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2024 IEEE Region 10 Conference, TENCON 2024

作者： Kho, Anderson Ngap Chai Then, Yi Lung Zaidel, Dyg Norkhairunnisa Abang You, Kok Yeow Universiti Malaysia Sarawak Faculty of Engineering Kota Samarahan Malaysia Swinburne University of Technology Faculty of Engineering Computing and Science Sarawak Campus Kuching Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Malaysia

ISBN: (纸本)9798350350821

This paper presents a parametric study of a microwave microstrip patch antenna based using finite element modelling software to conduct simulations applied to dielectric material characterization. A probe-fed U-slot patch antenna has been designed to function as a material sensing applicator. The primary objective of this study is to provide non-destructive measurements for predicting the grades of cast concrete in the construction industry. The size, shape, and dimensions of the designed patch antenna are described in detail. The parametric study focuses on the shift in the minimum peak of return loss, | S11| (dB) of the antenna in relation to changes in the dielectric constant of the material under test. The modelling done on the antenna show a significant response in the |S11|, when placed on materials selected to simulate concrete samples at different periods of the curing process, and also at different strength grades. It is known that different strength grades of concrete have varying relative permittivity and dielectric constant values. Consequently, the shift in the minimum peak of the measured |S11| (dB) correlates with changes in concrete strength, thus offering a simple, non-destructive, fast, and effective system for testing concrete quality. © 2024 IEEE.

关键词： Nondestructive examination

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

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

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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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Efficient Power Control for UAV Based on Trajectory and Game Theory

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Computers, Materials & Continua 2023年第3期74卷 5589-5606页

作者： Fadhil Mukhlif Ashraf Osman Ibrahim Norafida Ithnin Roobaea Alroobaea Majed Alsafyani Information Assurance and Security Research Group(IASRG) School of ComputingFaculty of EngineeringUniversiti Teknologi MalaysiaJohorMalaysia Faculty of Computing and Informatics University Malaysia SabahKota KinabaluMalaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

Due to the fact that network space is becoming more limited,the implementation of ultra-dense networks(UDNs)has the potential to enhance not only network coverage but also network *** Aerial Vehicle(UAV)communications have recently garnered a lot of attention due to the fact that they are extremely versatile and may be applied to a wide variety of contexts and purposes.A cognitive UAV is proposed as a solution for the Internet of Things ground terminal’s wireless nodes in this *** the IoT system,the UAV is utilised not only to determine how the resources should be distributed but also to provide power to the wireless *** quality of service(QoS)offered by the cognitive node was interpreted as a price-based utility function,which was demonstrated in the form of a non-cooperative game theory in order to maximise customers’net utility *** energyefficient non-cooperative game theory power allocation with pricing strategy abbreviated as(EE-NGPAP)is implemented in this study with two trajectories Spiral and Sigmoidal in order to facilitate effective power management in Internet of Things(IoT)wireless *** has also been demonstrated,theoretically and by the use of simulations,that the Nash equilibrium does exist and that it is one of a *** proposed energy harvesting approach was shown,through simulations,to significantly reduce the typical amount of power thatwas *** is taken into consideration to agree with the objective of 5G *** order to converge to Nash Equilibrium(NE),the method that is advised only needs roughly 4 iterations,which makes it easier to utilise in the real world,where things aren’t always the same.

关键词： UAV spiral&sigmoid trajectory drones IoT game theory energy efficiency 6G

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Target Two Birds With One STONE: Entity-Level Sentiment and Tone Analysis in Croatian News Headlines 9

Target Two Birds With One STONE: Entity-Level Sentiment and ...

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9th Workshop on Slavic Natural Language Processing, SlavicNLP 2023

作者： Barić, Ana Majer, Laura Dukić, David Grbeša, Marijana Šnajder, Jan University of Zagreb Faculty of Electrical Engineering and Computing TakeLab Croatia University of Zagreb Faculty of Political Science Croatia

ISBN: (纸本)9781959429579

Sentiment analysis is often used to examine how different actors are portrayed in the media, and analysis of news headlines is of particular interest due to their attention-grabbing role. We address the task of entity-level sentiment analysis from Croatian news headlines. We frame the task as targeted sentiment analysis (TSA), explicitly differentiating between sentiment toward a named entity and the overall tone of the headline. We describe STONE, a new dataset for this task with sentiment and tone labels. We implement several neural benchmark models, utilizing single- and multi-task training, and show that TSA can benefit from tone information. Finally, we gauge the difficulty of this task by leveraging dataset cartography. © 2023 Association for Computational Linguistics.

关键词： Sentiment analysis

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Research on an Intelligent Evaluation System for Used Car Prices Based on Improved Machine Learning Algorithms

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第2期8卷 461-477页

作者： Lin, Xianning Hashim, Salwa School of Information Technology Guangdong Technology College Zhaoqing526100 China Faculty of Engineering Computing and Science Swinburne University of Technology Kuching93350 Malaysia

The advent of the big data era offers great opportunities for the development of online trading platforms for used cars. However, problems such as lack of appraisal data, asymmetric appraisal information and high cost of the appraisal process can limit the use of the three traditional used car price appraisal methods. Therefore, it is important to design an accurate and reasonable used car valuation method in the current immature market. As an advanced machine learning model, the Random Forest algorithm has strong advantages in terms of prediction accuracy, missing value handling and noise tolerance. Therefore, this paper introduces the Random Forest model into the study of used car value evaluation and improves the Random Forest model. Firstly, based on the characteristic price theory, 16 indicators were selected as characteristic variables among the factors influencing the value of used cars, and divided into 7 physical variables, 6 functional variables and 3 market variables. Secondly, aiming at the problems of poor training accuracy and relatively poor voting ability, an Inertia Bacterial Foraging Optimization Random Forest algorithm (IBFO-RF) is proposed. A multiplicative weight is set for all decision trees to match their training accuracy, and then the basic parameters of the Random Forest algorithm are optimally selected iteratively using inertia weighted bacterial foraging optimization to improve the output correctness. Finally, the data is imported into the random forest model, and according to the average decreasing degree of mean square error, an intelligent evaluation system for evaluating the value of used cars is established. It was validated against other algorithms on four datasets in the UCI dataset. The experimental results show that the validation of the proposed IBFO-RF algorithm can effectively improve the accuracy of the final classification and has significant advantages in handling the classification problem. The proposed intelligent used ca

关键词： Mean square error

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Frontier of digitalization in Biomass-to-X supply chain:opportunity or threats?

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Journal of Bioresources and Bioproducts 2023年第2期8卷 101-107页

作者： Adrian Chun Minh Loy Karen Gah Hie Kong Juin Yau Lim Bing Shen How Department of Chemical and Biological Engineering Monash UniversityMelbourneAustralia Biomass Waste-to-Wealth Special Interest Group Research Centre for Sustainable TechnologiesFaculty of EngineeringComputing and ScienceSwinburne University of TechnologyKuching 93350Malaysia Integrated Engineering Department of Environmental Science and EngineeringCollege of EngineeringKyung Hee UniversityGyeonggi-do 17104Republic of Korea

The escalating climate crisis necessitates an urgent shift towards a sustainable business ***-der the context of bioeconomy,it has offered a promising alternative through its“Biomass-to-X”strategy for converting biological resources into value-added products or ***,the adoption of this approach remains scarce,which highlights the need to leverage digital technolo-gies to enhance its ***,this paper provides a comprehensive overview of the potential role of digital technologies in the Biomass-to-X supply chain,encompassing the entire value chain from upstream to downstream activities,specifically in the areas of 1)lab-to-fabrication transla-tion,2)biomanufacturing stage,and lastly,3)supply chain management ***,this study identifies and discusses research gaps in each niche area,along with potential future re-search prospects to facilitate the transition towards a sustainable bioeconomy,making it a crucial reference for stakeholders involved in decision-making processes.

关键词： Biomass valorization Internet of nano-things Bioeconomy Biomanufacturing Blockchain Biomass-to-X

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Advanced Weather Monitoring and Disaster Mitigation System with Interactive Weather Visualizations, Flood Zone Detection, Unplanned Drainage Identification, and Emergency Shelter Mapping including Optional Drought Intensity Prediction Capabilities 7

Advanced Weather Monitoring and Disaster Mitigation System w...

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7th International Conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Ranjani, M. Devaraju, Perada Sreeharshitha, Yengalasetty Viswesh, Mekala Dubey, Siddhanth SRM Institute of Science and Technology Faculty of Engineering and Technology Chennai India SRM Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798350372816

The Advanced Weather Monitoring and Disaster Mitigation System is an essential resource for enhanced preparedness and response to unexpected events. It applies modern methods to show us dynamic weather images, detect regions susceptible to flooding, and present us with interactive weather maps. It is able of forecasting the intensity of an impending drought. These stupendous pictures and weather forecasts can assist everyone, including the public and authorities, make educated decisions and get ready for bad weather. In the case of flooding, the technology can detect high-risk areas, allowing officials to prepare ahead of time and safely evacuate citizens. It also looks for drainage problems before they cause disastrous flooding. By providing up-to-date information on local shelters, the system helps people find safe havens throughout emergencies. The alternative drought forecast may help farmers and water managers plan more effectively during dry spells. All of these components work together to protect us and lowered the effects of natural disasters. © 2024 IEEE.

关键词： Drought

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A Comprehensive Review of Challenges Using AI for Smart Manufacturing 17

A Comprehensive Review of Challenges Using AI for Smart Manu...

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17th International Conference on Computer and Automation engineering, ICCAE 2025

作者： Sharma, Aman Sim, Kwan Yong Chandrasekaran, Sivachandran School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Australia Swinburne University of Technology Faculty of Engineering Computing and Science Sarawak Campus Kuching Malaysia

ISBN: (纸本)9798331533816

The manufacturing sector is experiencing a significant transformation through the integration of technologies such as Artificial Intelligence (AI), Predictive Maintenance (PdM), Big Data Analytics (BDA), and the Internet of Things (IoT), all anchored in Industry 4.0 principles. These cutting-edge technologies hold vast potential to improve efficiency, reduce downtime, and enhance product quality. Nevertheless, the complexity of manufacturing processes presents challenges like unpredictable machine behavior, interoperability issues, and difficulties in scaling AI-driven solutions. This thorough review investigates the developments in AI and PdM within the manufacturing field, highlighting the obstacles that obstruct seamless integration into manufacturing workflows. It points out the necessity for a hybrid model that merges synchronized machine processes with predictive abilities while ensuring adaptability and compatibility between systems. Additionally, the paper details current research challenges related to real-time processing, scalable frameworks, and privacy, aiming to create a more sustainable and resilient manufacturing environment. © 2025 IEEE.

关键词： artificial intelligence deep learning manufacturing predictive maintenance

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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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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah Al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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