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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Bisht, Nidhi Bajaj, Madhvan Rawat, Priyanshu Vats, Satvik Sharma, Vikrant Srivastava, Saket Graphic Era Hill University Computer Science and Engineering Dehradun India School of Engineering University of Lincoln Electrical Engineering United Kingdom

ISBN: (纸本)9798350321425

Women all around the world are affected by the endocrine condition known as polycystic ovary syndrome (PCOS). There is still a need for comparative research to find variations in PCOS prevalence, diagnosis, treatment, and results among other groups, even though the diagnosis and therapy of PCOS have been well explored. This study attempts to compare the prevalence of PCOS across various ethnic groups, age categories, and geographic locations. Data was gathered from medical records and patient surveys, and a thorough literature review was done to find pertinent studies. In order to assess PCOS prevalence, diagnostic standards, therapeutic alternatives, and patient outcomes across various demographics, statistical analysis was carried out. The study's findings will aid in identifying information gaps and improving PCOS patient treatment approaches. © 2023 IEEE.

关键词： Diagnosis

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IoT-based Automatic Pan Evaporimeter Monitoring and Irrigation Control System for Crops 8

IoT-based Automatic Pan Evaporimeter Monitoring and Irrigati...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Kabir, Md Shahriar Niloy, Khalid Mahmud Hossen, Md Imon Afrose, Sumaiya Mofazzol, Md. Ismail Hossain American International University-Bangladesh Dept. of Electrical & Electronics Engineering Dhaka Bangladesh Uttara University Dept. of Computer Science Engineering Dhaka Bangladesh

ISBN: (纸本)9798350376425

This research study intends to automate the manual pan evaporimeter system and scheduling irrigation by considering soil water content and crop evapotranspiration. Automating the pan evaporimeter means performing tasks without human intervention, such as measuring the daily water evaporation amount, calculating and storing data, and refilling the pan with water. A waterproof ultrasonic sensor was used to measure the water evaporation amount. The ultrasonic sensor was installed on an innovatively designed structure facing the pan's water surface. The sensor measured the distance between the water surface and the sensor. The surface level decreased as the water evaporated over time, which caused an increment in the distance between the ultrasonic and water surfaces. By this, the sensor calculated the daily evaporation amount. The pan needed to be refilled when all water evaporated;a submersible pump was used to refill the pan automatically. A relay switch controlled the pump, and a microcontroller turned on the switch based on sensor value. The entire setup was IoT-enabled to monitor and control the system remotely on a mobile device. The entire system was backed up by solar energy to run on clean energy. A solenoid valve was used to control the flow of irrigation water. Pan evaporation estimated the amount of water that could be lost owing to evaporation and transpiration. Soil moisture sensors provided a direct measurement of the amount of water present in the soil. The two combined generated a dynamic and responsive irrigation plan that maximized water use and promoted the healthy development of crops. That approach was used. The ultrasonic sensor accurately measured water evaporation, but the installation process was complex. So, a need arises to develop a simple system or scale-type sensors to overcome the complexity. © 2024 IEEE.

关键词： Solenoid valves

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Development of Area-Based Explosive Trace Detection Using Deep Transfer Learning 1

Development of Area-Based Explosive Trace Detection Using De...

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1st International Conference on Innovative engineering sciences and Technological Research, ICIESTR 2024

作者： Ohemu, Monday F. Azeta, Ambrose A. Adeyanju, Ibrahim A. Obasi, Chukwuemeka C. Airforce Institute of Technology Department of Electrical/Electronics Engineering Kaduna Nigeria Namibia University of Science and Technology Department of Software Engineering Namibia Federal University Department of Computer Engineering Oye-Ekiti Nigeria Edo State University Department of Computer Engineering Uzairue Nigeria

ISBN: (纸本)9798350348637

Terrorism poses a significant global threat, necessitating comprehensive security measures to protect people and critical infrastructure. With the increasing frequency of explosive-based attacks, there is a pressing need for advanced detection systems to mitigate potential devastation. This paper presents the development of an area-based explosive trace detection system using deep transfer learning. Leveraging deep learning technology trained on a substantial dataset collected from sensor networks, the proposed model, named Deep Transfer Learning for Explosive Trace Detection (DTLETD), demonstrates remarkable capabilities in classifying explosive gases based on concentrations of Carbon (C), Hydrogen (H), Oxygen (O), and Nitrogen (N). The methodology involves converting the dataset into 2D data using a serial data to image generator, followed by the adaptation of a pre-trained model for transfer learning. The DTLETD model outperformed conventional Convolutional Neural Network (CNN) models, achieving a training time reduction of about 92 seconds compared to 1287 seconds for the CNN model. Additionally, the transfer learning model exhibits faster convergence with nearly zero losses during training and validation, yielding an impressive accuracy of 99.7% and an average AUC value of approximately 0.89. This research significantly advances the field of explosive trace detection by integrating machine learning-based approaches with deep transfer learning techniques, thereby enhancing security protocols and mitigating potential threats. © 2024 IEEE.

关键词： Convolutional neural networks

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PolyFlows: Modular Test Framework Design for Autonomous Vehicles 2

PolyFlows: Modular Test Framework Design for Autonomous Vehi...

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2nd IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2024

作者： Akbas, Mustafa Ilhan Menase, Mahesh Verma, Shivendra Razdan, Rahul Embry-Riddle Aeronautical University Electrical Engineering and Computer Science FL United States Acclivis Technologies Pvt. Ltd. Pune India Florida Polytechnic University Department of Computer Science LakelandFL United States

ISBN: (纸本)9798350307733

Validation and verification of autonomous vehicles is a vexing research challenge. PolyVerif, an open-source validation and verification framework, is designed to accelerate research in this area. PolyVerif presents a comprehensive open-source validation and verification stack, including an autonomous vehicle engine, symbolic test generation, simulation at different fidelity levels, a digital twin creation environment, and a process for transitioning from simulation tests to physical tests. One of the key challenges for the validation and verification of autonomous vehicles is to construct a modular design for the test flows. Modular validation is critical to building an inductive argument for system correctness. Today, these techniques are not easily available to validation researchers or engineers due to the lack of visibility into the internals of an autonomous vehicle stack and the lack of standard definitions for these interface points. The realm of open-source allows for both visibility and experimentation to develop these very important interfaces. This paper introduces PolyFlows, the modular "Design for Test"framework in PolyVerif, focused on the main pieces of the complex autonomous vehicle stack: Detection, Location Services, Control, and Path Planning. PolyFlows creates open-source modular validation structures that can be used to check the precision of the intricate autonomous vehicle stack. The paper also presents the use of this framework in the Jacksonville Transportation Authority Ultimate Urban Circulator project, which is contributed to the open-source PolyVerif repository. © 2024 IEEE.

关键词： Autonomous vehicles

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An Efficient Hash Computing Unit for Kyber Algorithm 15

An Efficient Hash Computing Unit for Kyber Algorithm

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Wei, Hongshuai Zhang, Yuejun Zhang, Huihong Wang, Yang Yuan, Tengfei Wang, Chengjie Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

In the post-quantum Kyber algorithm, the Hash computation directly affects the processing speed of key generation, noise polynomial, and key exchange processes. To address the issues of multiple types of Hash computations, complex variables, and high resource consumption, this paper proposes an efficient Hash computation unit. The proposed scheme first establishes independent data interaction units through the sponge construction, achieving higher parallelism by combining the logically merged Keccak-1600 permutation function. Subsequently, the central binomial distribution sampling and optimized rejection sampling are integrated into the Hash unit, resulting in a compact and highly flexible Hash computation unit. Finally, the scheme is tested and verified under the Taiwan Semiconductor Manufacturing Company (TSMC) 65nm process. The proposed method consumes only 36.4K equivalent logic gates, and experimental results show that the Hash computation cycle is reduced by up to 30%, rejection sampling cycle by 16%, making it more efficient compared to related implementations. © 2023 IEEE.

关键词： CRYSTALS-KYBER hash computation unit quantum-resistant cryptography sampler sponge

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Theory of mechanical exfoliation of van der Waals bonded layered materials

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Physical Review Materials 2024年第6期8卷 064003-064003页

作者： Haoye Sun Ozan Sahin Ali Javey Joel W. Ager D. C. Chrzan Department of Materials Science and Engineering Department of Electrical Engineering and Computer Sciences Materials Sciences Division

A theoretical framework for analyzing the mechanical exfoliation of 2D materials at finite temperature is introduced. As an example, this framework, based on transition-state theory and calculation of the reaction pathway, is applied to the mechanical exfoliation of multilayer MoS2. The theory predicts that altering the bonding of the top layer to the bulk through straining or twisting and slowly exfoliating at low temperatures will enhance the yield of the monolayer material.

关键词： Adhesion

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Heterogeneous Network Recommendation Algorithm Based on Graph Convolution 4

Heterogeneous Network Recommendation Algorithm Based on Grap...

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4th International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2022

作者： Zhang, Quanxian Xin, Yu Yu, Ruowang Ningbo University Electrical Engineering and Computer Science Ningbo China

ISBN: (纸本)9781665463997

There are several types of objects and interaction relations in recommendation systems. However, most graph convolution models consider the network merely as a bipartite graph for convolution, as a result of which, the qualities of nodes in heterogeneous networks are underestimated under different interactions. Therefore, the present study aims at proposing a graph convolution recommendation algorithm for heterogeneous networks. The node interaction in the network were divided into two types of interactions, i.e., the homogeneous interaction and the heterogeneous one. Moreover, attention mechanism was used to extract the node features in the homogeneous interaction, which was subsequently integrated into the node features generated by the heterogeneous interaction convolution. Finally, to generate the prediction score, a multi-layer perceptron was used. Hence, the obtained results corroborated the better performance of the proposed algorithm. © 2022 IEEE.

关键词： Convolution

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Federated Model Heterogeneous Matryoshka Representation Learning 38

Federated Model Heterogeneous Matryoshka Representation Lear...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Yi, Liping Yu, Han Ren, Chao Wang, Gang Liu, Xiaoguang Li, Xiaoxiao College of Computer Science TMCC SysNet DISSec GTIISC Nankai University China College of Computing and Data Science Nanyang Technological University Singapore Department of Electrical and Computer Engineering The University of British Columbia Canada Vector Institute Canada

Model heterogeneous federated learning (MHeteroFL) enables FL clients to collaboratively train models with heterogeneous structures in a distributed fashion. However, existing MHeteroFL methods rely on training loss to transfer knowledge between the client model and the server model, resulting in limited knowledge exchange. To address this limitation, we propose the Federated model heterogeneous Matryoshka Representation Learning (FedMRL) approach for supervised learning tasks. It adds an auxiliary small homogeneous model shared by clients with heterogeneous local models. (1) The generalized and personalized representations extracted by the two models' feature extractors are fused by a personalized lightweight representation projector. This step enables representation fusion to adapt to local data distribution. (2) The fused representation is then used to construct Matryoshka representations with multi-dimensional and multi-granular embedded representations learned by the global homogeneous model header and the local heterogeneous model header. This step facilitates multi-perspective representation learning and improves model learning capability. Theoretical analysis shows that FedMRL achieves a O(1/T) non-convex convergence rate. Extensive experiments on benchmark datasets demonstrate its superior model accuracy with low communication and computational costs compared to seven state-of-the-art baselines. It achieves up to 8.48% and 24.94% accuracy improvement compared with the state-of-the-art and the best same-category baseline, respectively. © 2024 Neural information processing systems foundation. All rights reserved.

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Microgrid Recent Innovations & Uses 15

Microgrid Recent Innovations & Uses

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Kaushik, Neeraj Goswami, Shubhashis Sachan, Keerti Vijayalakshmi, V.J. Gajendran, P. Mishra, V.A. Tmu Department of Ece India Dev Bhoomi Uttarakhand University School of Engineering and Computer Uttarakhand India Iimt University School of computer science and application Meerut India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore India Vishwakarma Institute of Information Technology Computer Engg Pune India

ISBN: (纸本)9798350370249

Concerns about global warming brought on by increasing carbon dioxide levels in the environment have sped up technological development in the sustainable energy sector over the past few years. The advancement in science while the shift to less polluting materials sources possesses increased the appeal for DG, subsequent generations distributed generation, using renewable supplies. Nevertheless, it has become widely recognized that increasing DG entry can negatively affect the matrix's layout and operations. A suggestion made to reduce the effect about DG while improve the suitability of traditional grids over massive DG installation involves the Located concept. encompassing a variety of electrical devices', the elements and Micro-grids and related power gadgets fields are now very well-liked research areas. This essay examines the history and theory behind microgrids, as well as the present situation regarding the writing, active research initiatives, and pertinent requirements. It additionally provides a more thorough analysis of the numerous Located pilot initiatives which have been implemented surrounding the globe and addresses possible directions for future study. © 2024 IEEE.

关键词： Distributed generation IEEE Standard 1547 Microgrid control Microgrid management system Protection Renewable energy

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CIFER: A Cache-Coherent 12-nm 16-mm2SoC With Four 64-Bit RISC-V Application Cores, 18 32-Bit RISC-V Compute Cores, and a 1541 LUT6/mm2Synthesizable eFPGA

IEEE Solid-State Circuits Letters

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IEEE Solid-State Circuits Letters 2023年 6卷 229-232页

作者： Li, Ang Chang, Ting-Jung Gao, Fei Ta, Tuan Tziantzioulis, Georgios Ou, Yanghui Wang, Moyang Tu, Jinzheng Xu, Kaifeng Jackson, Paul Ning, August Chirkov, Grigory Orenes-Vera, Marcelo Agwa, Shady Yan, Xiaoyu Tang, Eric Balkind, Jonathan Batten, Christopher Wentzlaff, David Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States Princeton University Department of Computer Science PrincetonNJ08544 United States National Cheng Kung University Miin Wu School of Computing Tainan701 Taiwan Cornell University Department of Electrical and Computer Engineering IthacaNY14850 United States The University of Edinburgh School of Engineering EdinburghEH8 9YL United Kingdom University of California at Santa Barbara Department of Computer Science Santa BarbaraCA93106 United States

This letter presents CIFER, the world's first open-source, fully cache-coherent, heterogeneous many-core, CPU-FPGA system-on-chips. The 12 nm, 16-mm2 chip integrates four 64-bit, OS-capable, RISC-V application cores;three TinyCore clusters that each contain six 32-bit, RISC-V compute cores (18 in total);and an electronic design automation-synthesized, standard-cell-based eFPGA. CIFER enables the decomposition of real-world applications and tailored execution (parallelization or specialization) per decomposed task. Our evaluation shows that: 1) the TinyCore clusters increase the throughput and energy efficiency of data- and thread-parallel tasks by up to 7.95× and 7.75× over one 64-bit core, respectively;2) the eFPGA increases the throughput and energy efficiency of hardware-accelerable tasks by up to 9.29× and 10.62× , respectively;and 3) using coherent caches for data transfer between the processors and the eFPGA increases the throughput and energy efficiency by up to 11.1× and 10.5× , respectively. © 2018 IEEE.

关键词： Field programmable gate arrays (FPGA)

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