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2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023

作者： Braathen De Carvalho, Kevin De Oliveira, Iure Rosa L. Brandao, Alexandre S. Universidade Federal de Viçosa Nucleus of Specialization in Robotics Department of Electrical Engineering Graduate Program in Computer Science MG Viçosa36570-900 Brazil Federal University of Viçosa Department of Electrical Engineering MG Viçosa Brazil

ISBN: (纸本)9798350310375

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV's decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments. © 2023 IEEE.

关键词： Reinforcement learning

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Effects of the Window Size Variation in the RMS Voltage and Industrial Control Measures

Effects of the Window Size Variation in the RMS Voltage and ...

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Innovative Smart Grid Technologies (ISGT)

作者： Christopher R. Men Douglas E. Dow Umair Zia Afsaneh Ghanavati Electrical and Computer Engineering Program School of Enginnering Wentworth Institue of Technology Boston MA Director of Distribution Engineering Eversource Energy Boston MA

Sags and swells are types of power quality disturbances that involve fluctuations in voltage. Sags are decreases in a voltage’s magnitude while swells are increases in a voltage’s magnitude. There are a number of different techniques to identify and classify these power quality disturbances, however in an industrial setting power utilities typically employ the use of the CBEMA and ITIC curves to classify the power quality disturbances they encounter. The CBEMA and ITIC curves utilize RMS voltage to denote whether a disturbance is expected to impact the system it occurs on, however there are a number of ambiguities surrounding the use of both curves. One such ambiguity is the lack of specification surrounding the window size used to calculate RMS values. This paper proposes MATLAB scripts that can synthesize waveforms with sags and swells according to a variety of user-defined parameters and provide their RMS voltages. This paper also presents a MATLAB function that can plot the RMS voltage magnitude and durations of transient events onto the ITIC curve. This paper explores the effect of varying the window size used to calculate RMS voltage for each disturbance across different parameters. Moreover, the paper presents an analysis of the RMS voltage of a real-world voltage sag in a three-phase system.

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Optimization of Certainty Factor Algorithm to Overcome Uncertainty in Expert System Identification of Pests and Diseases of Cocoa 2

Optimization of Certainty Factor Algorithm to Overcome Uncer...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Gunawan, Rakhmat Dedi Ahmad, Imam Parjito Anggono, Harry Vernando, Ego Hengki Jaya, Firman Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandarlampung Indonesia Stkip Pgri Information Technology Education Study Program Situbondo Indonesia

ISBN: (纸本)9781665465410

Lampung Province is one of the regions with the highest cocoa production, but many factors can interfere with cocoa production. One of them is the factor of pests and diseases of cocoa that cannot be identified and prevented beforehand. An expert system is a system that adopts expert knowledge or experts in a particular field. However, the diagnosis usually contains uncertainty in the form of answers and statements used. Certainty Factor (CF) algorithm, is one of the algorithms that is able to overcome uncertainty by providing a value for the level of trust from experts and users. However, because the CF value is based on the level of confidence in the symptoms experienced by the user, it creates a problem, namely the consistency of the user's answers. So, it is necessary to make improvements to the CF algorithm, to overcome the inconsistency of user answers through the use of Consistency Ratio (CR). Through the use of CR, inconsistencies are overcome through comparisons between the consistency index and the random index. Based on the results of the accuracy test, the proposed model is able to produce an accuracy rate of 86.67% in the diagnosis of pests and diseases on cocoa plants. © 2022 IEEE.

关键词： Cocoa

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A Multi-phase Deep Learning Approach for Predicting HCC Response to TACE using Complete Computed Tomography

A Multi-phase Deep Learning Approach for Predicting HCC Resp...

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2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Chang, Shun Cheng Liu, Chien Fu Misztal, Marta Hsieh, Yi Hsien Lin, Che Taiwan School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Department of Electrical Engineering Ntu Taiwan Center for Computational and Systems Biology Center for Biotechnology Ntu Taiwan Smart Medicine and Health Informatics Program Ntu Taiwan

ISBN: (纸本)9798350383386

In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellular Carcinoma) patients. Using entire abdominal CT scans enabled a broader perspective available for the model, eliminating the need for segmentation during the preprocessing. Making use of both single-phase and multi-phase CT imaging, we have used DenseNet121 and have obtained an accuracy of 80% for the multi-phase *** Relevance: The ability to predict the effectiveness of TACE treatment prior to its administration makes it possible to provide a better decision-making aid for physicians and patients. © 2023 IEEE.

关键词： computerized tomography

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Diabetes Classification Problem with CatBoost Method and Optuna Gradient Boosting Optimization 6

Diabetes Classification Problem with CatBoost Method and Opt...

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6th International Conference on Information and Communications Technology, ICOIACT 2023

作者： Kurniawan, Safar Dwi Purwono, Purwono Ma'arif, Alfian Suwarno, Iswanto Politeknik Harapan Bersama Department of Computer Engineering Tegal Indonesia Universitas Harapan Bangsa Department of Informatics Purwokerto Indonesia Universitas Ahmad Dahlan Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Department of Engineer Professional Program Yogyakarta Indonesia

ISBN: (纸本)9798350315639

Diabetes mellitus is a dangerous global epidemic that can cause kidney failure, heart attack, blindness, and death. The main cause of this disease is too high blood sugar levels due to the irrelevant work of pancreatic beta cells. Rapid computer technology advances and implementations based on artificial intelligence have penetrated various fields, especially the health sector. Data mining and machine learning are technologies that continue to grow, are reliable, and can be used as research support tools in the medical field. This technology is considered capable of helping to automate diabetes prediction. Based on related research, our contribution to this research is to utilize the CatBoost method with Optuna optimization. In the data preprocessing stage, all 768 data sets have gone through removing outliers, normalizing features to reducing dimensions. The dataset is divided into 85\% composition for training data and 15\% for test data. At the feature selection stage with Correlation Pearson's, we found that Glucose correlated with diabetes outcome or disease because it had a value range of 0.47. The results' accuracy is considered less than optimal because it only produces an accuracy value below 80%, even after optimization with Optuna. It can be seen that there was only an increase of 7\% after optimizing with Optuna. © 2023 IEEE.

关键词： Data mining

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Polymethyl Methacrylate-based Light Collector for Enhanced Indoor Visible Light Communication

Polymethyl Methacrylate-based Light Collector for Enhanced I...

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Optics and Photonics Conference (SBFoton IOPC), SBFoton International

作者： David Esteban Farfán-Guillén João Pedro Duarte Jankosz Neri Volpato Alexandre de Almeida Prado Pohl Graduate Program in Electrical and Computer Engineering (CPGEI) Federal University Technology-Parana Curitiba Brazil Graduate Program in Mechanical Engineering and Material Science Federal University Technology-Parana. Curitiba Brazil

A new polymethyl methacrylate-based light collector has been designed and fabricated with additive manufacturing to optimize the efficiency of VLC systems. It enhances the area of detection, leading to a ~ 1.9x increa... 详细信息

ISBN: (数字)9798350388176

ISBN: (纸本)9798350388183

关键词： Optical device fabrication Optical variables measurement Three-dimensional printing Optics Optical receivers Optical sensors Reliability Visible light communication Testing Photonics

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Adaptive Neuro-Fuzzy Inference System As New Real-Time Approach for Parkinson Seizures Prediction 4

Adaptive Neuro-Fuzzy Inference System As New Real-Time Appro...

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4th International Conference on Bio-engineering for Smart Technologies, BioSMART 2021

作者： Daher, Alaa Yassin, Sally Alsamra, Hadi Ali, Hassan Abou Beirut Arab University Biomedical Engineering Program Faculty of Engineering Electrical and Computer Engineering Department Debbieh Lebanon

ISBN: (纸本)9781665408103

Parkinson's disease, as a definition, is a neurological condition that affects the brain and causes tremors, stiffness, and difficulties walking, balancing, and coordinating. Symptoms of Parkinson's disease normally appear gradually and worsen with time. People with Parkinson's disease may have difficulties walking and speaking as the condition develops. Numerous recent studies have shown a direct association between Parkinson's disease and the incident of having epileptic seizures, which is defined to be a burst of the uncontrollable electrical activity of the brain cells, that is associated with an increased risk of sudden unexplained deaths. This project aims to obtain a real-time seizure prediction system for Parkinson's disease patients based on the electroencephalogram (EEG) signals, enabling the detection of a seizure before it happens. This will hopefully save them from risky situations or sudden death, as they will be alerted and have the time enabling them to be prepared and take the needed precautions and steps to prevent the seizure from happening. For this project, we've used the Neural Network and the ANFIS ('udaptive neuro-fuzzy inference system '') to process and analyze the electroencephalogram (EEG) data signals of the Parkinson patients to detect seizures starting point. © 2021 IEEE.

关键词： Brain

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Coordinated Feeder Reconfiguration, Capacitor Placement and Allocation of Distributed Energy Resources for Loss Reduction Under Variable Loading Conditions 4

Coordinated Feeder Reconfiguration, Capacitor Placement and ...

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4th Annual IEEE Kansas Power and Energy Conference, KPEC 2023

作者： Mahdavi, Meisam Awaafo, Augustine Djokic, Sasa Z. Schmitt, Konrad Chamana, Manohar University of Jaén Department of Electrical Engineering Jaén Linares Spain The University of Edinburgh School of Engineering Edinburgh United Kingdom Texas Tech University Electrical & Computer Engineering Department LubbockTX United States Texas Tech University Renewable Energy Program Lubbock United States

ISBN: (纸本)9798350335408

Reduction of active power losses in distribution networks is an important issue, which is usually addressed through a separate, sequential, or simultaneous feeder reconfiguration (FR), volt-var regulation (e.g., capacitor placement, CP), and control of distributed energy resources (DERs). However, finding optimal solution for a coordinated FR, CP, and DER control requires significant computational efforts, which are additionally increased when variations in loading conditions are considered. Therefore, load variations are usually neglected in related analysis, although changes in power flows influence changes in network losses and, consequently, optimal controls for FR, CP and DERs. This paper presents the analysis of both benefits and disadvantages of including not only the peak demands, but also different loading conditions for a coordinated implementation of FR, CP and DER controls for the reduction of losses. The analysis is illustrated on the several distribution test networks and using representative load patterns from the existing literature. The obtained results suggest that the inclusion of load variations requires significantly longer computational times, but in some cases affects optimal solutions for FR, CP and DER controls (their numbers, locations and settings). © 2023 IEEE.

关键词： Electric power distribution

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Trajectory Planning with Obstacle Avoidance using APF and COLREGS for USVs

Trajectory Planning with Obstacle Avoidance using APF and CO...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Kelvin K. C. F. Nunes Tiago T. Ribeiro Andre G. S. Conceicao Postgraduate Program in Electrical Engineering Federal University of Bahia Salvador Brazil Department of Electrical and Computer Engineering Federal University of Bahia Salvador Brazil

ISBN: (数字)9798350352344

ISBN: (纸本)9798350352351

This paper presents a trajectory planning and obstacle avoidance system for Unmanned Surface Vehicles (USV) in complex and dynamic navigation environments. The developed system employs a modified Artificial Potential Field (APF) algorithm and the International Regulations for Preventing Collisions at Sea (COLREGS) to ensure safe and efficient navigation. Modifications were implemented to the original algorithm to deal with obstacles approaching the autonomous vehicle, including adding vectors to determine the direction of deviation based on the cross-product. The proposed system was validated in the Gazebo simulation environment within a dynamic scenario featuring static and moving obstacles.

关键词： Trajectory planning Navigation Heuristic algorithms Vectors Regulation Safety Vehicle dynamics

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Forward and Reverse Converters for the Moduli-Set {22q+1, 2q + 2q−1 ± 1}

arXiv

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arXiv 2024年

作者： Jaberipur, Ghassem Nadimi, Bardia Kazemi, R. Lee, Jeong-A The Brain Pool Program for Chosun University Gwangju Korea Republic of The University of South Florida TampaFL United States Computer Engineering The Department of Computer Science and Engineering Shahid Beheshti University Tehran Iran The Department of Computer Engineering Chosun University Korea Republic of

Modulo-(2q + 2q−1 ± 1) adders have recently been implemented using the regular parallel prefix (RPP) architecture, matching the speed of the widely used modulo-(2q ± 1) RPP adders. Consequently, we introduce a new moduli set τ+ = {22q+1, 2q + 2q−1 ± 1}, with over (2q+2)× dynamic range and adder speeds comparable to the conventional τ = {2q, 2q ± 1} set. However, to fully leverage τ+ in residue number system applications, a complete set of circuitries is necessary. This work focuses on the design and implementation of the forward and reverse converters for τ+. These converters consist of four and seven levels of carry-save addition units, culminating in a final modulo-(2q + 2q−1 ± 1) and modulo-(22q+1 + 22q−2 − 1) adder, respectively. Through analytical evaluations and circuit simulations, we demonstrate that the overall performance of a sequence of operations-including residue generation, k additions, and reverse conversion-using τ+ surpasses that of τ when k exceeds a certain practical threshold. Copyright © 2024, The Authors. All rights reserved.

关键词： Adders

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