DAs) to support the power grid remote operation. We introduce the heuristic method AIDA (AI-driven AMI network planning with DA-based information and a link-specific propagation model) to evaluate the connectivity condition between the meters and key devices. It also uses the link-received power calculated for the edges of a Minimum Spanning Tree to propose a simplified multihop analysis. The AIDA method proposes a balance between complexity and efficiency, eliminating the need for empirical terrain characterization. Using a spanning tree to characterize the connectivity topology between meters and routers, we suggest a heuristic approach capable of alleviating complexity and facilitating scalability. In our research, the interest is in proposing a method for positioning communication devices that presents a good trade-off between network coverage and the number of communication devices. The existing literature explores the theme by presenting different techniques for ideal device placement. Still rare are the references that meticulously explore real large-scale scenarios or the communication feasibility between meters and key devices, considering the detailed topography between the devices. The main contributions of this work include: (1) The presentation of an efficient AMI planning method with a large-scale focus; (2) The use of a propagation model that does not depend on an empirical terrain classification; and (3) The use of a heuristic approach based on a spanning tree, capable of evaluating a smaller number of connections and, even so, proposing a topology that uses fewer router and gateway positions compared to an approach that makes general terrain classification. Experiments in four real large-scale scenarios, totaling over 230,000 smart meters, demonstrate that AIDA can efficiently provide high-quality connectivity demanding a reduced number of devices. Additional experiments comparing AIDA’s detailed terrain-based propagation model to the Erceg-SUI Path Loss model suggest that AIDA can reach the smart meter’s coverage with a fewer router positions.
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STOHR, MARY K., CRAIG HEMMENS, ROBERT L. MARSH, GARY BARRIER, and DAN PALHEGYI. "Can't Scale This? The Ethical Parameters of Correctional Work." Prison Journal 80, no. 1 (March 2000): 56–79. http://dx.doi.org/10.1177/0032885500080001004.
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As most correctional institutions have retained their paramilitary structure, the power differentials and communication lines continue to favor concentration in the top echelons of the organizations. Yet, power and communication are regulated and delimited informally by the actions of middle-level managers and lower level workers, and by subcultural influences within the organization. Because of these attributes, correctional work is characterized by discretionary decision making, particularly when the matter is minor, hidden from view, and sanctioned by the subculture. Acting in an ethical manner (i.e., doing the right thing) in such a closed, structured, but informally functional environment requires a recognition and appreciation of the complexity of the milieu along with a willingness to forge ahead. This article explores the ethical parameters of corrections work in a typical medium-security prison. In an effort to determine what the correctional staff regarded as ethical behavior, the authors administered a questionnaire to them using a newly developed ethics instrument. The authors endeavor to identify the major attributes of ethical work in prison and to establish the heuristic value of the instrument for future research.
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He, Jun, Jie Li, Xiaowu Zhu, Shangkun Xiong, and Fangjiong Chen. "Design and Analysis of an Optical–Acoustic Cooperative Communication System for an Underwater Remote-Operated Vehicle." Applied Sciences 12, no. 11 (May 30, 2022): 5533. http://dx.doi.org/10.3390/app12115533.
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Underwater wireless communication technology plays a key role in the field of marine equipment technology. In this paper, we experimentally demonstrate an underwater optical–acoustic cooperative communication platform for an underwater wireless data transmission system. The system utilizes an underwater Remote-Operated Vehicle (ROV) as a carrier, equipped with LEDbased optical communication and acoustic communication modems. In particular, the system applies optical communication to transmit large-scale data and applies acoustic communication to provide acoustic-assisted signaling exchange before optical transmission and Automatic Repeat Request (ARQ) during optical transmission. By experimentally measuring the transmission distance under different water quality conditions, we found that the system can achieve a data rate of up to 5 Mb/s over a laboratory underwater channel of 7.6 m. By comparing the attenuation coefficients for the outdoor underwater environment with that in clear seawater, we estimate that the achievable link distance in clear seawater can reach 11 m with a data rate of 3.125 MB/s. The proposed system takes both implementation complexity and cost into consideration and also provides significant guidance for future real-time high-speed underwater optical–acoustic communications.
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Zou, Qifeng, Xuezhi Tan, Mei Liu, and Lin Ma. "Main-Branch Structure Iterative Detection Using Approximate Message Passing for Uplink Large-Scale Multiuser MIMO Systems." International Journal of Antennas and Propagation 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/2832584.
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The emerging large-scale/massive multi-input multioutput (MIMO) system combined with orthogonal frequency division multiplexing (OFDM) is considered a key technology for its advantage of improving the spectral efficiency. In this paper, we introduce an iterative detection algorithm for uplink large-scale multiuser MIMO-OFDM communication systems. We design a Main-Branch structure iterative turbo detector using the Approximate Message Passing algorithm simplified by linear approximation (AMP-LA) and using the Mean Square Error (MSE) criterion to calculate the correlation coefficients between main detector and branch detector for the given iteration. The complexity of our method is compared with other detection algorithms. The simulation results show that our scheme can achieve better performance than the conventional detection methods and have the acceptable complexity.
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Knobloch-Westerwick, Silvia, and Caterina Keplinger. "Murder for Pleasure." Journal of Media Psychology 20, no. 3 (January 2008): 117–28. http://dx.doi.org/10.1027/1864-1105.20.3.117.
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This experiment investigated how complexity of the presented clues and need-for-cognition affect crime fiction enjoyment. A short murder story, divided into four segments, was presented to 154 participants. Complexity was manipulated as three-step factor through combinations of clues hinting toward either suspect A or B in the first three segments, while the last segment revealed the culprit. Readers indicated suspicions and enjoyment after each segment. Finally, respondents reported overall enjoyment and affective responses before completing the need-for-cognition scale. Results for enjoyment of the entire mystery and during reception show that higher complexity was generally enjoyed less. Furthermore, need-for-cognition affected enjoyment in curvilinear fashion overall, with medium need-for-cognition resulting in greater enjoyment. Respondents with high need-for-cognition were an exception in that they enjoyed medium complexity during mystery exposure the most.
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Lv, Zhengnan, and Zhenghao Xi. "Radio Frequency Link and User Selection Algorithm for 5G Mobile Communication System." Complexity 2021 (May 18, 2021): 1–10. http://dx.doi.org/10.1155/2021/1976499.
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Based on the millimetre-wave time-domain channel detector, this paper conducts channel measurement and modelling for different scenarios and antenna types in typical frequency bands and thus carries out a study on the propagation characteristics of millimetre-wave channels in typical frequency bands and scenarios for 5G. The time-varying characteristics and modelling methods of millimetre-wave clusters are studied, and the time-varying channel simulation strategy and linear regression fitting method are used to establish the time-varying generation and extinction model of clusters by combining the measured data of 26 GHz large-scale antenna channels. The algorithm is based on the correlation dictionary and achieves the efficient and optimal selection of large-scale antenna arrays in the millimetre-wave band. A low-complexity multiuser hybrid precoding design scheme is proposed based on the wideband millimetre-wave large-scale Multiple-Input Multiple-Output (MIMO) system. The scheme aims to maximize the system spectral efficiency and introduces the net spectral efficiency as a bridge to decouple the analogy precoding design from the digital precoding design, thus significantly reducing the computational complexity. In the analogy precoding stage, a Hungarian algorithm-based beam assignment method is proposed to avoid beam conflicts and maximize the net spectral efficiency of the system; in the digital precoding stage, the equivalent channel matrix of each subcarrier is diagonalized to eliminate multiuser interference. Finally, the effectiveness of the scheme is verified by simulation. In this paper, we focus on the radio frequency (RF) link and user selection algorithm of 5G mobile communication system. Through the study of these two aspects, the RF link of our communication system has high stability and reliability, and through the study of the algorithm used for selection, our results also have a strong practical value.
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BENOIT, ANNE, YVES ROBERT, and ERIC THIERRY. "ON THE COMPLEXITY OF MAPPING LINEAR CHAIN APPLICATIONS ONTO HETEROGENEOUS PLATFORMS." Parallel Processing Letters 19, no. 03 (September 2009): 383–97. http://dx.doi.org/10.1142/s0129626409000298.
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In this paper, we explore the problem of mapping linear chain applications onto large-scale heterogeneous platforms. A series of data sets enter the input stage and progress from stage to stage until the final result is computed. An important optimization criterion that should be considered in such a framework is the latency, or makespan, which measures the response time of the system in order to process one single data set entirely. For such applications, which are representative of a broad class of real-life applications, we can consider one-to-one mappings, in which each stage is mapped onto a single processor. However, in order to reduce the communication cost, it seems natural to group stages into intervals. The interval mapping problem can be solved in a straightforward way if the platform has homogeneous communications: the whole chain is grouped into a single interval, which in turn is mapped onto the fastest processor. But the problem becomes harder when considering a fully heterogeneous platform. Indeed, we prove the NP-completeness of this problem. Furthermore, we prove that neither the interval mapping problem nor the similar one-to-one mapping problem can be approximated in polynomial time by any constant factor (unless P=NP).
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Thiemann-Bourque, Kathy S., Nancy Brady, and Lesa Hoffman. "Application of the Communication Complexity Scale in Peer and Adult Assessment Contexts for Preschoolers With Autism Spectrum Disorders." American Journal of Speech-Language Pathology 28, no. 1 (February 21, 2019): 29–42. http://dx.doi.org/10.1044/2018_ajslp-18-0054.
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Ding, Mingjun, Xiaodong Yang, Rui Hu, Zhitao Xiao, Jun Tong, and Jiangtao Xi. "On Matrix Completion-Based Channel Estimators for Massive MIMO Systems." Symmetry 11, no. 11 (November 6, 2019): 1377. http://dx.doi.org/10.3390/sym11111377.
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Large-scale symmetric arrays such as uniform linear arrays (ULA) have been widely used in wireless communications for improving spectrum efficiency and reliability. Channel state information (CSI) is critical for optimizing massive multiple-input multiple-output(MIMO)-based wireless communication systems. The acquisition of CSI for massive MIMO faces challenges such as training shortage and high computational complexity. For millimeter wave MIMO systems, the low-rankness of the channel can be utilized to address the challenge of training shortage. In this paper, we compared several channel estimation schemes based on matrix completion (MC) for symmetrical arrays. Performance and computational complexity are discussed and compared. By comparing the performance in different scenarios, we concluded that the generalized conditional gradient with alternating minimization (GCG-Alt) estimator provided a low-cost, robust solution, while the alternating direction method of multipliers (ADMM)-based hybrid methods achieved the best performance when the array response was perfectly known.
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Tian, Jia Le. "The Selection of BT Project Organizational Structure Based on Communication Efficiency." Applied Mechanics and Materials 357-360 (August 2013): 2250–53. http://dx.doi.org/10.4028/www.scientific.net/amm.357-360.2250.
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The key element in carrying out a successful construction project is a suitable project organizational structure, which should improve the efficiency of communication between members of different groups in the project. The increased scale and complexity of BT projects lead to difficulties in project control. Collaboration between different project stakeholders ensures smooth implementation of the project. In this paper, by constructing a matrix of activity relationship for BT projects, it analyzes the communication resistance value of different organizational structures, so that organizational structures with the most optimal communication efficiency can be selected, which will has a higher efficiency, speed up smooth implementation and achieve organization and coordination of the project.
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Lin, Huifa, Won-Yong Shin, and Jingon Joung. "Support Vector Machine-Based Transmit Antenna Allocation for Multiuser Communication Systems." Entropy 21, no. 5 (May 6, 2019): 471. http://dx.doi.org/10.3390/e21050471.
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In this paper, a support vector machine (SVM) technique has been applied to an antenna allocation system with multiple antennas in multiuser downlink communications. Here, only the channel magnitude information is available at the transmitter. Thus, a subset of transmit antennas that can reduce multiuser interference is selected based on such partial channel state information to support multiple users. For training, we generate the feature vectors by fully utilizing the characteristics of the interference-limited setup in the multiuser downlink system and determine the corresponding class label by evaluating a key performance indicator, i.e., sum rate in multiuser communications. Using test channels, we evaluate the performance of our antenna allocation system invoking the SVM-based allocation and optimization-based allocation, in terms of sum-rate performance and computational complexity. Rigorous testing allowed for a comparison of a SVM algorithm design between one-vs-one (OVO) and one-vs-all (OVA) strategies and a kernel function: (i) OVA is preferable to OVO since OVA can achieve almost the same sum rate as OVO with significantly reduced computational complexity, (ii) a Gaussian function is a good choice as the kernel function for the SVM, and (iii) the variance (kernel scale) and penalty parameter (box constraint) of an SVM kernel function are determined by 21.56 and 7.67, respectively. Further simulation results revealed that the designed SVM-based approach can remarkably reduce the time complexity compared to a traditional optimization-based approach, at the cost of marginal sum rate degradation. Our proposed framework offers some important insights for intelligently combining machine learning techniques and multiuser wireless communications.
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SZELL, MICHAEL, and STEFAN THURNER. "SOCIAL DYNAMICS IN A LARGE-SCALE ONLINE GAME." Advances in Complex Systems 15, no. 06 (August 2012): 1250064. http://dx.doi.org/10.1142/s0219525912500646.
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Complex systems — when treated as systems accessible to natural sciences — pose tremendous requirements on data. Usually these requirements obstruct a scientific understanding of social phenomena on scientific grounds. Due to developments in IT, new collective human behavior, new dimensions of data sources are beginning to open up. Here we report on a complete data set of an entire society, consisting of over 350,000 human players of a massive multiplayer online game. All actions of all players over three years are recorded, including communication behavior and social ties. In this work we review the first steps undertaken in analyzing this vast data set, focusing on social dynamics on friend-, enemy- and communication networks. This new data-driven approach to social science allows to study socio-economic behavior of humans and human groups in specific environments with unprecedented precision. We propose two new empirical social laws which relate the network properties of link weight, overlap and betweenness centrality in a nonlinear way, and provide strong quantitative evidence for classical social balance assumptions, the weak ties hypothesis and triadic closure. In our analysis of large-scale multirelational networks we discover systematic deviations between positive and negative tie networks. Exploring such virtual "social laboratories" in the light of complexity science has the potential to lead to the discovery of systemic properties of human societies, with unforeseen impact on managing human-induced crises.
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Gao, Chunxian, Wenwen Hu, and Keyu Chen. "Research on Multi-AUVs Data Acquisition System of Underwater Acoustic Communication Network." Sensors 22, no. 14 (July 6, 2022): 5090. http://dx.doi.org/10.3390/s22145090.
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In order to meet the needs of large-scale underwater operations, the underwater acoustic communication network emerged, marking a historic moment. At the same time, the development of artificial intelligence has promoted the application of intelligent underwater robots in large-scale underwater operations, and the research on related algorithms has been gradually promoted. Due to the complexity of underwater operations and the difficulty of replacing batteries, the energy efficiency of intelligent underwater robots is particularly important in multi-AUVs data acquisition systems. In view of the energy consumption of multi-AUVs data acquisition systems in water acoustic cluster networks, this paper proposed the AE (A*-Energy) algorithm for multi-AUVs task assignment and path planning. Through the simulation experiment, it was proved that the AE algorithm proposed in this paper can effectively reduce the energy consumption of multi-AUVs data acquisition systems and has good energy efficiency.
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Akhmadi, Heri, and Muhammad Fauzan. "Smartphone Adoption on Fruit Marketing Communication: a Traders Perception." Jurnal AGRISEP Kajian Masalah Sosial Ekonomi Pertanian dan Agribisnis 19, no. 2 (September 21, 2020): 433–46. http://dx.doi.org/10.31186/agrisep.19.2.433-446.
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Smartphone is one of the information technology devices that widely used by traders in marketing activities. Aside from being a communication tool, traders also utilize smartphones to obtain market information and communicate about products and services to consumers. This study aims to analyze profile and perceptions of fruit traders in using smartphones as a marketing communication tool. This research employed quantitative method and descriptive analysis using five point Likert scale to examine the perception of fruit traders in Yogyakarta City. The results revealed that traders adopted smartphones on fruit marketing communication due to it perceived to provide a relative advantage, with a high level of ease of use, visible benefits, and low complexity and risk. Furthermore, Samsung, Telkomsel, and WhatsApp were brands of smartphones, telecommunications providers, and social media applications mostly chose by traders.
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Métivier, Ludovic, and Romain Brossier. "The SEISCOPE optimization toolbox: A large-scale nonlinear optimization library based on reverse communication." GEOPHYSICS 81, no. 2 (March 1, 2016): F1—F15. http://dx.doi.org/10.1190/geo2015-0031.1.
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The SEISCOPE optimization toolbox is a set of FORTRAN 90 routines, which implement first-order methods (steepest-descent and nonlinear conjugate gradient) and second-order methods ([Formula: see text]-BFGS and truncated Newton), for the solution of large-scale nonlinear optimization problems. An efficient line-search strategy ensures the robustness of these implementations. The routines are proposed as black boxes easy to interface with any computational code, where such large-scale minimization problems have to be solved. Traveltime tomography, least-squares migration, or full-waveform inversion are examples of such problems in the context of geophysics. Integrating the toolbox for solving this class of problems presents two advantages. First, it helps to separate the routines depending on the physics of the problem from the ones related to the minimization itself, thanks to the reverse communication protocol. This enhances flexibility in code development and maintenance. Second, it allows us to switch easily between different optimization algorithms. In particular, it reduces the complexity related to the implementation of second-order methods. Because the latter benefit from faster convergence rates compared to first-order methods, significant improvements in terms of computational efforts can be expected.
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Wei, Xiaojuan, Meng Jia, and Mengke Geng. "A Multiagent Cooperative Decision-Making Method for Adaptive Intersection Complexity Based on Hierarchical RL." Wireless Communications and Mobile Computing 2022 (October 19, 2022): 1–10. http://dx.doi.org/10.1155/2022/9329186.
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In this paper, we propose a multiagent collaboration decision-making method for adaptive intersection complexity based on hierarchical reinforcement learning—H-CommNet, which uses a two-level structure for collaboration: the upper-level policy network fuses information from all agents and learns how to set a subtask for each agent, and the lower-level policy network relies on the local observation of the agent to control the action targets of the agents from each subtask in the upper layer. H-CommNet allows multiagents to complete collaboration on different time scales, and the scale is controllable. It also uses the computational intelligence of invehicle intelligence and edge nodes to achieve joint optimization of computing resources and communication resources. Through the simulation experiments in the intersection environment without traffic lights, the experimental results show that H-CommNet can achieve better results than baseline in different complexity scenarios when using as few resources as possible, and the scalability, flexibility, and control effects have been improved.
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Dwivedi, Siddharth, and Mahim Sagar. "Communication Protocols in Public Health." Journal of Health Management 19, no. 2 (May 15, 2017): 340–51. http://dx.doi.org/10.1177/0972063417699719.
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This work was initiated primarily to analyze the role of communication in public health policy and hence develop protocols to design effective communication strategies. Research was motivated by the fact that the traditional approaches towards communication in health management have proved inadequate in front of the complexity of recent challenges. New and innovative ‘Integrated Communication Strategies’, which employ targeted communication tools for achieving public cooperation, have emerged as the need of the hour. This was revealed by the extensive literature review carried out by the authors. The fact that most of the researches so far have been either to empirically determine factor linkages and hierarchies on a small population sample or to analyze some specific aspect of the whole public communication architecture restricts their usability to large-scale, real-life situations. This research aims at constructing that big picture, a wholesome view of the role communication is expected to play in a public health programme and how the researches so far can be collated with insights from the case study of dengue fever in New Delhi carried out by the authors to yield protocols for designing highly effective communication programmes, which shall go long way in ensuring a successful health campaign.
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Li, Qingyu, Keren Dai, Xiaofeng Wang, Yu Zhang, He Zhang, and Defu Jiang. "Low-Complexity Failed Element Diagnosis for Radar-Communication mmWave Antenna Array with Low SNR." Electronics 8, no. 8 (August 15, 2019): 904. http://dx.doi.org/10.3390/electronics8080904.
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The millimeter-wave (mmWave) antenna array plays an important role in the excellent performance of wireless sensors networks (WSN) or unmanned aerial vehicle (UAV) clusters. However, the array elements are easily damaged in its harsh working environment but hard to be repaired or exchanged timely, resulting in a serious decline in the beamforming performance. Thus, accurate self-diagnosis of the failed elements is of great importance. In previous studies, there are still significant difficulties for large-scale arrays under extremely low SNR. In this paper, a diagnosis algorithm with low complexity and high reliability for the failed elements is proposed, which is based on a joint decision of communication signal and sensing echoes. Compared with the previous studies, the complexity of the algorithm is reduced by the construction of low-dimensional feature vectors for classification, the decoupling of the degree of arrival (DOA) estimation and the failed pattern diagnosis, with the help of the sub-array division. Simulation results show that, under an ultra-low SNR of −12.5 dB for communication signals and −16 dB for sensing echoes, an accurate self-diagnosis with a block error rate lower than 8% can be realized. The study in this paper will effectively promote the long-term and reliable operation of the mmWave antenna array in WSN, UAV clusters and other similar fields.
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CHUNG, I.-HSIN, CHE-RUNG LEE, JIAZHENG ZHOU, and YEH-CHING CHUNG. "HIERARCHICAL MAPPING FOR HPC APPLICATIONS." Parallel Processing Letters 21, no. 03 (September 2011): 279–99. http://dx.doi.org/10.1142/s0129626411000229.
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As the high performance computing systems scale up, mapping the tasks of a parallel application onto physical processors to allow efficient communication becomes one of the critical performance issues. Existing algorithms were usually designed to map applications with regular communication patterns. Their mapping criterion usually overlooks the size of communicated messages, which is the primary factor of communication time. In addition, most of their time complexities are too high to process large scale problems. In this paper, we present a hierarchical mapping algorithm (HMA), which is capable of mapping applications with irregular communication patterns. It first partitions tasks according to their run-time communication information. The tasks that communicate with each other more frequently are regarded as strongly connected. Based on their connectivity strength, the tasks are partitioned into supernodes based on the algorithms in spectral graph theory. The hierarchical partitioning reduces the mapping algorithm complexity to achieve scalability. Finally, the run-time communication information will be used again in fine tuning to explore better mappings. With the experiments, we show how the mapping algorithm helps to reduce the point-to-point communication time for the PDGEMM, a ScaLAPACK matrix multiplication computation kernel, up to 20% and the AMG2006, a tier 1 application of the Sequoia benchmark, up to 7%.
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Sun, Weijia, Hui Wang, and Yongfeng Liu. "Research on an invasive and low-frequency power consumption data acquisition method." Journal of Physics: Conference Series 2078, no. 1 (November 1, 2021): 012059. http://dx.doi.org/10.1088/1742-6596/2078/1/012059.
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Abstract Aiming at the large-scale, compatibility and reliability problems faced by the data acquisition engineering for power consumption in the industrial field, for reducing the complexity and cost of the data acquisition engineering, and improving the quality, maintainability, scalability and manageability of the data acquisition, an engineering-oriented, intrusive, low-frequency data acquisition scheme for power consumption is proposed. The scheme leverages multi-agent networking technology to solve the large-scale problem, utilizes the communication driver of the dynamic loading adapter mode to tackle the compatibility trouble. Furthermore, the local storage, breakpoint retransmission, flow control, automatic recovery, automatic connection, and time synchronization are combined to solve the reliability issue. Engineering tests show that the proposed scheme possesses the significant backward compatibility characteristics, which can effectively reduce the complexity and cost of data acquisition engineering for power consumption, and significantly improve the quality, maintainability, scalability and manageability of data acquisition.
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DUTOT, PIERRE-FRANÇOIS, LIONEL EYRAUD, GRÉGORY MOUNIÉ, and DENIS TRYSTRAM. "SCHEDULING ON LARGE SCALE DISTRIBUTED PLATFORMS: FROM MODELS TO IMPLEMENTATIONS." International Journal of Foundations of Computer Science 16, no. 02 (April 2005): 217–37. http://dx.doi.org/10.1142/s0129054105002954.
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Today, large scale parallel systems are available at low cost, Many powerful such systems have been installed all over the world and the number of users is always increasing. The difficulty of using them efficiently is growing with the complexity of the interactions between more and more architectural constraints and the diversity of the applications. The design of efficient parallel algorithms has to be reconsidered under the influence of new parameters of such platforms (namely, cluster, grid and global computing) which are characterized by a larger number of heterogeneous processors, often organized in several hierarchical sub-systems. At each step of the evolution of the parallel processing field, researchers designed adequate computational models whose objective was to abstract the real world in order to be able to analyze the behavior of algorithms. In this paper, we will investigate two complementary computational models that have been proposed recently: Parallel Task (PT) and Divisible Load (DL). The Parallel Task (i.e. tasks that require more than one processor for their execution) model is a promising alternative for scheduling parallel applications, especially in the case of slow communication media. The basic idea is to consider the application at a coarse level of granularity. Another way of looking at the problem (which is somehow a dual view) is the Divisible Load model where an application is considered as a collection of a large number of elementary – sequential – computing units that will be distributed among the available resources. Unlike the PT model, the DL model corresponds to a fine level of granularity. We will focus on the PT model, and discuss how to mix it with simple Divisible Load scheduling. As the main difficulty for distributing the load among the processors (usually known as the scheduling problem) in actual systems comes from handling efficiently the communications, these two models of the problem allow us to consider them implicitly or to mask them, thus leading to more tractable problems. We will show that in spite of the enormous complexity of the general scheduling problem on new platforms, it is still useful to study theoretical models. We will focus on the links between models and actual implementations on a regional grid with more than 500 processors.
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Каргин, Nikolay Kargin, Щадилова, and I. Shchadilova. "Informational Services for Communicative Social Structures." Modern Communication Studies 5, no. 5 (October 17, 2016): 8–14. http://dx.doi.org/10.12737/21925.
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Paper considers methodological basis which provides a forming of a overall
theoretical knowledge about communication processes in social-economy
structure of a modern society. As a basic structure is taken natural science
law – which describes process of the internal informational interaction of a
systems differing in their structure type and complexity value. Paper considers
evolutional processes of interactions between systems of different
grades from simply and determinate to thin and probabilistic (which uses
different types of informational resources). Justifies key differences of interaction
process of a person to person type of social structures, in dealing
with different types and complexity scale problem solving.
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Wang, Lei, Kean Chen, Jian Xu, and Xuhua Tian. "Analyzing Convergence of Distributed FxLMS Algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 38, no. 5 (October 2020): 944–51. http://dx.doi.org/10.1051/jnwpu/20203850944.
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The distributed FxLMS algorithm based on acoustic sensor networks can solve the problem of the increased computational complexity caused by a large-scale active noise control (ANC) system. Firstly, the distributed algorithm is deduced theoretically. In the ANC process based on sensor networks, the iteration of partial weight coefficients is replaced by the real-time communication of weight coefficients among nodes. Then the convergence characteristics of the distributed algorithm in its mean and mean square senses are analyzed and verified with simulation. Finally, the noise reduction effects of different algorithms are compared. The results show that the distributed algorithm, with its computational complexity reduced, can achieve the same noise reduction effects as the centralized ANC system.
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Kim, Minhoe, Woongsup Lee, and Dong-Ho Cho. "Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System." Electronics 9, no. 11 (November 4, 2020): 1844. http://dx.doi.org/10.3390/electronics9111844.
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In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.
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Barbierato, Enrico, Marco Gribaudo, and Mauro Iacono. "Modeling and Evaluating the Effects of Big Data Storage Resource Allocation in Global Scale Cloud Architectures." International Journal of Data Warehousing and Mining 12, no. 2 (April 2016): 1–20. http://dx.doi.org/10.4018/ijdwm.2016040101.
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The availability of powerful, worldwide span computing facilities offering application scalability by means of cloud infrastructures perfectly matches the needs for resources that characterize Big Data applications. Elasticity of resources in the cloud enables application providers to achieve results in terms of complexity, performance and availability that were considered beyond affordability, by means of proper resource management techniques and a savvy design of the underlying architecture and of communication facilities. This paper presents an evaluation technique for the combined effects of cloud elasticity and Big Data oriented data management layer on global scale cloud applications, by modeling the behavior of both typical in memory and in storage data management.
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Ramos, Ana Paula Marques, Edmur Azevedo Pugliesi, Renan Furlan de Oliveira, Vilma Mayumi Tachibana, and Mônica Modesta Santos Decanini. "EVALUATION OF USABILITY OF MAPS OF DIFFERENT SCALES PRESENTED IN AN IN-CAR ROUTE GUIDANCE AND NAVIGATION SYSTEM." Boletim de Ciências Geodésicas 24, no. 3 (August 2018): 383–406. http://dx.doi.org/10.1590/s1982-21702018000300025.
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Abstract Noise from the information communication process produced by the interfaces of navigation systems has overloaded drivers' cognitive processing systems and increased the probability of traffic accidents. This work evaluates the usability of maps of different scales in a prototype route guidance and navigation system. The maps were designed on basic cartographic communication principles, such as perceptive grouping and figure-ground segregation, as well drivers’ requirements for performing a tactical task. Two different scales were adopted, 1:3,000 and 1:6,000, and the maps implemented in the prototype. A total of 52 subjects (26 males and 26 females) participated in an experiment performed in a driving simulator. The maps describe an urban route composed of 13 simple and complex maneuvers. The drivers’ mental workload was measured in terms of visual demand, navigational error and subjective preference. Results reveal that the usability of maps is influenced by map scale variation, and this is related to maneuver complexity. Also, an association between drivers’ visual demand and gender was found, and this was related to drivers’ spatial ability. More implications are presented and discussed.
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Mlecnik, E., and J. M. Hidalgo-Betanzos. "Policy instruments for energy-efficient renovations at district level." IOP Conference Series: Earth and Environmental Science 1085, no. 1 (September 1, 2022): 012035. http://dx.doi.org/10.1088/1755-1315/1085/1/012035.
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Abstract IEA EBC Annex 75 aims to investigate, amongst other policy for reducing carbon emissions and energy use in buildings at district level, combining both energy efficiency measures and renewable energy measures. Particularly policy instruments deployed at the local level targeting owners and investors could increase residential building renovation and renewable energy systems to a district scale. A desk and empirical research using 38 expert interviews from 8 European countries was used to investigate the use and development of various types of policy instruments, including regulations, incentives, communication and facilitating instruments. The research confirms interest of frontrunners to use or develop specific policy instruments further, such as enforcement of energy standards and inspections, financial incentives for district stakeholders and for groups of homeowners, renovation services and energy desks, digital communication and network meetings in districts. It also finds that low relative advantage for some stakeholders, lack of good examples, an incompatible legal or national framework and high complexity are serious risks that can further hinder adoption of energy efficiency and renewable energy systems in districts. Renovations at district scale including energy efficiency and renewable energy can benefit from adapted or improved regulations, incentives, communication and facilitation to better support renovations at district scale including energy efficiency and renewable energy systems.