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16th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2022

作者： Anorboev, Abdulaziz Javokhir, Musaev Hong, Jeongkyu Nguyen, Ngoc Thanh Hwang, Dosam Yeungnam University Department of Computer Engineering Gyeongsan Korea Republic of Wroclaw University of Science and Technology Department of Applied Informatics Wroclaw50-570 Poland Nguyen Tat Thanh University Faculty of Information Technology Ho Chi Minh City70000 Viet Nam

ISBN: (数字)9781665498104

ISBN: (纸本)9781665498104

Deep learning has been used in many applications where patterns from past-trained data can be extracted to predict future outcomes. Deep learning is characterized by training and testing data with the identical input feature space and same data distribution. However, whereas the data distribution is same between the training and testing data, the results might be different. This study introduces input image preprocessing, an enhanced neural network optimization method, and prediction probability ensemble to minimize the number of trainable parameters but maintain the outcome accuracy. In the suggested methodology, input images are separated into pixel interval and the fully connected layer jointly used with saved weights. Outcome results of separated input images are ensembled to the corresponding class probabilities of the original image. The results of the proposed method were compared with those of other previous methods in the image classification task and achieved successful performance accuracies in several datasets. © 2022 IEEE.

关键词： Classification (of information)

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Improved Gradient-Based Optimizer for solving real-world engineering problems

Improved Gradient-Based Optimizer for solving real-world eng...

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IEEE Middle East and North Africa Communications Conference (MENACOMM)

作者： Mohammad Shehab Omar Tarawneh Hani AbuSalem Fatima Shannag Walaa Al-Omari Faculty of Computer Sciences and Informatics Amman Arab University Amman Jordan Department of Computer Science Engineering and Mathematics University of South Carolina Aiken Aiken United States

ISBN: (数字)9781665494113

ISBN: (纸本)9781665494120

Gradient-based optimizer (GBO) is one of the most promising metaheuristic algorithms, where it proved its efficiency in various fields. GBO combine two major search mechanisms population-based and gradient-based Newton. Thus, it has a strong ability in global search. However, it suffers from dealing with local search problems. In this paper, a new version introduces which integrates the feature of Simulating annealing method (SA) with the GBO (GBOSA) to enhance the local search technique. The proposed GBOSA has been compared with various popular algorithms and improved variants on a set of real-world engineering problems. The experiment results show that GBOSA outperformed the other algorithms in the literature.

关键词： Annealing Metaheuristics Simulated annealing Africa Search problems

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Interactive Educational Game Development Using Modified Single Stage Detector

Interactive Educational Game Development Using Modified Sing...

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International computer Science and engineering Conference (ICSEC)

作者： Kristiawan Dwi Usmanto Nova Eka Budiyanta Eko Mulyanto Yuniarno Cyprianus Kuntoro Adi Dept. of Informatics Universitas Sanata Dharma Yogyakarta Indonesia Dept. of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Dept. of Computer Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350366860

ISBN: (纸本)9798350366877

This research develops a real-time hand gesture detection system using the You Only Look Once (YOLO) algorithm for simple math learning applications aimed at children with special needs. This application is a simple drag and drop game using hand gesture indicators. The system utilizes computer vision and deep learning technology to recognize hand gestures in videos which are then converted into interactive inputs in learning media. System testing involves hyperparameter tuning methods, including learning rate, image size, and momentum adjustments. The test results show that the YOLO algorithm with hyperparameter tuning method with hyperparameter values of learning rate 0.0001, image size 320, and momentum 0.937 is effective in detecting hand gestures with an mAP@0.5: 0. 95 score of 93.27%. The test results provide the potential for using a real-time hand gesture detection system as an interesting and interactive learning method for children with disabilities, especially for those who have limitations in communication.

关键词： YOLO Training Learning systems System testing Games Detectors Media Real-time systems Tuning Videos

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Indonesian Traditional Shadow Puppet Classification using Convolutional Neural Network

Indonesian Traditional Shadow Puppet Classification using Co...

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2021 International Seminar on Application for Technology of Information and Communication, iSemantic 2021

作者： Prabowo, Dwi Puji Nugraha, M. Kuncoro Aji Ulumuddin, Dimas Irawan Ihya' Pramunendar, Ricardus Anggi Santosa, Stefanus Universitas Dian Nuswantoro Faculty of Computer Science Department of Visual Communication Design Semarang50131 Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Department of Informatics Engineering Semarang50131 Indonesia Politeknik Negeri Semarang Department of Civil Engineering Semarang50275 Indonesia

ISBN: (纸本)9781665428040

The reduced interest and knowledge of the Indonesian people about traditional culture has threatened the wayang kulit culture with extinction. Young people have forgotten and do not know the wayang kulit culture. Therefore, computer vision technology is expected to help introduce wayang kulit to young congregations. The technology that utilizes the Convolutional Neural Network (CNN) method is widely used by researchers and allows it to provide high recognition performance. Therefore, this study applies the CNN method with the MobileNet architecture to help recognize shadow puppets, especially character name recognition. The results of the MobileNet architecture on CNN provide a higher recognition performance than using the VGG-16 architecture, which gives an increase of 1.67% become 86,67%.. © 2021 IEEE.

关键词： Convolutional neural networks

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Sentence Embedding Models for Similarity Detection of Software Requirements

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SN computer Science 2021年第2期2卷 1-11页

作者： Das, Souvick Deb, Novarun Cortesi, Agostino Chaki, Nabendu Department of Computer Science and Engineering University of Calcutta Kolkata 700106 India Indian Institute of Information Technology Vadodara Gujarat Gandhinagar 382028 India Department of Environmental Science Informatics and Statistics Ca’ Foscari University Venezia 30172 Italy Department. of Computer Science and Engineering University of Calcutta Kolkata 700106 India

Semantic similarity detection mainly relies on the availability of laboriously curated ontologies, as well as of supervised and unsupervised neural embedding models. In this paper, we present two domain-specific sentence embedding models trained on a natural language requirements dataset in order to derive sentence embeddings specific to the software requirements engineering domain. We use cosine-similarity measures in both these models. The result of the experimental evaluation confirm that the proposed models enhance the performance of textual semantic similarity measures over existing state-of-the-art neural sentence embedding models: we reach an accuracy of 88.35%—which improves by about 10% on existing benchmarks. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.

关键词： Requirements similarity Semantic similarity Sentence embedding

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Crossover Methods Comparison in Flood Evacuation Route Optimization

Crossover Methods Comparison in Flood Evacuation Route Optim...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： M. Adnan Nur Hazriani Nur Khaerat Nur Dept. of Informatics Handayani University Makassar Indonesia Dept. of Computer System Handayani University Makassar Indonesia Dept. of Civil Engineering Fajar University Makassar Indonesia

This study aims to implement the genetic algorithm by testing the appropriate crossover methods in order to obtain optimal disaster evacuation routes based three main indicators, namely travel time, possible transportation mode, and affected road conditions. The research phase begins with establishing a flood-affected area scenario consisting of the victim's initial location, evacuation location, routing areas, affected road conditions, distance, as well as travel time. The genetic algorithm is applied by representing the genes and chromosomes based on the available data, generating the initial population and calculating the fitness value. At the stage of determining the parent in forming a new individual, roulette wheel selection is used. For the crossover method to produce new individuals, there are 3 methods tested namely single-point, two-point and uniform crossover. The new formed individuals are then mutated with a probability level of 0.1. The last stage is to form a new population by sorting individuals with the highest fitness value. These processes took place with an iteration limit of 1000. Based on the results of the implementation and tests conducted, the uniform crossover method has the most optimal results with accuracy 90% and highest fitness value of 0.896. Meanwhile, the two others methods two-point and single-point have extremely lower accuracy which are 70% and 60% respectively. This result confirmed the statement of previous research which convinced that the uniform crossover is the most effective crossover method.

关键词： Roads Sociology Wheels Transportation Routing Floods Statistics

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Application of Photovoltaic Systems for Power Supply of Heat Pumps

Application of Photovoltaic Systems for Power Supply of Heat...

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International Conference on Smart Systems and Technologies (SST)

作者： Alen Mazalica Dominik Buzov Danijel Topić KONČAR - Electronics and Informatics Ltd. for Production and Service Zagreb Croatia IN ELEKTRO D.O.O. Slavonski Brod Croatia Faculty of Electrical Engineering Computer Science and Information Technlogy Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

Electricity consumption worldwide is increasing day by day, and as we all aim to reduce the harmful impact on the environment due to increased electricity production, humanity is turning to electricity generation from renewable energy sources. In 2021, a total of 315 GW of new renewable energy sources were installed. The Republic of Croatia recognized the importance of renewable energy sources in due time, and the share of renewable energy sources in the final electricity consumption is above the European Union average. This paper aims to demonstrate the profitability of photovoltaic systems for powering heat pumps, specifically replacing gas heating with an air-water heat pump powered by a photovoltaic system.

关键词： Photovoltaic systems Renewable energy sources Heat pumps Electricity Europe Boilers Turning Smart systems Resistance heating Investment

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Stress Detection of Children With ASD Using Physiological Signals

Stress Detection of Children With ASD Using Physiological Si...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Sevgi Nur Bilgin Aktaş Pı nar Uluer Buket Coş kun Elif Toprak Duygun Erol Barkana Hatice Kö se Tatjana Zorcec Ben Robins Agnieszka Landowska Department of AI and Data Engineering Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Department of Computer Engineering Faculty of Technology and Engineering Galatasaray University Istanbul Turkey Department of Electrical and Electronics Engineering Faculty of Engineering Yeditepe University Istanbul Turkey University Children&#x2019 s Hospital Skopje North Macedonia School of Computer Science University of Hertfordshire Hatfield UK Department of Software Engineering Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450935

This paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot intervention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect the stress of children based on the previously provided reference baselines. Furthermore, a comparison has been made with the stress values determined using low frequency (LF) and high frequency (HF) values extracted from BVP signal.

关键词： Pediatrics Autism Social robots Signal processing Feature extraction Assistive robots Physiology

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AAG: Adversarial Attack Generator for evaluating the robustness of Machine Learning Models against Adversarial Attacks

AAG: Adversarial Attack Generator for evaluating the robustn...

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IEEE International Conference on Big Data

作者： Dimitrios Christos Asimopoulos Panagiotis Radoglou-Grammatikis Thomas Lagkas Vasileios Argyriou Ioannis Moscholios Jorgen Cani Georgios Th. Papadopoulos Evangelos K. Markakis Panagiotis Sarigiannidis MetaMind Innovations Kozani Greece Department of Information and Electronic Engineering International Hellenic University Thessaloniki Greece Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece K3Y Sofia Bulgaria Department of Computer Science Democritus University of Thrace Kavala Greece Kingston University London Surrey UK Department of Informatics & Telecommunications University of Peloponnese Tripolis Greece Department of Informatics and Telematics Harokopio University of Athens Attiki Greece Hellenic Mediterranean University Heraklion Greece

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

With the ongoing integration of machine learning models into critical infrastructure, the resilience of these systems against adversarial attacks is important for all domains. This paper introduces an adversarial attack generator framework against a network dataset that is part of OCPP Dataset using CI-CFlowMeter parser. We conduct a comprehensive evaluation of various prominent adversarial attacks, including FGSMA, JSMA, PGD, C&W, and more to assess their efficacy on the OCCP dataset. The Adversarial Generator is meticulously evaluated, demonstrating a significant impact in the models performance to detect potential perturbations. The results showcased the impact of the different type of adversarial attacks, contributing to a critical advancement in future defense strategies that need to be utilised in order to protect industrial control systems.

关键词： Perturbation methods Industrial control Machine learning Big Data Generators Robustness Data models Critical infrastructure Resilience

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The State of Diversity and Inclusion in Apache: A Pulse Check

arXiv

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arXiv 2023年

作者： Feng, Zixuan Guizani, Mariam Gerosa, Marco A. Sarma, Anita School of Electrical Engineering and Computer Science Oregon State University CorvallisOR United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ United States

Diversity and inclusion (D&I) in open source software (OSS) is a multifaceted concept that arises from differences in contributors’ gender, seniority, language, region, and other characteristics. D&I has received growing attention in OSS ecosystems and projects, and various programs have been implemented to foster contributor diversity. However, we do not yet know how the state of D&I is evolving. By understanding the state of D&I in OSS projects, the community can develop new and adjust current strategies to foster diversity among contributors and gain insights into the mechanisms and processes that facilitate the development of inclusive communities. In this paper, we report and compare the results of two surveys of Apache Software Foundation (ASF) contributors conducted over two years (n=624 & n=432), considering a variety of D&I aspects. We see improvements in engagement among those traditionally underrepresented in OSS, particularly those who are in gender minority or not confident in English. Yet, the gender gap in the number of contributors remains. We expect this study to help communities tailor their efforts in promoting D&I in OSS. Copyright © 2023, The Authors. All rights reserved.

关键词： Open source software

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