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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Souto, Gabriel Aritsugi, Masayoshi Mendonca, Israel Simonetti, Luidi González, Pedro Henrique Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350308365

This paper presents a hybrid BRKGA (Q-HBRKGA) that combines BRKGA with Q-learning and a Local Branching technique to solve the Knapsack Problem with Forfeits(KPF). The aim is to tackle this problem, a vari-ant of the 0-1 Knapsack Problem, where a penalty cost is imposed when both items of a forfeit pair are included in the solution. Notably, Q-HBRKGA achieves superior results compared to existing approaches, establishing a valid strategy for KPF problem-solving. Computational experiments, utilizing benchmark instances, demonstrate the efficacy of Q-HBRKGA by outperforming state-of-the-art methods documented in the literature. © 2024 IEEE.

关键词： Reinforcement learning

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Domain Adaptation in Color-Shifted Datasets Through Adversarial Learning Balancing 4

Domain Adaptation in Color-Shifted Datasets Through Adversar...

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4th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2023

作者： Hidayaturrahman Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo School of Computer Science Bina Nusatara University Mathematics Department Jakarta11480 Indonesia Bina Nusatara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Engineering Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Due to the disparity in the levels of difficulty presented by the several tasks, doing domain adaptation in an adversarial way may result in an imbalanced learning process. In the MNIST dataset, this phenomenon also manifests itself in the form of domain adaptation for color-shifted distribution. In this particular situation, the domain classifier has a higher tendency to fit more quickly, but the category classifier fits quite poorly in the learning process. In order to address this problem, a new hyper-parameter has been added to the loss function in order to strike a compromise between the learning speed of the domain and the categorical classifier. By using this technique, the categorical classifier may better match the data while still maintaining the same level of performance as the domain classifier. In order to determine whether or not making use of this hyper-parameter is useful, the phenomena in question is examined using three distinct color-shifted settings. Following the evaluations, it was discovered that the newly introduced hyper-parameter is capable of coping with imbalanced learning while simultaneously engaging in domain adaptation. © 2023 IEEE.

关键词： Color

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Smart Energy Management with Integrated WSN and WMN: Advancing Efficiency and Sustainability

Smart Energy Management with Integrated WSN and WMN: Advanci...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Ali Alrasheedi Mousa Al-Abdulhadi Raha Almutairi Abdullah AlRuwaiei Almas Khlaif Abdullah AlAlati Omar R. Daoud Electrical and Computer Engineering Program School of Engineering and Computing American International University Aljahra Kuwait

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

The aim of this paper is to provide an advanced WSN solution for power-sustainable energy management and efficient communication, integrating the latest developments from the SEMS. This work will focus on the research effort directed at improving M2M communication and integrating WSNs with wireless mobile networks, as well as addressing PAPR, energy consumption, and scalability. It now applies to real-time monitoring of power usage, room temperature, and lighting by integrating renewable resources of energy with sophisticated algorithms and sensor networks. Key results include a 16.6% saving in energy consumptions, 78% in system delay improvements, and the implementation of solar energy systems that have realized significant cost savings while assuring environmental sustainability. This work proves the ability of the approach through wide simulations and real-world deployments for scalable and eco-friendly energy management solutions. Besides, this work is closely related to worldwide goals for reduction of carbon footprints and efficient resource utilization.

关键词： Wireless sensor networks Renewable energy sources Energy consumption Scalability Peak to average power ratio Real-time systems Parity check codes Energy efficiency Delays Sustainable development

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A Secure Cloud-Based Infrastructure for Virtual Sensors in IoT Environments 6

A Secure Cloud-Based Infrastructure for Virtual Sensors in I...

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6th International Conference of Women in Data Science at Prince Sultan University, WiDS-PSU 2023

作者： Makda, Tahira Jehan Luiza Barros, Ana Dilek, Selma University of Doha for Science and Technology College of Business Management Doha Qatar University of Ceará Computer Science Program State Fortaleza Brazil Hacettepe University Department of Computer Engineering Ankara Turkey

ISBN: (纸本)9781665477239

Recent work has proven the effort of researchers to integrate small sensors and a cloud environment, delivering the Internet of Things (IoT). Sensors as a service are one of the leading research concerns in this context. Nevertheless, security is becoming one of the most significant attributes of the IoT as sensors become more human-independent and are being extensively used to monitor human lives. That way, IoT brings many key security challenges that need attention, some of which we address in this position paper. We present a cloud-based infrastructure that can deliver sensors and actuators as a service, providing secure communication between them and the control nodes on which IoT applications rely while implementing Big Data algorithms. For mapping our proposal, two scenarios related to Health Assistance are discussed, considering secure communications in a sensor network. In conclusion, we propose a scope for future research in this field considering digital twin concepts. Since domains exploiting IoT technologies can benefit from adopting Digital Twin, our goal is to evolve a virtual sensor and actuator system into this technology. © 2023 IEEE.

关键词： Actuators

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Optimized Instruction Set Architecture for programmable Memory Test Pattern Generation 21

Optimized Instruction Set Architecture for Programmable Memo...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Park, Seokmin Park, Jewoo Lee, Young-Woo Inha University School of Electrical and Computer Engineering Incheon Korea Republic of Inha University Program in Semiconductor and Device Korea Republic of Hyundai Motor Company Hwaseong Korea Republic of

ISBN: (纸本)9798350377088

Continuous progress in memory semiconductor manufacturing technology has significantly increased capacities, densities, and operating frequencies. However, these developments have also increased the probability of memory defects, consequently diminishing yield rates. To overcome this issue, various memory test pattern algorithms have been devised to identify the type of memory defect, primarily categorized into linear and nonlinear patterns. This paper presents an instruction-based approach for efficiently generating diverse nonlinear patterns. The proposed instruction set architecture (ISA) provides flexibility in generating both linear and intricate nonlinear patterns, while also ensuring a compact memory test setup cycle, regardless of the memory cell size. © 2024 IEEE.

关键词： Cost reduction

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Prediction of Internet Broadband Connectivity Classification in West Java Indonesia using Machine Learning

Prediction of Internet Broadband Connectivity Classification...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Kusuma Atmaja, Wahyu Haris Heryadi, Yaya Sonata, Ilvico Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department West Jakarta Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Engineering Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

A location's Take-up Rate was significantly influenced by its Internet connectivity and availability. The purpose of this research is to answer concerns about internal Internet Service Provider issues that affect Internet connectivity in clusters of West Java, Indonesia. It also aims to evaluate the results of models that forecast how these internal factors will affect internet connectivity. According to the research findings, the FTTH Cluster has eight significant Internet predictor connectivity out of 18 elements. Activation delay and Administration Documentation of Activation with Connectivity were the two major parameters modeled out of the 18 components. Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree (DT) models were used to predict Internet Broadband Connectivity Classification based on the two most important variables. According to the study, ANN is the best model, with 99% accuracy and 99.6% precision when compared to SVM and DT. Furthermore, it exceeds previous studies that used the ANN model and achieved 97.92% accuracy. © 2023 IEEE.

关键词： Prediction models

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Android-Based Application for Ripeness Classification and Shelf-Life Determination of Philippine Bananas

Android-Based Application for Ripeness Classification and Sh...

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computer Graphics and Image Processing (CGIP), International Conference on

作者： Fernandrigo R. Lumpay Jon Waldson T. Canoy Ryu Mhar A. Caballero Kimberly M. Nepa Computer Engineering Program College of Engineering Education University of Mindanao Davao City Philippines

ISBN: (数字)9798350374186

ISBN: (纸本)9798350374193

Lauded as the world's most popular fruit, bananas are one of the main exports of the Philippines. It contains essential nutrients that can have a protective impact on health. Commonly, farmers can distinguish the different types of bananas and potentially predict their shelf-life. Nevertheless, human judgment is not always reliable. It needs to have support and evidence to minimize the margin of error. Hence, this study focuses on developing an android application to determine the Philippine bananas' ripeness, variety, and shelf-life. This application identifies different bananas sold in the local market, specifically Cardava, Lakatan, and Latundan. Also, the application determines the shelf-life of bananas, such as the remaining days for unripe bananas to become ripe and ripe bananas to overripe. A Convolution Neural Network-based (CNN) model classifier is used as an architecture categorizing the Philippine local market bananas. The proponents used real-life image data to increase the accuracy of the CNN model. The application was proven effective and has reached 90% accuracy.

关键词： Convolution Image processing Computational modeling computer graphics computer architecture Data models Reliability

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Sample-efficient adversarial imitation learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2024年第1期25卷 1545-1576页

作者： Dahuin Jung Hyungyu Lee Sungroh Yoon Electrical and Computer Engineering Seoul National University Seoul Republic of Korea Electrical and Computer Engineering Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Republic of Korea

Imitation learning, in which learning is performed by demonstration, has been studied and advanced for sequential decision-making tasks in which a reward function is not predefined. However, imitation learning methods still require numerous expert demonstration samples to successfully imitate an expert's behavior. To improve sample efficiency, we utilize self-supervised representation learning, which can generate vast training signals from the given data. In this study, we propose a self-supervised representation-based adversarial imitation learning method to learn state and action representations that are robust to diverse distortions and temporally predictive, on non-image control tasks. In particular, in comparison with existing self-supervised learning methods for tabular data, we propose a different corruption method for state and action representations that is robust to diverse distortions. We theoretically and empirically observe that making an informative feature manifold with less sample complexity significantly improves the performance of imitation learning. The proposed method shows a 39% relative improvement over existing adversarial imitation learning methods on MuJoCo in a setting limited to 100 expert state-action pairs. Moreover, we conduct comprehensive ablations and additional experiments using demonstrations with varying optimality to provide insights into a range of factors.

关键词： imitation learning adversarial imitation learning self-supervised learning data efficiency

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Enhanced Keypoint-Based Approach for Identifying Copy-Move Forgery in Digital Images 7

Enhanced Keypoint-Based Approach for Identifying Copy-Move F...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Bisht, Girish Singh Jain, Arpit Bansla, Vandna Sharma, Khemraj Bhutia, Rudramani Kumar, Vikas Tula's Institute Department of Computer Science & Engineering Dehradun248001 India Koneru Lakshamaiah Education Foundation Department of Computer Science & Engineering A.P. Vadessahwaram India Shivalik Engineering College Dehradun248001 India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering A.P. India Dev Bhoomi Uttrakhand University School Engineering and Computing Uttrakhand Dehradun India

ISBN: (纸本)9798350350067

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of 89.2%, 93.9% and 98.98%.) © 2024 IEEE.

关键词： Image analysis

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MOSFET Based Active Rectifier Design in Wireless Capacitive Power Transfer for Electric Vehicles 1

MOSFET Based Active Rectifier Design in Wireless Capacitive ...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Dragon, Klemens Raphael Lie, Zener Sukra Muharam, Aam Ika, Juan Luciano Perdana, Muhamad Arjuna Amin Hapid, Abdul Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Badan Riset dan Inovasi Nasional Research Center for Transportation Technology Jawa Barat Bandung Indonesia

ISBN: (纸本)9798350368918

While the rise of electric vehicles reflects a push for clean energy as envisioned by international agreements like the Paris Agreement, wireless charging's convenience can overcome limitations and hasten their adoption, making it a strategic step alongside regulations such Permenhub No. 15/2022 and SDG 9 'Industry, Innovation, and Infrastructure' for cleaner air and sustainable transportation. The aim is to convert the high frequency AC voltage from the coupling capacitor into a stable DC voltage. Further increase the system sensitivity to the load variations, by designing a MOSFET based active rectifier. By changing load parameters, the accuracy of PFC adaptation to the battery State of Charge (SOC) obtained is at 98% with 2% tolerance for errors. It is concluded that the research is said to be successful because it has met the parameters of general research hypothesis where the system is able to convert high frequency AC voltage into a stable DC voltage. © 2024 IEEE.

关键词： State of charge

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