Browsing by Author "Huang, Chung-Yuan"

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A community detection algorithm using network topologies and rule-based hierarchical arc-merging strategies
(2017-11-09)
Fu, Yu-Hsiang
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Huang, Chung-Yuan
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems.
A computer virus spreading model based on resource limitations and interaction costs
(2013-03-01)
Huang, Chung-Yuan
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Lee, Chun-Liang
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Wen, Tzai-Hung
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Sun, Chuen-Tsai
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資訊工程學系
Computer viruses are major threats to Internet security and privacy, therefore many researchers are addressing questions linked to virus propagation properties, spreading models, epidemic dynamics, tipping points, and control strategies. We believe that two important factors - resource limitations and costs - are being overlooked in this area due to an overemphasis on power-law connectivity distributions of scale-free networks affecting computer virus epidemic dynamics and tipping points. The study show (a) a significant epidemic tipping point does exists when resource limitations and costs are considered, with the tipping point exhibiting a lower bound; (b) when interaction costs increase or usable resources decrease, epidemic tipping points in scale-free networks grow linearly while density curves decrease linearly; (c) regardless of whether Internet user resources obey delta, uniform, or normal distributions, they retain the same epidemic dynamics and tipping points as long as the average value of those resources remains unchanged across different scale-free networks; (d) it is possible to control the spread of a computer virus in a scale-free network if resources are restricted and if costs associated with infection events are significantly increased through the use of a throttling strategy. (C) 2012 Elsevier Inc. All rights reserved.
A Multilayer Epidemiological Model Integrating Daily Commuting Network
(2010)
Tsai, Yu-Shiuan
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Huang, Chung-Yuan
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Wen, Tzai-Hung
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Sun, Chuen-Tsai
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資訊工程學系
To assess the impacts of various interventions on epidemic dynamics, the authors propose an integrated epidemiological simulation framework called Multilayer Epidemic Dynamics Simulator (MEDSim), which combines four contact structures: within age group, between age groups, daily commute, and nationwide interaction. We use the daily commuting network to simulate outbreak locations and intervention scenarios for the 2009 A/H1N1 influenza epidemic in Taiwan. Our three main findings are: (a) lower transmission rates and earlier intervention activation times did not reduce total numbers of infected cases, but did delay peak times; (b) when transmission rate was decreased by a minimum of 70%, significant slowing-down effects were observed when interventions were activated before the 50th new case (c) peaks times were achieved more quickly when initial outbreaks occurred in urban rather than rural areas. The innovative simulation framework reflects the dynamic processes of epidemics under different intervention scenarios, thus clarifying the effects of complex contact structures on disease transmission dynamics.
A Network-based Simulation Architecture for Studying Epidemic Dynamics
(2010-05-01)
Huang, Chung-Yuan
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Tsai, Yu-Shiuan
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Wen, Tzai-Hung
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資訊工程學系
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Department of Computer Science
Epidemiology instructors are collaborating with computer scientists to construct network-based simulations to recreate infectious disease transmission dynamics and to examine intervention strategy efficacies. Here we propose an architecture based on demographic and geographic properties to support the learning efforts of undergraduate students and novice researchers, and describe our simulations of HIV, SARS, and influenza transmission dynamics in Taiwan. Our findings are offered to support the construction of new network-based epidemic simulations.
A Novel Private Attitude and Public Opinion Dynamics Model for Simulating Pluralistic Ignorance and Minority Influence
(2014-06-30)
Huang, Chung-Yuan
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Wen, Tzai-Hung
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交大名義發表
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National Chiao Tung University
Pluralistic ignorance, a well-documented socio-psychological conformity phenomenon, involves discrepancies between private attitude and public opinion in certain social contexts. However, continuous opinion dynamics models based on a bounded confidence assumption fail to accurately model pluralistic ignorance because they do not address scenarios in which non-conformists do not need to worry about holding and expressing conflicting opinions. Such scenarios reduce the power of continuous opinion dynamics models to explain why certain groups doubt or change their opinions in response to minority views. To simulate the effects of (a) private acceptance of informational social influence and (b) public compliance with normative social influence on pluralistic ignorance and minority influences, we have created an agent-based simulation model in which attitude and opinion respectively represent an agent\'s private and expressed thoughts. Results from a series of simulation experiments indicate model validity equal to or exceeding those of existing opinion dynamics models that are also based on the bounded confidence assumption, but with different dynamics and outcomes in terms of collective opinion and attitude. The results also support the use of our proposed model for computational social psychology applications.
A Proposal for Intelligent Agents with Adjusting Self-Reputation Capability for Preventing Fraud in Multi-Agent Societies
(2014-03-01)
Wang, Sheng-Wen
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Huang, Chung-Yuan
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
Intelligent agents are increasingly being used for tasks such as e-commerce auto-bidding. Cooperation and defection challenges commonly found in multi-agent systems make the design and construction of a reliable reputation mechanism an important research and engineering goal. Here we describe our proposal for an intelligent agent model that addresses learning issues in terms of self-reputation. The agents in our proposed model are capable of evaluating their behaviors based on a mix of public and private interest considerations, and of testing various solutions aimed at mitigating self-discrepancy and meeting social standards. Our results indicate promise for integrating a self-reputation mechanism into a self-learning framework in a manner that encourages the early emergence of social cooperation among multiple agents and specific cooperation with individual agents.
Beyond bond links in complex networks:Local bridges, global bridges and silk links
(2019-12-15)
Huang, Chung-Yuan
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Chin, Wei-Chien-Benny
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Fu, Yu-Hsiang
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Tsai, Yu-Shiuan
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資訊工程學系
Many network researchers use intuitive or basic definitions when discussing the importance of strong and weak links and their roles. Others use an approach best described as "if not strong, then weak" to determine the strengths and weaknesses of individual links, thus deemphasizing hierarchical network structures that allow links to express different strength levels. Here we describe our proposal for a hierarchical edge type analysis (HETA) algorithm for determining link types at multiple network hierarchy levels based on the common neighbor concept plus statistical factors such as bond links, kth-layer local bridges, global bridges, and silk links-all generated during long-term network development and evolution processes. Two sets of networks were used to validate our proposed algorithm, one consisting of 16 networks employed in multiple past studies, and one consisting of two types of one-dimensional small-world networks expressing different random rewiring or shortcut addition probabilities. Two applications with potential for developmental contributions are demonstrated: a network fingerprint analysis framework, and a hierarchical network community partition method. (C) 2019 The Authors. Published by Elsevier B.V.
Bridge and brick motifs in complex networks
(2007-04-01)
Huang, Chung-Yuan
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Sun, Chuen-Tsai
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Cheng, Chia-Ying
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Hsieh, Ji-Lung
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資訊工程學系
Acknowledging the expanding role of complex networks in numerous scientific contexts, we examine significant functional and topological differences between bridge and brick motifs for predicting network behaviors and functions. After observing similarities between social networks and their genetic, ecological, and engineering counterparts, we identify a larger number of brick motifs in social networks and bridge motifs in the other three types. We conclude that bridge and brick motif content analysis can assist researchers in understanding the small-world and clustering properties of network structures when investigating network functions and behaviors. (c) 2006 Elsevier B.V. All rights reserved.
Bridge and brick network motifs: Identifying significant building blocks from complex biological systems
(2007-10-01)
Huang, Chung-Yuan
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Cheng, Chia-Ying
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
Objective: A major focus in computational system biology research is defining organizing principles that govern complex biological network formation and evolution. The task is considered a major challenge because network behavior and function prediction requires the identification of functionally and statistically important motifs. Here we propose an algorithm for performing two tasks simultaneously: (a) detecting global statistical features and Local connection structures in biological networks, and (b) locating functionally and statistically significant network motifs. Methods and material: Two gene regulation networks were tested: the bacteria Escherichia coli and the yeast eukaryote Saccharomyces cerevisiae. To understand their structural organizing principles and evolutionary mechanisms, we defined bridge motifs as composed of weak links only or of at least one weak link and multiple strong links, and defined brick motifs as composed of strong links only. Results: After examining functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions, we found that most genetic network motifs belong to the bridge category. This strongly suggests that the weak-tie links that provide unique paths for signal control significantly impact the signal processing function of transcription networks. Conclusions: Bridge and brick motif content analysis can provide researchers with global and local views of individual real networks and help them locate functionally and topologically overlapping or isolated motifs for purposes of investigating biotogical system functions, behaviors, and similarities. (C) 2007 Elsevier B.V. All rights reserved.
Collective opinion and attitude dynamics dependency on informational and normative social influences
(2011-10-01)
Huang, Chung-Yuan
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Tzou, Pen-Jung
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Sun, Chuen-Tsai
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教育研究所
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資訊工程學系
In a continuous opinion dynamics model using a bounded confidence assumption, individuals can only influence each other's opinions when those opinions are sufficiently close. However, we often observe real-world cases in which opinions are very different, yet individuals feel compelled to change their ideas to conform with their peers or superiors (or in rare cases, are willing to change them voluntarily). In other words, individuals tend to consider the practical value of conformity and worry about rejection if they do not adopt the opinions of the majority. To explore the influences of private acceptance of informational social influences and public compliance with normative social influences on collective opinion and attitude dynamics, we have created a model in which attitude and opinion respectively represent an agent's private and expressed thoughts. Results from a series of simulation experiments indicate that our simplified model is as valid as previous opinion dynamics models also based on the bounded confidence assumption, but with different dynamics and outcomes regarding group opinion and attitude. To demonstrate our proposed model's potential value and applications, we briefly discuss two issues of import to sociologists: pluralistic ignorance formation and destruction and minority influence.
Effects of friend-making resources/costs and remembering on acquaintance networks
(2010-02-01)
Huang, Chung-Yuan
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Tsai, Yu-Shiuan
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資訊工程學系
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Department of Computer Science
We consider two overlooked yet important factors that affect acquaintance network evolution and formation-friend-making resources and remembering-and propose a bottom-up, network-oriented simulation model based on three rules representing human social interactions. Our proposed model reproduces many topological features of real-world acquaintance networks, including a small-world phenomenon and a sharply peaked connectivity distribution feature that mixes power-law and exponential distribution types. We believe that this is an improvement over fieldwork sampling methods that fail to capture acquaintance network node connectivity distributions. Our model may produce valuable results for sociologists working with social opinion formation and epidemiologists studying epidemic dynamics. (C) 2009 Elsevier B.V. All rights reserved.
Effects of Resource Limitations and Cost Influences on Computer Virus Epidemic Dynamics and Tipping Points
(2012)
Huang, Chung-Yuan
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
One of the most important assessment indicators of computer virus infections is epidemic tipping point. Although many researchers have focused on the effects of scale-free network power-law connectivity distributions on computer virus epidemic dynamics and tipping points, few have comprehensively considered resource limitations and costs. Our goals for this paper are to show that (a) opposed to the current consensus, a significant epidemic tipping point does exist when resource limitations and costs are considered and (b) it is possible to control the spread of a computer virus in a scale-free network if resources are restricted and if costs associated with infection events are significantly increased.
EpiRank: Modeling Bidirectional Disease Spread in Asymmetric Commuting Networks
(2019-04-01)
Huang, Chung-Yuan
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Chin, Wei-Chien-Benny
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Wen, Tzai-Hung
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Fu, Yu-Hsiang
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Tsai, Yu-Shivan
Commuting network flows are generally asymmetrical, with commuting behaviors bi-directionally balanced between home and work locations, and with weekday commutes providing many opportunities for the spread of infectious diseases via direct and indirect physical contact. The authors use a Markov chain model and PageRank-like algorithm to construct a novel algorithm called EpiRank to measure infection risk in a spatially confined commuting network on Taiwan island. Data from the country's 2000 census were used to map epidemic risk distribution as a commuting network function. A daytime parameter was used to integrate forward and backward movement in order to analyze daily commuting patterns. EpiRank algorithm results were tested by comparing calculations with actual disease distributions for the 2009 H1N1 influenza outbreak and enterovirus cases between 2000 and 2008. Results suggest that the bidirectional movement model outperformed models that considered forward or backward direction only in terms of capturing spatial epidemic risk distribution. EpiRank also outperformed models based on network indexes such as PageRank and HITS. According to a sensitivity analysis of the daytime parameter, the backward movement effect is more important than the forward movement effect for understanding a commuting network's disease diffusion structure. Our evidence supports the use of EpiRank as an alternative network measure for analyzing disease diffusion in a commuting network.
Evaluating subjective compositions by the cooperation between human and adaptive agents
(2006)
Huang, Chung-Yuan
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Hsieh, Ji-Lung
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Sun, Chuen-Tsai
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Cheng, Chia-Ying
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資訊工程學系
We describe a music recommender model that uses intermediate agents to evaluate music composition according to their own rules respectively, and make recommendations to user. After user scoring recommended items, agents can adapt their selection rules to fit user tastes, even when user preferences undergo a rapid change. Depending on the number of users, the model can also be applied to such tasks as critiquing large numbers of music, image, or written compositions in a competitive contest with other judges. Several experiments are reported to test the model\'s ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.
Identify influential social network spreaders
(2014)
Huang, Chung-Yuan
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Fu, Yu-Hsiang
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
Identifying the most influential individuals spreading ideas, information, or infectious diseases is a topic receiving significant attention from network researchers, since such identification can assist or hinder information dissemination, product exposure, or contagious disease detection. Hub nodes, high betweenness nodes, high closeness nodes, and high k-shell nodes have been identified as good initial spreaders. However, few efforts have been made to use node diversity within network structures to measure spreading ability. The two-step framework described in this paper uses a robust and reliable measure that combines global diversity and local features to identify the most influential network nodes. Results from a series of SusceptibleInfected- Recovered (SIR) epidemic simulations indicate that our proposed method performs well and stably in single initial spreader scenarios associated with various complex network datasets.
Identifying Super-Spreader Nodes in Complex Networks
(2015-01-01)
Fu, Yu-Hsiang
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Huang, Chung-Yuan
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
Identifying the most influential individuals spreading information or infectious diseases can assist or hinder information dissemination, product exposure, and contagious disease detection. Hub nodes, high betweenness nodes, high closeness nodes, and high k-shell nodes have been identified as good initial spreaders, but efforts to use node diversity within network structures to measure spreading ability are few. Here we describe a two-step framework that combines global diversity and local features to identify the most influential network nodes. Results from susceptible-infected-recovered epidemic simulations indicate that our proposed method performs well and stably in single initial spreader scenarios associated with various complex network datasets.
Impact of Vehicular Networks on Emergency Medical Services in Urban Areas
(2014-11-01)
Lee, Chun-Liang
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Huang, Chung-Yuan
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Hsiao, Tzu-Chien
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Wu, Chun-Yen
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Chen, Yaw-Chung
The speed with which emergency personnel can provide emergency treatment is crucial to reducing death and disability among acute and critically ill patients. Unfortunately, the rapid development of cities and increased numbers of vehicles are preventing emergency vehicles from easily reaching locations where they are needed. A significant number of researchers are experimenting with vehicular networks to address this issue, but in most studies the focus has been on communication technologies and protocols, with few efforts to assess how network applications actually support emergency medical care. Our motivation was to search the literature for suggested methods for assisting emergency vehicles, and to use simulations to evaluate them. Our results and evidence-based studies were cross-referenced to assess each method in terms of cumulative survival ratio (CSR) gains for acute and critically ill patients. Simulation results indicate that traffic light preemption resulted in significant CSR increases of between 32.4% and 90.2%. Route guidance was found to increase CSRs from 14.1% to 57.8%, while path clearing increased CSRs by 15.5% or less. It is our hope that this data will support the efforts of emergency medical technicians, traffic managers, and policy makers.
Influences of Resource Limitations and Transmission Costs on Epidemic Simulations and Critical Thresholds in Scale-Free Networks
(2009-03-01)
Huang, Chung-Yuan
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Tsai, Yu-Shiuan
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Sun, Chuen-Tsai
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Hsieh, Ji-Lung
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Cheng, Chia-Ying
Critical thresholds represent one of the most important diffusion indicators of epidemic outbreaks. However, we believe that recent studies have overemphasized ways that the power-law connectivity distribution features of social networks affect epidemic dynamics and critical thresholds. As a result, two important factors have been overlooked: resource limitations and transmission costs associated with social interactions and daily contact. Here we present our results from the simultaneous application of mean-field theory and an agent-based network simulation approach for analyzing the effects of resources and costs on epidemic dynamics and critical thresholds. Our main findings are: (a) a significant critical threshold does exist when resources and costs are taken into consideration, and it has a lower bound whenever contagion events occur in scale-free networks; (b) when transmission costs increase or individual resources decrease, critical contagion thresholds in scale-free networks grow linearly and steady density curves shrink linearly;(c) regardless of whether the resources of individuals obey delta, uniform, or normal distributions, they have the same critical thresholds and epidemic dynamics as long as the average value of usable resources remains the same across different scale-free networks; and (d) the spread of epidemics in scale-free networks remains controllable as long as resources are properly restricted and intervention strategy investments are significantly increased.
Integrating epidemic dynamics with daily commuting networks: building a multilayer framework to assess influenza A (H1N1) intervention policies
(2011-05-01)
Tsai, Yu-Shiuan
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Huang, Chung-Yuan
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Wen, Tzai-Hung
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Sun, Chuen-Tsai
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Yen, Muh-Yong
We describe an innovative simulation framework that combines daily commuting network data with a commonly used population-based transmission model to assess the impacts of various interventions on epidemic dynamics in Taiwan. Called the Multilayer Epidemic Dynamics Simulator (MEDSim), our proposed framework has four contact structures: within age group, between age groups, daily commute, and nationwide interaction. To test model flexibility and generalizability, we simulated outbreak locations and intervention scenarios for the 2009 swine-origin influenza A (H1N1) epidemic. Our results indicate that lower transmission rates and earlier intervention activation times did not reduce total numbers of infected cases, but did delay peak times. When the transmission rate was decreased by a minimum of 70%, significant epidemic peak delays were observed when interventions were activated before new case number 50; no significant effects were noted when the transmission rate was decreased by less than 30%. Observed peaks occurred more quickly when initial outbreaks took place in urban rather than rural areas. According to our results, the MEDSim provides insights that reflect the dynamic processes of epidemics under different intervention scenarios, thus clarifying the effects of complex contact structures on disease transmission dynamics.
Mining bridge and brick motifs from complex biological networks for functionally and statistically significant discovery
(2008-02-01)
Cheng, Chia-Ying
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Huang, Chung-Yuan
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Sun, Chuen-Tsai
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資訊工程學系
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Department of Computer Science
A major task for postgenomic systems biology researchers is to systematically catalogue molecules and their interactions within living cells. Advancements in complex-network theory are being made toward uncovering organizing principles that govern cell formation and evolution, but we lack understanding of how molecules and their interactions determine how complex systems function. Molecular bridge motifs include isolated motifs that neither interact nor overlap with others, whereas brick motifs act as network foundations that play a central role in defining global topological organization. To emphasize their structural organizing and evolutionary characteristics, we define bridge motifs as consisting of weak links only and brick motifs as consisting of strong links only, then propose a method for performing two tasks simultaneously, which are as follows: 1) detecting global statistical features and local connection structures in biological networks and 2) locating functionally and statistically significant network motifs. To further understand the role of biological networks in system contexts, we examine functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions. After observing brick motif similarities between E. coli and S. cerevisiae, we note that bridge motifs differentiate C. elegans from Drosophila and sea urchin in three types of networks. Similarities (differences) in bridge and brick motifs imply similar (different) key circuit elements in the three organisms. We suggest that motif-content analyses can provide researchers with global and local data for real biological networks and assist in the search for either isolated or functionally and topologically overlapping motifs when investigating and comparing biological system functions and behaviors.