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Application of Accelerated Learning method in educational games periodic table of chemical elements

AIP Conference Proceedings 2024年第1期2970卷

作者： Donaya Pasha Yohana Tri Utami Teddy Azidane M. Hamdan Sobirin Department of Information Technology Faculty of Engineering and Computer Science Universitas Teknokrat Jl. ZA. Pagar Alam No. 9-11 Labuhan Ratu Kec. Kedaton Kota Bandar Lampung Lampung 35132 Indonesia Department of Computer Science Faculty of Mathematics and Natural Science University of Lampung Jl. Sumantri Brojonegoro No. 1 Bandar Lampung Lampung 35145 Indonesia

One of the subjects in chemistry learning is the periodic system of elements. In the periodic system of elements, some concepts require sufficient understanding and memorization from students. The problem in this study is students’ lack of knowledge in memorizing the periodic system of chemical elements. Using media in the form of games is one of the efforts that can provide solutions to improving students’ understanding and memorization of these subjects. The method that will be applied in the educational Game is the Accelerated Learning method, which is expected to increase students’ interest in learning and make learning easier and faster to understand. The tools used are Unity which is run on the Android operating system. The testing method uses ISO 9126 with four aspects: usability, functionality, portability, efficiency, and the paired sample t-test. The test results of the educational game application for periodic chemical elements using ISO 9126 resulted in a usability aspect of the overall value of 89%, which means it is very feasible. The functionality aspect shows that the application can perform 100% of its functions correctly. The portability results show that the application can be installed on several devices with the KitKat, marshmallow, and nougat versions of the Android operating system. The efficiency aspect with testdroid shows that it does not experience a lack of memory that causes the application to stop. The maximum CPU usage is 37% at the beginning of running the application, and the average CPU generates 9%. Paired sample t-test showed that the average score of students before (pre-test) and after (post-test) increased, namely (pre-test) 19.60 and (post-test) 54.53.

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CorrDetector: A framework for structural corrosion detection from drone images using ensemble deep learning

arXiv

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arXiv 2021年

作者： Mohammad Forkana, Abdur Rahim Kang, Yong-Bin Jayaraman, Prem Prakash Liao, Kewen Kaul, Rohit Morgan, Graham Ranjan, Rajiv Sinha, Samir Department of Computer Science and Software Engineering Swinburne University of Technology MelbourneVIC Australia Department of Media and Communication Swinburne University of Technology MelbourneVIC Australia Discipline of Information Technology Peter Faber Business School Australian Catholic University SydneyNSW Australia Newcastle University Newcastle upon TyneNE1 7RU United Kingdom Robonomics AI York Street SydneyNSW Australia

In this paper, we propose a new technique that applies automated image analysis in the area of structural corrosion monitoring and demonstrate improved efficacy compared to existing approaches. Structural corrosion monitoring is the initial step of the risk-based maintenance philosophy and depends on an engineer’s assessment regarding the risk of building failure balanced against the fiscal cost of maintenance. This introduces the opportunity for human error which is further complicated when restricted to assessment using drone captured images for those areas not reachable by humans due to many background noises. The importance of this problem has promoted an active research community aiming to support the engineer through the use of artificial intelligence (AI) image analysis for corrosion detection. In this paper, we advance this area of research with the development of a framework, CorrDetector. CorrDetector uses a novel ensemble deep learning approach underpinned by convolutional neural networks (CNNs) for structural identification and corrosion feature extraction. We provide an empirical evaluation using real-world images of a complicated structure (e.g. telecommunication tower) captured by drones, a typical scenario for engineers. Our study demonstrates that the ensemble approach of CorrDetector significantly outperforms the state-of-the-art in terms of classification accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Application of different feature selection and machine learning techniques in web page classification

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AIP Conference Proceedings 2022年第1期2405卷

作者： S. Markkandeyan P. Kalyanasundaram U. Muthaiah Nilavu Niza P. Gnanapriya 1Department of Computer Science and Engineering Sri Shanmugha College of Engineering and Technology Pullipalayam Sankari- 637304 Salem District Tamilnadu India 2Institute of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai - 602105 Tamilnadu India

It is obvious that search engines are in rampant use in today's web world for tracing Web documents) through particular keynotes which ultimately projects both the relevant and irrelevant ones, which contains the same keywords. Of course, web information is exponentially increasing now and then. While so, manual classifications of Web documents are redundant, inaccurate, complex and also a time consuming process. Though several researchers do sustained research for classifying the Web documents, they are not able to produce the accurate results. Hence, automatic classification of Web documents is the need of the hour to solve all such issues. At this juncture, this paper here presents different feature selection, machine learning techniques and its methods, performance and dataset applied in the classification of Web pages

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Deep learning assisted calibrated beam training for millimeter-wave communication systems

arXiv

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arXiv 2021年

作者： Ma, Ke He, Dongxuan Sun, Hancun Wang, Zhaocheng Chen, Sheng Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Tsinghua University Beijing100084 China Tsinghua Shenzhen International Graduate School Shenzhen518055 China The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless communications. To address this issue, in this paper, we propose a wide beam based training approach to calibrate the narrow beam direction according to the channel power leakage. To handle the complex nonlinear properties of the channel power leakage, deep learning is utilized to predict the optimal narrow beam directly. Specifically, three deep learning assisted calibrated beam training schemes are proposed. The first scheme adopts convolution neural network to implement the prediction based on the instantaneous received signals of wide beam training. We also perform the additional narrow beam training based on the predicted probabilities for further beam direction calibrations. However, the first scheme only depends on one wide beam training, which lacks the robustness to noise. To tackle this problem, the second scheme adopts long-short term memory (LSTM) network for tracking the movement of users and calibrating the beam direction according to the received signals of prior beam training, in order to enhance the robustness to noise. To further reduce the overhead of wide beam training, our third scheme, an adaptive beam training strategy, selects partial wide beams to be trained based on the prior received signals. Two criteria, namely, optimal neighboring criterion and maximum probability criterion, are designed for the selection. Furthermore, to handle mobile scenarios, auxiliary LSTM is introduced to calibrate the directions of the selected wide beams more precisely. Simulation results demonstrate that our proposed schemes achieve significantly higher beamforming gain with smaller beam training overhead compared with the conventional and existing deep-learning based counterparts. Copyright © 2021, The Authors. All rights reserved.

关键词： Forecasting

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Semantic Communications: Principles and Challenges

arXiv

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arXiv 2021年

作者： Qin, Zhijin Tao, Xiaoming Lu, Jianhua Tong, Wen Li, Geoffrey Ye The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electronic Engineering The Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Wireless Technology Labs Huawei Technologies Ottawa Canada The School of Electrical and Electronic Engineering Imperial College London LondonSW7 2AZ United Kingdom

Semantic communication, regarded as the breakthrough beyond the Shannon paradigm, aims at the successful transmission of semantic information conveyed by the source rather than the accurate reception of each single symbol or bit regardless of its meaning. This article provides an overview on semantic communications. After a brief review of Shannon information theory, we discuss semantic communications with theory, framework, and system design enabled by deep learning. Different from the symbol/bit error rate used for measuring conventional communication systems, performance metrics for semantic communications are also discussed. The article concludes with several open questions in semantic communications. Copyright © 2021, The Authors. All rights reserved.

关键词： Semantics

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IoT based energy monitoring and energy theft detection

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AIP Conference Proceedings 2023年第1期2690卷

作者： Vishakha Yadav Anita Keshav Patil P. Janardhan Saikumar Santaji Krishna Shinde B. Karunamoorthy S. Hemavathi 1Department of Computer Science and Engineering BMS Institute of Technology and Management Yelahanka Bengaluru-560064 Karnataka India 2Department of Electronics and Telecommunication Dr.Vithalrao Vikhe Patil College of Engineering MIDC Vilad Ghat Ahemdnagar– 414111 Maharashtra India 3Department of Electronics and Communication Engineering Audisankara Institute of Technology Gudur-524101 Andhra Pradesh India 4Department of Computer Engineering Vidya Pratishthan’s Kamalnayan Bajaj Institute of Engineering and Technology Baramati Pune-413133 Maharashtra India 5Department of Electrical & Electronics Engineering Kumaraguru College of Technology Coimbatore-641049 Tamil Nadu India 6Battery Division Central Electrochemical Research Institute and Academy of Scientific and Innovative Research CSIR Madras Complex Chennai - 600113 Tamil Nadu India

One of the greatest issues facing the nation today is the energy crisis. The energy crisis can be mitigated to some extent if people keep track of our energy consumption and avoid wasting it. People nowadays confront a variety of issues, including electricity theft. One’s own country’s economy has a major significant influence on electric power theft and is a type of crime. In this research, an IoT-based power utilizedis proposed andit is measured utilizing current and voltage sensor reading. The proposed IoT technology will readily detect energy theft. This Internet of Things is connected with an Arduino UNO IDE with a Wi-Fi module for IoT connectivity andcustomers will receive information viathe Blynk app. A current sensor is also included in this smart electricity meter, which relays the current information to the microcontroller. Users must connect cell phones to Blynk app so that the electricity theft can be tracked and monitored,which can help you to set up your system. The reading appears on the IoT screen as soon as it activates the system. The reading will be altered following the passage of time. If energy theft occurs, the theft will be detected and displayed on the IoT screen. To prevent theft, the user can use the IoT Blynk app to monitor the tracking of power utilized by the system anywhere and at any time, even after receiving the theft indication signal.

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Cramér-rao bound optimization for joint radar-communication design

arXiv

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arXiv 2021年

作者： Liu, Fan Liu, Ya-Feng Li, Ang Masouros, Christos Eldar, Yonina C. The Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The School of Information and Communications Engineering Faculty of Electronic and Information Engineering Xi’an Jiaotong University Xi’anShaanxi710049 China The Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom The Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramér-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the CRB of radar sensing while guaranteeing a pre-defined level of signal-to-interference-plus-noise ratio (SINR) for each communication user. For the single-user scenario, we derive a closed form for the optimal solution for both cases of point and extended targets. For the multi-user scenario, we show that both problems can be relaxed into semidefinite programming by using the semidefinite relaxation approach, and prove that the global optimum can always be obtained. Finally, we demonstrate numerically that the globally optimal solutions are reachable via the proposed methods, which provide significant gains in target estimation performance over state-of-the-art benchmarks. Copyright © 2021, The Authors. All rights reserved.

关键词： Signal to noise ratio

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IoT based mobile app for continuous health monitoring of the person

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AIP Conference Proceedings 2023年第1期2690卷

作者： Indira Priyadarsini I. S. Chakrapani S. Manochitra B. Tejaswini S. Ramesh Kamal Alaskar 1Department of Botany SKR Govt. Degree College Nagari Andhra Pradesh-517590 India 2Department of Zoology PRR & VS Govt College Vidavalluru Nellore Andhra Pradesh-524318 India 3Department of Computer science & Information Technology Kalasalingam Academy of Research & Education Anand Nagar Krishnankoil-626126Tamil Nadu India 4Department of Information Science and Engineering East point college of engineering and Technology Avalahalli Bengaluru Karnataka 560049 India 5Department of Electronics and Communication Engineering St. Mother Theresa Engineering College Vagaikulam Mudivaithanenthal Post Thoothukudi District–628102 Tamil Nadu India 6Department of Computer Application Bharati Vidyapeeth (Deemed to be University) Institute of Management Kadamwadi Rd Laxminarayan Nagar Tarabai Park Kolhapur Maharashtra 416003India

In the sphere of medicine, IOT is meant to keep people safe and healthy plays a crucial part in communicating with doctors and patients through the use of health monitoring equipment and lowering healthcare costs in the future years. The internet of things (IoT) is making the world a smarter and more efficient village by allowing a variety of sensors and smart gadgets to gather and analyse data for a variety of reasons. As a result of these smart things, the healthcare system is growing wiser. When basic health facilities lack comprehensive medical care infrastructure, emerging countries gain. However, there is currently no specialized architecture for smart health units that can allow for this gathering and transferring patient health information to headquarters hospitals where live patient assistance is offered. Here, a smart IoT-based healthcare system is proposed, which includes a smart medical kit linked to sensors and a server for frequent health tracking. This smart medical kit is associated with sensors to measure the health parameters like body temperature, blood pressure, and heart rate for the effective function of the body. The proposed idea can alert the patient and their relatives in case of any abnormalities in their health parameters and also get suggestions from the doctor without physical contact with the doctor.

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An intelligent road traffic data management for upgrading real time performance

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AIP Conference Proceedings 2022年第1期2426卷

作者： MD. Rafeeq V. Harsha Shastri Ba Anandh V. Shanmugasundaram Prathipati Ratna Kumar D. Jyothsna 1Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Hyderabad Telangana India. 2Department of Computer Science Department Of Computer Science and Engineering Loyola Academy Secunderabad-500010 Telangana India 3Department of Electronics PSG College of Arts & Science Coimbatore - 641 014 Tamilnadu India. 4Department of Electrical and Electronics Engineering Sona College of Technology Salem - 636005 Tamilnadu India.

The distributed road traffic simulation is an important tool for control and analysis of large road traffic networks (e.g., an entire city or even state). For performing the simulation, it is necessary to divide the simulated road traffic network into sub networks, which are then simulated as processes on computers (nodes) of the distributed computer. To ensure a good performance of the distributed road traffic simulation, two aspects should be considered during the division of the road traffic network - the load-balancing of the resulting sub-networks and the minimization of the inter process communication [1, 2]. Legacy transportation systems are among the most important systems that need to be addressed in a proper manner. Congestion is considered as one of the common problems, especially during peak times of the day because of the weakness of the absorptive capacity of the roads network and the inefficiency of the transportation system to meet the required demands of the increasing traffic size

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PV system with high voltage gain based DC-DC boost converter for grid applications

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AIP Conference Proceedings 2022年第1期2519卷

作者： S. Peniel Pauldoss K. Sekar Balachandra Pattanaik V. Senthil Nayagam 1Department of Mechanical Engineering Brilliant Group of Technical Institutions Hyderabad Telangana India 2Department of Electrical and Electronics Engineering Hindustan College of Engineering and Technology Coimbatore Tamil Nadu India 3Department of Electrical and Computer Engineering Wollega University Nekemte Ethiopia Africa 4School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India

The production of electricity from renewable sources is growing. The study proposes to use the wind power grid-based PV system and to use a PWM control system to regulate the solar system with a three-phase grid. This study aims to create a system that enhances power on the spring and controls harmonics on the grid. The converters linked up with the 3-phase RL load of the generated PV arrays. The system is comprised of the inverter, PV module, and non-linear power boost converter. The proposed way of controlling PWM makes the system robust and reliable. The converter is connected to the input side voltage source inverter to step up the generated PV array voltage. A three-phase inverter uses sliding mode control to switch signals and control the transferred active power to the grid system and load. The suggested arrangement model is developed using MATLAB/Simulink.

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