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1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Kawalpreet Jain, Mohit Kumar Chandigarh Engineering College Department of Computer Science & Engineering Jhanjeri India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9781665456876

Radio engineering programs are useful for radio amateurs. And this is not surprising. This program is required for simulation and modeling of radio engineering structures. These books contain very interesting ideas useful devices, the hall sensor gives every radio amateur the opportunity to choose what he needs from a variety of solutions and designs, tried and tested in practice. In this paper, an intuitive user interface model for circuit prototyping to create powerful battery in the form of transient diagrams. A nice simple simulator of electronic circuits. It is very easy to draw radio circuits on it - interface. Well organized. Specify the stop time calculation time, for example 25 m. In simulation mode, a half-screen map opens. When you click the cursor on the required wire in the circuit element, the diagram will show the possible change in this point. They provide schematics and results obtained during simulation while running the circuit. © 2022 IEEE.

关键词： Timing circuits

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Enhancing Non-Destructive Examining of Composite materials Using Lightweight Structures And Machine Learning

Enhancing Non-Destructive Examining of Composite Materials U...

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2023 International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2023

作者： Gangwar, Prashant Kumar Pattanaik, Balachandra Madiajagan, M. Sohail, Mohammed Ali Babu, M. Dinesh Sarala, B. Woldia University Department of Construction Technology & Management Amhara Region Ethiopia Wollega University College of Engineering and Technology Department of Electrical and Computer Engineering Nekemte Ethiopia Vellore Institute of Technology School of Computer Science and Engineering Tamil Nadu Vellore India Jazan University College of Computer Science & Information Technology Department of Computer & Network Engineering Jazan Saudi Arabia Rajalakshmi Institute of Technology Department of Mechanical Engineering Chembarabakkam Chennai India R.M.K Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350344387

Composite materials and structures are becoming more efficient and cost-effective, and new special features are being developed to improve their specific properties. Their use in a variety of applications such as wind turbines, aeronautical, medical equipment, transportation, and other load-bearing structures is becoming increasingly important. It is necessary for non-destructive composite examining to be robust and trustworthy in order to limit the risk of damage as well as the cost of maintenance. In order to ensure the product quality throughout its life cycle, many non-destructive examining procedures based on a wide range of concepts have been created. In this paper, nondestructive examining was used to obtain vibration measurements of composites in high-frequency regimes, which were then analysed. Both end-to-end classifications of the data and classifications of data acquired by feature engineering with modal analysis employ Support Vector Machine (SVM) to carry out damage localization in their respective applications. Finally, the findings display a large number of plates made of various materials and with defects of varying magnitudes. © 2023 IEEE.

关键词： Composite Localization Machine Learning Nondestructive Examining

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Strain-regulated flexible molecular sensors enabled by 2D PtTe2

Strain-regulated flexible molecular sensors enabled by 2D Pt...

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2022 IEEE International Conference on Integrated Circuits, Technologies and Applications, ICTA 2022

作者： Wang, Zhehan Kang, Dingxuan Chen, Jiayi Xu, Xiao Jing, Xu Tao, Li School of Materials Science and Engineering Southeast University China Center of 2D Materials Southeast University China The University of Texas at Austin Department of Electrical and Computer Engineering United States

ISBN: (数字)9781665492690

ISBN: (纸本)9781665492690

Two-dimensional transition metal dichalcogenide (TMDs) holds great promise for future wearable technologies. The large-scale synthesis of TMDs and the investigation of their molecular sensing properties are current research hotspots. Herein, we construct flexible PtTe2 molecular sensors directly on polyimide, followed by the exploration on ammonia sensing properties and stability under strain. The sensor shows an excellent ammonia response of 0.4% ppm-1surpassing most reported semimetal-based sensors. In-situ sensing testing reveals 500% enhancement in response after controlled strain engineering, which suggests the potential to expand limit of detection and linearity range. © 2022 IEEE.

关键词： Ammonia

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Impact of Different Noise Distributions in the Application of Kalman Filter in Sensor Fusion 5

Impact of Different Noise Distributions in the Application o...

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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Čvek, Kristijan Mostarac, Marija Miličević, Kruno Department of Power Engineering Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

This paper explains the concept of the Kalman filter as an estimator of the system state based on measurements in the presence of noise. Sensor fusion allows for the measurement of factors that are not immediately measurable as well as the creation of more accurate data. The theoretical underpinning for the definition of a filter and Kalman-based sensor fusion, and filter and sensor fusion algorithms are explained and implemented in simulation. The application of the filter for sensor fusion is presented, and in the end, simulation results are obtained for different types of noise distribution – normal as the usual one for physical quantities and uniform as dominant in digitized values. © 2022 IEEE.

关键词： Extended Kalman filters

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Colored Structured Light Based on Nanoscale 3D Printing

Colored Structured Light Based on Nanoscale 3D Printing

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2023 Flat Optics: Components to Systems, FLatOptics 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Wang, Hongtao Wang, Hao Yang, Joel K.W. Engineering Product Development Singapore University of Technology and Design Singapore487372 Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Institute of Materials Research and Engineering Singapore138634 Singapore

Through nanoscale two-photon polymerization (TPP) 3D printing, structured optical beams can be extended to colored structured light under incoherent white light illumination, promising higher-dimensional structured li... 详细信息

ISBN: (纸本)9781957171289

关键词： 3D printing

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Electric Vehicle Management and Tracking using AI and IoT

Electric Vehicle Management and Tracking using AI and IoT

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart electrical Systems, ICSES 2023

作者： Packialatha, A. Vadlamudi, Bindu Sai Thrinath, B.V. Sundar Ganesh, C.S. Ishrat, Mohammad Bhaskar, Archana Vels Institute of Science Technology & Advanced Studies Department of Computer Science and Engineering Tamil Nadu Chennai600117 India Velagapudi Ramakrishna Siddhartha Engineering College Department of Electrical and Electronics Engineering Andhra Pradesh Vijayawada520007 India Mohan Babu University School of Engineering Department of Electrical and Electronics Engineering Andhra Pradesh Tirupati517102 India Karpagam College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore641032 India KoneruLakshmaiah Education Foundation Vaddeswaram Department of Computer Science and Engineering Andhra Pradesh Guntur522502 India REVA University School of CSA Karnataka Bengaluru560064 India

ISBN: (纸本)9798350319200

Technology has come a long way, and now many problems can be solved with the help of new developments in the field. With this technology, we can finally put an end to the suffocating effects of air pollution. Air pollution is on the rise due to the widespread use of automobiles powered by internal combustion engines. By replacing internal combustion engines with electric motors, we can end our reliance on polluting fossil fuels and ensure future generations have access to clean air. Electric vehicles are similar to machines in that they are powered by a rechargeable battery. To what extent an EV functions depends on its battery. Voltage, current, and temperature are the indicators of battery health. These factors are used to calculate the state of charge (SOC). These results are tracked by a BMS (Battery Management System). This article details how to create an EV monitoring system that makes use of AI and IoT to collect data from the vehicle's battery and send it to the cloud. Using a cloud-based smartphone app, we can track how well the battery is doing. © 2023 IEEE.

关键词： AI and the cloud are all components of this project battery monitoring current sensor Internet of Things NodeMCU temperature sensor voltage sensor

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Pyneapple-L: Scalable Expressive Learning-based Spatial Analysis 24

Pyneapple-L: Scalable Expressive Learning-based Spatial Anal...

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32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL 2024

作者： Liu, Yongyi Lee, Nicolas Kang, Yunfan Shahneh, Mohammad Reza Mahmood, Ahmed Chinnam, Vishal Rohith Sarawadekar, Aparna Vivek Oymak, Samet Sabek, Ibrahim Magdy, Amr Department of Computer Science and Engineering University of California Riverside United States Center for Geospatial Sciences University of California Riverside United States Google LLC United States Thomas Lord Department of Computer Science University of Southern California United States Department of Geography & Geographic Information Science University of Illinois Urbana-Champaign United States Electrical Engineering and Computer Science Department University of Michigan-Ann Arbor United States

ISBN: (纸本)9798400711077

This paper demonstrates Pyneapple-L, an open-source library designed to enhance scalable spatial analysis through learning-based techniques. Through collaboration with social scientists and domain experts, we identify scalability challenges inherent in conventional spatial analysis methods, particularly as the data size increases. Pyneapple-L addresses these challenges by leveraging learning-based models to offer scalable solutions. We demonstrate two modules: scalable learning of spatial hotspots along spatial networks and augmented geographically weighted regression. To showcase Pyneapple-L, we have developed a user-friendly frontend web application to interact with different datasets, algorithms, model configurations, and visualize outcomes on interactive maps that support both broad and analytical views. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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Intelligent IoT-Based Water Quality Monitoring System Using TD-CNN-LSTM Approach

Intelligent IoT-Based Water Quality Monitoring System Using ...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Velammal, M. Rakesh, Vittam Kartheeban, K. Ali Qidwai, Khalid Shyamala, G. Thulasimani, T. Karpagam College of Engineering Department of Computer Science and Technology Tamil Nadu Coimbatore India Geethanjali College of Engineering and Technology Electrical and Electronics Engineering Telangana Hyderabad India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Krishnankoil Tamilnadu Anand Nagar India College of Computer Science and Information Technology Jazan University Computer Science Jazan Saudi Arabia School of Engineering Sr University Civil Engineering Telangana Warangal India Bannari Amman Institute of Technology Department of Mathematics Tamilnadu Sathyamangalam India

ISBN: (纸本)9798350300857

Today, water contamination affects a large portion of the world's population. Manually collecting water samples from various sites and analyzing them in a lab as part of the routine monitoring technique. These approaches used to be effective, but they are now too slow and laborious to be practical. In addition, cutting-edge methods consider a wide range of physical and chemical elements. The standard method of quality monitoring and data sharing is time-consuming, unreliable, and costly. This emphasizes the need for constant, around-the-clock water quality monitoring. Basic Data Preprocessing, feature selection, and model training are the three main pillars of the proposed approach. The proposed method employs the preprocessing tools. The proposed system used the SOFM method (Structure-From-Function-Movement) to identify and eliminate unnecessary features selection. A model's accuracy can be measured with the help of prediction tools like utilizing CNN, LSTM, and TD-CNN-LSTM, models are trained. The proposed model outperforms two current top-tier contenders. The proposed method achieves higher accuracy (about 98.37%) when compared to other approaches like CNN and LSTM. © 2023 IEEE.

关键词： Water pollution

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A New MRA and AA based Algorithm for the Higher Order Reduction Uncertain Systems 9

A New MRA and AA based Algorithm for the Higher Order Reduct...

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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Shende, Vaishali Gajendra Raviraja, S. Kavitha, P. Aancy, H. Mickle Kumar, M. Jogendra Mittal, Varsha East Point College of Engineering And Technology Department of Information Science And Engineering Karnataka Bangalore560049 India University of Garden City Royal Research Foundation® Mysuru Department of Computer Studies Karnataka 570028 India R.MK. Engineerine College Department of Electrical And Electronics Eneineering Chennai Tamil Nadu Kavaraipettai601206 India Panimalar Engineering College Department of Management Studies Tamil Nadu Chennai600123 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram India Graphic Era Deemed To Be University Department of Computer Science And Engineering Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350365092

The MRA and AA algorithms are utilized in this paper to present a novel approach for the reduction of high-order uncertain systems. The development of the program makes use of both of these mathematical approaches. As a result of this creative approach, the Continuous SISO system might be reduced. Measurement mistakes brought on by variations in the environment have the potential to render the system ambiguous, in contrast to other systems that have been reported in the literature. This strategy, in contrast to the methods that were used in the prior iteration literature, has the potential to build a stable reduced order (r-o) model from a stable initial high order uncertain system. By avoiding many of the constraints of interval arithmetic, affine arithmetic is used. One of the problems is that there is not a solution that is unbounded in many of the key scenarios. Through the utilization of typical numerical examples derived from interval literature, the methodology was validated. Among the topics that we investigate are uncertain systems, lower order models, affine arithmetic, and the modified Routh approximation approach. © 2024 IEEE.

关键词： Uncertain systems

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Collection: The Aegean Ro-Boat Race 2023

IEEE Data Descriptions

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IEEE Data Descriptions 2024年 1卷 87-94页

作者： Alexandros Troupiotis-Kapeliaris Nikolaos Sapountzis Giannis Spiliopoulos Thomas Kogias Piyabhum Chaysri Bernardo AntÓnio Correia Gabriel Miguel Filipe Santos Silva Elias Xidias Konstantinos Blekas João Tasso de Figueiredo Borges de Sousa Dimitris Zissis Department of Product and Systems Engineering University of the Aegean Syros Greece Department of Computer Science and Engineering University of Ioannina Ioannina Greece Department of Electrical and Computer Engineering of the Faculty of Engineering University of Porto Porto Portugal

In this article, we introduce a publicly available real-world dataset collected during the Aegean Ro-Boat Race 2023, which took place at the University of the Aegean in Syros, Greece. The Aegean Ro-Boat Race represents an international competition at the university level, challenging teams to innovate and develop autonomous marine robotic systems capable of performing in unknown dynamic maritime environments under real-world conditions. The 2023 competition featured three primary mission tasks, each designed to test different aspects of the robotic systems: 1) high-speed performance for evaluating the speed and agility of the autonomous vessels; 2) collision avoidance for assessing the systems’ ability to detect and avoid obstacles in real-time; and 3) endurance for testing the operational longevity and efficiency of the robotic systems over extended periods. In total, seven teams registered for the competition, with five of them being from Greece and two from the countries of Portugal and Latvia. Due to several technical difficulties, three vessels were able to complete all races, and data were recorded during their entire participation. The spatiotemporal data for the “Aegean Ro-Boat Race” was gathered through an onboard data logging system that continuously monitored various sensors, including global positioning system (GPS), for all vessels during the entire competition. The dataset includes positional reports from the vessels during all three races (totaling over 6500 records), the positions of the external track and obstacle buoys, together with a file regarding the weather conditions during the race day. IEEE SOCIETY/COUNCIL computer Society (CS), Aerospace and Electronic Systems Society (AESS), Signal Processing Society (SPS), Oceanic engineering Society (OES), Intelligent Transportation Systems Society (ITSS) DATA TYPE/LOCATION CSV; Syros, Greece DATA DOI/PID 10.5281/zenodo.13318421

关键词： Robots Collision avoidance Boats Navigation Trajectory Testing Spatiotemporal phenomena Drones Technological innovation Sea measurements

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