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8th International HCI and UX Conference in Indonesia, CHIuXiD 2022

作者： Subandi, Subandi Syahidi, Aulia Akhrian Zakiah, Siti Kiyokawa, Kiyoshi Riyadi, Ahmad Noor, M. Helmy Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin Indonesia Universitas Brawijaya Informatics Engineering Undergraduate Program Faculty of Computer Science Malang Indonesia Nara Institute of Science and Technology Cybernetics and Reality Engineering Laboratory Ikoma Japan Politeknik Negeri Banjarmasin Informatics Engineering Diploma Program Banjarmasin Indonesia

ISBN: (纸本)9781665476645

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91. © 2022 IEEE.

关键词： Virtual reality

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Camera-Only Perception System for Traffic Jam Assistance

Camera-Only Perception System for Traffic Jam Assistance

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International Automatic Control Conference

作者： Xiao-Wei Huang Xiu-Zhi Chen Yen-Lin Chen Master Program in Artificial Intelligence Technology National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

Traditional perception systems for TJA (Traffic Jam Assistance) are mostly implemented by fusing images with radar or lidar. As computer vision techniques become more powerful, cameras can almost replace the need for radar and lidar in perception tasks, which reduces the hardware cost of the system. In this research, we propose a camera-only perception system for TJA, which is able to provide the information of the vehicles ahead and the drivable area. The proposed system has been evaluated through real-world scenario sequences, and proved that it achieves high robustness, which is highly possible to be adopted for TJA development.

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Feasibility Study of Semi-supervised Intrusion Detection Systems for Industrial Control Systems 10

Feasibility Study of Semi-supervised Intrusion Detection Sys...

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10th International Conference on Applied System Innovation, ICASI 2024

作者： Loo, Fu-Nie Chen, Tung-Shou Tsai, Chia-Wei Lin, Jason Yang, Chun-Wei National Taichung University of Science and Technology Department of Computer Science and Information Engineering No.129 Sec.3 Sanmin Rd. North Dist. Taichung City404 Taiwan National Chung Hsing University Department of Computer Science and Engineering 145 Xingda Rd. South Dist. Taichung City402202 Taiwan China Medical University Master Program for Digital Health Innovation No. 100 Sec. 1 Jingmao Rd. Beitun Dist. Taichung City406040 Taiwan

ISBN: (纸本)9798350394924

Industrial Control systems (ICS) automate industrial processes but also introduces cybersecurity threats. Intrusion Detection System (IDS) are crucial for detecting cyber-attacks on ICS, yet zero-day attacks are often inefficiently detecting with supervised learning. This study employs semi-supervised learning using one-class SVM, isolation forest, and Local Outlier Factor (LOF), to train IDS models. Utilizing dataset collected from a self-build virtual ICS environment, the study demonstrates the feasibility of these models in detecting common attack like Injection, ARP, and Man-in-the-Middle. © 2024 IEEE.

关键词： Zero-day attack

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Based-on computer Vision Applications for Bus Stop Passenger Detection System

Based-on Computer Vision Applications for Bus Stop Passenger...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Yu-Cheng Chang Hua-Wen Tsai Chao-Yi Huang Zong-Rong Wu Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taiwan Department of Bachelor's Program in Intelligent Robot National Yunlin University of Science and Technology Taiwan Department of Technical and Vocational Program in Artificial Intelligence National Yunlin University of Science and Technology Taiwan

Passenger transport is one of the most common ways of commuting in Taiwan. It plays an important role in the transportation system due to its large number of stations, dense frequency, and cheap transportation. Due to the unfriendly transportation environment and a large number of passengers, a blind spot of passenger transportation exists, which leads to traffic accidents at the station. We research to make the "Bus Stop Passenger Detection System". Taking the object detection of "Wheelchairs" into consideration, it is more convenient to assist the disabled to find the passenger transportation system, which makes Taiwan's transportation system more convenient.

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Hotel information System Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management information technology Interviews information systems

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A Census-Based Genetic Algorithm for Target Set Selection Problem in Social Networks

arXiv

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arXiv 2024年

作者： Rahman, Md Samiur Ahsan, Mohammad Shamim Chen, Tim Varadarajan, Vijayakumar Department of Computer Science & Engineering Presidency University Bangladesh Department of Computer Science & Engineering UIU Bangladesh Faculty of Information Technology Ton Duc Thang University Viet Nam Program Leader Engineering Ajeenkya D Y Patil University India

This paper considers the Target Set Selection (TSS) Problem in social networks, a fundamental problem in viral marketing. In the TSS problem, a graph and a threshold value for each vertex of the graph are given. We need to find a minimum size vertex subset to "activate" such that all graph vertices are activated at the end of the propagation process. Specifically, we propose a novel approach called "a census-based genetic algorithm" for the TSS problem. In our algorithm, we use the idea of a census to gather and store information about each individual in a population and collect census data from the individuals constructed during the algorithm's execution so that we can achieve greater diversity and avoid premature convergence at locally optimal solutions. We use two distinct census information: (a) for each individual, the algorithm stores how many times it has been identified during the execution;(b) for each network node, the algorithm counts how many times it has been included in a solution. The proposed algorithm can also self-adjust by using a parameter specifying the aggressiveness employed in each reproduction method. Additionally, the algorithm is designed to run in a parallelized environment to minimize the computational cost and check each individual's feasibility. Moreover, our algorithm finds the optimal solution in all cases while experimenting on random graphs. Furthermore, we execute the proposed algorithm on 14 large graphs of real-life social network instances from the literature, improving around 9.57 solution size (on average) and 134 vertices (in total) compared to the best solutions obtained in previous studies. Copyright © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Predicting Oil and Gas Pipe Wall Thickness Using Machine Learning

Predicting Oil and Gas Pipe Wall Thickness Using Machine Lea...

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2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021

作者： Mohammed, Abdulrahim Hewahi, Nabil College of Science University of Bahrain Big Data Science and Analytics Program Sakhir Bahrain College of Information Technology University of Bahrain Department of Computer Science Sakhir Bahrain

ISBN: (纸本)9781665416566

Pipeline networks are crucial for process industries transportation and business operation. These vital elements, however, are highly exposed to material degradation due to corrosion that seriously impedes operational profitability, reliability, and safety. Industries usually monitor pipeline corrosion rate by gauging pipe wall thickness. Predicting pipe wall thickness helps industries to identify locations with high corrosion rate at an early stage and take necessary actions. The aim of this research is to predict pipe wall thickness at different locations using different machine learning algorithms including Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbor (KNN), fully connected Artificial Neural Network (ANN), and Long Short-Term Memory (LSTM). The data processed and analyzed in this study included six different process variables as well as pipe wall thickness at three different locations in a downstream oil and gas industry. The study findings demonstrated that LSTM with test Root Mean Squared Errors (RMSEs) of 0.019 mm, 0.015 mm, and 0.017 mm for the three selected locations, outperformed the other methods applied and successfully identified the pipe wall thickness pattern. © 2021 IEEE.

关键词： Long short-term memory

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Performance LoRa technology for Autonomous Vehicles 24

Performance LoRa Technology for Autonomous Vehicles

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24th International Seminar on Intelligent technology and Its Applications, ISITIA 2023

作者： Adi, Puput Dani Prasetyo Purnama, Iwan Siregar, Arfanda Anugrah Juledi, Angga Putra Edi, Firman Karim, Abdul Wahyu, Yuyu Maulana, Fairuz Iqbal Susilo, Suhardi Atmoko Budi Toni Harahap, Ilham Maliki Patria, Lintang Bandung Indonesia Labuhanbatu University Faculty of Science and Technology North Sumatra Labuhanbatu Indonesia Politeknik Negeri Medan Telecommunication Engineering Study Program North Sumatra Medan City Indonesia Batam Institute of Technology Faculty of Industrial Technology Department of Engineering Management Riau Islands Batam City Indonesia Budi Darma University Department of Information Technology North Sumatra Medan Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia University Labuhanbatu Faculty of Teacher Training and Education North Sumatra Labuhanbatu Indonesia Universitas Terbuka Faculty of Engineering Jakarta Indonesia

ISBN: (纸本)9798350313956

This research is an approach to intelligent vehicles with a LoRa communication system, LoRaWAN compatible for Long-Range and Outdoor Communication, but in this paper, we will test the ability of LoRa to handle autonomous vehicles, a Blind-Adaptive Data method will be tried on vehicles systems. The system offered is when the vehicle is running, the sensor will send position data in real-time, the number of vehicles is four, and GPS data is sent alternately using the Blind Adaptive Data Rate principle to avoid data collisions, and when the GPS shows a certain position, the value of SF is ascertained, which affects the data rate and ToA, and the output given is RSSI on each car, speed of a car, power consumption of sensor nodes, signal power, SNR, Bit rate or data rate, and sensitivity. With the Blind ADR principle, it is ensured that there is no data collision between car position data that causes packet loss. © 2023 IEEE.

关键词： Autonomous vehicles

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Ant Colony Optimization (ACO) Algorithm for Determining the Nearest Route Search in Distribution of Light Food Production 4

Ant Colony Optimization (ACO) Algorithm for Determining the ...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Fahmi, H. Zarlis, M. Nababan, E.B. Sihombing, P. Computer Science Doctoral Degree Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

At this time the development of technology that forces everything must move fast, the efficiency of time becomes a measure of the success of a distribution or production. the continuity of production and the success of production itself is related to distribution. When the distribution fails, production will fail. Indonesian people especially in North Sumatra often consume snacks when free time and snacks are the most consumed food by the Indonesian population until now the production of snacks in Indonesia rose to 50% in 2019, causing the food production to have a concept in timely distribution without experiencing delays in distributing goods that have been produced. One of the expeditions in Indonesia experienced problems in terms of late distribution of goods up to 15-20%, this would have a bad impact on the industry in the future, so to overcome the problems above the application of the ant colony optimization algorithm can help the above problems by placing 4 ants and the ants will spread from point A to point H. In the results of this study, there are 4 ants that move together where the best results are obtained by ant 2, closest to the point H, where the value obtained reaches 0,00015 © Published under licence by IOP Publishing Ltd.

关键词： Ant colony optimization

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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