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3rd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2023

作者： Dadi, Pradeep Surya Saranya, G. Tamilvizhi, T. Nelson, Leema Surendran, R. Chennai Institute of Technology Department of Mechatronics Engineering Chennai India Amrita Vishwa Vidyaapeetham Chennai Campus Amrita School of Computing Department of Computer Science and Engineering Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India Chitkara University Institute of Engineering and Technology Chitkara University Department of Computer Science and Engineering Punjab India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665462167

Visual simultaneous localization and mapping (SLAM), which has numerous potential uses, is swiftly emerging as a significant development in embedded vision. In our analysis, there remain several unsolved dilemmas about SLAM that are visual, making it less favored over Lidar SLAM. Because it offers an affordable solution for mapping and navigation in mobile robots. These mobile robots can be defined as robots whose unique base is not fixed, so as technology establishes and advances, we. In this report, a real-time light, that is, dim or image or video in low light problem enhancement algorithm is proposed that significantly improves the overall performance of the Canny Edge part detection algorithm, which usually may be useful for benefit recognition in low light issues in cellular robots for several mapping and navigation tasks. © 2023 IEEE.

关键词： Mobile robots

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COVID-19 Detection and Localization: A Novel Fused Attention Mechanism Network Based on YOLO V5 5

COVID-19 Detection and Localization: A Novel Fused Attention...

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5th International Conference on Electronic engineering and Informatics, ICEEI 2023

作者： Yang, Wenyi Wang, Ruihu Zhang, Jianxun Liu, Chang Zeng, Li Shen, Xiaoyu Chongqing University of Technology College of Computer Science and Engineering Chongqing China Chongqing University of Arts and Sciences School of Tourism & Event Management Chongqing China Chongqing Vocational and Technical University of Mechatronics Information Engineering Institute Chongqing China Industrial and Commercial Bank of China Shapingba Sub-branch Chongqing China

ISBN: (纸本)9781643685021

COVID-19 is a very contagious viral disease that has shown characteristics of being insidious and spreading rapidly since its emergence at the end of 2019, leading to many suspected cases and increased difficulty in protection. However, COVID-19 has become a huge clinical challenge in terms of rapid identification and precise treatment due to the similarity between its pathogen and the common pneumonia virus. In order to help physicians to diagnose patients quickly and accurately, we proposed a powerful target detection virus model. This innovative model based on the deep network of the YOLO V5 model structure, is used to detect lesion areas of COVID-19, combined with attention mechanism thinking. Meanwhile, to improve the category imbalance problem in the data, we proposed an innovative loss function based on Focal Loss. This approach helps our network to be more focused on the learning of complex cases and effectively improves the model accuracy. Finally, we compared it with other experiments. The proposed improved YOLO V5 model detected novel coronavirus infections with an mAP of 62.23%. Obviously, the effective YOLO V5 we propose has better results and judgment ability compared to existing models and can be effectively used as an aid to detect novel coronavirus infections. © 2024 The Authors.

关键词： COVID-19

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Automatic robotic system design and development for vertical hydroponic farming using IoT and big data analysis

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Materials Today: Proceedings 2023年 80卷 3546-3553页

作者： Shrivastava, Anurag Nayak, Chinmaya Kumar Dilip, R. Samal, Soumya Ranjan Rout, Sandeep Ashfaque, Shaikh Mohd ECE Lakshmi Narain College of Technology and Science Indore India Faculty of Emerging Technology Sri Sri University Odisha India Dept. of Mechatronics Eng. Acharya Institute of Technology India Faculty of Telecommunications Technical University of Sofia Sofia Bulgaria Faculty of Agriculture Sri Sri University Cuttack India Department of Computer Engineering Rizvi College of Engineering India

In this digital world, all the developing countries' growth has improved drastically with farmers' influence and innovative farming processes. Generally, the farming process includes ancient traditional methodologies for maintaining the crops' quality and yields. Their farming was developed and has given more profit only with the quality of the soil and the nutrition used on land. But the drawback is they were spending much time to get their yields from their land, and the nutrition level was not maintained at all times. Moreover, more space was used for farming, with huge manpower required to maintain the entire land. Most countries are moved to smart farming concepts with IoT platforms to optimize the time and techniques. In that hydroponic, the best innovative idea to produce more crops, vegetables, and fruits without soil. Rockwool is used for farming processes with water contaminants at regular intervals will provide huge productions as well as no need to wait for a long time for cultivation. This method was implemented in most of the countries that were doing smart farming with less manpower and low cost. The hydroponic farming methodology is implemented with IoT sensors for monitoring crop's status and health continuously. Once their nutrition level or water level has decreased, it will provide all at constant time intervals to the entire system effectively. A few years ago, hydroponic farming was horizontally implemented on smaller spaces for the regular water flow. But now a day it is implemented on a vertical surface to reduce the space, and water flow is only at the time of need. This technology is used to increase the productivity of the crops with a small space of land and less manpower. Perhaps the cost of the entire system has been taken into consideration by small-scale unit farmers;vertical hydro farming provides better results when compared with previous classical methods. This research paper has given the design and implementation of automated ver

关键词： Hydroponics

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Optimizing Droplet Coalescence Dynamics in Microchannels: A Comprehensive Study Using Response Surface Methodology and Machine Learning Algorithms

SSRN

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SSRN 2024年

作者： Javadpour, Seyed Morteza Kadivar, Erfan Zarneh, Zienab Heidary Kadivar, Ebrahim Gheibi, Mohammad Department of Mechanical Engineering University of Gonabad Gonabad Iran Department of Physics Shiraz University of Technology Shiraz71555-313 Iran Institute of Ship Technology Ocean Engineering and Transport Systems University of Duisburg-Essen Duisburg47057 Germany Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Liberec46117 Czech Republic Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Liberec Czech Republic

Droplet coalescence in microchannels is a complex phenomenon influenced by various parameters such as droplet size, velocity, liquid surface tension, and droplet-droplet spacing. In this study, we thoroughly investigate the impact of these control parameters on droplet coalescence dynamics within a sudden expansion microchannel using two distinct numerical methods. Initially, we employ the boundary element method to solve the Brinkman integral equation, providing detailed insights into the underlying physics of droplet coalescence. Furthermore, we integrate Response Surface Methodology (RSM) to effectively optimize droplet coalescence dynamics, harnessing the power of machine learning algorithms. Our results showcase the efficacy of these computational techniques in enhancing experimental efficiency. Through rigorous evaluation utilizing Regression Coefficient and Mean Absolute Error metrics, we ascertain the accuracy of our estimations. Our findings highlight the significant influence of key parameters, specifically droplet diameter (D), viscosity (Vis), and width (W), as identified by droplet-droplet spacing (DD), velocity of the first droplet (VFD), and velocity of the second droplet (VBD), respectively. This comprehensive approach provides valuable insights into droplet coalescence phenomena and offers a robust framework for optimizing microfluidic systems. © 2024, The Authors. All rights reserved.

关键词： Coalescence

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Development of Mutal Recognition of Education Approach in Advanced computer-Oriented engineering Technologies in the Baltic Region 64

Development of Mutal Recognition of Education Approach in Ad...

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64th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga technical university, RTUCON 2023

作者： Kunicina, Nadezhda Rassolkin, Anton Bruzgiene, Rasa Plonis, Darius Caiko, Jelena Riga Technical University Institute of Electrical Engineering and Electronics Feee Riga Latvia Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Kaunas University of Technology Faculty of Informatics Department of Computer Sciences Kaunas Lithuania Vilnius Gediminas Technical University Department of Electronic Systems Vilnius Lithuania

ISBN: (纸本)9798350317732

The continued improvement and development of study programmes content for mutual recognition of study programmes among the largest technical universities in the Baltic region provides a very good opportunity for regional development as it brings a good advancement in academics and research at the involved universities, allows for more flexible and reliable collaboration with industrial partners, and provides an opportunity to develop new technologies and implement them for regional support. The goal of the development is to promote the involvement of students in the design of adaptive systems by providing them with the necessary set of skills that will allow them to immediately engage in the design of innovative adaptive systems and successfully solve technological challenges that have been identified through the cooperation of educational and research institutions. The adoption of an innovative educational strategy will aid in the creation of new technology and creative solutions even before students begin their studies. Collaboration between academic personnel and industry will help students build their abilities. © 2023 IEEE.

关键词： Students

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Dynamic Independent Component Extraction with Blending Mixing Vector: Lower Bound on Mean Interference-to-Signal Ratio

Dynamic Independent Component Extraction with Blending Mixin...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jaroslav Čmejla Zbyněk Koldovský Václav Kautský Tülay Adali Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Czech Republic Department of Electrical and Computer Engineering University of Maryland Baltimore MD USA

This paper deals with dynamic Blind Source Extraction (BSE) from where the mixing parameters characterizing the position of a source of interest (SOI) are allowed to vary over time. We present a new source extraction model called CvxCSV which is a parameter-reduced modification of the recent Constant Separation Vector (CSV) mixing model. In CvxCSV, the mixing vector evolves as a convex combination of its initial and final values. We derive a lower bound on the achievable mean interference-to-signal ratio (ISR) based on the Cramér-Rao theory. The bound reveals advantageous properties of CvxCSV compared with CSV and compared with a sequential BSE based on independent component extraction (ICE). In particular, the achievable ISR by CvxCSV is lower than that by the previous approaches. Moreover, the model requires significantly weaker conditions for identifiability, even when the SOI is Gaussian.

关键词： Analytical models Signal processing algorithms Signal processing Data models Acoustics Speech processing

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Soft kind of Computing Based Least Resource Data finding which is Used for Analysis purpose 4

Soft kind of Computing Based Least Resource Data finding whi...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Rani, L. Pattathu Surendran, S. Monica, D. Kumar, V. Senthil Rajaram, Gnanajeyaraman Dwibedi, Rajat Kumar Simats University Saveetha School of Engineering Chennai India Tagore Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Chennai Institute of Technology Department of Mechatronics Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats Saveetha School of Engineering Department of Computer Science and Engineering India Aarupadai Veedu Institute of Technology Department of Ece Tamil Nadu Chennai India

ISBN: (纸本)9798350360165

Deep learning (DL) approaches are utilized across three distinct contexts to showcase their applicability in commercial environments with restricted data for training. This study showcases the application of unsupervised DL with autoencoders that vary & illustrates how federation learning serves as a successful collaboration approach for machine learning (ML) that safeguards confidentiality of data. © 2024 IEEE.

关键词： Federated learning

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IoT-Aided Intelligent Irrigation System Using Edge Computing 2

IoT-Aided Intelligent Irrigation System Using Edge Computing

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2nd International Conference on Multidisciplinary engineering and Applied Science, ICMEAS 2023

作者： Ayoade, Idowu Adetona Nwakanma, Cosmas Ifeanyi Alimi, Sheriff Akinde, Olusola Kunle Adebisi, Oluwadare Oladeji, Dolapo Michael Ajayi, Dolapo Boluwatife Kayode, Michael Ife First Technical University Department of Mechatronics Engineering Ibadan Nigeria Kumoh National Institute of Technology ICT Convergence Research Center Gumi Korea Republic of Babcock University Ilishan Department of Computer Science and Artificial Intelligence Remo Nigeria First Technical University Department of Electrical and Electronics Engineering Ibadan Nigeria

ISBN: (纸本)9798350358834

Farmers in developing nations are faced with limited technology for smart and economical ways of irrigation. This is worsened by the high cost of imports since most of these nations are import-dependent. Increasing agricultural yield to meet the growing population in most of these nations has led their governments to pursue cost-effective ways of managing water and other resources required for optimum agricultural yield. In this study, the Internet of Things (IoT) and edge computing are proposed to provide an intelligent irrigation system to bridge the irrigation gap. This research was carried out using a greenhouse with a controlled environment i.e., the ambient temperature, air humidity, ultraviolet radiations (UV), soil temperature, and soil moisture content were all monitored and measured in real-Time within the controlled environment. These data were collected using field sensors processed using IoT-enabled microcontrollers (Arduino kits). The data were processed via Amazon Web Services (A WS) for ontological capabilities of the system consisting of computational capabilities of IoT server and Edge Server. Internet-enabled mobile devices were used to monitor and adopt preferential yield rates for cultivation. Also, an irrigation sequencing algorithm was developed, which uses predictive machine learning K-Mean Clustering Algorithm to predict a more accurate soil moisture content with minimum standard error and a lower mean square error of 0.11 to the predicted soil content compared to when only SVR with mean square error of 0.12. © 2023 IEEE.

关键词： Internet of things

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Statistical correlations of random polarization and electric depolarization fields in ferroelectrics

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Physical Review B 2023年第13期108卷 134101-134101页

作者： Yuri A. Genenko Olga Y. Mazur Leonid I. Stefanovich Institute of Materials Science Technical University of Darmstadt Otto-Berndt-Str 3 64287 Darmstadt Germany Institute of Mechatronics and Computer Engineering Technical University of Liberec Studentska 1402/2 46117 Liberec Czech Republic Branch for Physics of Mining Processes M.S. Poliakov Institute of Geotechnical Mechanics National Academy of Sciences of Ukraine Simferopolska st. 2a 49600 Dnipro Ukraine

A conceptual problem of the electric-field-mediated polarization correlations during a stochastic formation of polarization domain structure in ferroelectrics is addressed by using an exactly solvable stochastic model of polarization development in a uniaxial ferroelectric [Phys. Rev. B 107, 144109 (2023)]. A full set of time-dependent two-point correlation coefficients between all random variables is derived analytically, evaluated numerically, and presented graphically in three dimensions. They are particularly required for the analysis of nonlinear phenomena involving spatial dispersion like optical second harmonic generation and scattering.

关键词： Domains Ferroelectricity Stochastic processes

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Pyramidal charged domain walls in ferroelectric BiFeO3

arXiv

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arXiv 2025年

作者： Marton, Pavel Paściak, Marek Gonçalves, Mauro Novák, Ondřej Hlinka, Jiří Beanland, Richard Alexe, Marin Institute of Mechatronics and Computer Engineering Technical University of Liberec Studentská 2 Liberec46117 Czech Republic Department of Dielectrics Institute of Physics The Czech Academy of Sciences Na Slovance 2 Praha182 00 Czech Republic Department of Physics University of Warwick CoventryCV4 7AL United Kingdom

Domain structures play a crucial role in the electric, mechanical and other properties of ferroelectric materials. In this study, we uncover the physical origins of the enigmatic zigzag domain structure in the prototypical multiferroic material BiFeO3. Using phase-field simulations within the Landau-Ginzburg-Devonshire framework, we demonstrate that spatially-homogeneous defect charges result in domain structures that closely resemble those observed experimentally. The acquired understanding of the underlying physics of pyramidal-domain formation may enable the engineering of new materials with self-assembled domain structures exhibiting defined domain periodicity at the nanometre scale, opening avenues for advanced applications. © 2025, CC BY.

关键词： Ferroelectricity

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