• Title/Summary/Keyword: network life

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Candidate First Moves for Solving Life-and-Death Problems in the Game of Go, using Kohonen Neural Network (코호넨 신경망을 이용 바둑 사활문제를 풀기 위한 후보 첫 수들)

  • Lee, Byung-Doo;Keum, Young-Wook
    • Journal of Korea Game Society
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    • v.9 no.1
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    • pp.105-114
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    • 2009
  • In the game of Go, the life-and-death problem is a fundamental problem to be definitely overcome when implementing a computer Go program. To solve local Go problems such as life-and-death problems, an important consideration is how to tackle the game tree's huge branching factor and its depth. The basic idea of the experiment conducted in this article is that we modelled the human behavior to get the recognized first moves to kill the surrounded group. In the game of Go, similar life-and-death problems(patterns) often have similar solutions. To categorize similar patterns, we implemented Kohonen Neural Network(KNN) based clustering and found that the experimental result is promising and thus can compete with a pattern matching method, that uses supervised learning with a neural network, for solving life-and-death problems.

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STO-based Cluster Header Election Algorithm (STO 기반 클러스터 헤더 선출 알고리즘)

  • Yoon, Jeong-Hyeon;Lee, Heon-Guk;Kim, Seung-Ku
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.587-590
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    • 2019
  • This paper is about to improve the network life's reduction due to the deviation of sensor node and frequently change of network, the main problem of sensor network. The existing Scalable Topology Organization(STO)-based ZigBee Tree Topology Control Algorithm did not consider ways to consume power so the network lifetime is too short. Accordingly, per each round, electing a new parent node and consisting of the new network topology technique, The Cluster Header Selection, extending the network's overall lifetime. The OMNet++ Simulator yielded results from the existing STO Algorithm and the proposed Cluster Header Selection Technique in the same experimental environment, which resulted in an increase in overall network life by about 40% and an improvement of about 10% in performance in the remaining portion of the battery.

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Wireless sensor network protocol comparison for bridge health assessment

  • Kilic, Gokhan
    • Structural Engineering and Mechanics
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    • v.49 no.4
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    • pp.509-521
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    • 2014
  • In this paper two protocols of Wireless Sensor Networks (WSN) are examined through both a simulation and a case study. The simulation was performed with the optimized network (OPNET) simulator while comparing the performance of the Ad-Hoc on demand Distance Vector (AODV) and the Dynamic Source Routing (DSR) protocols. This is compared and shown with real-world measurement of deflection from eight wireless sensor nodes. The wireless sensor response results were compared with accelerometer sensors for validation purposes. It was found that although the computer simulation suggests the AODV protocol is more accurate, in the case study no distinct difference was found. However, it was shown that AODV is still more beneficial in the field as it has a longer battery life enabling longer surveying times. This is a significant finding as a large factor in determining the use of wireless network sensors as a method of assessing structural response has been their short battery life. Thus if protocols which enhance battery life, such as the AODV protocol, are employed it may be possible in the future to couple wireless networks with solar power extending their monitoring periods.

Prediction on the fatigue life of butt-welded specimens using artificial neural network

  • Kim, Kyoung Nam;Lee, Seong Haeng;Jung, Kyoung Sup
    • Steel and Composite Structures
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    • v.9 no.6
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    • pp.557-568
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    • 2009
  • Fatigue tests for extremely thick plates require a great deal of manufacturing time and are expensive to perform. Therefore, if predictions could be made through simulation models such as an artificial neural network (ANN), manufacturing time and costs could be greatly reduced. In order to verify the effects of fatigue strength depending on the various factors in SM520C-TMC steels, this study constructed an ANN and conducted the learning process using the parameters of calculated stress concentration factor, thickness and input heat energy, etc. The results showed that the ANN could be applied to the prediction of fatigue life.

Social Network Contact Frequency and Life Satisfaction of the Elderly: Focusing on the Moderating Effect of Digital Capabilities (노인의 사회적 관계망 접촉빈도와 삶의 만족도: 디지털역량의 조절효과를 중심으로)

  • Eun Hye Kim
    • Human Ecology Research
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    • v.62 no.2
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    • pp.217-231
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    • 2024
  • The aims of this study were to identify (a) the social network contact frequency of the elderly with children, relatives, and friends; (b) the impact of contact frequency (face-to-face/non-face-to-face) on life satisfaction of the elderly; and (c) the moderating effect of digital capabilities of the elderly on the relationship between social contact frequency and life satisfaction. Data were obtained from the National Survey of Older Koreans 2020. The sample comprised 6,119 adults aged 65+ who were in single or couple households. The principal findings were as follows. First, couple households, higher levels of education, and better health status increased life satisfaction of the elderly. Second, the higher the frequency of face-to-face contact with children and the higher the frequency of non-face-to-face contact with friends, the more positive the effect on life satisfaction of the elderly. Third, the interaction effect of the digital capabilities of the elderly differed according to children, relatives and friends. There was a significant and positive moderating effect on the relationship between life satisfaction and the frequency of face-to-face/non-face-to-face contact with children and the frequency of face-to-face contact with relatives. Conversely, there was a significant negative effect on the relationship between life satisfaction and the frequency of face-to-face/non-face-to-face contact with friends. By examining the impact of non-face-to-face contact on life satisfaction of the elderly in the era of digital transformation, the findings have significance in that they provide basic data to support policies and education programs aimed at improving the digital capabilities of the elderly.

Flipping EFL Classrooms: Impacts on Students' Achievement and Life Skills Learning

  • Alsamadani, Hashem A.
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.229-236
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    • 2022
  • This study investigates the impact of flipped classroom strategy in developing students' achievement and acquisition of life skills. The study employed a quasi-experimental design where students were divided into two groups: an experimental (N=22) and a control (N=22). The randomly selected and assigned sample consisted of sixth-year elementary school students studying English as a basic course. The findings revealed statistically significant differences between the two group's means in both achievement and life skills tests in favor of the experimental group. Students of the experimental group who studied using the flipped classroom strategy outperformed the control group who studied in the standard way in achieving the English language and in the life situations test, where the effect size of the use of the strategy was large in both dependent variables. The study is concluded with some recommendations to facilitate the use of flipped classroom strategy for EFL teachers. This can be achieved by training teachers on using the strategy and providing technological resources at schools to implement the strategy efficiently.

Remaining Useful Life Prediction for Litium-Ion Batteries Using EMD-CNN-LSTM Hybrid Method (EMD-CNN-LSTM을 이용한 하이브리드 방식의 리튬 이온 배터리 잔여 수명 예측)

  • Lim, Je-Yeong;Kim, Dong-Hwan;Noh, Tae-Won;Lee, Byoung-Kuk
    • The Transactions of the Korean Institute of Power Electronics
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    • v.27 no.1
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    • pp.48-55
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    • 2022
  • This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

Relationship between Participation in the Elderly Job Project and Quality of Life: focused on the Social Capital Mediating Effect

  • Jang, Yumi
    • International Journal of Advanced Culture Technology
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    • v.10 no.3
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    • pp.11-17
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    • 2022
  • This study investigates income support, labor opportunities, and social capital by the demographic characteristics of the elderly who participate in the elderly job project, and especially the relationship between social and quality of life. We want to provide empirical data on how the elderly vocational business ultimately affects the lives of the elderly through the intervention of social capital. The intervention effect of social capital is as follows. Satisfaction with the elderly job project has a great impact on the quality of life, trust, network, and social participation. In particular, trust in the quality of life of the elderly had a great influence on the quality of life and was indirectly effective. In addition, the intervention of social participation between social capital was known, and the elderly job project increased social participation to improve the quality of life of the elderly. Therefore, it can be evaluated that the elderly job project has an important positive effect on the quality of life of the elderly, and the social capital formed through the elderly job project plays a role in directly or indirectly improving the quality of life of the elderly.

Clustering Algorithms for Reducing Energy Consumption - A Review

  • Kinza Mubasher;Rahat Mansha
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.109-118
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    • 2023
  • Energy awareness is an essential design flaw in wireless sensor network. Clustering is the most highly regarded energy-efficient technique that offers various benefits such as energy efficiency and network lifetime. Clusters create hierarchical WSNs that introduce the efficient use of limited sensor node resources and thus enhance the life of the network. The goal of this paper is to provide an analysis of the various energy efficient clustering algorithms. Analysis is based on the energy efficiency and network lifetime. This review paper provides an analysis of different energy-efficient clustering algorithms for WSNs.

Network Analysis on Ageing Problems : Identifying Network Differences between Types of Cities

  • Seo, Bojun;Lee, Soochang
    • International Journal of Advanced Culture Technology
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    • v.5 no.2
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    • pp.19-25
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    • 2017
  • The research is to identify social networks of problems that have an influence on the quality of ageing people's lives by using social network analysis, based on the premise that there are differences in networks of ageing problems in urban and rural areas. From analyzing network of ageing people's problems using NodeXL, vertices in the networks of both urban and rural areas are well-connected. For urban areas, financial poverty is the core problem related to the quality of life. It has direct connections with illness and health, family responsibility, housing, role loss in community, and employment, which have positive or negative interactions with the quality of older people's lives. For rural areas, on the other hand, role loss in community is the major problem. It has direct connections with the elderly abuse, financial poverty, leisure activity, divorce, isolation and loneliness from society, education, and suicide. As a result, the research shows that the problems of ageing people have strong linkages and interactive effects with a structure of network, and the networks are different depending on types of places for living.