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Phased Array with Non-Ideal Double Phase Shifters for Multi-Target Vital Sign Monitoring

Phased Array with Non-Ideal Double Phase Shifters for Multi-...

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IEEE International Symposium on Biomedical Imaging

作者： Zhaoyi Xu Donglin Gao Shuping Li Chung-Tse Michael Wu Athina Petropulu Dept. of Electrical and Computer Engineering Rutgers University

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

A phased array equipped with double phase shifters (DPS) can reduce interference and enable multi-target vital sign monitoring (VSM) based on a single receive antenna. The DPS-phased array can control both the magnitude and the phase of the signal transmitted by each antenna, allowing for flexibly creating a desired beampattern. We consider the DPS-phased array weight design problem, taking into account practical constraints on the phase shifters, such as deviations from the nominal phases and insertion loss. The weights of practical phase shifters are selected so that the resulting DPS-phased array performs as close as possible to an ideal beamformer and transmits maximum power in the desired direction. The proposed design’s effectiveness is demonstrated in experiments where the transmit power is focused on a specific human target to monitor corresponding vital signs. Simultaneously, an adjacent but unwanted human target is effectively nullified.

关键词： Phased arrays Phase shifters Transmitting antennas Receiving antennas Interference Insertion loss Biomedical monitoring

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Impact of Diverse Turbulene Conditions on Spatial-UWOC system 3

Impact of Diverse Turbulene Conditions on Spatial-UWOC syste...

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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Kumari, Meet Sharma, Neha Chauhan, Rahul Joshi, Kireet UIE Chandigarh University Dept. of ECE Mohali Gharuan140413 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350354171

Underwater optical communication links, mult hop scattering may result in beam temporal spread characterized via the impulse response, which causes in interference and deteriorates system performance. Thence, an underwater VLLC spatial architecture incorporating two LDs of red (620nm) and green (520nm) are utilized at 20 Gbps throughput. Two Laguerre-Gaussian modes at [0, 0] and [0, 1] are used at green and red LD respectively, for enhancing system capacity. Results represent that -22 to -21dBm received power is obtained considering clear, costal as well as turbid water. Also, the system offers 60-75km range at 2Gbps data rate with wide open eye patterns, under acceptable limit of 10e-9. Proposed design provides optimum performance over existing underwater systems. © 2024 IEEE.

关键词： Optical links

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Tidal Power Plant Exploration: Low Head Water Turbine in Barrage System 13

Tidal Power Plant Exploration: Low Head Water Turbine in Bar...

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13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Noman, S.M. Hasan, Mohammad Mahedy Haque, Obaidul Baki-Ul-Islam Salehin, Imrus Moon, Nazmun Nessa Daffodil International University Dept. of Electrical and Electronic Engineering Dhaka Bangladesh Pabna University of Science and Technology Dept. of Electrical and Electronic Engineering Pabna Bangladesh Dongseo University Department of Computer Engineering Busan Korea Republic of Daffodil International University Dept. of Computer Science Engineering Dhaka Bangladesh

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Tidal energy is an environmentally benign, practical, and cost-effective renewable energy source. The hydropower potential appropriate site for electrical power production accessible in Bangladesh's coastline region is investigated in this article. We propose a model for determining the feasibility of power production via the tidal barrage system using a Compact Axial Kaplan (CAK) turbine in a low-head water turbine. Tidal power supplies enormous quantities of electrical energy in coastal locations across the globe without generating carbon or harming the environment. The world's wealthiest nations are increasingly resorting to tidal power generation. Where tidal power is available, we may be used tidal energy to alleviate the power shortage in coastal areas. A hydropower station may supply clean energy and fulfill a significant amount of the country's electrical demands. The notion of establishing a tidal power plant with a barrage model system would be a better long-term outlook for energy production and flourishing economic expansion. Dublar Char is an ideal location for tidal energy to be used to solve the electricity crisis in distant coastal regions. This article analyzes the electricity generating capability of Dublar Char, estimated at 120.17 megawatts (MW). © 2022 IEEE.

关键词： Tidal power

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Machine Learning-Based Crop Recommendation System for Mizoram

Machine Learning-Based Crop Recommendation System for Mizora...

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International Symposium on Advanced Computing and Communication (ISACC)

作者： V.D. Ambeth Kumar Ajoy Kumar Khan Vanlalhruaia Saithantluanga Ramesh Prabhakaran R Zaitinkhuma Dept. of Computer Engineering Mizoram University Aizawl India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Agriculture is an important sector of Mizoram domicile as more than half of its population relies on Agriculture as principle source of income and sustenance. Some farmers rely on the knowledge acquire from their parents through explicit explanation, and by observing and modelling their practices. But most farmer often struggle to understand the method and type of crops to cultivate for better crop yield. Even experienced farmer believed that using more fertilizer result in better crop yield in spite of that it damages the soil properties. To resolve this challenge, this paper presents a Crop Recommendation System using Machine Learning, tailored for Mizoram, enhancing Agriculture practices towards sustainable development. The Crop Recommendation System analyzes historical data, soil properties, weather pattern and crop performance to recommend the best crop for a specific region and its condition. The aim is to provide the Crop Recommendation System with information about the soil and the condition of the region. The study utilizes various Machine Learning Algorithms such as Random Forest, Decision Trees, Support Vector Machine and Logistic Regression to make optimal recommendation. The results indicate that Random Forest provides superior performance of 99% across all the evaluations metrics. Although many prevention measures need to be taken to avoid complications such as overfitting, etc. The overall results suggested that Random Forest achieved the best results as compared to all the other state of the art algorithms utilized with the same preprocessing steps. This approach enhances the crop and soil. After a long and often complicated process of farming method and selection of crop problem the Crop Recommendation System will aid Mizoram farmers to achieve better crops, yield and higher profit.

关键词： Support vector machines Machine learning algorithms Soil properties Agriculture Decision trees Sustainable development Recommender systems Random forests Crop yield Overfitting

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Soft Switched MEMS Power Relay Using a Resonant Auxiliary Circuit

Soft Switched MEMS Power Relay Using a Resonant Auxiliary Ci...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Agamy, Mohammed Todorovic, Maja Harfman Khamis, Ahmed University at Albany Suny Dept. of Electrical and Computer Engineering AlbanyNY United States Menlo Microsystems Inc. AlbanyNY United States

ISBN: (纸本)9798350376067

This paper proposes a parallel resonant soft switching auxiliary circuit that enables zero voltage turn-on and zero current turn-off of microelectromechanical switches. This provides a scalable soft switching method that is practical for emerging higher power rating switches compared to existing bypass approaches. Analytical, simulation and experimental results are presented to verify the operation of the proposed circuit in different modes of operation. © 2024 IEEE.

关键词： Resonant circuits

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Enhancing VANET Efficiency with ACRR Technique for Improved Traffic Management and Network Scalability

Enhancing VANET Efficiency with ACRR Technique for Improved ...

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Science, Technology, engineering and Management (ICSTEM), International Conference on

作者： K Karthick Praveen Talari Nishadevi V R Krishna Prakash R. Asokan Velusamy A Dept. of Computer Science and Engineering Kongunadu College of Engineering and Technology Trichy Tamilnadu Dept. of Computer Science and Engineering Vignan Bharathi institute of technology Hyderabad Telangana Dept. of Computer Science and Engineering Mahendra College of Engineering Salem Tamilnadu Dept. of Information Technology Sona College of Technology Salem India Dept. of Electronics and Communication Engineering Kongunadu College of Engineering and Technology Trichy Tamilnadu

ISBN: (数字)9798350376913

ISBN: (纸本)9798350388473

The role of Vehicular Ad Hoc Networks (VANETs) is crucial in enabling Intelligent Transportation System (ITS) technologies such as safe financial transactions, media applications, and effective traffic control. As traffic increases, the topology of vehicular networks is in constant flux, and the sparse distribution of vehicles, particularly on highways, presents challenges for network scalability. This situation makes it difficult for cars to keep consistent routes inside the network, which affects the stability of the network. To address these challenges, the developed Adaptive-ant Colony based Randomized Recommendation (ACRR) technique emerges as a unique solution for enhancing VANETs by reducing travel time. In instances of high traffic density on busy roads, the ACRR algorithm is effectively utilized to group vehicles. Leveraging data collected from these densely populated road segments, the system identifies congestion-prone areas and formulates optimal vehicle routes based on customized vehicle groupings. The framework's performance evaluation encompasses various parameters, including packet loss, message transmission rate, energy consumption, and average cluster growth. The proposed VANET framework, empowered by the ACRR algorithm, achieves an impressive message transmission rate of approximately 80%. In comparison, alternative methods like Re-RouTE exhibit a limited transmission rate of 70%, while others such as Net Run Rate (NRR), DIVERT 30, and DIVERT-60 demonstrate rates below 20%. Furthermore, the framework's parcel loss is significantly reduced to only 33% of that observed in the standard VANET framework. As a result, the ACRR algorithm integrated into the VANET framework demonstrates notable efficiency when compared to other approaches. It is crucial to recognize that, even with a refined technique, managing traffic congestion remains challenging if drivers disregard the recommended routing suggestions. Overall, this research offers insights into the p

关键词： Performance evaluation Roads Scalability Vehicular ad hoc networks Clustering algorithms Packet loss Routing

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Binary and Multiclass Classification of Attacks in Edge IIoT Networks

Binary and Multiclass Classification of Attacks in Edge IIoT...

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Advances in Science and engineering Technology International Conferences (ASET)

作者： Sidra Aslam Mohammad M.R. Alshoweky Mohamed Saad Dept. of Computer Engineering University of Sharjah UAE

ISBN: (数字)9798350344134

ISBN: (纸本)9798350344141

The Internet of Things (IoT) refers to a smart network of digitally connected physical devices and systems, with applications ranging from predictive maintenance, optimization, enhanced efficiency in manufacturing and critical infrastructure. Over the years the applications of IoT have been extended from domestic to Industrial Internet of Things (IIoT). The increased integration of IoT in real-world applications exposes the networks to cyber threats, e.g., Man in the Middle and ransomware attacks. Such attacks on IoT networks impact their operational integrity, data confidentiality, and overall system reliability, especially in IIoT networks. Therefore, the timely and accurate detection of cyber attacks can save these networks from unauthorized access, malware propagation, and denial of service attacks. In this paper, we present a cyber attack detection technique using Edge-IIoTset dataset for IIoT applications. The proposed detection approach is based on binary and multi-class classification of cyber attacks in IIoT networks, leveraging machine learning (i.e., logistic regression, decision tree) and deep learning (i.e., recurrent and convolutional neural networks) algorithms. The proposed classification techniques showcase the effectiveness of the applied algorithms achieving an average accuracy of 90 %.

关键词： Machine learning algorithms Accuracy Image edge detection Classification algorithms Reliability Ransomware Cyberattack Optimization Industrial Internet of Things Predictive maintenance

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Smart Contracts based on Hyperledger Fabric Blockchain for the Purpose of Higher Education Subsidizing 3

Smart Contracts based on Hyperledger Fabric Blockchain for t...

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3rd International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2022

作者： Valchanov, Hristo Aleksieva, Veneta Technical University of Varna Dept. of Computer Science And Engineering Varna Bulgaria

ISBN: (数字)9781665491495

ISBN: (纸本)9781665491495

During their studies, many students drop out of one specialty, then apply and enroll in another. The state subsidized several semesters of their studies, then again subsidized the student's studies in another specialty. A number of students start but do not complete their studies, but this has been subsidized by the state as well. No research has been focused on the state's losses from subsidizing education in these cases. This paper proposes a model where any citizen can receive a subsidy for his studies, but only for up to 10 semesters. After that, he has to pay the full cost of his education. Under this model, students are motivated to complete their studies within the subsidized semesters, and the state does not suffer losses from refinancing the same student whose study period exceeds these semesters. The model is based on a smart contract on Hyperledger Fabric platform. © 2022 IEEE.

关键词： Smart contract

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From Product Sheet to Text and Video: A NLG Pipeline to Transform Structured Data into Comprehensive Descriptions 32

From Product Sheet to Text and Video: A NLG Pipeline to Tran...

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32nd Italian Symposium on Advanced Database Systems, SEBD 2024

作者： Avignone, Andrea Fiori, Alessandro Chiusano, Silvia Rizzo, Giuseppe Dept. of Control and Computer Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 Torino10129 Italy LINKS Foundation Torino Italy

The recent improvement of powerful Large Language Models is the key to automatically produce satisfactory written and spoken language, in contrast to the constraints of conventional template-based solutions. However, the most advanced models can be costly and complex to integrate into practical applications, especially in business contexts where the output quality significantly matters. This study presents a tailored pipeline for data-to-text and text-to-speech generation, primarily harnessing the availability of open source pre-trained language models and leveraging established Natural Language Processing tasks. As a use case, we worked on the automatic generation of both textual and video product descriptions from the structured information about the product features. The pipeline involves all the required steps, providing the final trained and customized model. The obtained descriptions showed the capability of replicating the overall semantic, lexical and linguistic style of the corresponding human counterpart, despite being based on a cost-effective model. © 2024 Copyright for this paper by its authors.

关键词： Semantics

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A DRAM-Based Processing-in-Memory Accelerator for Privacy-Protecting Machine Learning

A DRAM-Based Processing-in-Memory Accelerator for Privacy-Pr...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Bokyung Kim Dept. of Electrical and Computer Engineering Rutgers University USA

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

The sensational outcomes of machine learning (ML) are witnessed. As the big success relies on continual training with massive data encompassing sensitive information, deep neural network (DNN) models easily leak private information. For instance, large pre-trained language models contain a substantial volume of private information, which can be acquired by querying with appropriate prompts. This raises concerns regarding privacy in ML, and DNN models are evolving for privacy-preserving ML (PPML).

关键词： Training Solid modeling Privacy Tensors Europe Artificial neural networks Machine learning Data transfer Energy efficiency Data models

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