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9th International Conference on Applied System Innovation, ICASI 2023

作者： Chang, Che-Wei Zhang, Kai-Jie Chang Gung University School of Electrical and Computer Engineering College of Engineering Department of Computer Science and Information Engineering No.259 Wenhua 1st Rd. Guishan Dist. Taoyuan333 Taiwan

ISBN: (纸本)9798350398380

It is a promising approach to include Non-Volatile Memory (NVM) and DRAM together as the main memory to provide huge memory space for large objects and guarantee short access latency for frequent writes and reads. To provide feasible and suitable memory allocation for all applications on a sever, our solution analyzes applications to derive the read-write ratio, memory footprint, and access pattern of each application. Heterogenous memory allocation scheme is then developed to reduce the makespan of batch jobs. © 2023 IEEE.

关键词： Dynamic random access storage

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Human Fatty Liver Monitoring Using Nano Sensor and IoMT

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Intelligent Automation & Soft Computing 2023年第2期35卷 2309-2323页

作者： Srilekha Muthukaruppankaruppiah Shanker Rajendiran Nagalingam Priya Murugasen Rajesh Nandaamarnath Department of Electrical and Electronics Engineering Saveetha Engineering CollegeChennai602105India Department of Computer Science and Engineering Aalim Muhammed Salegh College of EngineeringChennai600055India Department of Physics Saveetha Engineering CollegeChennai602105India Department of Medical Gastroentrology SRM Medical College Hospital and Research CentreChennai603203India

Malfunction of human liver happens due to non-alcoholic fatty *** liver measurement is used for grading hepatic steatosis,ﬁbrosis and *** various imaging techniques for measuring fatty liver are Magnetic Reso-nance Imaging,Ultrasound and Computed *** modalities lead to the exposure of harmful radiation of electromagnetic waves because of frequent *** continuous monitoring of fatty liver is never achieved through imaging *** this paper,the human fatty liver measured through a Fatty Liver Sensor(FLS).The continuous monitoring of the fatty liver is achieved through the *** is fabricated through the screen-printing with materials such as graphene and *** fatty liver sensor is placed around the liver surface for continuous measuring fatty *** signal acquired from the fatty liver sensor is processed using blind source separation,aﬁltering technique removes the random noise from the acquired *** denoised signal is pro-cessed with tunable Q wavelet transform(TQWT),of FLS based fatty liver mea-surement fatty liver *** continuous fatty liver volume measured and analysis are performed through Long-short term memory and internet of medical things(IoMT).The experimental results are validated with ultrasound lab values.

关键词： Fatty liver sensor ultrasound tunable Q wavelet transform non-alcoholic fatty liver disease long short-term memory

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Blockchain-Enabled Rental System for Agricultural Asset Management Using Hyperledger Fabric

Blockchain-Enabled Rental System for Agricultural Asset Mana...

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IEEE Conference on Vehicular Technology (VTC)

作者： Ishtiaque Ahmed Toke Md Fahad Monir Md Zoheb Hassan Tarem Ahmed Department of Computer Science and Engineering Independent University Bangladesh Department of Electrical and Computer Engineering Virginia Tech USA Department of Electrical and Computer Engineering Université Laval Quebec City Canada

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

In the digital age, the agricultural industry faces unique challenges, including the efficient management and maintenance of farm vehicles and tools. This paper introduces a blockchain-based agricultural vehicle and tool rental system leveraging Hyperledger Fabric. By utilizing blockchain technology, the system ensures immutability, transparency, and trust among all parties involved. The primary focus is on creating a decentralized and secure platform that not only facilitates the rental process but also introduces next-generation farm vehicle and tool maintenance capabilities. Throughout the development process, we faced and overcame significant challenges, including the need for a custom-tailored blockchain solution to meet the unique requirements of agricultural asset management. The proposed solution enhances traceability and accountability, thereby reducing fraudulent activities and improving overall operational efficiency. A working demo of the system is available on GitHub, providing an open-source resource for researchers and developers. This accessibility enables further exploration and adaptation of the system across various fields, from supply chain management to peer-to-peer marketplaces. The blockchain’s immutability aspect serves as a cornerstone for building trust in digital transactions, offering potential applications in diverse sectors such as finance, healthcare, and government services. The implementation details, innovative approaches to technical obstacles, and practical implications of our solutions are thoroughly discussed, providing valuable insights for researchers and practitioners in blockchain technology and agricultural systems.

关键词： Vehicular and wireless technologies Supply chain management Distributed ledger Smart contracts Fabrics Blockchains Peer-to-peer computing Maintenance Asset management Software development management

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Mechanical properties prediction of metakaolin and fly ash - based geopolymer concrete using SVR

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Journal of Building Pathology and Rehabilitation 2024年第1期9卷 1-14页

作者： Pratap, Bheem Sharma, Sanjay Kumari, Pooja Raj, Sumit Department of Civil Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India Department of Electrical Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India Department of Computer Science and Engineering National Institute of Technology Jamshedpur Jharkhand Jamshedpur 831014 India

The field of construction materials and sustainable infrastructure has witnessed a significant shift towards environmentally friendly alternatives. Geopolymers, as an emerging class of materials, have gained substantial attention due to their eco-friendly nature and mechanical properties. One of the key ingredients in geopolymer formulations is metakaolin, a thermally activated aluminosilicate material derived from kaolin clay. This paper delves into an in-depth exploration of the diverse applications of fly ash and metakaolin in geopolymer concrete, highlighting its contributions to the construction industry, environmental sustainability, and technological advancements. In this investigation, the fly ash was substituted in varying proportions of 0%, 10%, 20%, 30%, and 40% across NaOH molar concentrations of 1 M, 3 M, 5 M, and 7 M. The objective was to assess the mechanical characteristics of the newly formulated geopolymer concrete. As consider the scenario where the concentration of NaOH was maintained at 5 M. In this case, the compressive strength of a geopolymer concrete (FM2), which comprised 20% metakaolin, demonstrated a maximum compressive strength of 55.28 MPa. Notably, the influence of metakaolin on bolstering compressive strength seems to be most noticeable when employed as a substitute at the 20% proportion. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Compressive strength Fly ash Geopolymer Metakaolin Sodium hydroxides

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Volt-Var Control for Utility-scale Solar PV Plants to Replace SVCs 4

Volt-Var Control for Utility-scale Solar PV Plants to Replac...

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4th International Conference on High Voltage engineering and Power Systems, ICHVEPS 2023

作者： Shimomukai, Ken Maeda, Haruka Fujita, Goro Shibaura Institute of Technology Functional Control Systems Graduate School of Engineering and Science Tokyo Japan Shibaura Institute of Technology Graduate School of Engineering and Science Department of Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan

ISBN: (纸本)9798350318678

One way to increase solar photovoltaic penetration in the grid is management of voltage fluctuations. This is because a photovoltaic plant cannot be interconnected to the grid if it causes voltage violations. Voltage violation is where voltage exceeds the acceptable range. Often, grid operators request photovoltaic plant owners to regulate voltage sufficiently with expensive and space-consuming static Var compensators. Unfortunately, this sometimes makes the project less feasible. This paper argues that there are better ways to regulate voltage. We ran a simulation with a 70 MWp photovoltaic plant as an addition to the grid. Without voltage regulation, voltage violations were found to be significant. This paper found that oversizing the inverter sufficiently would remove all voltage violations without deploying a static Var compensator. This is often a cheaper and space-saving solution for voltage management. This paper argues that economics and spatial efficiency of reactive power compensation devices is key to increasing photovoltaic penetration. © 2023 IEEE.

关键词： Reactive power

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Classification of Freezing of Gait in Parkinson's Disease Using Machine Learning Algorithms

Classification of Freezing of Gait in Parkinson's Disease Us...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Önder, Mithat Şentürk, Ümit Polat, Kemal Paulraj, D. Department of Electrical and Electronics Engineering Bolu Abant İzzet Baysal University Bolu Turkey Department of Computer Engineering Bolu Abant İzzet Baysal University Bolu Turkey Department of Computer Science and Engineering R.M.K. Engineering College Chennai Chennai India

ISBN: (纸本)9798350305708

Freezing of gait (FoG) is a prevalent and incapacitating symptom that affects individuals diagnosed with Parkinson's disease (PD) and other movement disorders. Detecting FoG is crucial for accurate diagnosis, fall prevention, and providing objective measurements, all of which are essential for optimizing treatment strategies and improving the quality of life for individuals with FoG. In this study, FoG has been detected using three different classification algorithms: Medium Gaussian Support Vector Machine (SVM), Medium K-Nearest Neighbor (KNN), and Boosted Trees. The process starts with data segmentation, where the dataset is divided into smaller segments. Then, feature extraction is performed on each segment to obtain various statistical measures such as mean, root mean square, maximum, standard deviation, kurtosis, skewness, and peak of root mean square. To ensure a robust and reliable analysis, the dataset is resampled using bootstrapping, a statistical technique that involves drawing random samples from the dataset with replacement. This leads to a more representative sample and reduces the impact of outliers or imbalanced data. The next step is to split the resampled dataset into three different approaches for the classification algorithm: In 5-FCV, the dataset is divided into five equal-sized subsets. Similarly, 10-FCV splits the dataset into ten subsets and follows the same process. Finally, the Medium Gaussian SVM, Medium KNN, and Boosted Trees classification algorithms are applied to the FoG dataset. The classification accuracy achieved is 86.9%, 87.6%, and 92.7% with 10-fold cross-validation, indicating that these algorithms are effective in accurately classifying FoG. © 2023 IEEE.

关键词： acceleration signal Boosted Trees freezing of gait (FoG) Parkinson disease

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Classification of Quantum Graph State Codes using Decision Trees

Classification of Quantum Graph State Codes using Decision T...

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2022 International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2022

作者： Belanje, Vishnu Shetty Raina, Ankur Vellore Institute of Technology School of Computer Science and Engineering Vellore India Indian Institute of Science Education Research Department of Electrical Engineering and Computer Science Bhopal India

ISBN: (纸本)9781665454995

Graph states are multipartite quantum states that exhibit rich entanglement because of their topology. We consider graph states for studying a family of quantum error correcting codes such as [[n,\ 1,\ d]] encoding one logical qubit into n physical qubits of the graph state. We investigate the impact of edge connectivity on the minimum d of the resulting graph state codes (GSCs). © 2022 IEEE.

关键词： Decision trees

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A Comparative Study of DeepLabCut and Other Open-Source Pupillometry Data Analysis Algorithms – Which to Choose?

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Machine Graphics and Vision 2024年第2期33卷 77-90页

作者： Badkul, Amitesh Mishra, Sonakshi Kommajosyula, Srinivasa P. Department of Electrical & Electronics Engineering Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Department of Pharmacy Birla Institute of Technology and Science Hyderabad Campus Jawahar Nagar Hyderabad India Ph.D. Program in Computer Science The Graduate Center The City University of New York New YorkNY United States

Pupillometry measures pupil size, and several open-source algorithms are available to analyse pupillometry data. However, only a few studies compared these algorithms’ accuracy and computational resources. This study aims to compare the accuracy of computer vision-based algorithms (Swirski, Starburst, PuRe, ElSe, ExCuSe algorithms) and the machine learning algorithm, DeepLabCut, to the double-blinded human examiners (gold-standard). Training of DeepLabCut with different architectures and a variable number of markers (2-9 markers) was done on an open-source dataset. The duration of training was statistically longer for the ResNet152 model compared to the MobileNet model. The pupil diameters in computer vision-based software such as PuRe, Starburst, and Swirski were statistically different from human measurements. MobileNet 2 and 3 marker models were the closest to the human measurements. In conclusion, this work highlights the efficiency of lower marker models based on MobileNet architecture in DeepLabCut, which consumes fewer computational resources and is more accurate. © 2024 Institute of Information Technology, Warsaw University of Life sciences - SGGW. All rights reserved.

关键词： Adversarial machine learning

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A Segmentation-Based Scheme to Expedite Block Propagation in Blockchain Networks 21

A Segmentation-Based Scheme to Expedite Block Propagation in...

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21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Qiu, Zhihan Zhao, Qinglin Feng, Li Zhou, MengChu Shen, Meng Liu, Yi Sun, Yi School of Computer Science and Engineering Macau University of Science and Technology Taipa China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China School of Computer Science Guangdong University of Technology Guangzhou510006 China Institute of Computing Technology Chinese Academy of Sciences Beijing100045 China

ISBN: (纸本)9798350365221

Blockchain technology, the foundation of cryptocurrencies like Bitcoin, has utility beyond finance due to its decentralized and secure transactional nature. However, today's blockchain networks face the challenge of low transaction throughput due to block propagation delays. In this study, we propose a novel approach that divides large blocks into segments and leverages multi-origin pipelining for segment dissemination, thereby expediting block propagation. The scheme also integrates the use of a Bloom filter for lightweight segment integrity verification to prevent the reception of tampered segments. Simulation results reveal that our scheme outperforms Bitcoin's legacy approach, demonstrating significant improvement in propagation speed, particularly for large blocks, while maintaining a low fork rate. © 2024 IEEE.

关键词： Blockchain

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Tolerant Tracking Control Protocol for PMSM Based on Policy Iteration Algorithm and Fault Compensation 16th

Tolerant Tracking Control Protocol for PMSM Based on Polic...

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16th International Conference on Social Robotics, ICSR + InnoBiz 2024

作者： Yan, Shuya Li, Xiaocong Qian, Huaming Ma, Jun Al Mamun, Abdullah College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Guangzhou China Information Science and Technology Eastern Institute of Technology Ningbo China

ISBN: (纸本)9789819611508

In robotics applications, ensuring reliable performance in the presence of actuator faults is essential for maintaining system safety and reliability. This paper presents a tolerant tracking control method for permanent magnet synchronous motors (PMSMs) based on adaptive dynamic programming and fault compensation. The method simultaneously considers tracking accuracy and energy consumption through a policy iteration algorithm. In the optimality analysis of the algorithm, more relaxed conditions are provided to demonstrate that the performance function can converge to a near-optimal value within a finite number of iterations. In practical implementation, an actor-critic network is used to approximate the performance function and control protocol, alongside a fault detection mechanism based on an expanded time horizon, which achieves fault detection from arbitrary initial values. The effectiveness of the proposed algorithm is verified using a high-fidelity PMSM model in Simulink. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Permanent magnets

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