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CNN Based Features Extraction and Selection Using EPO Optimizer for Cotton Leaf Diseases Classification

computers, Materials & Continua 2023年第9期76卷 2779-2793页

作者： Mehwish Zafar JaveriaAmin Muhammad Sharif Muhammad Almas Anjum Seifedine Kadry Jungeun Kim Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science University ofWahWah Cantt47040Pakistan National University of Technology(NUTECH) Islamabad44000Pakistan Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Worldwide cotton is the most profitable cash *** year the production of this crop suffers because of several *** an early stage,computerized methods are used for disease detection that may reduce the loss in the production of *** several methods are proposed for the detection of cotton diseases,however,still there are limitations because of low-quality images,size,shape,variations in orientation,and complex *** to these factors,there is a need for novel methods for features extraction/selection for the accurate cotton disease *** in this research,an optimized features fusion-based model is proposed,in which two pre-trained architectures called EfficientNet-b0 and Inception-v3 are utilized to extract features,each model extracts the feature vector of length N×*** that,the extracted features are serially concatenated having a feature vector lengthN×*** prominent features are selected usingEmperor PenguinOptimizer(EPO)*** method is evaluated on two publically available datasets,such as Kaggle cotton disease dataset-I,and Kaggle *** EPO method returns the feature vector of length 1×755,and 1×824 using dataset-I,and dataset-II,*** classification is performed using 5,7,and 10 folds *** Quadratic Discriminant Analysis(QDA)classifier provides an accuracy of 98.9%on 5 fold,98.96%on 7 fold,and 99.07%on 10 fold using Kaggle cotton disease dataset-I while the Ensemble Subspace K Nearest Neighbor(KNN)provides 99.16%on 5 fold,98.99%on 7 fold,and 99.27%on 10 fold using Kaggle cotton-leaf-infection dataset-II.

关键词： Deep learning cotton disease detection features selection classification efficientnet-b0 inception-v3 quadratic discriminant analysis subspace KNN

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Squid-inspired and wirelessly controllable display for active camouflage in aquatic-environment

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npj Flexible Electronics 2024年第1期8卷 900-909页

作者： Doyoung Kim Seung Won Seon Minkyung Shin Jihwan Kim Bogeun Kim Janghoon Joo Sang Uk Park Wooseok Kim Hee Kyu Lee Byeong Woon Lee Se Gi Lee Su Eon Lee Ji-Hun Seo Seung Ho Han Bong Hoon Kim Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon 16419Republic of Korea Department of Smart Wearable Engineering Soongsil UniversitySeoul 06978Republic of Korea Electronic Convergence Materials and Devices Research Center Korea Electronics Technology Institute(KETI)Seongnam 13509Republic of Korea Department of Materials Science and Engineering Korea UniversitySeoul 02841Republic of Korea Department of Robotics and Mechatronics Engineering DGISTDaegu 42988Republic of Korea

Achieving optimal camouflage in an aquatic environment necessitates the ability to modulate transmittance in response to the surrounding obscurity and potential *** adaptation involves a dynamic transition from transparency to a deep-blue color,especially in low-light or dark *** a strategy promotes a seamless assimilation with the surroundings,enabling the absorption of searchlights and,subsequently,diminishing the risk of detection by ***,the presence of sophisticated mechanisms that facilitates stable and efficient control of transmittance is imperative,enabling smooth transition between transparent and deep-blue hues within the aquatic *** study presents nature-inspired programmable camouflage system that integrates an electrochromic display as the primary transmittance change element and a wireless base module for power and data *** technology offers a robust and flexible construction,ensuring stable operation as demonstrated through mechanical-fatigue experiments and quantitative simulation.A custom circuit and a power-control software package enable active control of multiple electrochromic displays while submerged in water.

关键词： transparency submerged lights

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Toward hybrid integration of exotic materials in an electronic-photonic CMOS platform via substrate removal

Toward hybrid integration of exotic materials in an electron...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Onural, Deniz Gevorgyan, Hayk Eschenbaum, Carsten Koos, Christian Popovic, Milos Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Karlsruhe Institute of Technology Karlsruhe76131 Germany

We demonstrate direct access to the silicon device layer of a monolithic CMOS electronics-photonics platform with a full-digital back-end-met al stack, in post-fabrication at die level, allowing the integration of fun... 详细信息

ISBN: (纸本)9781957171258

关键词： Substrates

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Cloud thermodynamic phase retrievals with a low-cost, division-of-focal-plane polarization camera 28

Cloud thermodynamic phase retrievals with a low-cost, divisi...

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Earth Observing Systems XXVIII 2023

作者： Venkatesulu, Erica Shaw, Joseph A. Electrical and Computer Engineering Department and Optical Technology Center Montana State University P.O. Box 173515 BozemanMT United States

ISBN: (纸本)9781510665842

Cloud thermodynamic phase is an important parameter in climate models and cloud remote sensing because it controls whether a cloud tends to have a net heating or cooling effect and it must be known to retrieve other cloud parameters. Passive remote sensing of cloud thermodynamic phase using shortwave infrared radiance ratios is a well-known technique, and adding polarization sensitivity to the radiance ratio method can increase accuracy. Ground-based passive polarimetric remote sensing of cloud phase has also been performed in visible and near infrared wavelengths. Prior work has relied on highly sensitive, expensive polarimeters to detect the small change in polarization state between ice and liquid clouds. We explored the use of a low-cost, commercial division-of-focal-plane polarization imager for cloud thermodynamic phase retrievals. We calibrated and deployed a monochrome polarization imager, with both a moderate field-of-view lens and a fisheye lens. The imagers were deployed alongside a verified dual-polarization lidar that provided a truth measurement at the zenith. In this paper, we discuss the relationship between the Stokes S1 parameter measured by the low-cost polarization imager with both lenses and the cloud thermodynamic phase retrieved by a dual-polarization lidar. © 2023 SPIE · 0277-786X ·

关键词： Cameras

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ASSESSMENT OF REANALYSIS DATA FOR SOLAR PV OUTPUT FORECASTING IN THE PHILIPPINES: CASE OF PANGASINAN, NEGROS OCCIDENTAL, AND DAVAO DEL NORTE

ASSESSMENT OF REANALYSIS DATA FOR SOLAR PV OUTPUT FORECASTIN...

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2023 Philippine Geomatics Symposium, PhilGEOS 2023

作者： Gavina, C.J.A. Ibañez, J.A. Benitez, I.B. Lumabad, C.D. Principe, J.A. Department of Electrical Engineering Pamantasan ng Lungsod ng Maynila Philippines National Engineering Center University of the Philippines Diliman Quezon City Philippines Electrical Engineering Department FEU Institute of Technology City of Manila Philippines Department of Computer Electronics and Electrical Engineering Cavite State University Don Severino Delas Alas Campus Indang Cavite Philippines Department of Geodetic Engineering University of the Philippines Diliman Quezon City Philippines

The sustainable energy transition in the Philippines requires accurate forecasting of solar PV output to optimize energy efficiency and grid management. While existing studies have emphasized the positive correlation between solar irradiance and PV production, this study aims to explore whether forecasting improves with the inclusion of weather data. This research conducts a comparative analysis between relying solely on solar irradiance against integrating various weather parameters to enhance solar PV output forecasting. The study focuses on three distinct locations (Pangasinan, Negros Occidental, and Davao Del Norte) and employs two models per each site: Model 1 (M1), which relies only on solar irradiance as predictors, and Model 2 (M2), which incorporates solar irradiance and weather parameters. Using Fifth Generation ECMWF Reanalysis (ERA5) Data, Principal Component Analysis (PCA) is conducted on the significant weather parameters. Extreme Gradient Boosting (XGBoost) with 5-fold nested cross-validation is applied for solar PV output forecasting. Models are assessed using Mean Absolute Percentage Error (MAPE) and skill scores. Results showthat while solar irradiance alone suffices for predicting solar PV output in Negros Occidental, incorporating weather parameters improves forecasting accuracy in Davao Del Norte and Pangasinan. This paper recommends caution in generalizing the findings to different regions with varying weather patterns, as the forecasting performance of the models is influenced by data quality, specific location, and prevailing weather conditions. © Author(s) 2024.

关键词： Principal component analysis

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A computer-aided diagnosis system for breast pathology: a deep learning approach with model interpretability from pathological perspective

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Service Oriented Computing and Applications 2023年第2期18卷 183-193页

作者： Hsu, Wei-Wen Wu, Yongfang Chen, Chung-Hao Hao, Chang Hou, Yu-Ling Gao, Xiang Shao, Yun Zhang, Xueli He, Tao Tai, Yanhong Department of Computer Science and Information Technology National Taitung University Taitung Taiwan Department of Pathology The Fifth Medical Center of Chinese PLA General Hospital Beijing China Department of Electrical and Computer Engineering Old Dominion University Norfolk VA United States Institute of Big Data Technology Bright Oceans Corporation Beijing China

In this study, a computer-aided diagnosis (CAD) system for whole-slide images (WSIs) with breast cancer was proposed to achieve lesion detection and classification. Different from the previously proposed works that performed segmentation directly and applied the segmentation metrics for performance evaluation, here we computed the accuracy in patch-level, region-level, and slide-level to access our proposed framework to meet the clinical requirements, instead of simply regarding it as an AI segmentation task. To achieve that for WSIs, lesion detection was conducted at high magnification (× 40) first for region proposal by patching using the modified AlexNet model;and then, several patches were sampled from the detected regions at lower magnification (× 10) to observe cells’ patterns for lesion classification by the model of ResNet50. With such fashion, the deep features being distinguishing in lesion classification from the convolutional neural networks (CNN) were further analyzed in this work to provide comprehensive interpretability for the proposed CAD system based on pathological knowledge. For our experiments, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). The slide-level accuracy rate for the three-category classification reached 90.8% (99/109) through a fivefold cross-validation and achieved 94.8% (73/77) on the testing set. In addition, the learned features reflect the clinical insights in lesion classification for explainable AI, which enhanced the reliability and validity of our proposed system. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

关键词： computer aided diagnosis

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Improve Harris Hawkes optimizer algorithm via Laplace crossover

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2057-2072页

作者： Nasab, Seyed Taha Mousavi Abualigah, Laith Department of Applied Mathematics Iran University of Science and Technology Tehran Iran Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Nowadays, the speed of solving optimization problems by increasing various issues and the number of variables is critical. The Harris Hawk optimization method is a brand-new, intelligent system that resolves optimization issues by mathematically simulating the natural behavior of hawks. In this study, the Harris Hawks optimization method and the Laplace crossover operator are merged, and a new enhanced Harris Hawks algorithm (LX-HHO) based on the Laplace optimization algorithm is suggested. The purpose of improving this algorithm is to increase the convergence speed while maintaining good accuracy in achieving the optimal solution. The results of the proposed method on the test functions demonstrate that the algorithm has achieved faster convergence than the original version of the Harris Hawks algorithm and other meta-heuristic algorithms. This is due to the algorithm's accuracy in obtaining the best answer in these functions and to a reduction in the evaluation of the optimization function. Also, comparing and evaluating the proposed algorithm with other algorithms by Friedman and MAE test shows the superiority of the LX-HHO algorithm. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Optimization

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Investigation on Structures of Axial Gap Type Magnetic Multiple Spur Gear for In-Wheel Motor System of Electric Vehicle

Investigation on Structures of Axial Gap Type Magnetic Multi...

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2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023

作者： Kamijo, Taiga Aiso, Kohei Akatsu, Kan Aoyama, Yasuaki Shibaura Institute of Technology Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan Yokohama National University Division of Intelligent Systems Engineering Department of Faculty of Engineering Yokohama Japan Center for Technology Innovation - Materials Hitachi Ltd. Research & Development Group Ibaraki Japan

ISBN: (纸本)9798350314274

A novel drive system using Magnetic Multiple Spur Gear (MMSG) and multiple high-speed motors is characterized by small size, lightweight, and high efficiency even at high-speed region, it is expected to apply to in-wheel motor systems. However, there is a risk of contact between the rotors when applied to in-wheel motor system. In this study, a novel axial-gap MMSG is proposed to solve this problem, stabilize the air gap between the high-speed and low-speed rotors, and effectively utilize the magnets, and its performance is evaluated by finite element analysis. © 2023 IEEE.

关键词： Electric vehicles

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WiMA:Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

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computers, Materials & Continua 2023年第5期75卷 2347-2363页

作者： Sohaib Manzoor Hira Manzoor Saddaf Rubab Muhammad Attique Khan Majed Alhaisoni Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Electrical Engineering Mirpur University of Science and Technology(MUST)Mirpur-10250(AJK)Pakistan Faculty of Electronics Telecommunications and InformaticsGdansk University of Technology80-233 GdanskPoland Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates National University of Sciences and Technology(NUST) Islamabad44000Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Despite the planned installation and operations of the traditional IEEE 802.11 networks,they still experience degraded performance due to the number of *** of the main reasons is the received signal strength indicator(RSSI)association problem,in which the user remains connected to the access point(AP)unless the RSSI becomes too *** this paper,we propose a multi-criterion association(WiMA)scheme based on software defined networking(SDN)in Wi-Fi *** association solution based on multi-criterion such as AP load,RSSI,and channel occupancy is proposed to satisfy the quality of service(QoS).SDNhaving an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput *** implementWiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network *** performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30%and enhances the throughput by 20%–50%,hence maintaining user fairness and accommodating more wireless devices and traffic load in the network,when compared to traditional client-driven(CD)approach and state of the art Wi-Balance approach.

关键词： Association multi-criterion SDN Wi-Fi

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Detection of Magnetite Rust Using Circular Microstrip Patch Antenna-based Chipless RFID Sensor

Detection of Magnetite Rust Using Circular Microstrip Patch ...

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2023 International electrical engineering Congress, iEECON 2023

作者： Nongpromma, Sirisak Janin, Suwan Kaemarungsi, Kamol Boonpoonga, Akkarat Chudpooti, Nonchanutt Bannawat, Lakkhana King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Rajamangala University of Technology Lanna Lampang Faculty of Engineering Department of Engineering and Technology Lampang52000 Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Industrial Physics and Medical Instrumentation Bangkok Thailand Rajamangala University of Technology Rattanakosin Faculty of Engineering Department of Computer Engineering Nakhon Pathom Thailand

ISBN: (纸本)9798350332360

In this paper, detection of the magnetite rust is presented by using a chipless RFID sensor based on a circular microstrip patch antenna (CMPA). The sensor is designed at the resonant frequency of 4.89 GHz by using a single-layer PCB with its dielectric constant of 4.3. Simulations were conducted to verify that the designed sensor can detect the magnetite rust through shifted resonant frequency. In simulations, the sensor was mounted on the iron with its magnetite rust. The width and depth of iron rust were varied in order to investigate the effect of iron rust on the resonant frequency. Simulation results have been shown that the proposed chipless RFID sensor and RCS' can be utilized to detect the effect of the iron rust. © 2023 IEEE.

关键词： Microstrip antennas

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