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Usage of Machine Learning Methods for Cause-Effect Graph Feasibility Prediction 5

Usage of Machine Learning Methods for Cause-Effect Graph Fea...

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5th International Conference on Machine Learning and Intelligent Systems, MLIS 2023

作者： Krupalija, Ehlimana Cogo, Emir Pozderac, Damir Ali Al Zayat, Aya Bešić, Ingmar Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo71 000 Bosnia and Herzegovina

ISBN: (纸本)9781643684468

Cause-effect graphs (CEGs) are usually applied for black-box testing of complex industrial systems. The specification process is time-consuming and can result in many errors. In this work, machine learning methods were applied for predicting the feasibility of CEG elements. All information was extracted from graphs contained in CEGSet, a dataset of CEGs. The data was converted to two different formats. The Boolean features format represents relations as separate data rows, whereas the Term-Frequency times Inverse-Document-Frequency (TF-IDF) format represents graphs as data rows. Eight machine learning models were trained on this data. The results of testing by using the 80-20 holdout method indicate that important information is lost when converting the graphs to the TF-IDF format, whereas the Boolean feature format enables 100%-accurate predictions of ensemble methods. The achieved results indicate that pre-trained models can be used as help for domain experts during the CEG specification process. © 2023 The authors and IOS Press.

关键词： Machine learning

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Software and Hardware Cooperative Implementation of the Rafflesia Optimization Algorithm 5th

Software and Hardware Cooperative Implementation of the R...

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5th International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2022

作者： Fu, Zonglin Pan, Jeng-Shyang Guo, Yundong Snášel, Václav College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava70032 Czech Republic

ISBN: (纸本)9789819908479

With the development of edge technology in the fields of transportation, wireless sensor networks, and the internet of things, more and more intelligent optimization algorithms are implemented in hardware structures. The Rafflesia optimization algorithm (ROA) is a novel intelligent optimization algorithm proposed recently. To observe its performance on hardware, this paper implements the ROA algorithm in a cooperative way of software and hardware, referred to as the FROA algorithm. To convenient testing and accelerated computing, the initialization module, fitness module, and update module of the FROA algorithm are deployed on the advanced RISC machine (ARM) platform and the field programmable gate array (FPGA) platform, respectively. In the experimental part, we test the FROA algorithm on nine different benchmark functions. The results are compared with those implemented in software. The experimental results demonstrate the effectiveness and superiority of the FROA algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless sensor networks

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NiaNetAD: Autoencoder architecture search for tabular anomaly detection powered by HPC 23

NiaNetAD: Autoencoder architecture search for tabular anomal...

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23rd IEEE International Symposium on Computational Intelligence and Informatics, CINTI 2023

作者： Pavlic, Saso Karakatic, Saso Fister, Iztok University of Maribor Faculty of Electrical Engineering and Computer Science Koroška cesta 46 Maribor2000 Slovenia

ISBN: (纸本)9798350342949

In the era of Industry 4.0, predictive maintenance (PdM) has become increasingly important for ensuring the efficient and reliable operation of machinery. However, the complexity and diversity of industrial datasets acquired from these sensors can make it challenging to detect anomalies and predict when preventative maintenance is necessary. The proposed NiaNetAD (Nature-Inspired Algorithms for Deep Neural NeEtwork creaTion for Anomaly Detection) method addresses this challenge by using nature-inspired algorithms (NIAs) to construct an auto-encoder (AE) neural network, which identifies anomalies in the machine's operation. The anomalies in this case refers to unusual patterns in the machine state, which could indicate an eventual breakdown. By using NiaNetAD on industrial datasets, it can help identify potential failures and schedule maintenance before they occur, reducing downtime, improving equipment lifespan, and lowering maintenance costs. The results of the NiaNetAD experiment, which was conducted on a high-performance computing (HPC) platform with multiple NIAs, demonstrated the significance of an effective and dispersed search strategy when constructing an AE architecture for a specific task. When applied to unsupervised anomaly detection (AD) on a fault detection dataset, the results indicate that improving the AE's reconstruction loss, reducing the bottleneck size, and avoiding excessive complexity in the topology can result in better outcomes. © 2023 IEEE.

关键词： Anomaly detection

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Pilot Study on Aerial Wireless Superdirectional Sound Sources Utilizing Parametric Array Loudspeakers via Local 5G Networks

Pilot Study on Aerial Wireless Superdirectional Sound Source...

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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Iihoshi, Yohei Okubo, Kan Department of Electrical Engineering and Computer Science Faculty of System Design Tokyo Metropolitan University Hino Tokyo Japan

ISBN: (纸本)9798350341140

This study presents a pilot study on the potential future use of aerial sound sources utilizing parametric array loudspeakers (PALs) in drones via fifth-generation (5G) networks. Integrating superdirectional loudspeakers with high-speed wireless communication is essential for projecting sound from the air to specific locations using drones. Herein, as an experimental approach, we have evaluated the performance of wireless communication, specifically local 5G, for realizing aerial sound sources. The results demonstrated the high performance of the local 5G connection intended for PALs in the air. © 2023 IEEE.

关键词： 5G networks aerial sound source millimeter wave band parametric array loudspeaker wireless communication

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Lightning and Surge Arrester Simulation in Power Distribution System 8

Lightning and Surge Arrester Simulation in Power Distributio...

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8th IEEE International Conference on engineering Technologies and Applied sciences, ICETAS 2023

作者： Ibrahim, Babul Salam Soomro, Dur Muhammad Sundarajoo, Sharman Akhir Tahrir, Muhammad Noor Gulf University for Science & Technology Electrical and Computer Engineering Department Kuwait Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Johor Malaysia

ISBN: (纸本)9798350327090

Lightning is a very significant occurrence that exists on earth. One stroke of lightning on a distribution network can be enough to be the root of a power outage. Therefore, this study examines and investigates the consequences of lightning and surge arresters in the power distribution system. A lightning surge is designed to examine consequences on a network. The metal oxide surge arrester (MOSA) performance illustration is pointedly diverse during significant impulse transients are considered. The MOSA is selected after comparing the shielding stages, momentary overvoltage, and power captivation competency. Picking a greater valued surge arrester raises its momentary overvoltage scope. Hence, its capability to endure against network voltage pressures develops but decreases the arrester's safety level for a specified shielding range. However, for the fast front surge arrester, its vital features are important for overvoltage related investigations relating quick front surges. Lightning surge and surge arrester simulation were carried out in the PSCAD software environment to investigate the effects of lightning and surge arresters in the distribution system. This study's simulation results indicate the significance and requirement of lightning defense systems installation in distribution networks. © 2023 IEEE.

关键词： computer software

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Software Sustainability Requirements for Knowledge Management Systems in the Cultural Heritage Domain 17th

Software Sustainability Requirements for Knowledge Manageme...

引用

17th International Conference on Knowledge Management in Organisations, KMO 2023

作者： Heričko, Tjaša Heričko, Marjan Brdnik, Saša Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor2000 Slovenia

ISBN: (纸本)9783031340444

As technology continues to advance and become more integrated into our society, especially in the era of digital transformations, it is imperative that software engineering practices and products are sustainable. However, in the Cultural Heritage domain, sustainability is often overlooked, even though knowledge management solutions are essential for the long-term capture, preservation, and dissemination of cultural heritage in a digital form. This paper aims to address this gap by identifying the key sustainability requirements to consider when designing and developing sustainability-aware knowledge management software solutions for the Cultural Heritage sector. A survey was conducted among professionals with experience in digitizing and managing cultural heritage materials, including cultural heritage experts and software engineers. Despite some differences in the perceived importance of sustainability requirements between the two groups of professionals, the most important sustainability features were mainly agreed upon. The acknowledged requirements encompass features from both the social and technical dimensions of sustainability, such as Usefulness, Effectiveness, and Trust for the former and Maintainability, Functional Suitability, and Efficiency for the latter. The research results provide valuable insights into how domain experts and software engineers view software sustainability in the studied domain. The findings can aid the decision-making process for prioritizing requirements related to sustainability and can serve as recommendations for developing knowledge management information systems in the Cultural Heritage domain with sustainability in mind. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Knowledge management

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Adaptive Frame Selection In Two Dimensional Convolutional Neural Network Action Recognition 8

Adaptive Frame Selection In Two Dimensional Convolutional Ne...

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8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Rahnama, Alireza Esfahani, Alireza Mansouri, Azadeh Kharazmi University Faculty of Engineering Department of Electrical and Computer Engineering Tehran Iran University of Science and Technology Faculty of Engineering Department of Electrical and Computer Engineering Behshahr Iran

ISBN: (纸本)9781665476232

We presented a technique in this research for dynamic frame selection to achieve robust features. This situation results in less redundancy and useful input for the network. Because it uses fewer processing resources and offers adequate accuracy, the suggested technique is appropriate for real-time applications. The network becomes more efficient and maintains adequate accuracy when informative frames are chosen and computation is minimized. The framework is tested on UCFIOI as one of the large and realistic datasets. The experiments show acceptable results employing both Resnet-50 and Mobilenet pretrained features. © 2022 IEEE.

关键词： Convolutional neural networks

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Scenario-Oriented Multi-Cut Generalized Benders Decomposition-Based Distributed OPF for AC/DC Hybrid Grids

Scenario-Oriented Multi-Cut Generalized Benders Decompositio...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Li, Hai-Xiao Ergun, Hakan Van Hertem, Dirk Lekic, Aleksandra Delft University of Technology Faculty of Electrical Engineering Mathematics & Computer Science Delft Netherlands Chongqing University of Technology School of Electrical and Electronic Engineering Chongqing China Ku Leuven Department of Electrical Engineering Leuven Belgium Etch-EnergyVille Genk Belgium

ISBN: (纸本)9789531842976

In this paper, a distributed optimal power flow (OPF) for the AC/DC hybrid grid, composed of the AC grid, renewable energy system (RES), and voltage source converter (VSC)-based multi-terminal DC (MTDC) grid, is presented. Firstly, we apply a series of linear approximations/convex relaxations to construct a mixed-integer convex AC/DC OPF model. To address the uncertainties from RESs, we then illustrate scenario-oriented decision making for the constructed AC/DC OPF model. Additionally, we verify that considering all possible scenarios can be replaced by a small set of extreme scenarios if the OPF model is (mixed-integer) convex. Furthermore, we develop a scenario-oriented multi-cut generalized Benders decomposition to achieve more efficient distributed problem solving for the constructed AC/DC OPF model. Finally, numerical results are provided to validate the effectiveness of our constructed AC/DC OPF model and our developed distributed problem-solving approach. © 2024 IEEE.

关键词： Mixed-integer linear programming

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Generative Adversarial Networks for Spatio-Spectral Compression of Hyperspectral Images 14

Generative Adversarial Networks for Spatio-Spectral Compress...

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14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2024

作者： Fuchs, Martin Hermann Paul Byju, Akshara Preethy Walda, Alisa Rasti, Behnood Demir, Begum Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India Technische Universität Berlin Faculty of Electrical Engineering and Computer Science Germany BIFOLD - Berlin Institute for the Foundations of Learning and Data Germany

ISBN: (纸本)9798331513139

Deep learning-based hyperspectral image (HSI) compression has recently attracted great attention in remote sensing due to the growth of hyperspectral data archives. Most of the existing models achieve either spectral or spatial compression and do not jointly consider the spatio-spectral redundancies present in HSIs. To address this problem, in this paper, we propose High Fidelity Compression (HiFiC)-based models for spatio-spectral compression of HSIs. In detail, we introduce two new models: i) HiFiC using Squeeze and Excitation (SE) blocks (denoted as HiFiCsE);and ii) HiFiC with 3D convolutions (denoted as HiFiC3D) in the framework of compression of HSIs. We analyze the effectiveness of HiFiCsE and HiFiC3D in compressing the spatio-spectral redundancies with channel attention and inter-dependency analysis. Experimental results show the efficacy of the proposed models in performing spatio-spectral compression, while reconstructing images at reduced bitrates with higher reconstruction quality. The code of the proposed models is publicly available at https://***/rsim/HSI-SSC. © 2024 IEEE.

关键词： Generative adversarial networks

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Maintenance Optimization of Dormant Systems Submitted to Failure Based PM and Imperfect CM.

Maintenance Optimization of Dormant Systems Submitted to Fai...

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2023 International Conference on Information and Digital Technologies, IDT 2023

作者： Bris, Radim Jahoda, Pavel Vsb - Technical University of Ostrava Faculty of Electrical Engineering and Computer Science Department of Applied Mathematics Czech Republic

ISBN: (纸本)9798350305869

This paper deals with the exploration of a system which acts on demand in case of emergency matter. To verify functionality, each component of the system must be regularly inspected with a specified inspection interval and tested to find latent failures. A failure-based preventive maintenance (PM) is considered, in context with the imperfect corrective maintenance model. This means that PM brings full renew which is realized after a beforehand setting the number of failures. If a failure occurs, it is detected during the first follow-up inspection and the reparation process starts. The imperfect corrective maintenance model is intended where each repair deteriorates the system life-time whose probability distribution is gradually altered through rising failure rate. Reliability mathematics for unavailability analysis is briefly demonstrated. The new renewal process model, including the failure-based PM, has been termed as a real ageing process. The imperfect corrective maintenance as well as increasing length of the inspection interval result in unwanted increase of system unavailability function which can be eliminated as well as optimized by the properly selected failure-based PM applied to all system components. If the PM is fixed due to cost, inspection intervals of system components can be optimized to keep the maximal value of the unavailability function in its original level. Sensitivity analysis applied to the length of the optimal inspection intervals with regard to gradually changing PM is demonstrated. This optimization process is demonstrated on a four-component system adopted from references. © 2023 IEEE.

关键词： Preventive maintenance

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