• Title/Summary/Keyword: Cognitive network

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Students' Experience in Using Twitter for Online Learning: Social-Affective and Cognitive Perspectives

  • CHOI, Hyungshin;KWON, Soungyoun
    • Educational Technology International
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    • v.13 no.1
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    • pp.175-205
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    • 2012
  • The current study investigated whether SNS such as Twitter can be an assisting tool to compensate the limitations of online learning from social-affective and cognitive perspectives. Such limitations include low level of motivation to participate, feeling of isolation, rare exchanges of ideas and feedback from peers or instructors. This paper reports findings from a research study on the use of Twitter in online learning in Higher Education. Survey and subsequent interviews were conducted to examine students' perceptions about the cognitive and social-affective aspects of their participation in Twitter activities. Some of the challenges and potentials in integrating Twitter into online course are also addressed. It can be concluded that Twitter contributes not only to building close relationships among peers and instructors but also to opening a communication channel that can extend cognitive potentials.

The Effect of Virtual Reality-Based Complex Cognitive Training Program on Cognitive Function, Depression, Digital Divide Reduction in the Elderly: An exploratory study (가상현실(Virtual Reality) 기반 복합인지중재 프로그램이 노인의 인지기능, 우울, 디지털 격차 해소에 미치는 영향: 탐색적 연구)

  • Bit-Na Cho;Pumsoo Kim;Dong-Gi Hong;Min-Jung Kwak
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.1
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    • pp.109-124
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    • 2024
  • Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

Spatial Correlation-based Resource Sharing in Cognitive Radio SWIPT Networks

  • Rong, Mei;Liang, Zhonghua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.9
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    • pp.3172-3193
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    • 2022
  • Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.

A Design of Cassifier Using Mudular Neural Networks with Unsupervised Learning (비지도 학습 방법을 적용한 모듈화 신경망 기반의 패턴 분류기 설계)

  • 최종원;오경환
    • Korean Journal of Cognitive Science
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    • v.10 no.1
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    • pp.13-24
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    • 1999
  • In this paper, we propose a classifier based on modular networks using an unsupervised learning method. The structure of each module is designed through stochastic analysis of input data and each module classifier data independently. The result of independent classification of each module and a measure of the nearest distance are integrated during the final data classification phase to allow more precise c classification. Computation time is decreased by deleting modules that have been classified to be incorrect during the final classification phase. Using this method. a neural network sharing the best performance was implemented without considering. lots of of variables which can affect the performance of the neural network.

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Hangeul Character Classification Model Based on Cognitive Theory and ART Neural Network (인지이론과 ART 신경회로망에 기반한 한글 문자 분류 모델)

  • Park Joong-Yang;Park Jae-Heung;Jang Jae-Hyuk
    • The Journal of the Korea Contents Association
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    • v.5 no.5
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    • pp.33-42
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    • 2005
  • In this paper, we propose a new training algorithm for improving pattern classification performance of ART neural network. The proposed train algorithm restricts unnecessary cluster generation and transition, applies the location extraction algorithm, and operates the reset system based on the agreement between the present learning pattern and the initial pattern. As a result, repetitive input of a pattern does not generate a new cluster and mis-recognition rate decreases.

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Log-Average-SNR Ratio and Cooperative Spectrum Sensing

  • Yue, Dian-Wu;Lau, Francis C.M.;Wang, Qian
    • Journal of Communications and Networks
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    • v.18 no.3
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    • pp.311-319
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    • 2016
  • In this paper, we analyze the spectrum-sensing performance of a cooperative cognitive radio (CR) network consisting of a number of CR nodes and a fusion center (FC). We introduce the "log-average-SNR ratio" that relates the average SNR of the CR-node-FC link and that of the primary-user-CR-node link. Assuming that the FC utilizes the K-out-of-N rule as its decision rule, we derive exact expressions for the sensing gain and the coding gain - parameters used to characterize the CR network performance at the high SNR region. Based on these results, we determine ways to optimize the performance of the CR network.

Frequency Allocation and Path Selection Scheme in Underlay Cognitive Radio Networks Using Network Coding (네트워크 코딩을 쓰는 언더레이 인지 무선 네트워크에서의 주파수 할당과 경로 선택 기법)

  • Lee, Do-Haeng;Lee, Won Hyoung;Kang, Sung-Min;Hwang, Ho Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.12
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    • pp.2372-2380
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    • 2015
  • In this paper, we propose frequency allocation and path selection scheme in underlay cognitive radio (CR) networks using network coding. In the proposed scheme, we choose the path with consideration of network coding and interference temperature in underlay CR networks and propose an optimization problem to maximize the system throughput of secondary users (SUs). Then, we represent the proposed optimization problem as the multi-dimensional multiple-choice knapsack problem and give the theoretical upper bound for the system throughput of SUs by using linear programming. Finally, we compute the system throughput of SUs by using brute-force search (BFS) and link quality first (LQF) scheme in underlay CR networks. Simulation results show that the system throughput of SUs with BFS is higher than that with LQF in underlay CR networks with and without application of network coding, respectively.

Cooperative Spectrum Sensing with Ad-Hoc Network for Cognitive Radio (애드 혹 네트워크에서의 협력 센싱 기법의 성능 분석)

  • Lee, Kyung-Sun;Kim, Yoon-Hyun;Kim, Jin-Young
    • Journal of Satellite, Information and Communications
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    • v.6 no.1
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    • pp.75-79
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    • 2011
  • Wireless devices can communicate between each other without existing infrastructure in mobile Ad-hod network. Ad hoc networks can be used under difficult conditions, where it is difficult to construct infrastructures, such as shadowing areas, disaster areas, war area, and so on. In order to support to considerable and various wireless services, more spectrum resources are needed. However, efficient utilization of the frequency resource is difficult because of spectrum scarcity and the conventional frequency regulation. Ad-hoc networks employing cognitive radio (CR) system that guarantee high spectrum utilization provide effective way to increase the network capacity. In this paper, we simulate and compare the performance of conventional single and cooperative spectrum sensing with CR system using ad-hoc networks in additive white Gaussian noise (AWGN) and Rayleigh channel model. And we demonstrate performance improvement by analyzing the system performance.

A Control Channel Access Scheme for Clustered Multi-interface Multi-hop Cognitive Radio Networks (클러스터 형태의 다중 인터페이스 다중 홉 인지 라디오 네트워크를 위한 제어 채널 접근 기법)

  • Lee, Ji-Wun;Jeon, Wha-Sook;Jeong, Dong-Geun
    • Journal of KIISE:Information Networking
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    • v.37 no.4
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    • pp.301-306
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    • 2010
  • We propose the control channel access scheme for multi-interface multi-hop cognitive radio (CR) environment having a cluster structure. Due to the difficulty of obtaining common channels across the entire CR network, most multi-interface multi-hop CR networks put the control channel outside the CR bandwidth and dedicate one network interface to it in order to exchange the control information such as the activation of licensed users. However, this will be the waste of the network interface. Our focus is how to alternate between the control and the data channel without multichannel hidden node problem under the cluster structure where CR nodes connect with neighbors through multiple data channels. By using simulation, we evaluate the performance of the proposed scheme. The results show that the proposed scheme achieves higher network throughput than the dedicated scheme where one network interface card should dedicate to the control channel and cannot be used for data transmission.

Multihop Transmission in Cognitive Underlay Network Over Rayleigh Fading Channels (레일리 페이딩 채널에서 이상 인지 언더레이 네트워크 멀티 홉 전송)

  • Park, Sang-Young;Kong, Hyung-Yun
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.6
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    • pp.291-296
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    • 2012
  • In this Paper, we propose a multi-hop transmission in cognitive underlay network. In Secondary network, We assume that a secondary source S attempts to transmit D its signal to a secondary destination via N+1 hops with help of N relays $R_1$, $R_2$, ${\ldots}$, $R_N$. At hop k between relay $R_k$ and relay $R_{k+1}$. we assume that there is a primary user $PU_k$. In this paper, we assume that these channels are Rayleigh fading channels. In underlay network, the secondary transmitter has to adapt its power so that the interference caused at the primary user is less than a maximum interference threshold. considering the hop transmission between the transmitter and the repeater, we find transmit power and signal-to-noise ratio(SNR). Between the transmitter from the receiver depending on the number of relay in the underlay network, we compared to find the transmit power and signal-to-noise ratio(SNR). Finally we find optimal number of relay and optimal threshold value.