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Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Jonathan Rendel William Balte Harrison Kurunathan Hazem Ismail Ali Alexandre Dos Santos Roque Wagner Ourique De Morais Mahdi Fazeli Department for Computing and Electronics for Real-time and Embedded Systems (CERES) School of Information Technology (ITE) Halmstad University Halmstad Sweden CISTER/ISEP Polytechnic Institute of Porto Portugal Graduate Program of Electrical Engineering Federal University of Rio Grande do Sul - UFRGS Porto Alegre Brazil

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Zero-day attacks present a significant security threat to vehicular networks, exploiting vulnerabilities at both software and hardware levels within such systems that remain undiscovered. Mitigating these threats is essential to ensuring the safety and security of vehicular systems. Support Vector Machine (SVM) is a good candidate for anomaly detection of zero-day attacks within vehicular networks because it can handle highdimensional data and effectively distinguish between normal and abnormal patterns in complex and dynamic environments. A trained SVM on the normal operation data of in-vehicular network can identify flag deviations, thus making it effective in the detection of any previously unknown attack patterns, which is a common behaviour of zero-day attacks. In this paper, we introduce an anomaly detection method called “ZeroCAN” which models the behaviour of every single electronic control unit on the network with a separate SVM and a set of high-level features that capture the timing and data payload aspects of CANbus traffic. This approach achieves an anomaly detection rate of over $\mathbf{9 9 \%}$ and a false positive rate below $\mathbf{0. 0 1 \%}$ during normal operation in most cases.

关键词： Support vector machines Telecommunication traffic Feature extraction Data models Timing Security Vehicle dynamics Anomaly detection Standards Payloads

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IoT-based Efficient Waste management on University Campus : Enhancing Monitoring and Optimization through Machine Learning

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Procedia Computer Science 2025年 258卷 4157-4168页

作者： Sumathi M. Hanumanthappa J. K.S. Santhosh Kumar S.P. Shiva Prakash Meghana J. Department of Studies in Computer Science Manasagangothri Campus University of Mysore Mysuru Karnataka 570006 India Department of Artificial Intelligence and Machine Learning Mysore University School of Engineering Manasagangothri Campus University of Mysore Mysuru Karnataka 570006 India Department of Information Science and Engineering & Computer Science and Business Systems JSS Science and Technology University Mysuru Karnataka 570006 India Department of Computer Science Mahajana Post Graduate Center Mysuru Karnataka 570016 India

The introduction of an IoT-based smart waste management system is proposed to optimize various aspects of university campus waste recycle management processes, such as garbage collection scheduling, waste type identification, and collection routes. This system utilizes advanced data analytics algorithms, wireless communication protocols, and sensors to measure and document variations in trash levels, enabling real-time monitoring of waste accumulation. Through this IoT-based infrastructure, university administrators and waste management staff gain fine-grained visibility and control over garbage collection processes. The implications for sustainability advocacy and environmental stewardship in academic environments are significant. By fostering a culture of environmental awareness and accountability, universities can instill ideals of conservation and resourcefulness in their student populations and staff. The proposed IoT-enabled waste bin system exemplifies the synergy between technological innovation and environmental responsibility, serving as a model for institutions worldwide. Collaboration among universities can leverage IoT technology to drive positive change, mitigate environmental degradation, and promote sustainable practices beyond campus boundaries. Efficient waste management is crucial for nurturing sustainability on college and university campuses, as evidenced by the urgent need for the collection and recycling of compost, general waste, and recyclables. Our models consistently achieve high performance, with perfect scores (1.000) across all split ratios, indicating flawless classification of waste types. Although the Artificial Neural Network (ANN) demonstrates slightly lower accuracy, ranging from 0.973 to 0.997 depending on data splits, it still performs well. As a result, Naive Bayes produces less accurate results, typically surpassing 0.93 but falling short of Random Forest, K-Nearest Neighbors (KNN), and Support Vector Machine (SVM)’s flawless

关键词： Artificial Intelligence Smart Parking: Smart city Machine Learning Smart Applications

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Comparative analysis of various oxygen production techniques using multi-criteria decision-making methods

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International Journal of Thermofluids 2023年 17卷

作者： Aljaghoub, Haya Alasad, Shamma Alashkar, Adnan AlMallahi, Maryam Hasan, Ranem Obaideen, Khaled Alami, Abdul Hai Department of Industrial Engineering and Engineering Management University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Department of Mechanical and Aerospace Engineering United Arab Emirates University Al Ain City United Arab Emirates Department of Sustainable and Renewable Energy Engineering University of Sharjah Sharjah United Arab Emirates Sustainable Energy and Power Systems Research Center RISE University of Sharjah Sharjah United Arab Emirates Center for Advanced Materials Research University of Sharjah Sharjah United Arab Emirates

The current pandemic has adversely affected oxygen production and supply chain, where oxygen treatment is essential for the emergency treatment protocol of patients infected by the virus. This work reports on various techniques of oxygen generation methods, as well as the challenges facing its production, storage, and transportation. Moreover, this study offers a comparative analysis of various oxygen production techniques using Multi-Criteria Decision-Making Methods (MCDM). Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), in addition to the weighting methodologies, Multiplicative Exponential Weighting (MEW) and Simple Additive Weighting (SAW) are chosen as tools to carry out the statistical analysis and rank the oxygen production methods. The ranking criteria includes cost, performance, environmental impact and safety. Moreover, this paper utilizes the Entropy Weight Method (EWM), Criteria Importance Through Inter-criteria Correlation (CRITIC) method, and the Stochastic Dominance (SD) method to distribute the criteria weights. The results show thar oxygen production using membrane technologies is the optimal technique based on all the provided tools and criteria. as it attained the maximum Entropy and Sd values of 0.548 through the TOPSIS method, and the highest CRITIC value through SAW and MEW methods which were 0.260 and 0.236, respectively. © 2022 The Author(s)

关键词： Stochastic systems

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Heterogeneity of the Dominant Causes of Performance Loss in End-of-Life Cathodes and Their Consequences for Direct Recycling

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Advanced Energy Materials 2025年第0期

作者： Popeil, Melissa Usseglio-Viretta, Francois L.E. Pu, Xiaofei Gasper, Paul Dutta, Nikita Wang, Evelyna Allen, Eva Mangum, John S. Sunderlin, Nathaniel Fink, Kae Allen, Jeffery M. Weddle, Peter J. DeCaluwe, Steven C. Finegan, Donal P. Mines/NREL Advanced Energy Systems Graduate Program Colorado School of Mines GoldenCO80401 United States National Renewable Energy Laboratory GoldenCO80401 United States Argonne National Laboratory LemontIL60439 United States Department of Mechanical Engineering Colorado School of Mines GoldenCO80401 United States

Recycling Li-ion batteries from electric vehicles is critical for reducing costs and supporting the development of a domestic battery supply chain. Direct recycling of cathodes, like LiNixMnyCozO2 (NMC), is attractive due to its low cost, energy use, and emissions compared to traditional recycling techniques. However, a comprehensive understanding of the active material properties at end-of-life is needed to guide direct recycling processes and the performance-dependent reuse applications. Here, NMC material from an end-of-life commercial pouch cell is characterized and bench-marked against pristine non-cycled counterparts with respect to capacity, impedance, crystallography, morphology, and microstructure to identify major degradation modes and understand variability in the end-of-life material. The spatial heterogeneity of each property throughout the cell is also quantified. While the degraded material demonstrated similar capacity as the pristine, its impedance and rate capability are severely diminished. Furthermore, samples from the periphery of the electrode layers showed more severe performance loss compared to samples extracted from central regions. The dominant culprit of performance loss is the material microstructure, where the magnitude of particle cracking showed the strongest correlation to the impedance components that are most unfavorably impacted. This work suggests severe cracks in cathode active materials are the primary challenge that direct recycling methods must overcome. © 2025 The Author(s). Advanced Energy Materials published by Wiley-VCH GmbH.

关键词： battery NMC recycling

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Towards Cross-speaker Reading Style Transfer on Audiobook Dataset

arXiv

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arXiv 2022年

作者： Li, Xiang Song, Changhe Wei, Xianhao Wu, Zhiyong Jia, Jia Meng, Helen Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Department of Computer Science and Technology Tsinghua University Beijing China

Cross-speaker style transfer aims to extract the speech style of the given reference speech, which can be reproduced in the timbre of arbitrary target speakers. Existing methods on this topic have explored utilizing utterance-level style labels to perform style transfer via either global or local scale style representations. However, audiobook datasets are typically characterized by both the local prosody and global genre, and are rarely accompanied by utterance-level style labels. Thus, properly transferring the reading style across different speakers remains a challenging task. This paper aims to introduce a chunk-wise multi-scale cross-speaker style model to capture both the global genre and the local prosody in audiobook speeches. Moreover, by disentangling speaker timbre and style with the proposed switchable adversarial classifiers, the extracted reading style is made adaptable to the timbre of different speakers. Experiment results confirm that the model manages to transfer a given reading style to new target speakers. With the support of local prosody and global genre type predictor, the potentiality of the proposed method in multi-speaker audiobook generation is further revealed. Copyright © 2022, The Authors. All rights reserved.

关键词： Speech synthesis

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Digital Twin-Based Production-Delivery Synchronization Under Batch Processing Mode

Digital Twin-Based Production-Delivery Synchronization Under...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： ZhiCong Hong Ting Qu Yongheng Zhang Kai Zhang Mingxing Li George Q. Huang School of Management Jinan University Guangzhou China Base of Science and Technology for GBA Smart Logistics Guangdong International Cooperation Zhuhai China The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen China School of Intelligent Systems Science and Engineering Jinan University Zhuhai China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798350379167

ISBN: (纸本)9798350379174

Batch processing of small-batch customer orders can effectively reduce operating costs. Manufacturers need third-party logistics (3PLs) to provide services in the production process to quickly deliver finished products to customers. However, the two have very different batch processing of cus-tomer orders: manufacturers merge customer orders with identical demands, while 3PLs merge customer orders in prox-imate regions. Consequently, when both manufacturers and 3PLs are involved in decision-making, the efficiency and economy of production-logistics operations are severely compromised under batch processing. Therefore, the key issue ad-dressed in this paper is how to achieve production-delivery synchronization under batch processing mode, as well as synchronized control in a highly dynamic environment. To ad-dress this issue, a digital twin-based production-delivery synchronized decision framework is proposed, centered on the concept of “cloud-edge-terminal”. A synchronization control mechanism based on digital twin is designed. A collaborative optimization-based synchronized mathematical model and optimization algorithm are developed. Finally, a comparison between two synchronization modes, demonstrates that the proposed solution effectively achieves optimal production-logistics operational states and reduces total costs.

关键词： Costs Heuristic algorithms Batch production systems Interference Real-time systems Mathematical models Digital twins Synchronization Optimization Logistics

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DISENTANGLING CONTENT AND FINE-GRAINED PROSODY INFORMATION VIA HYBRID ASR BOTTLENECK FEATURES FOR VOICE CONVERSION

arXiv

引用

arXiv 2022年

作者： Zhao, Xintao Liu, Feng Song, Changhe Wu, Zhiyong Kang, Shiyin Tuo, Deyi Meng, Helen Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Shenzhen International Graduate School Tsinghua University Shenzhen China Huya Inc Guangzhou China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Hong Kong

Non-parallel data voice conversion (VC) have achieved considerable breakthroughs recently through introducing bottleneck features (BNFs) extracted by the automatic speech recognition(ASR) model. However, selection of BNFs have a significant impact on VC result. For example, when extracting BNFs from ASR trained with Cross Entropy loss (CE-BNFs) and feeding into neural network to train a VC system, the timbre similarity of converted speech is significantly degraded. If BNFs are extracted from ASR trained using Connectionist Temporal Classification loss (CTC-BNFs), the naturalness of the converted speech may decrease. This phenomenon is caused by the difference of information contained in BNFs. In this paper, we proposed an any-to-one VC method using hybrid bottleneck features extracted from CTC-BNFs and CE-BNFs to complement each other advantages. Gradient reversal layer and instance normalization were used to extract prosody information from CE-BNFs and content information from CTC-BNFs. Auto-regressive decoder and Hifi-GAN vocoder were used to generate high-quality waveform. Experimental results show that our proposed method achieves higher similarity, naturalness, quality than baseline method and reveals the differences between the information contained in CE-BNFs and CTC-BNFs as well as the influence they have on the converted speech. Copyright © 2022, The Authors. All rights reserved.

关键词： Speech recognition

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Dramatic reduction in thermal conductivity by high-density dislocations in SrTiO3

arXiv

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arXiv 2025年

作者： Ding, Jinxue Zhang, Jiawen Dong, Jinfeng Higuchi, Kimitaka Nakamura, Atsutomo Lu, Wenjun Sun, Bo Fang, Xufei Institute for Applied Materials Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China School of Materials Science and Engineering Nanyang Technological University Singapore639798 Singapore Institute of Materials and Systems for Sustainability Nagoya University Aichi Nagoya464-8601 Japan Graduate School of Engineering Science Osaka University Toyonaka Osaka560−8531 Japan Tsinghua SIGS and Guangdong Provincial Key Laboratory of Thermal Management Engineering & Materials Tsinghua University Shenzhen518055 China

Decreasing thermal conductivity is important for designing efficient thermoelectric devices. Traditional engineering strategies have focused on point defects and interface design. Recently, dislocations as line defects have emerged as a new tool for regulating thermal conductivity. In ceramics-based thermoelectric materials, the key challenge lies in achieving sufficiently high-density dislocations to effectively scatter phonons, as the typical dislocation density in ceramics after bulk deformation is constrained to ~1012 m−2. In this work, we adopted the mechanical imprinting method and achieved a dislocation density of ~1015 m−2 in single-crystal SrTiO3, which is known for its room-temperature plasticity and acts as a promising material for thermoelectric applications. Using the time-domain thermoreflectance (TDTR) method, we measured a ~50% reduction in the thermal conductivity over a broad temperature range (80−400 K) with the engineered high-density dislocations. These results suggest that tuning dislocations could offer a new path to minimizing thermal conductivity for engineering thermoelectric materials. © 2025, CC BY.

关键词： Single crystals

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Multi-Faceted Ergonomics Assessment in Medical Device Manufacturing: A Case Study

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Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2021年第1期10卷 247 - 250页

作者： Bukola Saliu Bernadette McCrory Industrial and Management Systems Engineering Department of Mechanical and Industrial Engineering Montana State University Bozeman MT

Background: According to the National Safety Council and the Bureau of Labor Statistics there were over 4,000 preventable injury related deaths. The Occupational Health and Safety Administration emphasizes that safety cultures should consist of shared beliefs, practices, and attitudes that exist at an establishment. The purpose of this industry-sponsored research project was to assist a medical manufacturing facility with safety program OSHA compliance. Method: Job Safety Analysis (JSA), also ca lled job hazard analysis, and facility inspections were used to identify hazards focused on the worker, task, tools, and the work environment. Results: Areas with high hazard scores according to the JSA were a ssigned to supervisors and the research team to provide immediate process and environment changes. Conclusion: JSA is a great tool to identify safety hazards on a job site though job functions. This will prevent injuries and a llow even small companies to remain compliant with federal regulations. Creating an atmosphere from top to bottom with a culture of safety responsibility andownership can promote a safe and productive environment.

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Leverage from Blockchain in Commodity Exchange: Asset-Backed Token with Ethereum Blockchain Network and Smart Contract 4th

Leverage from Blockchain in Commodity Exchange: Asset-Backed...

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4th International Conference on Smart Trends for Computing and Communications, SmartCom 2020

作者： Richard Heryadi, Yaya Lukas Trisetyarso, Agung Information Systems Department School of Information Systems Bina Nusantara University Jakarta11840 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara Univesity Jakarta11840 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (纸本)9789811552236

Ethereum is one of the most popular blockchain platforms with a high number of adoption in the blockchain world today. Ethereum token (ERC-20) can tokenize any real-world object while it is also possible to exchange the token across the network participants. This utility from the token drives many blockchain enthusiasts to create decentralized applications. ERC-20 token could be used to collect project funds, decision voting, or even can be used to provide investment platforms for people that want to hedge the volatility of the currency with buying an asset that is back to back with the crypto-token. This research shows the main characteristics of asset-backed token and its implementation on a complete end-to-end "digitalization assets system" (assets buy and assets redemption). The result shows that asset-backed token needs support from government and other legalizing parties to verify the legitimacy of the asset that backing the token itself. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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