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共 19016 条记录，以下是301-310 订阅

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PricingTheCloud: A Pricing Estimator for an Informed Cloud-Migration Process 20th

PricingTheCloud: A Pricing Estimator for an Informed Cloud...

引用

20th International Conference on the Economics of Grids, Clouds, Systems, and Services, GECON 2024

作者： Djouela Kamgang, Ines Raissa Elhabbash, Abdessalam Elkhatib, Yehia Department of Computer Engineering Faculty of Engineering and Technology University of Buea Buea Cameroon School of Computing and Communications Lancaster University Lancaster United Kingdom School of Computing Science University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9783031812255

One of the main challenges facing businesses migrating to the cloud is getting an estimate of their costs in advance. The estimators available to date allow companies to compare the different virtual machine offerings from each operator, but only venture very slightly into estimating the overall cost, which includes operational and network costs. Existing estimators include operational costs in their estimates, but almost no one considers the network cost, which is a complex but far from negligible component. In this paper, we seek to address this issue by proposing a new estimator called PricingTheCloud. It is an estimator that enables companies to have an accurate estimate of their costs in advance. Unlike other estimators, PricingTheCloud considers network costs in the cost estimation. Its evaluation shows an average accuracy of 86.73% for compute costs and 65.44% for network costs in different AWS-to-AWS scenarios as compared to AWS invoices and shows the effectiveness of the proposed estimator compared to three other cloud costs estimators namely, Cloudorado, Holori, and Vantage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Computational cost

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A Derived Framework for Immersive Analytics: Use Cases in Smart City and Pokémon Interactive Data Visualization

A Derived Framework for Immersive Analytics: Use Cases in Sm...

引用

2024 IEEE International Conference on computing, ICOCO 2024

作者： Jamaludin, Najwa Ayuni Binti Mohamed, Farhan Bin Siang, Chan Vei Heng, Lee Jun Sunar, Mohd Shahrizal Bin Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Media and Game Innovation Centre of Excellence Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Institute of Human Centered Engineering Faculty of Computing Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9798331530303

Immersive analytics (IA) explores the use of immersive technologies to enhance data visualization and interaction. To maximize the potential of IA, it is essential to develop effective and practical applications. In this context, an IA design framework plays a crucial role as it provides a structured approach to define user requirements and guide the development of the application. This paper proposed a design framework for IA, adapted from several established works. The framework was applied to two use cases: visualizing smart city data in a virtual reality environment and Pokémon data in a mixed reality environment. These use cases demonstrate the applicability of the framework in guiding the development of IA applications that can be used to perform various tasks in different immersive settings and domains. Besides, a user study was conducted with 30 participants to assess their perceived workload while interacting with these applications. Future work will focus on conducting more comprehensive evaluations in terms effectiveness and efficiency to provide insights for further enhancements. ©2024 IEEE.

关键词： Virtual environments

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An Evolutionary Multi-objective Optimization of Vision Transformer 8

An Evolutionary Multi-objective Optimization of Vision Trans...

引用

8th International Conference on Information Technology, InCIT 2024

作者： Sacheewapasuk, Suvipa Jewajinda, Yutana Praditwong, Kata Silpakorn University Faculty of Engineering and Industrial Technology Department of Electrical Engineering Nakhon Pathom Thailand Silpakorn University Faculty of Science Department of Computing Nakhon Pathom Thailand

ISBN: (纸本)9798350366303

This paper presents an evolutionary multi-objective optimization of vision transformer architecture and the effect of two genetic crossover operators, two-point and uniform crossover, on the quality of the solutions. The proposed method employs the multi-objective genetic algorithm (NSGA-II) and uses a block-based encoding for visual transformer models. By adopting configurable blocks, the encoding method allows the search for various ViT architectures. The paper comprehensively analyzes the effect of genetic operators on the quality of the solution, providing practical insights for future research. The experimental results, which are reported on the Cifar-10 dataset, demonstrate a trade-off between model size and accuracy and are compared to the state-of-the-art models, providing solid evidence of the findings. © 2024 IEEE.

关键词： Crossover Genetic algorithm Multiobjective optimization Vision Transformer

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Utilizing Energy Storage System for Three-Level Voltage Balancing Mechanism in Electric Vehicle Fast Charging Station 6

Utilizing Energy Storage System for Three-Level Voltage Bala...

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6th IEEE Conference on Energy Conversion, CENCON 2023

作者： Kua, Covington Afrouzi, Hadi Nabipour Kannan, Ramani Mechranzamir, Kamyar Faculty of Engineering Computing and Science Sarawak Kuching Malaysia Faculty of Engineering Universiti Technologi Petronas Seri Iskandar Malaysia Faculty of Engineering University-of Nottingham Semenyih Malaysia

ISBN: (纸本)9798350325096

The growing demand for electric vehicles necessitates the expansion of charging infrastructure. This paper introduces a three-level voltage Fast Charging Station architecture using a Neutral-Point-Clamped Converter, offering higher power and efficiency compared to traditional converters. However, the Converter faces voltage imbalances due to neutral-point potential drift, potentially damaging the converter. To address this, this paper employ Voltage-Oriented Control and Space Vector Modulation for power redistribution. Nonetheless, the modulation stage alone cannot handle extreme uneven load. Therefore, the paper also proposes a balancing mechanism that uses any existing energy storage system to act as a load to drain the minimum amount of current from the less congested bus to maintain the power ratio between the upper and lower bus. This method eliminates any additional balancing circuit and thus reduces the fast-charging station equipment and cost. © 2023 IEEE.

关键词： Electric vehicles

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Adaptive Exponential Feeding Control for a Fedbatch Yeast Fermentation Process Using Reinforcement Learning 6

Adaptive Exponential Feeding Control for a Fedbatch Yeast Fe...

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6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Sodiwal, Khairul Aznizam Chai, Wan Ying Tan, Min Keng Kin Teo, Kenneth Tze Tham, Heng Jin Chemical Engineering Programme Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu88400 Malaysia Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

The fermentation process is complex and nonlinear because the growth pattern of microorganisms is sensitive to environmental conditions. Exponential feeding (EF) is a common and simple control strategy for regulating substrate feed flow rates using a pre-determined calculation based on growth kinetics. However, this method does not adapt to changes in the fermentation process. Reinforcement Learning (RL) is a subset of Artificial Intelligence (AI) that focuses on teaching optimal behaviors through interaction with an environment using rewards or penalties. This work explores an Adaptive Exponential Feeding (AEF) control using RL to determine the gain value of the feeding rate, aimed at maximizing yeast concentration and minimizing the by-product formation in a fed-batch baker's yeast fermentation. The kinetic and dynamic behavior of the fermentation process was modeled and simulated using MATLAB. The AEF approach uses an RL agent to optimize the feeding rate by interacting with the fermentation environment and selecting actions based on yeast concentration, glucose levels, and ethanol changes. The gain value ranges from 0 to 2.5 with a 0.1 interval. After iterations, the optimal policy is obtained. Simulations with four different initial yeast and substrate concentrations showed that AEF significantly improved the fermentation performance, yielding a higher yeast concentration of 64.86 g/L compared to 44.68 g/L with EF, a 45.17 % increase, and reducing ethanol formation by 0.15 g/L. This adaptive approach demonstrates potential for enhanced efficiency and productivity in industrial fermentation processes. © 2024 IEEE.

关键词： Reinforcement learning

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On Dataset Transferability in Active Learning for Transformers 61

On Dataset Transferability in Active Learning for Transforme...

引用

Findings of the Association for Computational Linguistics, ACL 2023

作者： Jelenić, Fran Jukić, Josip Drobac, Nina Šnajder, Jan University of Zagreb Faculty of Electrical Engineering and Computing Text Analysis and Knowledge Engineering Lab Croatia

ISBN: (纸本)9781959429623

Active learning (AL) aims to reduce labeling costs by querying the examples most beneficial for model learning. While the effectiveness of AL for fine-tuning transformer-based pre-trained language models (PLMs) has been demonstrated, it is less clear to what extent the AL gains obtained with one model transfer to others. We consider the problem of transferability of actively acquired datasets in text classification and investigate whether AL gains persist when a dataset built using AL coupled with a specific PLM is used to train a different PLM. We link the AL dataset transferability to the similarity of instances queried by the different PLMs and show that AL methods with similar acquisition sequences produce highly transferable datasets regardless of the models used. Additionally, we show that the similarity of acquisition sequences is influenced more by the choice of the AL method than the choice of the model. © 2023 Association for Computational Linguistics.

关键词： Classification (of information)

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Hybrid CNN-BiLSTM Model for Power Quality Disturbance Classification 1

Hybrid CNN-BiLSTM Model for Power Quality Disturbance Classi...

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1st IEEE International Conference on Advanced Power engineering and Energy, APEE 2024

作者： Lin, Jiajian Tavalaei, Jalal Yeo, Lit Yen Zhou, Yutong Afrouzi, Hadi Nabipour Ektesabi, Mehran Motamed Swinburne University of Technology Faculty of Engineering Computing and Science Kuching Malaysia College of Mechancial Engineering Taishan University Taian China School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC Australia

ISBN: (纸本)9798350360936

With the evolution of intelligent grid tech, the need for monitoring power quality has markedly risen, essential for the continuous functioning of the power grid. Addressing this matter, this research proposes a combined approach combining Convolutional Neural Networks (CNN) with Bidirectional Long Short-Term Memory (BiLSTM) networks. The model effectively catches spatial or temporary aspects of power quality disruptions using CNN and employs BiLSTM to document long-term or temporal aspects, thus creating a profound correlation between input and output sequences. By substantially decreasing reliance on conventional physical attributes, this technique markedly enhances the precision in detecting power quality anomalies. Crucially, this technique, independent of particular original samples and existing information, holds widespread applicability and is applicable in identifying patterns in various other intricate systems. Research on experiments indicates that, as opposed to conventional machine learning frameworks, deep learning approaches are more effective in detecting disruptions in power quality. Our hybrid model excels in identifying power quality disturbance (PQD) and produces highly accurate recognition outcomes by autonomously analyzing central features of the disturbance indications. © 2024 IEEE.

关键词： Convolutional neural networks

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Automated Optimal Resistance Measurement Method for Precision Resistor Stress Response Analysis 47

Automated Optimal Resistance Measurement Method for Precisio...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Žamboki, Andro Gočan, Leo Mikulić, Josip Schatzberger, Gregor Fellner, Johannes Marković, Tomislav Barić, Adrijan University Of Zagreb Faculty Of Electrical Engineering And Computing Zagreb Croatia Ams-OSRAM Ag Premstaetten Austria

ISBN: (纸本)9798350382495

This article presents a resistance measurement method developed for stress response analysis, specifically targeting the automatic positioning of measurement points to achieve maximum precision based on the measured resistance value. The encapsulation process, involving the pouring of material over silicon chips, introduces static mechanical stress in integrated circuits (ICs) that alters their performance characteristics. To compensate for the deviations caused by the stress, previously developed stress models can be used to simulate the stress response of complex circuits. To calibrate the models, the stress characteristics of the integrated components must be measured. Here, precise measurements are required because the stress-induced changes during the operation of the IC components are predominantly small. In this paper, a mathematical proof is presented that determines the optimal voltage-current measurement point for any resistance value and any measurement instrument. In addition, a measurement method is developed that automatically positions itself at this optimal measurement point. Experimental results show that this method consistently provides highly accurate measurements for a used range of resistance values. © 2024 IEEE.

关键词： Integrated circuits

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Investigation of damage to wind turbine blades caused by atmospheric discharges in Croatia 37

Investigation of damage to wind turbine blades caused by atm...

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37th International Conference on Lightning Protection, ICLP 2024

作者： Pletikosa, Nikola Milardić, Viktor Miloš, Dominik ENCRO d.o.o. Zagreb Croatia Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9783800764174

The paper shows damages of wind turbine blades despite the implemented lightning protection system and overvoltage protection. The classification of the blade damage in accordance with the norm and examples of actual damage of the wind turbine blades are presented. The recorded damage of the wind turbine blades at individual wind power plants in Croatia, which occur because of lightning strike to the wind turbine blade, is presented in detail. The strategy of inspection and maintenance of the wind turbine blades and their changes over time is explained. Systems for measuring lightning currents are briefly explained, and examples of recorded values of lightning stroke parameters in the wind turbine with the measuring system installed at the Voštane wind power plant in Croatia are presented. The waveform of the lightning current that strikes the wind turbine is also shown. © 2024 IEEE, © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Wind turbine blades

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Person re-identification with transformers and image stacking 32

Person re-identification with transformers and image stackin...

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32nd Telecommunications Forum, TELFOR 2024

作者： Stojanovic, Dimitrije Pavkovic, Bogdan Cetic, Nenad University of Novi Sad Faculty of Technical Sciences Departmant of Computing and Control Engineering Novi Sad Serbia

ISBN: (纸本)9798350391053

Person re-identification (ReID) is increasingly important due to the expansion of surveillance cameras. ReID can effectively operate in various conditions, making it suitable for security, retail analytics, and smart city applications. We propose a transformer-based model, DeepChangeVIT-ReID, fine-tuned with triplet loss, using the DeepChange dataset. We address long-term ReID challenges, including pose variations, camera angle differences, and clothing alterations. DeepChangeVIT-ReID achieves state-of-the-art performance, significantly improving Rank-1 accuracy compared to existing methods on the DeepChange dataset. © 2024 IEEE.

关键词： Distribution transformers

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