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A DC-DC Boost Converter with Switching Inductor and Capacitor with High Gain for Solar Microgrid applications 2

A DC-DC Boost Converter with Switching Inductor and Capacito...

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2nd international conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Neels Ponkumar, D. David Salma, Nazrin Dhanalakshmi, S. Baskar, S. Ashok, Chitrada Periyasamy, Duraipandy Saravanakumar, R. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Thamirabharani Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Tirunelveli India Velammal College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Madurai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Civil Engineering Tamil Nadu Chennai India J. B. Institute of Engineering and Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350366570

A high-gain DC-DC booster converter using a changing inductor and capacitors is described in this study for usage in solar microgrids. The suggested converter effectively boosts its low-voltage outputs to make photovoltaic (PV) panels more appropriate for integration into microgrids. As a result of performance losses and excessive stress on internal components, traditional boost converters are unable to provide the necessary voltage rise. Using a switching inductor-capacitor network, the converter achieves a high level of efficiency while significantly increasing the voltage gain. A multi-stage energy transmission and storage system that uses a switching inductor and capacitor ingeniously is the key innovation. Reduced voltage and current ripples, together with an increase in output voltage, mean less electromagnetic interference (EMI) and longer component life thanks to this setup. We validate the converter's performance across a variety of load and input scenarios common to solar microgrids by conducting thorough examinations of its functioning via theoretical modeling and simulation studies. Compared to conventional boost converters, the testing results from the prototype demonstrate a considerable voltage gain and a peak efficiency of more than 95%. In addition, the converter consistently performs competently over many different voltage sources and workload situations, demonstrating its durability for real-world solar applications. Consequently, solar microgrids would be far more effective and dependable with the help of the suggested high-gain boost converter, which would increase the consumption of clean energy sources in DGS. © 2024 IEEE.

关键词： Microgrids

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Machine learning in the analog circuit simulation loop 16

Machine learning in the analog circuit simulation loop

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2021 international conference on Synthesis, modeling, Analysis and simulation Methods and applications to Circuit Design, SMACD 2021 and 16th conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Tzenov, Petar Sokar, Ahmed Infineon Technologies AG Neubiberg Germany

ISBN: (纸本)9783800755899

This paper presents the software coupling of an analog circuit simulator (ACS) to a machine learning (ML) execution engine, in order to enable usage of ML models in circuit simulation context. This is achieved by interfacing Infineon’s in-house simulator, TITAN, with the widely accepted machine learning framework TensorFlow (TF), via an easy to use Verilog-A API. Here we introduce the basic characteristics of this interface and present an application example for its usage in analog circuit behavioral modeling. © VDE VERLAG GMBH.

关键词： Analog circuits

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modeling of Feature Selection Based on Random Forest Algorithm and Pearson Correlation Coefficient 4

Modeling of Feature Selection Based on Random Forest Algorit...

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2021 4th international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2021

作者： Mei, Kai Tan, Meifang Yang, Zhihui Shi, Shaoyue School of Automation Wuhan University of Technology Hubei province Wuhan China

This paper establishes a feature selection model to selects 20 molecular descriptors of compounds with the most significant influence on biological activity. Random forest algorithm was used to calculate the correlation between molecular descriptors and pIC50 values of biological activity. In this way, the top 26 molecular descriptors with high correlation were screened out. The Pearson correlation coefficient was used to analyze the 26 molecular descriptors just selected and eliminate the variables with high correlation between the independent variables. By consulting literature, the parameters such as MlogP, XlogP and TopoPSA in the selected molecular descriptors were found that had a prominent effect on the biological activity, indicating that the screening methods and results of the 20 molecular descriptors were reasonable. © Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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16th KES international conference on Agents and Multi-Agent Systems: technologies and applications, KES-AMSTA 2022

16th KES International Conference on Agents and Multi-Agent ...

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16th KES international conference on Agents and Multi-Agent Systems: technologies and applications, KES-AMSTA 2022

ISBN: (纸本)9789811933585

The proceedings contain 26 papers. The special focus in this conference is on Agents and Multi-Agent Systems: technologies and applications. The topics include: Impact of COVID-19 on Digital Business Models—Focus on Sustainability;an Investigation into Influences of Tweet Sentiments on Stock Market Movements;negotiation-Based Multi-agent System for Ambient Conditions Control in Accordance with Multiple User Preferences;preface;temporal Logic in Multi-agent Environment;altruistic Behavior Structural Holes and Team Performance;construction of a News Classification System Related to Information Security Incidents;system for Analyzing Innovation Activities in Mergers and Acquisitions by Measuring Technological Distance;how Can We Make the Best Use of Intellectual Capital? Building an Analysis System Through Agent-Based Models;a Customer Experience Mapping for Knowledge Extraction from Social simulation Results;Corporate Governance Considerations for Driving ESG Performance;using the Knowledge of Competent Salespeople: modeling Business Negotiation Topics to Obtain Customers’ Real Needs;Explainable AI for Autism Classification in Children;Voice Control System Through NLP (Natural Language Processing) as an Interactive Model for Scalable ERP Platforms in Industry 4.0;Use of Multi-agent System to Classify Control EEG Signals: A Preliminary Study;cost-Aware Dynamic Task Sharing Among Decentralized Autonomous Agents: Towards Dynamic Patient Sharing Among Hospitals;online Social Networks and Psychological Experiences: Analysis of Youth Perceptions Through Data Mining;implementation of an Intelligent Agent for Decision Making Tasks in the Hanoi Towers;a Systematic Review About Requirements Elicitation for Multi-Agent Systems;Implications of the Exact Time Use for the simulation of Business Processes’ Costs with the TDABC Approach;coping with Diverse Product Demand Through Agent-Led Type Transitions.

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Enhanced Camouflage Detection Using Advanced Image Processing Techniques for Real-Time Object Recognition and Pattern Differentiation 5

Enhanced Camouflage Detection Using Advanced Image Processin...

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5th international conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Manikandan, G. Deepa, R. Jayalakshmi, V. Thilakavathy, P. Surendran, R. St. Joseph's College of Engineering Anna University Department of Artificial Intelligence and Machine Learning Chennai India School of Computing SRM Institute of Science and Technology Department of Computing Technologies Chennai India SRM Institute of Science and Technology Department of Computer Science and Applications Chennai India Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Computer Science and Engineering Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

The identification of objects that blend in with their surroundings has long been a concern in fields including defence, wildlife monitoring, and surveillance due to the difficulty of detecting such objects. This finding is significant because it could greatly enhance our capacity to detect camouflaged objects, transforming the field of real-time object detection. Existing image processing methods often fail miserably when adequately capturing this aspect. This dissertation's primary focus is identifying devices with complicated patterns, legacy interference, and inadequate contrast;nonetheless, in disguised scenarios, all of these features cause identification to be unsuccessful. This research often suggests a new approach called the Linear Edge Detecting Scheme for Camouflaged Object Detection (LEDS-COD) in these difficult cases. The LEDS-COD system can enhance item visibility in low-comparison settings by highlighting critical edges and descriptions. Pattern differentiation methodologies and modern facility-side recognition techniques are combined to accomplish this goal. The approach successfully differentiated items because it zeroed in on texture and comparative details that would otherwise go unnoticed by humans or advanced algorithms. LEDS-COD is useful in many areas, including the Navy, autonomous surveillance systems, and animal protection, where the real-time identification of hidden devices is essential. Results from a simulation study using various datasets, including concealed objects, show that LEDS-COD surpasses conventional detection methods in recognition accuracy, processing speed, and perseverance. The recommended technique exceeded the requirements for obtaining improved object detection estimates for challenging conditions like those with complex backdrops and changing illumination. According to this study, LEDS-COD can be devastating in improving real-time camouflage detection. © 2024 IEEE.

关键词： Accuracy Image processing Surveillance Image edge detection Wildlife Lighting Object detection Real-time systems Object recognition Protection

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Weighted Particle-Based Optimization for Efficient Generalized Posterior Calibration

Weighted Particle-Based Optimization for Efficient Generaliz...

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Data Science and Its applications (ICoDSA), international conference on

作者： Masahiro Tanaka Faculty of Economics Fukuoka University Fukuoka Japan

ISBN: (数字)9798350365351

ISBN: (纸本)9798350365368

In the realm of statistical learning, the increasing volume of accessible data and increasing model complexity ne-cessitate robust methodologies. This paper explores two branches of robust Bayesian methods in response to this trend. The first is generalized Bayesian inference, which introduces a learning rate parameter to enhance robustness against model misspecifications. The second is Gibbs posterior inference, which formulates infer-ential problems using generic loss functions rather than proba-bilistic models. In such approaches, it is necessary to calibrate the spread of the posterior distribution by selecting a learning rate parameter. The study aims to enhance the generalized posterior calibration (GPC) algorithm proposed by [1]. Their algorithm chooses the learning rate to achieve the nominal frequentist coverage probability, but it is computationally intensive because it requires repeated posterior simulations for bootstrap samples. We propose a more efficient version of the GPC inspired by sequential Monte Carlo (SMC) samplers. A target distribution with a different learning rate is evaluated without posterior simulation as in the reweighting step in SMC sampling. Thus, the proposed algorithm can reach the desirable value within a few iterations. This improvement substantially reduces the computational cost of the GPC. Its efficacy is demonstrated through synthetic and real data applications.

关键词： Solid modeling Monte Carlo methods Computational modeling Statistical learning Big Data applications Inference algorithms Robustness

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RISC-V Processor technologies for Aerospace applications in the ISOLDE Project 23rd

RISC-V Processor Technologies for Aerospace Applications in ...

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23rd international conference on Embedded Computer Systems: Architectures, modeling, and simulation, SAMOS 2023

作者： Fornaciari, William Reghenzani, Federico Agosta, Giovanni Zoni, Davide Galimberti, Andrea Conti, Francesco Tortorella, Yvan Parisi, Emanuele Barchi, Francesco Bartolini, Andrea Acquaviva, Andrea Gregori, Daniele Cognetta, Salvatore Ciancarelli, Carlo Leboffe, Antonio Serri, Paolo Burrello, Alessio Pagliari, Daniele Jahier Urgese, Gianvito Martina, Maurizio Masera, Guido Di Carlo, Rosario Sciarappa, Antonio Politecnico di Milano Milan Italy University of Bologna Bologna Italy E4 Computer Engineering SpA Scandiano Italy Thales Alenia Space Italia S.p.A Turin Italy Politecnico di Torino Torino Italy Leonardo SpA Rome Italy

ISBN: (纸本)9783031460760

Modern space applications impose significant challenges to the design of hardware and software platforms. Beyond traditional applications such as avionics, Attitude Orbit Control, and signal/telemetry processing, new developments increasingly leverage Machine Learning models to enhance the autonomy of spacecraft. Such AI-based functional-ities promise significant advantages, but require computing power beyond what can be provided by current on-board platforms. At the same time, the challenge of technological sovereignty requires a move towards open hardware and software. To achieve these objectives, within the KDT ISOLDE project started in 2023, we propose the development of a new family of processors for AI-based applications to be deployed on board of satellites. In this paper, we showcase some examples of space applications with their requirements, and highlight the possible solutions as well as the corresponding work that will be carried out in ISOLDE, and the expected results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Space applications

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A New Perspective on Sensitivity for Biosensing applications in Nanocavity-Embedded Dual Metal Surrounding Gate TFETs

A New Perspective on Sensitivity for Biosensing Applications...

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Research methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), international conference on

作者： E. Rajalakshmi N.B. Balamurugan Department of ECE Thiagarajar College of Engineering Madurai Tamilnadu India

The dual metal surrounding gate tunnel FET (DMSG TFET) with nanocavity embedding is suggested in this work for biosensing applications. Surface potential, sensitivity, and threshold voltage are derived as the electrical parameters for biomolecules to use in the label-free detection. DMSG TFET is utilized because of its better electrostatic control that it possesses over the channel, which results in a lower threshold voltage for the device. The device's embedded nanocavity is exposed to the biomolecules, altering the threshold voltage. The observed disparity in the threshold voltage can be attributed to the device's level of sensitivity. The proposed technology employs a parabolic approximation technique to analytically resolve the 2-dimensional Poisson equation. For the proposed device, the outcomes of both the graphical simulation and the analytical modeling exhibit congruence. Additionally, the Single Metal Surrounding Gate Tunnel FET (SMSG TFET) is contrasted with the DMSG TFET in terms of sensitivity, and the graphical simulations of the parameters are examined and confirmed using the TCAD software tool.

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Framework to Drone Part Selection, Verification and Fabrication of UAV for Multiple applications

Framework to Drone Part Selection, Verification and Fabricat...

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modeling, simulation & Intelligent Computing (MoSICom), international conference on

作者： Nanda Kumar BVN Anita Agrawal BITS Pilani K K Birla Goa Campus Goa India

Drone technologies have become an essential tool in multiple industries and are a hotspot for researchers to explore the plethora of its applications. Unmanned Aerial Vehicles (UAVs) have revolutionised the technology in farming, defence, photography, industry, payload delivery and disaster management. Their ability to have onboard computing power and a multitude of sensors is incredibly beneficial. However, choosing the parts to build a custom-made drone to cater to the specific requirements of the task is a tedious process and requires much research. This paper intends to serve as a guide to choosing the layout configuration, electronic and hardware components. It discusses all the technicalities and calculations required to choose parts, making the daunting process of parts selection straightforward and methodical. It is novice-friendly and begins with a discussion of the types of drones and their constraints; rigorous calculations are explained to cater to the application’s specific requirements. The paper will serve as a one-stop guide for students, researchers and entrepreneurs to build their own drones.

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Immersive Tech Solutions to Overcome Speaking Anxiety

Immersive Tech Solutions to Overcome Speaking Anxiety

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international conference on Signal Processing, Communication, Power and Embedded System (SCOPES)

作者： Prajna Pani Anubha Ray School of Mangement Centurion University of Technology and Management Odisha India Birla Global University Odisha India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

This paper explores the use of immersive technologies, namely Augmented Reality (AR) and Virtual Reality (VR), to mitigate speaking anxiety and enhance communication skills. Speaking anxiety is a prevalent issue that hinders effective communication in personal and professional environments. The research aims to (1) assess the effectiveness of AR and VR in reducing speaking anxiety and (2) propose an immersive tech model for improving confidence and speaking abilities. The study involved hundred participants from a multi-sector state private university in Odisha, India who completed VR-based speech simulations and were evaluated on six parameters: speech duration, eye contact, filler words, speaking pace, volume and listen ability. Survey and workshop methodologies were used in the study. The findings showed significant improvement in confidence and reductions in anxiety and filler word usage. Moderate improvements in eye contact and gestures suggested room for further development. The study proposes an immersive tech model integrating VR for real-time feedback and AR for audience simulation, offering promising applications in speaking training, language acquisition and professional skill enhancement.

关键词： Training Surveys Solid modeling Embedded systems conferences Anxiety disorders Signal processing Speech Real-time systems Augmented reality

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