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Preliminary Plan for Data Collection on Stakeholder information Interdependence in Area-Business Continuity Management: A Case Study of Flood Management in Thai Industrial Zones

Preliminary Plan for Data Collection on Stakeholder Informat...

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International Symposium on Communications and information Technologies (ISCIT)

作者： Penpitcha Arayachookiat Kumpol Saengtabtim Akira Kodaka Natt Leelawat Jing Tang Kenji Watanabe Risk and Disaster Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Faculty of Engineering International School of Engineering Chulalongkorn University Bangkok Thailand Graduate School of Social Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

The 2011 flood in Thailand exposed significant vulnerabilities in industrial areas, highlighting the necessity for enhanced disaster risk management through Area-Business Continuity Management (Area-BCM). This preliminary study focuses on identifying how stakeholders rely on information from each other to improve disaster preparedness and response. The research involves systematically identifying Area-BCM stakeholders and designing interview questions, which are evaluated by experts using the Index of Item-Objective Congruence (IOC) to ensure relevance and clarity. All interview questions surpassed the IOC threshold of 0.5, confirming their effectiveness in capturing information interdependencies. Expert feedback led to refinements in the questions, underscoring the importance of tailored data collection. This initial plan provides a critical foundation for understanding information interdependence and highlights the importance of well-designed data collection methods. The findings have significant implications for developing more resilient disaster management strategies in industrial areas, emphasizing the need for precise and relevant stakeholder communication to enhance Area-BCM effectiveness.

关键词： Disasters Disaster management Data collection information and communication technology Stakeholders Floods Risk management Iterative methods Interviews Resilience

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Air Particulate Matters Auto-Rule-Based Labeling to Support Long-Distance Run Environment Data Classification

Air Particulate Matters Auto-Rule-Based Labeling to Support ...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Wandy Wandy Kusworo Adi Media Anugerah Ayu Doctoral Program of Information Systems School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Computer Science Faculty of Engineering and Technology Sampoerna University South Jakarta Indonesia

Sports Science is an interdisciplinary and multidisciplinary science that strives to increase athletic performance and endurance. Sport Science recognizes and prevents injuries. Sensors and statistics formalize Sports Science. Runners need coaches and teams to support them before, during, and after the run race. Coaches generate running training plans to boost performance. Running race performances may be impacted by air pollution exposure while training, so coaches should consider limiting air pollution exposure when training. One of the external factors is Particulate Matter (PM 2.5 and PM 10 ). Sensors connecting to the Internet can record external factors and produce csv data. The foundation of supervised machine learning is the labeling process. Labeling a set of data is one of the laborious and time-consuming phases in every machine-learning application because it requires verifying the accuracy of the labels and making any necessary revisions. This research aimed to find a solution to automatically label numerous air particulate matter raw data using a rule based on parameters to reduce manual work, human errors and faster processes. This labeled data will later be used for supervised machine learning classification to support the coach in generating training programs for the runners in a Sports information System. Based on Indonesia Air Quality index rule-based approach, labeled text data in csv has been generated and tested with PM 2.5 and PM 10 parameters in three scenarios with a 100% success rate. It was possible to automate the labeling process, and it explained how automation results in fast and accurate results.

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A review of automatic solar tracking systems 7

A review of automatic solar tracking systems

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7th International Conference on Applications and Design in Mechanical engineering, ICADME 2021

作者： Mohamad, A. Mhamdi, H. Amin, N.A.M. Izham, M. Aziz, N.A. Chionh, S.Y. Mechanical Engineering Program Faculty of Mechanical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Laboratory of Electronic Systems Information Processing Mechanics and Energetics Faculty of Sciences University Ibn Tofail Kenitra Morocco Institute of Engineering Mathematics Faculty of Applied Sciences and Humanities Universiti Malaysia Perlis Perlis Malaysia

Solar tracking systems which can track the Sun movement can increase the power generation rate by maximizing the surface area of the solar panels that are exposed to the sunlight. By utilizing a solar tracker, the number of solar panels needed to generate the same amount of electrical energy will be significantly lower. In general, solar tracking systems are classified as single-axis solar tracking systems and dual-axis solar tracking systems. Several researchers had conducted both simulation and experimental work to compare and evaluate the performance of solar tracking systems against static solar panels systems, as well as between different solar tracking system mechanisms. General agreements among the researchers are that the performance of solar tracking systems is always exceeding that of static solar panels. Some researchers also conducted studies on how the weather conditions affect the performance of solar panels, and they concluded that the systems with tracking mechanisms are more resilient toward a variation of weather conditions. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Meteorology

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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Influence of information about Minimal Risk Maneuvers on Driver Behavior during Conditional Driving Automation

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International Journal of Automotive engineering 2022年第3期13卷 122-131页

作者： Ichinose, Yusaku Zhou, Huiping Saito, Yuichi Itoh, Makoto Master's Program in Risk and Resilience Engineering University of Tsukuba 1-1-1 Tennoudai Tsukuba Ibaraki305-8573 Japan Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 TennoudaiTsukuba Ibaraki305-8573 Japan

In Japan, the guidelines of safety technology for automated vehicles clearly state the requirement of level-3 equipment with minimal risk maneuver (MRM) in automated vehicles. In case the drivers fail to respond to a request for intervention, the conditional driving automation system activates an MRM to control the vehicle to a halt in the driving lane or on the side of the road. The current study aims to explore the research question: how does the information of the MRM functionality equipped within the automated vehicle affect the driver behavior during conditionally automated driving? In this study, we hypothesized that drivers who are provided with information about MRM functionality may reduce their attention toward the surrounding environment. The attention allocation to the surrounding environment may be related to the quality of take-over performance. Therefore, we attempted to observe the drivers' takeover performance in response to RtI. Accordingly, a driving simulator experiment was conducted with 28 drivers as participants to investigate the influence of information regarding MRM on driver behavior. Two groups were formed by randomly placing the participants with and without providing MRM information. The results revealed that the information on MRM triggered a behavioral change in the drivers and reduced their attention toward the surrounding environment or allocated more attention toward the surrounding environment. In future, we would examine the method and content of communicating the MRM information to drivers using automated driving systems. © 2022. Society of Automotive Engineers of Japan, Inc. All Rights Reserved.

关键词： Automation

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AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Forged content shared widely on social media platforms is a major social problem that requires increased regulation and poses new challenges to the research community. The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous work on detecting AI-generated fake videos only utilizes visual modality or audio modality. While there are some methods in the literature that exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multi-modal datasets of deepfake videos involving acoustic and visual manipulations. Moreover, these existing methods are mostly based on CNN and suffer from low detection accuracy. Inspired by the recent success of Transformer in various fields, to address the challenges posed by deepfake technology, in this paper, we propose an Audio-Visual Transformer-based Ensemble Network (AVTENet) framework that considers both acoustic manipulation and visual manipulation to achieve effective video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multi-modal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that our best model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. © 2023, CC BY.

关键词： Statistical tests

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Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Van Huynh, Nguyen Du, Hongyang Hoang, Dinh Thai Niyato, Dusit Zhu, Kun Kang, Jiawen Xiong, Zehui Jamalipour, Abbas In Kim, Dong The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney Australia The School of Computer Science and Engineering Nanyang Technological University Singapore College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Information Engineering University of Sydney Australia The College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions. © 2024, CC BY.

关键词： Metadata

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Mean-variance and Safety-first Portfolio Selection Strategy for High-volume/Highvalue Traded Stocks in Philippine Stock Exchange (PSE)

Mean-variance and Safety-first Portfolio Selection Strategy ...

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IEEE International Conference on Industrial engineering and engineering Management

作者： T. C. De Guzman M. N. Young Y. T. Prasetyo S. F. Persada R. Nadilfatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This research evaluates the effectiveness of Mean-Variance (MV) and Safety-First (SF) portfolio selection strategies for high-volume/high-value traded stocks on the Philippine Stock Exchange (PSE). Analyzing data from 288 stocks over 7,670 trading days (30 years), we estimated stock returns, assigned probability weights, and conducted optimization models. The results show that the Mean-Variance (MV0.5) strategy achieved the best balance between risk and return, boasting the highest mean and cumulative returns with moderate volatility. The Safety-First (SF) strategy, however, yielded negative cumulative returns, indicating potential issues. The Market strategy had the lowest mean return but also the least risk, appealing to risk-averse investors. The Portfolio Mean-Variance (PMV) strategy provided a reasonable balance of returns and risk. Statistical analysis revealed that only the MV0.5 strategy outperformed market returns. These findings offer crucial insights into risk assessment and portfolio management for investors evaluating these strategies against market performance.

关键词： Statistical analysis Optimization models Oils Safety Risk management Stock markets Portfolios Standards Monitoring Investment

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A study on estimation of traveling direction for pedestrian dead reckoning by using inertial sensors 9

A study on estimation of traveling direction for pedestrian ...

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9th IEEE Global Conference on Consumer Electronics, GCCE 2020

作者： Matsumoto, Takumi Fujii, Masahiro Utsunomiya University Graduate Program in Information Electrical and Electronics Systems Engineering 7-1-2 Yoto Utsunomiya Tochigi Japan

ISBN: (纸本)9781728198026

In this paper, we propose a new method to estimate the traveling direction for pedestrian by applying IMU (Inertial Measurement Unit) and PCA (Principal Component Analysis) to sensor information from a smartwatch. Because a result of PCA do not have orientation information, an estimate of the traveling direction includes an indeterminacy problem. We show that the proposed method can solve this problem and provide high accuracy in the traveling direction estimation by walking experiments. © 2020 IEEE.

关键词： Principal component analysis

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Enabling AI-Generated Content (AIGC) Services in Wireless Edge Networks

arXiv

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arXiv 2023年

作者： Du, Hongyang Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Shen, Xuemin Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of Waterloo Canada The Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

Artificial Intelligence-Generated Content (AIGC) refers to the use of AI to automate the information creation process while fulfilling the personalized requirements of users. However, due to the instability of AIGC models, e.g., the stochastic nature of diffusion models, the quality and accuracy of the generated content can vary significantly. In wireless edge networks, the transmission of incorrectly generated content may unnecessarily consume network resources. Thus, a dynamic AIGC service provider (ASP) selection scheme is required to enable users to connect to the most suited ASP, improving the users’ satisfaction and quality of generated content. In this article, we first review the AIGC techniques and their applications in wireless networks. We then present the AIGC-as-a-service (AaaS) concept and discuss the challenges in deploying AaaS at the edge networks. Yet, it is essential to have performance metrics to evaluate the accuracy of AIGC services. Thus, we introduce several image-based perceived quality evaluation metrics. Then, we propose a general and effective model to illustrate the relationship between computational resources and user-perceived quality evaluation metrics. To achieve efficient AaaS and maximize the quality of generated content in wireless edge networks, we propose a deep reinforcement learning-enabled algorithm for the optimal ASP selection. Simulation results show that the proposed algorithm can provide a higher quality of generated content to users and achieve fewer crashed tasks by comparing with four benchmarks, i.e., overloading-avoidance, random, round-robin policies, and the upper-bound schemes. © 2023, CC BY.

关键词： Reinforcement learning

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