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RNN Controller for Lane-Keeping Systems with Robustness and Safety Verification

RNN Controller for Lane-Keeping Systems with Robustness and ...

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American Control Conference (ACC)

作者： Ying Shuai Quan Jin Sung Kim Chung Choo Chung Dept. of Electrical Engineering Hanyang University Seoul Korea Dept. of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Dept. of Electrical Engineering Hanyang University Seoul Republic of Korea

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper proposes a Recurrent Neural Network (RNN) controller for lane-keeping systems, effectively handling model uncertainties and disturbances. First, quadratic constraints cover the nonlinearities brought by the RNN controller, and the linear fractional transformation method models the dynamics of system uncertainties. Second, we prove the robust stability of the lane-keeping system in the presence of uncertain vehicle speed using a linear matrix inequality. Then, we define a reachable set for the lane-keeping system. Finally, to confirm the safety of the lane-keeping system with tracking error bound, we formulate semidefinite programming to approximate the outer set of the reachable set. Numerical experiments demonstrate that this approach confirms the stabilizing RNN controller and validates the safety with an untrained dataset with untrained varying road curvatures.

关键词： Training Uncertainty Recurrent neural networks Semidefinite programming Robust stability Roads Robustness

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Modified EfficientNetB3 Deep Learning Model to Classify Colour Fundus Images of Eye Diseases 5

Modified EfficientNetB3 Deep Learning Model to Classify Colo...

引用

5th IEEE International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2023

作者： Sharma, Riya Gangrade, Jayesh Gangrade, Shweta Mishra, Ashish Kumar, Gautam Kumar Gunjan, Vinit Manipal University Jaipur Dept of Computer Science & Engineering Jaipur India Learning Manipal University Jaipur Dept. of Artificial Intelligence & Machine Jaipur India Manipal University Jaipur Dept of Information Technology Jaipur India Jaypee Institute of Information Technology Dept of Computer Science & Engineering Noida India CMR Institute of Technology Department of Computer Science & Engineering Hyderabad India

ISBN: (纸本)9798350338287

The only way to prevent blindness from eye problems is by early detection and prompt treatment. Although colour fundus photography (CFP) is useful for fundus inspection, there is a need for computer-assisted automated diagnosis tools due to the similarities between the early symptoms of many eye disorders. The suggested approach uses cutting-edge deep learning model to categorize images into several disease categories by learning distinguishing features from the input images. The high-resolution fundus photos from individuals with diabetic retinopathy (DR), glaucoma, cataract, and healthy eyes make up most of the dataset used for this research. The experimental findings show that the suggested system achieve 97% accuracy with modified efficientNetB3 model and surpasses current approaches for categorizing eye diseases. This approach may help doctors diagnose and treat eye conditions earlier, leading to better patient outcomes. © 2023 IEEE.

关键词： Color

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Classification of Gallbladder Cancer Using Average Ensemble Learning

Classification of Gallbladder Cancer Using Average Ensemble ...

引用

International Conference on electrical engineering and Information & Communication technology (ICEEICT)

作者： Sourav Basak Shuvo Mostafa Zaman Chowdhury Dept. of Biomedical Engineering Khulna University of Engineering & Technology Bangladesh Dept. of Electrical and Electronic Engineering Khulna University of Engineering & Technology Bangladesh

ISBN: (数字)9798350385779

ISBN: (纸本)9798350385786

Gallbladder cancer is a highly challenging malignancy within the field of oncology, distinguished by its diagnosis at an advanced stage and its restricted rates of survival. Gallbladder cancer classification from ultrasound images is a very difficult task due to poor image quality and speckle artifact. We suggest employing an ensemble of well-known Convolutional Neural Network models, such as VGG16, VGG19, XceptionNet, and ResNet50, to evaluate their effectiveness in differentiating between normal, benign, and malignant gall bladder conditions. As a result, the ensemble deep learning model significantly enhances the accuracy of classification.

关键词： Image quality Deep learning Ultrasonic imaging Speckle Gallbladder Oncology Ensemble learning

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Improved XM-18 Controller using Petroleum Liquid Gas-Based Automatic Heating Alternative for Egg Incubation in Developing Countries 5

Improved XM-18 Controller using Petroleum Liquid Gas-Based A...

引用

5th International Conference on Information technology for Education and Development, ITED 2022

作者： Musa, Mu'Azu Jibrin Salihu, Yahaya Otuoze Yusuf, Moshood Usman, Zubair Gatugel Ahmadu Bello University Dept. of Electronics and Telecommunications Engineering Zaria Nigeria Kaduna Polytechnic Dept. of Computer Engineering Kaduna Nigeria Kaduna Polytechnic Dept. of Electrical Electronics Engineering Kaduna Nigeria

ISBN: (纸本)9781509064229

Egg incubation is significant to modern agriculture;hence in this paper the design, implementation and integration of the Petroleum Liquid Gas (PLG) control into the existing XM-18 incubator controller will be presented. XM-18 controller is an automatic egg incubator controller, which has a reputable history of high % of hatchability and very low chick's mortality if operated on an uninterrupted AC power supply. However, the high rate of fluctuation of power supply in developing countries has resulted to the poor performance of the XM-18 controller. This hence makes it necessary to improve the XM-18 controller to suit the unique requirements of developing countries. The XM-18 circuit was improved using PIC12F683, ignition coil, spark plug, DC gas valve, and camp gas stove to accommodate the PLG and to automatically control the PLG as a heating source in the absence of the AC source. In so doing, the problem of power failure has been taking care by the standby PLG. With this improvement, the huge cost of running standby generator or setting of a power inverter plan is substituted with the low cost of the PLG control design. Furthermore, the huge labor associated with the use of kerosene source is now substituted with the autonomous control of the PLG. The improved LPG control incubator of 120 eggs capacity was compared with the Kerosene source incubator and incubator running on AC source and the hatchability of 65.3% and 72.22% respectively was obtained, while the hybrid of XM-18 PLG gave a hatchability of 94.8%. © 2022 IEEE.

关键词： Controllers

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A Comparative Analysis on Deep Learning Approaches for Patient Data Privacy Using Electronic Health Record 3

A Comparative Analysis on Deep Learning Approaches for Patie...

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3rd Odisha International Conference on electrical Power engineering, Communication and Computing technology, ODICON 2024

作者： Mishra, Ritunsa Satpathy, Rabinarayan Pati, Bibudhendu Sri Sri University Faculty of Engineering & Technology Odisha Cuttack India Rama Devi Women's University Dept. of Computer Science Odisha Bhubaneswar India

ISBN: (纸本)9798350354379

The widespread adoption of electronic health records (EHRs) across virtually all U.S. hospitals has facilitated the accumulation of vast amounts of unstructured medical data, which, while invaluable for advancing healthcare, also pose significant privacy risks. This paper presents a comparative analysis of various deep learning strategies aimed at bolstering the privacy of EHR data before it is made publicly accessible. We introduce and evaluate two innovative deep learning models on the MIMIC_III dataset, measuring their performance in terms of accuracy and F1 scores. Our research employs these models within a framework that emphasizes 'patient privacy preservation' (P3) and explores the application of differential privacy techniques using Recurrent Neural Networks (RNNs) and Artificial Neural Networks (ANNs) to secure the sharing of training data. The results demonstrate the efficacy of these advanced methodologies in enhancing the privacy protections of EHR data, thereby offering crucial insights for medical research. Our findings underscore the critical role of privacy-preserving measures in the dissemination of EHR data and validate the potential of sophisticated deep learning approaches to ensure secure data exchange. This study contributes to the broader discourse on reconciling the needs of medical research with the imperative to protect patient confidentiality. © 2024 IEEE.

关键词： Electronic health record

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A Compact Petal Shaped Two-Port MIMO Antenna for Quad-Band Millimeter Wave 5G Applications

A Compact Petal Shaped Two-Port MIMO Antenna for Quad-Band M...

引用

2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Parveez Shariff, B.G. Ali, Tanweer Mane, Pallavi R Kumar, Pradeep Kumar, Praveen Manipal Institute of Technology Manipal Academy of Higher Education Dept. of Electronics and Communication Manipal576104 India University of KwaZulu-Natal Discipline of Electrical Electronic and Computer Engineering Durban4041 South Africa

ISBN: (纸本)9798350326062

A compact size nature-inspired, petal shaped two-port MIMO antenna is proposed to operate at V- and E-band. Initially, a single-element antenna is designed to resonate for quad-band. The proposed antenna resonates at 41.7 GHz, 51.75 GHz, 71.4 GHz, and 78.9 GHz, with bandwidths of 41.25-42.3 GHz, 51.45-52.05, 70.35-72.3 GHz, and 78.15-79.65 GHz respectively. A two-port MIMO antenna design is supported by a full ground plane, where radiating elements are apart 0.25λ_0 from the edges. The overall dimension of the structure is 0.726λ_0x1.675λ_0. The MIMO antenna has obtained isolation of -30.36, -31.27, -22.9, and -34.27 dB at respective bands. A decent gain of 8.64, 7.93, 7.15, and 11.84 dBi is obtained at respective bands. The proposed MIMO antenna has satisfied the ECC, DG, CCL, and TARC validation. This antenna is suitable for aeronautical mobile, maritime, 5G mobile, and radio navigation applications. © 2023 IEEE.

关键词： 5G mobile communication systems

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Classification of Imbalanced Data in E-Commerce 1

Classification of Imbalanced Data in E-Commerce

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1st International Conference on Smart and Sustainable Technologies in Energy and Power Sectors, SSTEPS 2022

作者： Anthoniraj, S. Kumar, A Naresh Hemakumar Reddy, Galiveeti Raju, More Dept. of Computer Science and Engineering Karnataka Bangalore India Institute of Aeronautical Engineering Dept. of Electrical and Electronics Engineering Hyderabad India Akhildev IPR and Research Services Department of Research and Development Greater Noida India Maulana Azad National Institute of Technology Bhopal Dept. of Electrical Engineering Madhya Pradesh Bhopal India

ISBN: (纸本)9781665464147

The Privileges for the machine learning algorithms are actuality to lead the online exchange world with their does and power to match the fully customizable plot involvement. From expectable actions to social media to perceptive ways to shop online, big data quickly suppers within and is used frequently. Unfortunately, rare data conditions, called algebraic data, are still essentially unnoticed due to the uncommon of analytics method designed to manage the static data sets and external "quickening". As a result, very important rare functioning condition are being mistreated and leads to high cost loss Over the past applies, a number of ways to address the issue raised ranging from data processing to changes of the present algorithms having appeared with changing success. Though, most of them having major downsides when there are used indifferent claims domains due to the different nature of the active data presence. In the big E-Commerce domain, we suggest an unabled at a management methods, which consists of diverse subdivision solution that mix multi-methods data systems and algorithms to create the right balance between forecasts, accuracy and precision. Our solution helps in improving data service ability, class accuracy and results in cost analysis of large data sets used to mark client cognizance in E-Commerce. © 2022 IEEE.

关键词： Deep learning

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Epileptic Seizure Detection from EEG: Targeting Specific Brain Regions with Machine Learning Approaches

Epileptic Seizure Detection from EEG: Targeting Specific Bra...

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International Conference on electrical, computer and Communication engineering (ECCE)

作者： Mohammad Mostakim Md. Emdadul Haque Maruf Diba Das Md. Fazlul Karim Khondakar Mehdi Hasan Chowdhury Aditta Chowdhury Dept. of Electrical and Electronic Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of Biomedical Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The electroencephalogram (EEG) signal plays a vital role in diagnosing epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data, and the detection of epileptic activity requires an expert to analyze the entire length of the EEG data. The traditional methods of analysis being tedious, many automated diagnostic systems for epilepsy have emerged in recent years. This study aims to determine the most effective brain region in seizure detection so that the use of unnecessary electrodes and other time-consuming analyses can be reduced. Data from three distinct brain regions-central, frontal, and occipital are utilized. The denoised EEG signals are utilized to extract the time domain, frequency domain, and entropy-based features. Later, the features are used to develop machine learning algorithms for classifying the signals. Upon analysis with different combinations of features, the best accuracy has been achieved from the frontal region of the brain using the boosted tree algorithm with an accuracy of 83.5%. This approach leverages the diverse information provided by each region to enhance detection reliability. In the future, further analysis can be done targeting the frontal region for improving the performance.

关键词： Electrodes Accuracy Machine learning algorithms Fast Fourier transforms Epilepsy Machine learning Feature extraction Brain modeling Electroencephalography Recording

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The Project of Universal Static Converter Prototype Module for Aircraft Power Converting Equipment 24

The Project of Universal Static Converter Prototype Module f...

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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Korobkov, Dmitri V. Zaichenko, Georgy I. Ashurkov, Nikita V. Radosteva, Alena I. Novosibirsk State Technical University Dept. of Electronics and Electrical Engineering Novosibirsk Russia Novosibirsk State Technical University Dept. of Design and Technology of Radio-electronic Means Novosibirsk Russia

ISBN: (纸本)9798350336870

The article presents the methodology and the result of designing of universal static converter prototype module for aircraft power converting equipment. The module is designed for use as part of AC 'variable speed - constant frequency' power generation systems with an intermediate DC voltage link. The module is made according to the scheme of a two-level three-phase voltage inverter. The versatility of the module lies in the fact that the module is designed to operate in two modes - active rectifier and voltage inverter. In the active rectifier mode, the module complies with the requirements of GOST R 54073-2017 when operating from an AC single-phase or three-phase variable frequency voltage. In the voltage inverter mode, the module generates AC single-phase or three-phase constant frequency voltage in accordance with the requirements of the specified standard. In the single-phase mode, it is possible to use the phase shift algorithm for the reference voltages of the pulse-width modulation of the three racks of the module. © 2023 IEEE.

关键词： Static converters

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Achieving Magnetic Force and Cogging Torque Reduction in a Permanent Magnet Generator with Concentrated Slot Technique and Pole Arc Optimization at Magnet Edge

Achieving Magnetic Force and Cogging Torque Reduction in a P...

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International Conference on electrical Machines and Systems (ICEMS)

作者： Syamsir Abduh Tajuddin Nur Eduard Muljadi Herlina Dept. of Electrical Engineering Institut Teknologi PLN Dept. of Electrical Engineering Universitas Katolik Indonesia Atma Jaya-Jakarta Indonesia Dept. of Electrical and Computer Engineering Auburn University U.S.A Dept. of Electrical Engineering Sriwijaya University South Sumatera Indonesia

ISBN: (数字)9784886864406

ISBN: (纸本)9798350379105

The objective of this study is to minimize cogging torque in permanent magnet machines (PMMs) utilized for renewable energy generation. The primary concern identified is the interaction between the magnetic flux of the rotor and the slot opening of the stator, which interferes with rotor rotation and results in reduced efficiency. The techniques of concentrated slotting and pole arc optimization (PAO) are employed to address this issue at the magnet's edge. The study utilizes the response surface method (RSM) in conjunction with the finite element method (FEMM version 4.2) to illustrate a reduction in cogging torque by as much as 99.04% relative to the baseline model. This result underscores the capability of these techniques to substantially improve PMM performance, especially within renewable energy applications.

关键词： Magnetic flux Forging Renewable energy sources Torque Simulation Permanent magnet generators Rotors Stators Response surface methodology Optimization

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