• 제목/요약/키워드: Network behavior

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소셜 네트워크 사이트의 정보 매개하기 : 시뮬레이션 연구 (Information Mediating in Social Network Sites : A Simulation Study)

  • 노상규;김태경;박진수
    • 한국전자거래학회지
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    • 제18권1호
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    • pp.33-55
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    • 2013
  • 개인의 관심사나 사회적 문제를 토론하는 장으로 소셜 네트워크 사이트가 최근 활발하게 쓰인다. 기업에 대한 소식들이 소셜 네트워크 사이트의 사용자들 사이에서 회자되기는 마찬가지다. 이처럼 소셜 네트워크 사이트는 정보가 확산되는 주요 통로로 사용되나, 어떻게 그것이 가능한지에 대한 학문적 이해는 부족한 형편이다. 소셜 네트워크 사이트에서 정보가 전파될 때, 개인과 개인 간의 담화, 혹은 한 개인이 자신의 지인들에게 정보를 알려주는 방법에 따른다. 그런데 이와 같은 개인적 노력으로도 사회적 파장을 불러올 만큼 소셜 네트워크 서비스의 정보 확산은 대단하다. 본 논문은 '정보 매개하기'를 중심으로 어떻게 개인 수준의 정보 전파가 네트워크 수준의 정보 확산을 가져오는지를 이해하려 한다. 특히 정보 매개하기에 있어서 '정보 걸러내기의 효과'의 역할에 관심을 집중했다. 시뮬레이션의 결과를 통해, 정보 매개하기 활동이 정보 전파를 활성화시키며, 나아가 정보 확산에 기여하는 것으로 드러났다. 또한 정보 걸러내기 효과가 있을 때, 매우 작은 확률로 정보 매개하기 활동이 있다고 해도, 그 영향력은 아주 크다는 점을 보였다. 즉, 이미 정보 전파가 있었다는 사실이 다른 사람들의 관심을 끌 수 있다면 비록 소수만이 정보 전파 활동을 하더라도 정보는 아주 빨리 퍼져나갈 수 있다.

Deep neural network for prediction of time-history seismic response of bridges

  • An, Hyojoon;Lee, Jong-Han
    • Structural Engineering and Mechanics
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    • 제83권3호
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    • pp.401-413
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    • 2022
  • The collapse of civil infrastructure due to natural disasters results in financial losses and many casualties. In particular, the recent increase in earthquake activities has highlighted on the importance of assessing the seismic performance and predicting the seismic risk of a structure. However, the nonlinear behavior of a structure and the uncertainty in ground motion complicate the accurate seismic response prediction of a structure. Artificial intelligence can overcome these limitations to reasonably predict the nonlinear behavior of structures. In this study, a deep learning-based algorithm was developed to estimate the time-history seismic response of bridge structures. The proposed deep neural network was trained using structural and ground motion parameters. The performance of the seismic response prediction algorithm showed the similar phase and magnitude to those of the time-history analysis in a single-degree-of-freedom system that exhibits nonlinear behavior as a main structural element. Then, the proposed algorithm was expanded to predict the seismic response and fragility prediction of a bridge system. The proposed deep neural network reasonably predicted the nonlinear seismic behavior of piers and bearings for approximately 93% and 87% of the test dataset, respectively. The results of the study also demonstrated that the proposed algorithm can be utilized to assess the seismic fragility of bridge components and system.

Factors Affecting Value Co-Creation Behavior for Social Enterprises in Retail Sector

  • Sungjoon YOON;Heeyeon KIM
    • 유통과학연구
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    • 제22권9호
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    • pp.97-106
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    • 2024
  • Purpose: In view of increased social awareness of today's consumers, it is very important to understand how retail customers perceive their sense of social responsibility. This study aims to explore the decision processes of university students that affect the patronage of social enterprises in retail sector. Research design, data and methodology: This study proposes and tests whether and how social network traits, firm's image, and perceived trustworthiness serve as predictors of value co-creation behavior specific to two different industries (social enterprises and regular firms) operating in retail sector of South Korea. This study incorporated theoretical premise of value co-creation to verify the structural relationships among the predictors of value co-creation. Results: The result demonstrates that social network and firm's image both significantly influence consumers' value co-creation behavior. The study further found that the firm's image is overall more effective for eliciting consumers' value co-creation behavior than social network traits. Conclusions: As the result of comparing the industry type (social enterprises vs. regular firms), the study confirmed a meaningful difference such that consumers indicated greater impact of firm's image on value co-creation for social enterprises than for regular firms. The findings are expected to provide useful industrial insights for the management of social enterprises.

분산형 센서로 구현된 지능화 공간을 위한 계층적 행위기반의 이동에이젼트 제어 (Human Hierarchical Behavior Based Mobile Agent Control in Intelligent Space with Distributed Sensors)

  • 진태석;히데키 하시모토
    • 제어로봇시스템학회논문지
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    • 제11권12호
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    • pp.984-990
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    • 2005
  • The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.

Interactive Human Intention Reading by Learning Hierarchical Behavior Knowledge Networks for Human-Robot Interaction

  • Han, Ji-Hyeong;Choi, Seung-Hwan;Kim, Jong-Hwan
    • ETRI Journal
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    • 제38권6호
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    • pp.1229-1239
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    • 2016
  • For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play-based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.

Microwave Network Study by Bond Graph Approach. Application to Tow-Port Network Filter

  • Jmal, Sabri;Taghouti, Hichem;Mami, Abdelkader
    • International Journal of Computer Science & Network Security
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    • 제22권1호
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    • pp.121-128
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    • 2022
  • There are much processing techniques of microwave circuits, whose dimensions are small compared to the wavelength, but the disadvantage is that they cannot be directly applied to circuits working at high and/or low frequencies. In this article, we will consider the bond graph approach as a tool for analyzing and understanding the behavior of microwave circuits, and to show how basic circuit and network concepts can be extended to handle many microwaves analysis and design problems of practical interest. This behavior revealed in the scattering matrix filter, and which will be operated from its reduced bond graph model. So, we propose in this paper, a new application of bond graph approach jointly with the scattering bond graph for a high frequency study.

Game Theoretic based Distributed Dynamic Power Allocation in Irregular Geometry Multicellular Network

  • Safdar, Hashim;Ullah, Rahat;Khalid, Zubair
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.199-205
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    • 2022
  • The extensive growth in data rate demand by the smart gadgets and mobile broadband application services in wireless cellular networks. To achieve higher data rate demand which leads to aggressive frequency reuse to improve network capacity at the price of Inter Cell Interference (ICI). Fractional Frequency Reuse (FFR) has been recognized as an effective scheme to get a higher data rate and mitigate ICI for perfect geometry network scenarios. In, an irregular geometric multicellular network, ICI mitigation is a challenging issue. The purpose of this paper is to develop distributed dynamic power allocation scheme for FFR based on game theory to mitigate ICI. In the proposed scheme, each cell region in an irregular multicellular scenario adopts a self-less behavior instead of selfish behavior to improve the overall utility function. This proposed scheme improves the overall data rate and mitigates ICI.

LIN 프로토콜 시간 모델링 및 메시지 응답 시간 해석에 관한 연구 (A Study on Timing Modeling and Response Time Analysis in LIN Based Network System)

  • 연제명;선우명호;이우택
    • 한국자동차공학회논문집
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    • 제13권6호
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    • pp.48-55
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    • 2005
  • In this paper, a mathematical model and a simulation method for the response time analysis of Local Interconnect Network(LIN) based network systems are proposed. Network-induced delays in a network based control system can vary widely according to the transmission time of message and the overhead time of transmission. Therefore, in order to design a distributed control system using LIN network, a method to predict and verify the timing behavior of LIN protocol is required at the network design phase. Furthermore, a simulation environment based on a timing model of LIN protocol is beneficial to predict the timing behavior of LIN. The model equation is formulated with six timing parameters deduced from timing properties of LIN specification. Additionally, LIN conformance test equations to verify LIN device driver are derived with timing constraints of the parameters. The proposed model equation and simulation method are validated with a result that is measured at real LIN based network system.

B2C 트위터를 통한 고객참여행위가 기업충성도에 미치는 영향 (The Effect of Customer Participation Behavior on Brand Loyalty via B2C Microblogging)

  • 박종필
    • 한국경영과학회지
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    • 제38권1호
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    • pp.69-87
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    • 2013
  • Recently a large number of people have been using social networking and microblogging services such as Facebook and Twitter. These mediums play a pivotal communication channel in a business-to-customer (B2C) relationship. Given its importance in today's business, companies have invested in the strategic application of social network services to reach out to customers. This study provides a blueprint for mechanisms for successful execution of social network services in the context of developing an effective B2C relationship, such as customer participation behavior. The S-O-R(Stimulus-Organism-Response) framework lays out the foundation for developing our research model and provides a structured view for understanding customer participation behavior on brand loyalty. For the methodology, this study employed a mixed-method approach. Additionally, in order to provide empirical evidences, a total of 121 respondents have completed the survey. All the data were compiled and analyzed through structural equation modeling and were implemented in partial least square (PLS). To sum up, this study presented theoretical and practical implications by providing the effect of customer participation behavior on brand loyalty through B2C microblogging.

Development of Artificial Neural Network Model for Simulating the Flow Behavior in Open Channel Infested by Submerged Aquatic Weeds

  • Abdeen Mostafa A. M.
    • Journal of Mechanical Science and Technology
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    • 제20권10호
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    • pp.1576-1589
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    • 2006
  • Most of surface water ways in Egypt suffer from the infestation of aquatic weeds especially submerged ones which cause lots of problems for the open channels and the water structures such as increasing water losses, obstructing the water flow, and reducing the efficiency of the water structures. Accurate simulation of the water flow behavior in such channels is very essential for water distribution decision makers. Artificial Neural Network (ANN) has been widely utilized in the past ten years in civil engineering applications for the simulation and prediction of the different physical phenomena and has proven its capabilities in the different fields. The present study aims towards introducing the use of ANN technique to model and predict the impact of the existence of submerged aquatic weeds on the hydraulic performance of open channels. Specifically the current paper investigates utilizing the ANN technique in developing a simulation and prediction model for the flow behavior in an open channel experiment that simulates the existence of submerged weeds as branched flexible elements. This experiment was considered as an example for implementing the same methodology and technique in a real open channel system. The results of current manuscript showed that ANN technique was very successful in simulating the flow behavior of the pre-mentioned open channel experiment with the existence of the submerged weeds. In addition, the developed ANN models were capable of predicting the open channel flow behavior in all the submerged weeds' cases that were considered in the ANN development process.