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

作者： Sahoo, Girija Shankar Hannah Jessie Rani, R. Goyal, Manish Kumar Mohammed, Vazeer Ali Jana, D Little Femilin Wasatkar, Namrata N. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Lewis University Illinois Department of Computer & Information System United States Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

This paper proposes the use of adaptive algorithms for real-time data analysis. Adaptive algorithms are a set of practical methods used for acting information-driven optimization and studying. They have a wide variety of applications and may be implemented to a selection of facts analysis obligations. This paper offers an overview of existing adaptive algorithms and descriptions of several new programs in the area of actual-time facts analysis. In particular, the paper discusses the notion of adaptive thresholding, which allows for practical real-time evaluation of large datasets. The paper also provides a novel technique for making use of these algorithms in an online learning environment. Results from simulations illustrate the ability of the proposed method in real-international packages. Sooner or later, the paper presents numerous key lessons discovered and affords recommendations for future research and packages in this area. © 2024 IEEE.

关键词： Adaptive algorithms

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Split Lohmann computer holography: fast generation of 3D hologram in single-step diffraction calculation

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Advanced Photonics Nexus 2024年第3期3卷 1-13页

作者： Chenliang Chang Xian Ding Di Wang Zhizhou Ren Bo Dai Qi Wang Songlin Zhuang Dawei Zhang University of Shanghai for Science and Technology School of Optical-Electrical and Computer EngineeringEngineering Research Center of Optical Instrument and SystemMinistry of Education and Shanghai Key Laboratory of Modern Optics SystemShanghaiChina Beihang University School of Instrumentation and Optoelectronic EngineeringBeijingChina

Holographic display stands as a prominent approach for achieving lifelike three-dimensional(3D)reproductions with continuous depth ***,the generation of a computer-generated hologram(CGH)always relies on the repetitive computation of diffraction propagation from point-cloud or multiple depthsliced planar images,which inevitably leads to an increase in computational complexity,making real-time CGH generation ***,we report a new CGH generation algorithm capable of rapidly synthesizing a 3D hologram in only one-step backward propagation calculation in a novel split Lohmann lens-based diffraction *** introducing an extra predesigned virtual digital phase modulation of multifocal split Lohmann lens in such a diffraction model,the generated CGH appears to reconstruct 3D scenes with accurate accommodation abilities across the display *** with the conventional layer-based method,the computation speed of the proposed method is independent of the quantized layer numbers,and therefore can achieve real-time computation speed with a very dense of depth *** simulation and experimental results validate the proposed method.

关键词： computer holography holographic display diffraction calculation.

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Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. 5

Coil Optimization using Metaheuristic Techniques for Wireles...

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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Imtiaz, Tabish Elsanabary, Ahmed Mekhilef, Saad Mubin, Marizan Binti Soon, Tey Kok Aziz, Nur Fadilah Ab Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Tenaga Nasional Institute of Power Engineering Selangor Kajang Malaysia Swinburne University of Technology School of Science Computing and Engineering Technologies Melbourne Australia Universiti Malaya Department of Computer System & Technology Kuala Lumpur Malaysia Universiti Tenaga Nasional Department of Electrical & Electronic Engineering Selangor Malaysia

ISBN: (纸本)9798350339673

Wireless Power Transfer (WPT) used for charging of electric vehicles (EVs), suffers from the problem of misalignment. In this paper metaheuristic optimizing techniques are used to increase the misalignment tolerance of the receiver coil. This is done by optimizing the length of each turn of the transmitter coil such that a uniform magnetic field density is produced over the charging area, which is kept 26% higher than the transmitting coil area which further aids to accommodate misalignment of the receiver coil. Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. These algorithms are also compared by varying the number of turns while keeping the number of iterations to a fixed value. © 2023 IEEE.

关键词： ABC Coil DE Misalignment Opti-mization PSO Wireless Power Transfer

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A Simultaneous Wireless Information and Power Transfer-based Multi-hop Clustering Routing Protocol for RF Energy Harvesting-Cognitive Radio Sensor Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 991-1007页

作者： Wang, Ji-Hong Su, Xi-Tong Ge, Yi-Yang Chen, Yeh-Cheng Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University China School of Electrical Engineering Northeast Electric Power University 169 Changchun Road Jilin132012 China Department of Computer Science University of California DavisCA001313 United States

Radio frequency energy harvesting (RF EH) and clustering are promising solutions to solve the energy constraint problem faced by cognitive radio sensor networks (CRSNs). However, study on clustering routing protocol design for RF EH-CRSNs is still in the initial stage, and there lacks of solutions for inter-cluster routing problem, which restricts the network scalability. In addition, unbalanced harvested energy and energy consumption may result in premature death of nodes in key position, which will significantly reduce the network performance. In this paper, a simultaneous wireless information and power transfer (SWIPT)-based multi-hop clustering routing protocol (SMCRP) is proposed for RF EH-CRSNs to well balance the residual energy distribution among nodes and postpone node death. Apart from the RF energy harvested from dedicated or ambi-ent energy sources, the energy obtained through intra-cluster and inter-cluster SWIPT is also considered to facilitate high-quality cluster heads selection, cluster formation and inter-cluster route establishment. Power splitting ratio is derived based on the residual energy of CRSNs nodes and their energy consumption to enable effective implementation of SWIPT in CRSNs. Simulation results show that SMCRP is effective in balancing the residual energy distribution among nodes and improving node sustainability. To be specific, compared with current clustering protocols, the network lifetime is extended by 64.07% while intra-cluster energy balance degree and network energy balance degree are improved by 15.1% and 7.82%, respectively. © 2023 ISSN 2414-8105 (Online).

关键词： Cognitive radio

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CMOS Leaky Integrate-and-Fire Neurons with Local Dynamic Biasing and Inhibitory Self-Oscillation

CMOS Leaky Integrate-and-Fire Neurons with Local Dynamic Bia...

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2023 IEEE Biomedical Circuits and systems Conference, BioCAS 2023

作者： Cho, Mannhee Kang, Minil Um, Minseong Park, Hangue Lee, Hyung-Min Korea University School of Electrical Engineering Seoul Korea Republic of Korea University Department of Semiconductor System Engineering Seoul Korea Republic of Sungkyunkwan University Department of Biomedical Engineering Suwon Korea Republic of Sungkyunkwan University Department of Intelligent Precision Healthcare Convergence Suwon Korea Republic of Texas A&m University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350300260

This paper presents a CMOS-based neuromorphic circuit that can simulate self-oscillatory firing behaviors. Based on the leaky integrate-and-fire neuron model, a dynamic bias controller and an excitation integrator are added for controlling inhibitory connection between neurons as well as switching the operation mode with an integrated excitatory control signal. The proposed neuron circuit replicates extracellular fluidic biasing of membrane potential that oscillates at low frequency on top of the temporal integration of the action potential firing at high frequency. The proposed neuron can also replicate the synaptic fatigue by implementing inhibition declining over time, which leads the bias to oscillate. The proposed neuron model was implemented with 250nm CMOS process at 2.5V supply voltage. Each neuron consumes 46.16pJ energy/spike from leaky integration. Simulation results verified that a pair of proposed neuron cells can generate an oscillatory rhythm, where the bias waveform oscillates with the output spikes generated based on the bias level change. The proposed neuron circuit model can be utilized to reproduce more complicated oscillatory network behaviors of biological neurons. © 2023 IEEE.

关键词： biological oscillator leaky integrate-and-fire neuron Neuromorphic spiking neural network

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Research on Causal Model Construction and Fault Diagnosis of Control systems 7th

Research on Causal Model Construction and Fault Diagnosis of...

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7th International Conference on Computing, Control and Industrial engineering, CCIE 2023

作者： Zhu, Qun Chen, Zhi Liu, Jie Xu, Zhuoran Wen, Juan Yang, Jinghua Jian, Yifan School of Computer Science University of South China Hengyang421200 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610064 China School of Electrical Engineering University of South China Hengyang421200 China

ISBN: (纸本)9789819927296

Fault diagnosis of complex control systems is a difficult and hot topic of research at this stage. In order to explore the internal operation characteristics of complex control systems and fault propagation methods to achieve efficient and accurate fault diagnosis, this paper studies control system fault diagnosis methods based on cause-effect relationships, analyzes the role relationship between system components from the perspective of control equation structure, proposes the method of constructing cause-effect diagram models with control equations, and uses the algorithm of way to implement, and then combine the information flow to quantify the causal effect quantifiably, when the system steady state is disrupted, the information flow produces a jump, so as to extend the fault diagnosis reasoning method. The fault diagnosis is verified by simulation of the pressure control system of the nuclear power plant regulator, and the experimental results verify the effectiveness of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

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Efficient design and simulation of force analysis of rotary loading platform under automated processing mode 4

Efficient design and simulation of force analysis of rotary ...

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4th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2022

作者： Lu, Zhihong Shi, Huijie Zhang, Xiyu School of Electrical Computer and System Engineering Rensselaer Polytechnic Institute TroyNY12180 United States School of Information and Mechatronics Engineering Shanghai Normal University Shanghai201400 China School of Mechanical Engineering Guangxi University Guangxi530007 China

ISBN: (纸本)9781450398343

In industry, rotary lifting platforms are widely used. In this research, two models with different support plate thicknesses are designed for the same type of four support plates rotating lifting platforms. The research simplifies the model to a cantilever beam model to facilitate the theoretical calculation of mechanical parameters of materials. The stresses and deformations of the support plates of the two models under different loads are theoretically calculated. The calculation results all meet the safety requirements of the material. The finite element simulation software ANSYS WORKBENCH is used to verify whether the stresses and deformations of the actual models meet the requirements. The simulation results show that the stress and deformation of the simulation are different from those of the theoretical calculation. The reason lies in the simplification of the theoretical calculation. This difference does not affect the simulation result parameters to meet the design safety requirements. © 2022 ACM.

关键词： Finite element method

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Multimodal Learning to Improve Cardiac Late Mechanical Activation Detection from Cine MR Images

Multimodal Learning to Improve Cardiac Late Mechanical Activ...

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IEEE International Symposium on Biomedical Imaging

作者： Jiarui Xing Nian Wu Kenneth C. Bilchick Frederick H. Epstein Miaomiao Zhang Department of Electrical and Computer Engineering University of Virginia USA School of Medicine University of Virginia Health System USA Department of Biomedical Engineering University of Virginia Health System USA Department of Computer Science University of Virginia USA

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Class imbalance in the medical image dataset is almost inherent due to the limited availability of clinical data for certain diseases and patient populations. Under-represented classes in the training set affect the classification task because the classifier tends to learn more from the majority classes, which are more common in the dataset and ignore data from the minority classes. To mitigate this issue, we propose a method to learn using two different convolutional neural network-based experts; such experts try to learn boundaries within the head classes, between the head and tail classes, and within the tail classes. During expert training, we integrate the MixUp regularization method to augment imbalanced data, employing distinct data sampling strategies for more effective mixing compared to random selection in traditional MixUp. During the inference phase, we combine the logits of the different experts based on their expertise in the corresponding classes. This way, we can improve the accuracy of the head and tail classes. Experiments using highly imbalanced and long-tailed datasets demonstrate the effectiveness of the suggested framework.

关键词： Training Accuracy Head Three-dimensional displays Tail Data models Task analysis

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The Application of Regression Models to Market Rate of Return Prediction

The Application of Regression Models to Market Rate of Retur...

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2022 International Conference on Statistics, Data Science, and Computational Intelligence, CSDSCI 2022

作者： Chen, Weizhi Fu, Jiawei Yang, Yu Yang, Zhenbang College of Computer Science and Technology Zhejiang University Hangzhou China College of Engineering and Applied Science University of Cincinnati 2901 Woodside Drive Cincinnati United States School of information and Electrical engineering Zhejiang University City College Hangzhou China School of Intelligent System engineering Sun Yat-sen University Shen Zhen China

ISBN: (纸本)9781510661325

Quant investing is very popular nowadays. To predict returns, there are lots of algorithm and models for financial market trading. In this case, with some new methods, quantitative researchers' ability to forecast an investment's return. In this paper, a new dataset obtained from a Kaggle competition called Ubiquant Market Prediction will be introduced and some classical method and model will be tested on it. This dataset has following characteristics. Firstly, its' target is return rate instead of the return, which means it could adapt to different scales of investment. Secondly, 300 dimensional anonymous features extracted are used in prediction so that this method could be applied in the prediction of different kinds of investments which have different kinds of features. Thirdly, this dataset considers the types and time periods of investment behavior. For the reasons above, the dataset is quite valuable. The classical methods tested in the experiment include Support Vector Regression (SVR), ensemble learning, k-Nearest Neighbor (KNN), Deep Neural Network (DNN), random forest, Stochastic Gradient Descent (SGD) regressor, passive aggressive regressor and Multilayer Perceptron (MLP) regressor. These methods are tested on this dataset and their performance are compared in the result and discussion section, aiming to figure out whether these classical approaches could have a good result in the dataset. © 2023 SPIE.

关键词： Investments

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Preferences for Using Canva Apps as a Presentation Media Creation Tool Among Gen Z Students: SEM Analysis with TAM and UTAUT2 Approaches 25

Preferences for Using Canva Apps as a Presentation Media Cre...

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25th International Seminar on Intelligent Technology and Its Applications, ISITIA 2024

作者： Maulana, Fairuz Iqbal Lestari, Dian Purnomo, Agung Arifuddin, Rahman Widartha, Vandha Pradwiyasma Adi, Puput Dani Prasetyo Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Medicine Airlangga Surabaya60132 Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta11480 Indonesia University of Merdeka Malang Department of Electrical Engineering Malang Indonesia Telkom University Information System of Industrial Engineering Faculty Bandung Indonesia Research Center for Telecommunication Bandung Indonesia

ISBN: (纸本)9798350378573

The purpose of this study is to find out what makes Generation Z students accept and use Canva as a tool for making presentation materials. The conceptual framework of this study is the combination of "Technology Acceptance Model (TAM)"and the "Unified Theory of Acceptance and Use of Technology (UTAUT2)". "Structural Equation Modeling (SEM)"used for data analyzation. This research aims to understand the dynamics of Canva acceptance among students. The findings show that enjoyment, fun, and pleasure in using Canva, combined with its creative tools and design-centric approach, significantly resonate with Gen Z's preference for aesthetics. This research highlights that Canva is favored by students for creating engaging presentations. © 2024 IEEE.

关键词： Students

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