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1st International Conference on Circuits, Power, and Intelligent Systems, CCPIS 2023

作者： Behera, Bikash ranjan Sahu, Nibash Kumar Mishra, Sanjeev Kumar Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communucation Engineering Chennai India Department of Instrumentation and Electronics Engineering Bhubaneswar India International Institute of Information Technology Advanced Rf and Microwave Lab Department of Electronics and Communication Engineering Bhubaneswar India

ISBN: (纸本)9798350315769

In this research, a proximity coupled rectangular microstrip antenna for the rF energy harvesting application is reported here. Here, the proposed antenna belongs to category of printed antenna, where, rectangular shaped patch is utilized as radiator. It is fed by the 50-Ω proximity coupled microstrip line, in between the Fr-4 (ϵr1=4.4) and rogers rT duroid 5880 (ϵr2=2.2) substrate, having the overall dimensions of 60 (LSUB) × 80 (WSUB) × 2.4 (hSUB-1= hSUB-2) mm3. Then, parasitic patches & intuitive ground plane shaping method is incorporated out, for broadening the impedance bandwidth. The parameters such as impedance bandwidth, gain, efficiency, radiation pattern, and surface current distribution are reported & analyzed by using the EM solver CST microwave studio. It exhibits an impedance bandwidth of 277 MHz, a realized gain of 5.6 dB with antenna efficiency of 92% at a 2.4 GHz ISM Frequency Band (2.4-2.484 GHz). With the obtained results, the proposed antenna is a best candidate for ISM and can be even extended for the rF energy harvesting application. © 2023 IEEE.

关键词： Microstrip antennas

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Conversion of N-doped biochar from carotenoid-extracted Tetraselmis suecica and its application to produce supercapacitors

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Journal of Environmental Sciences 2025年第5期151卷 410-423页

作者： Se Hun Lee Kang Hyun Lee Sang-hwa Lee Soo Kweon Lee Ok Sung Jeon Young Pyo Jeon dongpyo Hong Young Joon Yoo Sang Yoon Park Hah Young Yoo Advanced Institute of Convergence Technology(AICT) Seoul National UniversitySuwon 16229Republic of Korea Department of Biotechnology Sangmyung University20 Hongjimun 2-GilJongno-GuSeoul 03016Republic of Korea Department of Bio-Convergence Engineering Dongyang Mirae University445-8Gyeongin-roGuro-guSeoul 08221Republic of Korea Fermentation team Lotte R&D Center210 Magokjungang-RoGangseo-GuSeoul 07594Republic of Korea School of Electronic Engineering Kyonggi UniversityGyeonggi-do 16227Republic of Korea

Microalgae are one of the promising feedstocks for biorefinery,contributing significantly to net-zero emissions through carbon capture and ***,the disposal of microalgal byproducts from the manufacturing process causes additional environmental pollution,thus,a new application strategy is *** this study,the Tetraselmis suecica byproduct from the carotenoid extraction process was carbonized and converted into *** converted biochar was proved to be nitrogen-doped biochar(NdB),up to 4.69%,with a specific surface area of 206.59m^(2)/g andwas used as an electrode for a *** NdB electrode(NdB-E)in half-cell showed a maximum specific capacitance of 191 F/*** a full-cell test,the NdB-E exhibited a high energy density of 7.396 Wh/kg and a high-power density of 18,100 W/kg,and maintained specific capacity of 95.5%after charge and discharge of 10,000 *** conclusion,our study demonstrated that the carotenoid-extracted microalgal byproducts are a useful resource for the supercapacitor *** approach is the first to convert *** into active materials for supercapacitors.

关键词： Microalgae Tetraselmis suecica Carbonization N-doped biochar Supercapacitor

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Optimizing E-Commerce Fraud detection with BiGrU and Capsule Network Architectures 2

Optimizing E-Commerce Fraud Detection with BiGRU and Capsule...

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2nd IEEE International Conference on data Science and Network Security, ICdSNS 2024

作者： Vii, Suman rede, Ganeshkumar d. ramesh, P. Kumar A, rajesh Bharathi, A. Anand, M. Clement Joe School of Management and Commerce Studies Shri Guru Ram Rai University Uttarakhand Dehradun India Nagpur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Cse Chennai India N.S.N College of Engineering and Technology Department of Cse Karur India Vels Institute of Science Technology and Advanced Studies Department of Information Technology Chennai India Department of Mathematics Bengaluru India

ISBN: (纸本)9798350373110

Computers and enterprises have proliferated to the point that most financial transactions may now be conducted through electronic commerce systems. This includes systems for credit, telephones, healthcare insurance, etc. The truth is that these solutions are used by both law-abiding citizens and criminals. Con artists also tried a variety of techniques to break into the e-commerce platforms. To provide adequate security for the e-commerce platforms, fraud prevention systems (FPSs) disappoint. Preprocessing, feature selection, and training the model are the three stages that make up the suggested method. Preprocessing includes discretization and min max normalization. discretization is used to shorten attribute intervals and normalization is used to divide attribute values. Improving the efficacy of machine learning (ML) models in the intrusion detection system domain by GA-based feature selection. When training the model, a BiGrU-A-CapsNet was utilized. The suggested method outperforms BiGrU and CapsN et with an average accuracy of 95.44 percent. © 2024 IEEE.

关键词： Feature Selection

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Waveguide absorbers based on spiral acoustic black holes for damping vibration in a plate structure 24

Waveguide absorbers based on spiral acoustic black holes for...

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24th International Congress on Acoustics, ICA 2022

作者： Park, Seongmin Lee, Jae Yeon Jeon, Wonju Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Korea Republic of 1st R&D Center Agency for Defense Development Korea Republic of

We propose a waveguide absorber (WGA) based on a spiral acoustic black hole (ABH) to reduce vibration in plates. The geometrical dimensions of the WGA are determined so that it has a lower cut-on frequency than a target frequency by using the impedance method. We also determine the attachment location and direction of the WGA on a plate to maximize its damping performance based on the structural intensity analysis. A couple of WGAs attached to a plate could reduce the mobility of the plate by more than 10 dB. In addition, the WGAs had far less weight but could achieve larger peak reductions compared to thick damping material or spiral ABHs attached to edges. © ICA *** rights reserved

关键词： Acoustic black hole (ABH) Elastic wave Vibration damping

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Pulse‑Charging Energy Storage for Triboelectric Nanogenerator Based on Frequency Modulation

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Nano-Micro Letters 2025年第9期17卷 139-151页

作者： Kwon‑Hyung Lee Min‑Gyun Kim Woosuk Kang Hyun‑Moon Park Youngmin Cho Jeongsoo Hong Tae‑Hee Kim Seung‑Hyeok Kim Seok‑Kyu Cho donghyeon Kang Sang‑Woo Kim Changshin Jo Sang‑Young Lee Department of Chemical and Biomolecular Engineering Yonsei UniversitySeoul 03722Republic of Korea Ulsan Advanced Energy Technology R&D Center Korea Institute of Energy Research(KIER)Ulsan 44776Republic of Korea Department of Battery Engineering Pohang University of Science and Technology(POSTECH)Pohang 37673Republic of Korea Research and Development Center Energy-Mining LTDSuwon 16226Republic of Korea Department of Chemical Engineering POSTECHPohang 37673Republic of Korea Department of Battery and Chemical Engineering Hanyang University ERICAGyeonggi 15588Repubilc of Korea UBATT Inc Daejeon 34036Republic of Korea Department of Materials Science and Engineering Yonsei UniversitySeoul 03722Republic of Korea Center for Human‑Oriented Triboelectric Energy Harvesting Yonsei UniversitySeoul 03722Republic of Korea Institute for Convergence Research and Education in Advanced Technology Yonsei UniversitySeoul 03772Republic of Korea Department of Battery Engineering Yonsei University50Yonsei‑RoSeodaemun‑GuSeoul 03722Republic of Korea

Energy harvesting storage hybrid devices have garnered considerable attention as self-rechargeable power sources for wireless and ubiquitous *** nanogenerators(TENGs),a common type of energy harvester,generate alternating current-based,irregular short pulses,posing a challenge for storing the generated electrical energy in energy storage systems that typically operate with direct current(dC)-based low-frequency *** this study,we propose a new strategy that leverages high-frequency response to develop efficient chargeable TENG-supercapacitor(SC)hybrid devices.A highfrequency SC was fabricated using hollow-structured MXene electrode materials,resulting in a twofold increase in the charging efficiency of the hybrid device compared to a control SC made with conventional carbon electrode *** a systematic understanding,the electrochemical interplay between the TENGs and SCs was investigated as a function of the frequency characteristics of SCs(f_(SC))and the output pulse duration of TENGs(Δt_(TENG)).Increasing the fSC·Δt_(TENG) enhanced the charging efficiency of the TENG-SC hybrid *** study highlights the importance of frequency response design in developing efficient chargeable TENG-SC hybrid devices.

关键词： Energy harvesting storage hybrids Triboelectric nanogenerators Supercapacitors Frequency response MXene

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Comprehensive Experimental Study on Shaft Voltage of Traction Motor with Ceramic Bearing for Electric Vehicles

Comprehensive Experimental Study on Shaft Voltage of Tractio...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Jun-Woo Chin deok-Jin Kim Seojun Park Ho-Chang Jung Advanced Powertrain R&D Department Korea Automotive Technology Institute (KATECH) Cheonan Republic of Korea

This study investigates the experimental analysis of shaft voltage, focusing on the variables of the inverter and motor in electric vehicles (EVs), applying ceramic bearings. The aim of the study is to analyze the tendencies of shaft voltage in the inverter-fed EV traction motor using experimental methods. The variables for trend analysis include the switching frequency of pulse width modulation (PWM), the oil temperature, and the usage of shaft ground ring (SGr) as variables. Moreover, the variables cover the rotational speed and the torque as load conditions. In order to investigate the stochastic shaft voltage data rigorously, the post-process method using the probability density function is proposed. Using the proposed method, the trends of shaft voltage are analyzed according to the variables above in terms of the mean value and the probability over certain value. The results are figured out that the switching frequency of PWM and the oil temperature influence the shaft voltage, while the rotational speed has little effect on the shaft voltage. Under the load condition, it is shown that the torque, proportional to the current, rather than the rotational speed affects the shaft voltage. The effect of SGr will be handled as a future work with test results of prototype applying SGr.

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Harvesting Insights: Predicting Vegetable Prices with Hybrid CLA-Conv BiGrU Techniques 3

Harvesting Insights: Predicting Vegetable Prices with Hybrid...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Lal Ambashtha, Kanahaiya Praveen Kumar, Chatakunta Pandey, Vivekanand Sakthivel Padaiyatchi, S. Bharathi, A. Navaz, K. Gnsu Faculty of Information Technology Bihar Sasaram India Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad India Amity University Bihar Patna India Nehru Institute of Engineering and Technology Department of Electrical and Electronics Engineering TN Coimbatore India Vels Institute of Science Technology and Advanced Studies Department of Information Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350381931

The system delves into the important topic of agricultural market pricing, with a specific emphasis on the ever-changing realm of vegetable supply and prices. Stabilizing the supply and prices of vegetables becomes an enormous task when consider that the system are grown outdoors and that weather variables significantly impact harvests. Such unpredictability has far-reaching consequences for the country's economy, highlighting the critical need to develop efficient methods of precise forecasting. The government has made multiple attempts to stabilize vegetable prices and supplies, but these have all been unsuccessful due to the unpredictable weather patterns of late. This system uses state-of-the-art deep learning methods, notably the Hybrid CLA-Conv BiGrU model, which incorporates a novel preprocessing strategy based on the HP Filter, to conquer this obstacle. A strong prediction model for vegetable prices is constructed using the process, which includes feature extraction, scoring, and selection. © 2024 IEEE.

关键词： Vegetables

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Using NSCTS and dCNN, rapid Prediction and Forecasting of Breast Cancer 1

Using NSCTS and DCNN, Rapid Prediction and Forecasting of Br...

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1st IEEE International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Seethalakshmi, K. Bhagyalakshmi, A. Sangeetha, A. Vijitha, S. Palukuri, P. Suhas Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India R.M.K. College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Vels Institute of Science Technology & Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350316469

Utilizing the CAd system, which aids radiologists in various diagnostic procedures, a recent study has been conducted on the early identification of breast cancer. Next to lung cancer, breast cancer ranks among the most deadly diseases. Initially, detection is done based on screening tests done through Magnetic resonance imaging (MrI), subsequently Infrared thermography, and digital mammography (dM). Whenever a suspicion is raised, these tests might be recommended by the specialist. region-based segmentation is used for the test picture in this work, while NSCTS (Non-subsample Contourlet transform segmentation) is used for preprocessing. resNet-164 dCNN architecture performs feature extraction and classification between normal and aberrant tumor pictures. The diagnosis system adopts the deep learning technology to increase its performance rate. The approach to prediction starts with screening test photos, then preprocessing to enhance the image quality, rOI detection, rOI segmentation, and classification. The resulting images are examined using a variety of evaluation measures, including performance rate, sensitivity, specificity, and accuracy. When compared to other recent work, the outcome is exceptional. The obtained accuracy, sensitivity of the proposed system is 98.58% and 98.78%. The application takes advantage of the MIAS mammography image dataset. © 2023 IEEE.

关键词： Breast cancer contourlet segmentation dCNN digital mammograms Image preprocessing MrI resNet

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Prior austenite grain boundary recognition in martensite microstructure based on deep learning

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Journal of Iron and Steel research International 2023年第5期30卷 1050-1056页

作者： Xuan-dong Wang Nan Li Hang Su Hui-min Meng Institute for Advanced Materials and Technology University of Science and Technology BeijingBeijing 100083China Department of Structural Steel Central Iron and Steel Research Institute Co.Ltd.Beijing 100081China Material Digital R&D Center China Iron&Steel Research Institute Group Co.Ltd.Beijing 100081China Central Laboratory Central Iron and Steel Research Institute Co.Ltd.Beijing 100081China

Grain size determination is essential in producing and testing iron and steel *** size determination of martensitic steels usually requires etching with picric acid to reveal the prior austenite grain ***,picric acid is toxic and explosive and belongs to hazardous chemicals,which makes it difficult for laboratories and testing institutions to obtain.A new experimental method was developed to use Nital etchant instead of picric *** deep learning method was used to recognize the prior austenite grain boundaries in the etched martensite microstructure,and the grain size could be determined according to the recognition ***,the polished martensite specimen was etched twice with Nital etchant and picric acid,respectively,and the same position was observed using an optical *** images of the martensitic structure and its prior austenite grain boundary label were obtained,and a data set was ***,based on this data set,a convolutional neural network model with a semantic segmentation function was trained,and the accuracy rate of the test set was 87.53%.Finally,according to the recognition results of the model,the grain size rating can be automatically determined or provide a reference for experimenters,and the difference between the automatic determination results and the measured results is about 0.5 level.

关键词： Prior austenite grain boundary Microstructure etching Image recognition deep learning

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Beta-phase transformation of polyvinylidene fluoride with supersonically sprayed ZnSnO_(3) cuboids for flexible piezoelectric nanogenerators

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Journal of Materials Science & technology 2024年第10期177卷 103-113页

作者： Bhavana Joshi Taegun Kim Woojin Lim Edmund Samue Chanwoo Park Ali Aldalbahi Mohamed El-Newehy Hae-Seok Lee Seongpil An Sam S.Yoon School of Mechanical Engineering Korea UniversitySeoul 02841Republic of Korea Core Component Technology Team Samsung Electronics Co Ltd.Mobile R&D CenterSamsung-roSuwon-siGyeonggi-doRepublic of Korea Energy Environment Policy and Technology Graduate School of Energy and Environment(KU-KIST Green School)Korea UniversitySeoul 02841Republic of Korea Department of Chemistry College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia SKKU Advanced Institute of Nanotechnology(SAINT) Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Nano Science and Technology Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Nano Engineering Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea

Flexible self-powered electromechanical devices,such as piezoelectric nanogenerators(PENGs),which are used in wearable and implantable devices,are emerging as state-of-the-art clean energy *** this study,a scalable supersonic spraying technique was used to prepare flexible piezocomposite films of polyvinylidene fluoride(PVdF)and hydrothermally synthesized ZnSnO_(3)(ZSO)cubes for *** spectra confirmed that the transformation of the α-phase of PVdF to its β-phase was induced by the shear stress generated between the ZSO particles and PVdF polymer during supersonic *** op-timized sample comprising 0.43 g of ZSO cubes and 1 g of PVdF produced a maximum piezopotential of 41.5 V and a short-circuit current,I_(sc),of 52.5 μA.A maximum power density of 50.6 μW cm-2 was ob-tained at a loading resistance of 0.4 MΩ,which matched the impedance of the ***-term tapping and bending cycles of N_(tap)=4200 and N_(bend)=600 yielded piezopotentials of 40.5 and 1.7 V,*** addition,electrical poling for 2 h increased the piezopotential to 52 V owing to the alignment of the ferroelectric dipoles in the PVdF.

关键词： ZnSnO_(3) PVdF Composite Perovskite Supersonic cold spray Piezoelectric nanogenerator

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