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Advanced technology (KhPIWeek), IEEE KhPI Week on

作者： Dmytro Kucherov Tetiana Shmelova Olexii Poshyvailo Valerii Tkachenko Ignat Miroshnichenko Ihor Ogirko dept. Computerized Control Systems Faculty of Computer Science and Technology National Aviation University Kyiv Ukraine dept. Air Navigation Systems Faculty of Air Navigation Electronics and Telecommunications National Aviation University Kyiv Ukraine dept. Mathematic Ukrainian Academy of Printing City Lviv Ukraine

Currently, the use of unmanned vehicles for the delivery of goods is becoming a trend in many areas of human activity. At the same time, it is necessary to solve the problem of the integrity of the cargo because of its possible fluctuations. The paper deals with the problem of delivering cargo attached to a 4-motor UAV on a rigid cable. A control system is needed to achieve the UAV equilibrium position that can compensate for significant mismatches in the XY coordinate plane. A combination of two control algorithms is proposed for solving this problem, one of which provides a given position in the horizontal plane at small mismatch angles and the second at large mismatch angles. The first controller uses the PID controller algorithm with the corresponding optimal setting of its parameters, and the second one uses the bang-bang control scheme. An additional controller is used to coordinate these controllers, which ensures their timely switching. Some simulation is also proposed.

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Study on sleep environment by difference of air-conditioning in summer: Influence of total heat exchange type whole-house air-conditioning ventilation system

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Journal of Environmental Engineering (Japan) 2020年第777期85卷 871-880页

作者： Iwaki, Akemi Akimoto, Takashi Furuhashi, Takuya SIT Research Laboratories Shibaura Institute of Technology Japan Dept. of Architecture School of Architecture Shibaura Institute of Technology Japan Living Environment Systems Laboratory Mitsubishi Electric Corporation Japan

We will use air conditioning to improve the quality of sleep as a summer sleep measure, but when using air conditioning at night, there are concerns about adverse effects such as poor health, so air conditioning control that does not affect people is necessary. The purpose of this study is to investigate the thermal environment caused by good sleep and to construct a comfortable sleep environment. We compared the individual air conditioning (indoor air conditioning) that allows rapid temperature changes with the air conditioning in the entire room using a total heat exchange ventilation system, and investigated the influence on sleep. © 2020 Architectural Institute of Japan. All rights reserved.

关键词： Air conditioning

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A Novel Hybrid Deep Learning Model for Detecting Breast Cancer

TechRxiv

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TechRxiv 2023年

作者： Banerjee, Avishek Chakraborty, Debasis Bhattacharyya, Basanti Nath, Ira Dey, Debashis Garg, Deepak Dept. of Computer Science and Business Systems Asansol Engineering College West Bengal 713305 India Dept. of Computer Science and Engineering Asansol Engineering College Asansol713305 India Dept. of Computer Science and Engineering Pailan College of Management and Technology West Bengal 700139 India Dept. of Computer Science and Engineering JIS College of Engineering West Bengal 741235 India Dept. of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology West Bengal 700064 India School of Computer Science and Artificial Intelligence SR University Telangana Warangal506371 India

Cancer is a deformity of the body cells that grow out of control and spread to other parts of body. According to the American Cancer Society, early identification of cancer resulted in a 99% chance of survival in the localized stage. In this article, a benchmark cancer dataset is considered for the purpose of investigation. After data preprocessing, we attempt to predict cancer type using our proposed deep learning model named as CNN-Soft-T that combines the feature selection (FS) and classification. FS is introduced using histogram technique for anomaly detection and dimension reduction. We have compared the performance of this model to other cutting-edge machine learning approaches including Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN) and Decision Tree (DT) in order to demonstrate its utility. We have experimentally exhibited the exceptional empirical effectiveness and biological applicability of our suggested hybrid model for cancer diagnostics and medication development. © 2023, CC BY.

关键词： Decision trees

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Talk to your data: Enhancing Business Intelligence and Inventory Management with LLM-Driven Semantic Parsing and Text-to-SQL for Database Querying

Talk to your data: Enhancing Business Intelligence and Inven...

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Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Jerry Zhu Saad Ahmed Bazaz Srimonti Dutta Bhavaraju Anuraag Imran Haider Srijita Bandopadhyay Faculty of Mathematics University of Waterloo Ontario Canada Dept. of Computer Science National University of Computer and Emerging Sciences Islamabad Pakistan School of Agro and Rural Technology Indian Institute of Technology Guwahati Guwahati India Dept. of Electronics and Communication Engineering Vellore Institute of Technology India Dept. of Industrial and Systems Engineering Indian Institute of Technology Kharagpur Kharagpur India Dept. of Electronics and Communication Engineering University of Engineering and Management Kolkata India

ISBN: (数字)9798350369786

ISBN: (纸本)9798350369793

This paper delves into the potential of Large Language Models (LLMs) in revolutionizing business intelligence and inventory management through semantic parsing and text-to-SQL methodologies. It assesses various LLM models, such as DIN-SQL, DSP, NSQL, GPT, CoPilot, and LLaMa, elucidating their capabilities and contributions. Two critical analyses are presented here. The first compares cutting-edge LLM models using cosine similarity and cost efficiency metrics. The second analysis enhances GPT’s precision through prompt engineerings, like few-shot techniques, and explores frameworks like DIN-SQL, NSQL, and DSP. DIN-SQL substantially boosts accuracy, and NSQL demonstrates potential in specific scenarios. This research underscores the transformative potential of LLM-driven models in business intelligence and inventory management. DIN-SQL, in particular, emerges as a game-changer with the potential to reshape inventory management practices. GPT showcases its versatility through fine-tuning for tasks beyond conventional programming, while CoPilot offers a cost-effective alternative. This study emphasizes the importance of cost-effectiveness in real-world applications, with LLaMa and CoPilot being practical choices. NSQL, with its budget-friendly and semi-accurate solution, holds promise for semantic parsing in growing companies. These insights are a foundation for further innovation, promising unmatched efficiency and competitiveness across industries in the evolving Artificial intelligence landscape.

关键词： Industries Structured Query Language Technological innovation Costs Large language models Semantics Inventory management

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New Algorithms for the Computation of Inverse Transforms

New Algorithms for the Computation of Inverse Transforms

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2022 International Conference on Computational Science and Computational Intelligence, CSCI 2022

作者： Zhang, Jun Fan, Ruzong Shen, Fangyang University of Maryland Eastern Shore Department of Computer Science and Engineering Technology Princess AnneMD21853 United States Georgetown University Department of Biostatistics Bioinformatics and Biomathematics WashingtonDC20057 United States City University of New York Dept. of Computer Systems Technology New York City College of Technology BrooklynNY11201 United States

ISBN: (纸本)9798350320282

The Laplace Transform has been widely used for about two centuries in problem solving in mathematics, engineering and sciences. The Sumudu Transform is very recent, it is as powerful as the Laplace Transform and has many nice features. Traditionally, when these transforms are used, the calculations of the inverse transforms are necessary;unfortunately, the calculations of Inverse Laplace Transform and Inverse Sumudu Transform are problematic and challenging. The authors studied Sumudu Transform in the computational approaches. We shall introduce a few novel algorithms on the computations of Inverse Sumudu Transform and Inverse Laplace Transform in this paper. The algorithms introduced here are straightforward to understand and powerful for problem solving, and some demo versions were implemented in the Maple computer Algebra systems. Type: Full / Regular Research Paper for CSCI-RTCS © 2022 IEEE.

关键词： Laplace transforms

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The Impact of the Energy Storage System Operation Strategy on Power Grid Reliability

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Transactions of the Korean Institute of Electrical Engineers 2021年第12期70卷 1820-1826页

作者： Kim, Beopsoo Lee, Dayoung Rusetskii, Nikita Shusterzon, Konstantin Sidorov, Denis Kim, Insu Dept. of Electrical Engineering Inha University Korea Republic of Dept. of Electrical and Computer Engineering Inha University Korea Republic of School of Information Technology and Data Science Irkutsk National Research Technical University Russia Energy Systems Institute Siberian Branch Russian Academy of Sciences Russia

Based on the empirical data published by the Korea Electric Power Exchange and the Korea Meteorological Administration, we present a methodology that predicts the system marginal prices. For this purpose, this study uses the long-short term memory (LSTM) technique, which is commonly used in time-series prediction problems. As a result, we present a strategy for operating energy storage systems (ESSs) from the perspective of a prosumer rather than a system operator or conventional utilities. This study also examines the effects of the proposed prosumer actions on the system. The proposed operating strategy is established based on dynamic programming. In particular, this study takes the proposed operation strategy of ESSs the point of view of system reliability. © The Korean Institute of Electrical Engineers This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://***/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

关键词： Reliability

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Dynamic Adaptation Gain Design and Tuning for Threat Discrimination

Dynamic Adaptation Gain Design and Tuning for Threat Discrim...

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IEEE Conference on Decision and Control

作者： Kangkang Zhang Kaiwen Chen Marios M. Polycarpou Thomas Parisini Dept. of Electrical and Electronic Engineering Imperial College London London U.K. Dept. of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Considering potential threats to cyber-physical systems such as component faults and stealthy cyber-attacks, an adaptive observer-based threat discrimination method is proposed for identifying the occurring threat type. Typically, stealthy attacks have only weak effects easily obscured by disturbances on the system outputs. To solve this problem, a parameter adaptation algorithm based on a newly designed dynamic adaptive gain generator is proposed, aiming at improving the sensitivity of the adaptive threat discrimination scheme to potential threats. Only the strictly positive real condition of the proposed gain generator sufficiently ensures the stability of the adaptive observer error system. A moment-matching method is then developed to determine the proper parameters of the gain generator, allowing for the improvement of the sensitivity of the threat discriminators. A numerical example to demonstrate the effectiveness of the proposed methodology is presented.

关键词： Fault diagnosis Sensitivity Adaptive systems Heuristic algorithms Observers Cyber-physical systems Generators Cyberattack Tuning Numerical stability

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Adaptive Modulation Metod for Communication systems Using Signals with Orthogonal Frequency Multiplexing 23

Adaptive Modulation Metod for Communication Systems Using Si...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Rogozhnikov, Eugeniy V. Kryukov, Yakov V. Dmitriyev, Edgar Pokamestov, Dmitriy A. Kondrashov, Danila A. Novichkov, Serafim A. Tomsk State University of Control Systems and Radioelectronics Dept. of Telecommunications and Basic Principles of Radio Engineering Tomsk Russia Leading Research Center '5G Radio Access Network with Open Architecture' Skolkovo Institute of Science and Technology Moscow Russia

ISBN: (纸本)9781665498043

This paper is devoted to the description of the adaptive modulation method for communication systems using signals with orthogonal frequency-division multiplexing. The present paper describes a method aimed at reducing the number of bit errors in signal transmission at low signal-to-noise ratio in channels with active interference, as well as multipath channels with unstable, rapidly changing characteristics. Reducing the probability of bit errors is one of the main tasks in the design of communication systems, along with increasing the data rate, reducing delay and increasing the number of users. Therefore, finding ways to optimally use the frequency-time resource for data transmission is an urgent task. The presented adaptive modulation technique uses pilot symbols to estimate the data link and compute maximum error vector magnitude. The proposed method made it possible to reduce the probability of a bit error by 15% compared to existing methods. Also, the presented method showed a spectral efficiency 1.5 times greater than the considered methods. © 2022 IEEE.

关键词： Orthogonal frequency division multiplexing

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Determination of Transformer Operating Condition with Different Classifiers

Determination of Transformer Operating Condition with Differ...

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International Conf on Electrical and Electronic Engineering (ICEEE)

作者： Merve Demirci Mustafa Saka Haluk Gozde Nurmammad Mammadov Mahir Dursun M. Cengiz Taplamacioglu Dept. of Electrical and Electronics Engineering Faculty of Engineering and Architecture Kafkas University Kars Turkey Dept. of Electrical and Electronics Engineering Faculty of Engineering and Naturel Sciences Iskenderun Technical University Hatay Turkey Turkish Aerospace Industries Ankara Turkey Construction of Eng Systems and Facilities Azerbaijan University of Architecture and Construction Baku Azerbaijan Dept. of Electrical and Electronics Engineering Technology Faculty Gazi University Ankara Turkey Dept. of Electrical and Electronics Engineering Engineering Faculty Gazi University Ankara Turkey

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

When diagnosing the condition of transformers, classification is generally made into normal and faulty states. However, in some cases, an increase in the amount of hydrogen and hydrocarbons in the insulating oil is observed even if there is no malfunction. This situation is called stray gassing. Ignoring stray gassing may lead to misdiagnosis. In this study, real transformer data have been classified as normal state, faulty state and stray gassing. First, real data has been labeled with gas percentages using the Duval Pentagon 1 method. Then, two data sets have been created, consist of 5 gas and 9 gas concentrations. Transformer condition diagnosis has been made using the classification algorithms Fine Tree, Linear SVM, Bagging Trees and Subspace KNN for the raw data set and pre-processed data, and the results have been compared. In addition to using different gases to increase diagnostic performance, the data has pre-processed and analyzed. The highest diagnostic accuracy has been achieved with the pre-processed version of Dataset-2, which contains 9 gas data with a large number of features.

关键词： Training Support vector machines Accuracy Oils Hydrogen Oil insulation Hydrocarbons Transformers Classification algorithms Power transformer insulation

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Comparative analysis of deepfake detection methods using machine learning and deep learning

Comparative analysis of deepfake detection methods using mac...

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International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Poorva Agrawal Soham Pathak Shruti Potey Vaishnavi Dhengre Nitin Rakesh R. Parvathi Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Dept. of Smart Computing School of Computer Science Enginnering and Information Systems (SCORE) VIT Vellore

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372823

The paper examines the growing issue of deepfake technology, which uses cutting-edge machine learning to spoof face features in videos. This technology has the potential to be abused in a number of situations, including blackmail, political manipulation, and the staging of terrorist acts. The study’s main goal is to present a thorough summary of current studies that use cutting-edge deep learning techniques to identify fake information. The Deepfakes Detection Challenge (DFDC) dataset is introduced, neural network applications are covered, and the effectiveness of current deepfake detection models is assessed. Because deepfake applications potentially pose a hazard, the research emphasizes the need for tools that can automatically detect and evaluate the integrity of digital visual data. Additionally, it discusses numerous algorithms and approaches that have been put out in the literature for producing and identifying deepfakes, with a focus on deep learning-based methods.

关键词： Deep learning Deepfakes Visualization Accuracy Biological system modeling Computational modeling Terrorism

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