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Battle Royale Optimizer for solving binary optimization problems[Formula presented]

Software Impacts 2022年 12卷

作者： Akan, Taymaz Agahian, Saeid Dehkharghani, Rahim Istanbul Ayvansaray University Istanbul Turkey Faculty of Electrical Engineering and Informatics University of Pardubice Pardubice Czech Republic Erzurum Technical University Erzurum Turkey Department of Computer Engineering Işik University Istanbul Turkey

Battle Royale Optimizer (BRO) is a recently proposed metaheuristic optimization algorithm used only in continuous problem spaces. The BinBRO is a binary version of BRO. The BinBRO algorithm employs a differential expression, which utilizes a dissimilarity measure between binary vectors instead of a vector subtraction operator, used in the original BRO algorithm to find the nearest neighbor. To evaluate BinBRO, we applied it to two popular benchmark datasets: the uncapacitated facility location problem (UFLP) and the maximum-cut (Max-Cut) graph problems from OR-Library. An open-source MATLAB implementation of BinBRO is available on CodeOcean and GitHub websites. © 2022 The Author(s)

关键词： Battle Royale Optimization Binary Battle Royale Optimization Discrete optimization Optimization

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Development of first-person shooter game with survival maze based on virtual reality 6

Development of first-person shooter game with survival maze ...

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6th Information Technology International Seminar, ITIS 2020

作者： Herumurti, Darlis Yunanto, Andhik Ampuh Senna, Guruh Arya Kuswardayan, Imam Arifiani, Siska Institut Teknologi Sepuluh Nopember Keputih Department of Informatics Surabaya City Sukolilo East Java60111 Indonesia Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Keputih Sukolilo Surabaya City East Java60111 Indonesia

ISBN: (纸本)9781728177267

Game is one of the entertainment media that is rapidly growing. On this day, playing games is one way to spare time for refreshing. One of the popular games this year is an action game such as First-Person Shooter (FPS). Besides, the FPS game genre has developed rapidly to make it more interesting for the player. Non-player Character (NPC) has an essential function in artificially and automatically to make a game more immersive and consisting of various kinds. Also, from observation, adding challenges when playing, namely enemy characters, can make a player more enjoyable. Besides, one of modern technology to develop innovations for supporting a game is called virtual reality. So, in this research, the FPS game is built by adding NPC elements with virtual reality technology. Also, the gameplay in this game is a survival maze. Based on the evaluation, this game application can display objects in a virtual reality smoothly, and all feature in this game can display and run effectively. Besides, the respondents also give good feedback for user testing which has average score 4.66 from several users. So, the conclusion from this research is this game can make the FPS game more interesting for users by adding NPC, 3D element, and virtual reality. © 2020 IEEE.

关键词： Virtual reality

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Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models

Digital Forensics Investigation and Incident Response in Int...

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International Conference on Wireless and Telematics (ICWT)

作者： Syaiful Ahdan Eki Ahmad Zaki Hamidi Sampurna Dadi Riskiono Ridha Muldina Negara Ratna Mayasari Suci Ramadona Ade Nurhayati Adi Sucipto Jupriyadi Galih Nugraha Nurkahfi Dzata Farahiyah Muchammad Naseer Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau Indonesia Faculty of Engineering Institut Teknologi Telkom Jakarta Jakarta Indonesia National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Industrial Technology Universitas Islam Indonesia Yogyakarta Yogyakarta Indonesia Informatics Department Sekolah Tinggi Teknologi Bandung Bandung Indonesia

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article.

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Benchmark Comparison of Methods for Approximate Neighborhood Estimation of Road Segments in Large-Scale Traffic Networks 24

Benchmark Comparison of Methods for Approximate Neighborhood...

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24th Pan-Hellenic Conference on informatics, PCI 2020

作者： I. Salamanis, Athanasios A. Gravvanis, George K. Filelis-Papadopoulos, Christos Michail, Dimitrios Department of Electrical and Computer Engineering School of Engineering Democritus University of Thrace University Campus Xanthi67100 Greece University College Cork Cork Ireland Department of Informatics and Telematics Harokopio University of Athens Greece

ISBN: (纸本)9781450388979

The accuracy of a traffic prediction model used to predict the future state of a link (i.e. road segment) of interest in a traffic network, can be enhanced by integrating the traffic information of adjacent links. The approximate estimation of such a neighborhood of links for all links of the traffic network is a type of approximate k-nearest neighbor search problem (k-NNS), which can prove to be quite computationally expensive especially for large-scale networks. In this paper, methods for solving this problem in large-scale traffic networks are presented and compared with each other in terms of both accuracy and running-time performance. Experiments have been conducted using real-world map data from the city of Thessaloniki, and the preliminary results indicate the effectiveness of the methods in solving the neighborhood estimation problem. © 2020 ACM.

关键词： Nearest neighbor search

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iTCLab PID Control Tuning Using Deep Learning

iTCLab PID Control Tuning Using Deep Learning

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Information Technology International Seminar (ITIS)

作者： Basuki Rahmat Minto Waluyo Tuhu Agung Rachmanto Agussalim Alfan Rizaldy Pratama Muljono Muljono I Gede Susrama Mas Diyasa Made Hanindia Prami Swari Novirina Hendrasarie Information Technology Masters Department Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya Indonesia Industrial Engineering Department Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya Indonesia Environmental Engineering Department Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya Indonesia Center for Research and Innovation on Advanced Transportation Electrification - Politeknik Elektronika Negeri Surabaya Indonesia Computer Science Department Universitas Dian Nuswantoro Semarang Indonesia Informatics Department Universitas Pembangunan Nasional “Veteran” Jawa Timur Surabaya Indonesia

This paper presents a novel approach for tuning Proportional-Integral-Derivative (PID) controllers using deep learning techniques, specifically applied to the iTCLab, an advanced industrial control laboratory system. PID controllers are widely used in industrial processes for their simplicity and effectiveness. However, their performance heavily relies on proper tuning, which can be a complex and time-consuming task. In this study, we leverage the capabilities of deep learning to automate and optimize the PID tuning process for the iTCLab setup. We propose a data-driven methodology that combines system identification, Deep Learning networks, and optimization algorithms to achieve superior PID controller tuning.

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Enhancing Security and Scalability of Metaverse with Blockchain-based Consensus Mechanisms

Enhancing Security and Scalability of Metaverse with Blockch...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Anand Singh Rajawat S.B. Goyal Aarti Goyal Kavita Rajawat Maria Simona Raboaca Chaman Verma Traian Candin Mihaltan School of Computer Science & Engineering Sandip University Nashik India Faculty of Information Technology City University Petaling Jaya Malaysia Mind Intellect Technology Indore India ICSI Energy Department National Research and Development Institute for Cryogenics and Isotopic Technologies Ramnicu Valcea Romania Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest Hungary Faculty of Building Services Technical University of Cluj-Napoca Cluj-Napoca Romania

This study examines how blockchain technology and consensus mechanisms can safeguard and grow the metaverse ecosystem. Blockchain is transparent and decentralized. It is unchangeable, cryptographically verified, and runs without a central authority. Blockchain technology can secure the metaverse and users' data. This study compares blockchain-based consensus algorithms such as POW(PoW), PoS, and PBFT to ensure metaverse safety. These consensus mechanisms provide safe, decentralized transaction verification, waste reduction, and network consensus. Studying blockchain technology's metaverse scaling restrictions and scaling solutions, including sharding, sidechains, and off-chain protocols. These methods increase throughput, parallel computing, and transaction speed. They improve the metaverse's eco-system. Quantitative analysis, simulations, and experiments determine the security and scalability of blockchain-based metaverse consensus processes. Changes will be quantified by measuring transaction speed, network throughput, and resource consumption. This study enables safe, scalable metaverse environments. Blockchain-based consensus mechanisms allow the metaverse to retain user data safely, halt undesirable conduct, and allow users to join without trusting each other. Scalability solutions declutter networks, enabling the metaverse to handle more individuals and transactions. Blockchain-based consensus mechanisms could make the metaverse more secure, private, and scalable. Users will trust each other, create new apps, and be more open to this groundbreaking digital world.

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Indexed Multiple Access with Reconfigurable Intelligent Surfaces: The Reflection Tuning Potential

arXiv

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arXiv 2023年

作者： Singh, Rohit Kaushik, Aryan Shin, Wonjae Alexandropoulos, George C. Toka, Mesut Renzo, Marco Di The Department of Electronics and Communication Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar144027 India The School of Engineering and Informatics University of Sussex BrightonBN1 9RH United Kingdom The Department of Electrical and Computer Engineering Ajou University Suwon-si16499 Korea Republic of The Department of Electrical Engineering Princeton University PrincetonNJ08544 United States The Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece The Technology Innovation Institute Masdar City Abu Dhabi9639 United Arab Emirates Paris-Saclay University CNRS CentraleSupelec Laboratoire des Signaux et Systemes 3 Rue Joliot-Curie Gif-surYvette91192 France

Indexed modulation (IM) is an evolving technique that has become popular due to its ability of parallel data communication over distinct combinations of transmission entities. In this article, we first provide a comprehensive survey of IM-enabled multiple access (MA) techniques, emphasizing the shortcomings of existing non-indexed MA schemes. Theoretical comparisons are presented to show how the notion of indexing eliminates the limitations of non-indexed solutions. We also discuss the benefits that the utilization of a reconfigurable intelligent surface (RIS) can offer when deployed as an indexing entity. In particular, we propose an RIS-indexed multiple access (RIMA) transmission scheme that utilizes dynamic phase tuning to embed multi-user information over a single carrier. The performance of the proposed RIMA is assessed in light of simulation results that confirm its performance gains. The article further includes a list of relevant open technical issues and research directions. Copyright © 2023, The Authors. All rights reserved.

关键词： Transmissions

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A Trust Assisted Matrix Factorization based Improved Product Recommender System

A Trust Assisted Matrix Factorization based Improved Product...

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2020 International Conference on Computational Science and Computational Intelligence, CSCI 2020

作者： Rahim, Asma Maqsood, Muazzam Mehmood, Irfan Muhammad, Khan Kim, Mucheol Comsats University Islamabad Department of Computer Science Pakistan University of Bradford Faculty of Engineering Informatics Department of Media Design and Technology United Kingdom Sejong University Software Department Seoul Korea Republic of Chung-Ang University School of Computer Science and Engineering Seoul Korea Republic of

ISBN: (纸本)9781728176246

Smart services is an efficient concept to provide services to the citizen in an efficient manner. The online shopping and recommender system play an important role in this scenario that provides efficient item recommendations to the citizens. Though, the majority of the latest recommender systems can't get effective and efficient prediction accuracy because of the sparsity of the item matrix against each user. Additionally, the recommendations are not reliable when tested upon larger datasets. To handle these problems, a trust-based technique is proposed, called trustasvd++, which fuses a user's trust data in the MF con. The offered strategy combines trust data and rating values to deal with the sparsity and cold start user's issues. Matrix Factorization (MF) has been recognized as a persuasive method for the formation of an effective Recommender System. Pearson correlation coefficient (PCC) is used as a similarity metric in the proposed technique. To assess the efficiency of the offered strategy, numerous datasets have been done on datasets including Epinions, Filmtrust, and Ciao. © 2020 IEEE.

关键词： Recommender systems

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Feature Attention Based Blind Denoising Network for mmWave Beamspace Channel Estimation

Feature Attention Based Blind Denoising Network for mmWave B...

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IEEE Globecom Workshops

作者： Erhan Karakoca Hasan Nayir Ali Görçin Khalid Qaraqe Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar Department of Electronics and Communication Engineering Istanbul Technical University İstanbul Turkey HİSAR Lab. @Informatics and Information Security Research Center (BİLGEM) TÜBİTAK Kocaeli Turkey Department of Electronics and Communication Engineering Yildiz Technical University İstanbul Turkey

ISBN: (纸本)9781665459761

In millimeter-wave (mmWave) MIMO systems, when the number of radio frequency (RF) chains are limited, estimation of the beamspace channel can become compelling. Also, as the number of RF chains decreases, pilot overhead increases to make channel estimation reliable, eventually reducing the spectral efficiency. In this paper, we propose a channel estimation method which combines compressive sensing (CS) method of GM-LAMP that assumes beamspace channel elements follows the Gaussian mixture distribution a priori, with a novel denoising network based on sparse feature attention for the estimation. According to performance analysis and simulation results, the GM-LAMP combined with feature attention based denoising neural network outperforms state-of-the-art compressed sensing-based algorithms. Furthermore, the proposed method also outperforms previous LAMP-based neural networks with comparable processing time, albeit using less pilot transmission.

关键词： Radio frequency Spectral efficiency Simulation Noise reduction Neural networks Millimeter wave technology Channel estimation

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Epidemic spreading and digital contact tracing: Effects of heterogeneous mixing and quarantine failures

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Physical Review E 2022年第4期105卷 044313-044313页

作者： Abbas K. Rizi Ali Faqeeh Arash Badie-Modiri Mikko Kivelä Department of Computer Science School of Science Aalto University FI-00076 Finland Mathematics Applications Consortium for Science & Industry University of Limerick Limerick V94 T9PX Ireland Luddy School of Informatics Computing and Engineering Indiana University Bloomington Indiana 47408 USA

Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading. Its effectivity can be quantified by modifying the standard methodology for analyzing percolation and connectivity of contact networks. We apply this framework to networks with varying degree distributions, numbers of application users, and probabilities of quarantine failures. Further, we study structured populations with homophily and heterophily and the possibility of degree-targeted application distribution. Our results are based on a combination of explicit simulations and mean-field analysis. They indicate that there can be major differences in the epidemic size and epidemic probabilities which are equivalent in the normal susceptible-infectious-recovered (SIR) processes. Further, degree heterogeneity is seen to be especially important for the epidemic threshold but not as much for the epidemic size. The probability that tracing leads to quarantines is not as important as the application adoption rate. Finally, both strong homophily and especially heterophily with regard to application adoption can be detrimental. Overall, epidemic dynamics are very sensitive to all of the parameter values we tested out, which makes the problem of estimating the effect of digital contact tracing an inherently multidimensional problem.

关键词： Complex systems Continuous phase transition Epidemic Network phase transitions Percolation phase transition Stochastic processes Barabasi-Albert network Networks & random structures Poisson degree distribution networks Scale free & inhomogeneous networks Social networks Critical phenomena Epidemic spreading Percolation theory

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