• Title/Summary/Keyword: Multi-tool path

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State-Aware Re-configuration Model for Multi-Radio Wireless Mesh Networks

  • Zakaria, Omar M.;Hashim, Aisha-Hassan Abdalla;Hassan, Wan Haslina;Khalifa, Othman Omran;Azram, Mohammad;Goudarzi, Shidrokh;Jivanadham, Lalitha Bhavani;Zareei, Mahdi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.146-170
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    • 2017
  • Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients' traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users' mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows' routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

A Study on Effectiveness and Warrant Analysis for Two-Way Left-Turn Lanes (양방향 좌회전차로(TWLTLs) 적용효과 분석 및 설치준거 연구)

  • Bae, Gwang-Su;Sim, Gwan-Bo;Song, Chang-Yong
    • Journal of Korean Society of Transportation
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    • v.25 no.6
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    • pp.65-77
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    • 2007
  • A two-way left-turn lane is a continuous center left-turn lane that could be used as a deceleration and refuge area for both directions of left-turning vehicles. TWLTL's have been used effectively for access management treatment when applied to a highway that has wide-spread left turning traffic demand and a high-density of side streets. In this study, an effective analysis was carried out using a computer-based simulation tool, VISSIM, in order to evaluate performance and safety effects of TWLTLs and develop a warrant. In conclusion, the results indicated that there was a remarkable decrease of through and left-turning vehicle travel time delay on the main road and improvement of traffic safety.

An Exploratory Study on the Trustworthiness Analysis of Generative AI (생성형 AI의 신뢰도에 대한 탐색적 연구)

  • Soyon Kim;Ji Yeon Cho;Bong Gyou Lee
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.79-90
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    • 2024
  • This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.