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8th IEEE International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2023

作者： Abdulwahid, Ali Hadi Pattnaik, Manjula Palav, Manesh R. Tilak Babu, S.B.G. Manoharan, Geetha Pandi Selvi, G. Southern Technical University Engineering Technical College Control and Automation Engineering Department Basra Iraq Princess Nourah Bint Abdulrahman University College of Business Administration P.O.BOX:84428 Riyadh Saudi Arabia Dr.D.Y.Patil Vidyapeeth Pimpri Global Business School & Research Centre Mba Department Maharashtra Pune411018 India Aditya Engineering College Dept of Ece Surampalem India Sr University School of Business Telangana Warangal India Dhanalakshmi Srinivasan College of Engineering Dean Mba Coimbatore India

ISBN: (纸本)9798350347791

Artificial intelligence, which has resuscitated shrewd libraries, is one of the principal powers driving the improvement of present day civilisation. This exposition makes sense of the hidden association between artificial intelligence (simulated intelligence) and savvy libraries, examinations how computer based intelligence is utilized with regards to brilliant libraries, and gives instances of how computer based intelligence further develops library administrations. Artificial intelligence is an expansive, complex area of exploration that may be hard for nonexperts to comprehend. However, its definitive goal is to make PC systems with artificial intelligence, which clearly has significant ramifications for librarianship. In the event that we are to propel the investigation of canny systems, we should have an exhaustive comprehension of simulated intelligence advances. Through the ongoing utilization of computer based intelligence advancements, countless model shrewd library systems for classifying, ordering, data recovery, reference, and different purposes have been grown;notwithstanding, just few these systems have formed into items or systems that are utilized in the standard activities of libraries. © 2023 IEEE.

关键词： Libraries

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Hardware Implementation of a Sliding Detection Algorithm for Robotic Hands Using Force Sensors

Hardware Implementation of a Sliding Detection Algorithm for...

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Symposium on Integrated Circuits and Systems Design (SBCCI)

作者： Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Systems Graduate Program Automation and Control Group/GRACO Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field Programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.

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Optimizing Maximum Profit for Electric Vehicle Users in a Bipolar DC Distribution Grid with Probabilistic EV Load Demand and V2G Integration

Optimizing Maximum Profit for Electric Vehicle Users in a Bi...

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International Electrical engineering Congress (iEECON)

作者： Guntinan Sakulphaisan Sirirat Son-in Nitikorn Junhuathon Industrial technology and innovation management Faculty of science and technology Pathumwan institute of technology Bangkok Thailand Electrical Engineering and Automation Control Systems Faculty of engineering and industrial technology Bansomdejchaopraya Rajabhat University Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathumthani Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

This article delves into the synergistic potential of integrating Bipolar DC distribution grids, Probabilistic EV load demand forecasting, and Vehicle-to-Grid (V2G) technology. It offers a blueprint for electric vehicle (EV) users to smartly improve their financial results. Through the amalgamation of these components, individuals who possess electric vehicles have the potential to mitigate their energy expenditures while concurrently generating additional income. The study reveals that the integration of EV into the distribution system can lead to a substantial increase in daily energy loss, reaching up to 25.91%. However, when V2G technology is employed within the distribution grid, it has the remarkable capability to mitigate this increase in daily energy loss significantly, achieving a reduction of up to 64.12%.

关键词： Electrical engineering Vehicle-to-grid Energy loss Electric potential Demand forecasting Probabilistic logic Resilience

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Semi-Supervised Process Data Regression and Application Based on Latent Factor Analysis Model

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IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1-1页

作者： Zheng, Junhua Liu, Yangxuan Liu, Yi Hou, Beiping Yao, Yuan Zhou, Le Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

This article investigates the problem of modeling regression with labeled and unlabeled data samples commonly found in industrial processes. By incorporating additional information on unlabeled data samples, a new semi-supervised latent factor analysis model is developed. Compared with the purely supervised regression models which can only use the information of labeled dataset, the semi-supervised model can efficiently extract useful information for improvement of the regression performance. Furthermore, the proposed basic semi-supervised model has been extended to a mixture form, which is capable of describing data from more complex processes. For predictive modeling for key/mass variables, two soft sensors are constructed based on the semi-supervised models. Then, three case studies are used to evaluate the performance of the proposed soft sensing methods. © 2023 IEEE.

关键词： Regression analysis

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Senkerik, Roman Byrski, Aleksander Guzowski, Hubert Janku, Peter Kadavy, Tomas Oplatkova, Zuzana Kominkova Matusu, Radek Pluhacek, Michal Pekar, Libor Smolka, MacIej Viktorin, Adam Tomas Bata University A.I. Lab Faculty of Applied Informatics Department of Informatics and Artificial Intelligence Zlin Czech Republic Tomas Bata University Faculty of Applied Informatics Department of Automation and Control Engineering Zlin Czech Republic Institute of Computer Science Agh University of Science and Technology Krakow Poland

ISBN: (纸本)9798350337020

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics. © 2023 IEEE.

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MMC Based D-STATCOM control by Using a Modified ADRC Strategy

MMC Based D-STATCOM Control by Using a Modified ADRC Strateg...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： João A. Moor Neto Alessando R. Zachi Braulio Chuco Paucar Thiago Americano Do Brasil Samir Ahmad Mussa Department of Electrical Engineering CEFET-RJ Rio de Janeiro Brazil Department of Control System and Automation Engineering CEFET-RJ Rio de Janeiro Brazil Dept. of Electrical and Electronic Engineering UFSC - SC Florianopolis Brazil

This paper presents investigations of a transformerless half bridge sub-module (HBSM) modular multilevel converter based distribution static synchronous compensator (MMC D-STATCOM) performance in reactive power compensation considering the application of the modified ADRC controllers in the inner current loop and in the outer DC voltage loop using Synchronous Reference Frame control. Simulation results with the imposition of severe variations in reactive loads were obtained on a 5 km medium voltage feeder and will demonstrate that the modified ADRC controller enables superior performance for flexible operation with fast and efficient response of the MMC D-STATCOM in reactive power compensation.

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Comparison Performance on SOTA Deep Learning Models for Coffee Beans Grading Inspection

Comparison Performance on SOTA Deep Learning Models for Coff...

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Asian control Conference

作者： Achmad Norman Firdaus Amalia Rakhmawati Vebi Nadhira Suprijanto Endang Juliastuti Gema Nuran Utomo Ayu Gareta Risangtuni Master Program on Instrumentation and Control Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia Graduate Program on Engineering Physics Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia Instrumentation Control and Automation Research Group Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Several coffee producers rely on manual inspection for quality control, which is prone to inconsistencies and time consumption. Recent studies have proposed Comparison performance on State-of-The-Art (SOTA). Deep learning models were investigated as part of the proposed intelligent computer vision for faster and more reliable coffee bean grading. Performance Deep learning models, i.e., MobileNetV3Small, ResNet50, EfficientNetV2L, and DenseNet201, were evaluated to grade the quality of coffee beans that followed a grading procedure based on Indonesian National Standard (SNI) 01-2907-2008. A specific tray was designed to position coffee beans evenly without overlap for sample preparation, which consist of about 500–600 coffee beans. The process of capturing images is conducted systematically, focusing on each type of coffee bean defect individually. For comparison of SOTA models, five classes of coffee bean defects, With 1053 beans per class, the total dataset comprises 5265 beans. This dataset was divided into 10% for testing and 90% for training. Within the training data, 12% was reserved for validation. The result from this paper shows that MobileNetV3Small achieves the highest accuracy (99.43%) with minimal memory and parameters. Its efficient design allows for robust feature extraction, crucial for distinguishing subtle defect features. While larger models like ResNet50 and EfficientNetV2L also perform well, they exhibit higher memory and parameters.

关键词： Deep learning Training Accuracy Computational modeling Training data Inspection Feature extraction

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SpaGRA:Graph augmentation facilitates domain identification for spatially resolved transcriptomics

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Journal of Genetics and Genomics 2025年第1期52卷 93-104页

作者： Xue Sun Wei Zhang Wenrui Li Na Yu Daoliang Zhang Qi Zou Qiongye Dong Xianglin Zhang Zhiping Liu Zhiyuan Yuan Rui Gao Center of Intelligent Medicine School of Control Science and EngineeringShandong UniversityJinanShandong 250061China MOE Key Lab of Bioinformatics and Bioinformatics Division of BNRIST Department of AutomationTsinghua UniversityBeijing 100084China Institute of Precision Medicine Peking University Shenzhen HospitalShenzhenGuangdong 518036China Department of Clinical Laboratory The Second HospitalCheeloo College of MedicineShandong UniversityJinanShandong 250033China Institute of Science and Technology for Brain-Inspired Intelligence Center for Medical Research and InnovationShanghai Pudong HospitalFudan University Pudong Medical CenterFudan UniversityShanghai 200433China

Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various ***-based geometric deep learning has gained widespread adoption for spatial domain identification ***,most methods define adjacency relation between cells or spots by their spatial distance in SRT data,which overlooks key biological interactions like gene expression similarities,and leads to inaccuracies in spatial domain *** tackle this challenge,we propose a novel method,SpaGRA(https://***/sunxue-yy/SpaGRA),for automatic multi-relationship construction based on graph *** uses spatial distance as prior knowledge and dynamically adjusts edge weights with multi-head graph attention networks(GATs).This helps SpaGRA to uncover diverse node relationships and enhance message passing in geometric contrastive ***,SpaGRA uses these multi-view relationships to construct negative samples,addressing sampling bias posed by random *** results show that SpaGRA presents superior domain identification performance on multiple datasets generated from different *** SpaGRA,we analyze the functional regions in the mouse hypothalamus,identify key genes related to heart development in mouse embryos,and observe cancer-associated fibroblasts enveloping cancer cells in the latest Visium HD ***,SpaGRA can effectively characterize spatial structures across diverse SRT datasets.

关键词： Spatial domain identification Spatially resolved transcriptomics Multi-head graph attention networks Graph augmentation Geometric contrastive learning

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Physics-guided graph learning soft sensor for chemical processes

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Chemometrics and Intelligent Laboratory Systems 2024年 249卷

作者： Liu, Yi Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Chemical Engineering National Tsing Hua University Hsinchu300044 Taiwan

The surge in data-driven soft sensors for industrial processes is evident. However, most of them suffer from the limitation of being black-box models and this will hamper their widespread use. In response to this challenge, this study proposes a physics-guided graph-learning soft sensor that integrates a physical understanding of industrial processes by incorporating graph-based concepts with process physics. The soft sensor first constructs physical information based on causal relationships between variables using the conditional Granger causality test. Subsequently, it autonomously learns the unique sample information of each observation while employing a regularization loss to ensure the sparsity of the learned information. The model employs a two-stream structure for spatiotemporal encoding of both the physical and sample information. The modeling and prediction results on a penicillin fermentation process indicate that, using the proposed method, the knowledge gained from the data aligns with existing prior knowledge. This approach shows promise in filling the gap between data-driven and physics-based modeling in chemical processes. © 2024 Elsevier B.V.

关键词： Graphic methods

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A High Transparent Microfluidic Polymerase Chain Reaction(PCR) Chip Integrated with Localized Precise Temperature control System

A High Transparent Microfluidic Polymerase Chain Reaction(PC...

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2020年IEEE全球流体动力学会博士生论坛

作者： Tianhang Yang Hai Fu Yan Jiang Dayong Gao Songjing Li Department of Fluid Control and Automation Harbin Institute of Technology Department of Mechanical Engineering University of Washington

PCR(Polymerase chain reaction) is an approach widely used in bioengineering and disease-detection by making thousands and millions copies of a specific DNA(Deoxyribonucleic acid) segment in *** miniaturization and integration of PCR device could greatly reduce contamination and increase the efficiency of time,energy and materials consuming especially for many on-site working conditions outside a professional *** researches were done previously to achieve the main PCR procedures,usually including denaturing,annealing and extending,on an integrated microfluidic ***,there are much fewer studies focusing on efficient on-chip local cooling as well as temperature *** inadequacy usually leads to bulk cooling attachments and/or an opaque microfluidic *** this paper,we proposed and fabricated a multilayer transparent microfluidic chip with on-chip heating,cooling and temperature measurement *** transparency will help achieve observation of fluid flow and later help develop real-time fluorescence *** chip could be applied to both time and spatial stable *** chip was consisted by an ITO(Indium tin oxide) coated glass temperature control layer,a PDMS(Polydimethylsiloxane) fluid layer and a PDMS cooling and flow control *** performance of the on-chip microheater was tested and the on-chip micro temperature sensor was *** system is also compatible with other nucleic acid processing related microfluidic chip such as extraction and isolation.

关键词： microfluidics PCR ITO glass on-chip temperature control lithography etching microsensor

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