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Retinal disorder diagnosis based on hybrid deep learning models

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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An Effective Machine Learning Approach with Hyperparameter Tuning for Sentiment Analysis

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Data Intelligence 2025年第1期7卷 70-94页

作者： Saima Kanwal Ali Raza Chunyan Bai Dawei Zhang Jing Wen Dileep Kumar Engineering Research Centre of Optical Instrument and Systems Ministry of Education and Shanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and TechnologyNo.516 Jun Gong RoadShanghai 200093China Department of Mathematics School of SciencesHebei University of TechnologyBeichen CampusTianjin 300401China Shanghai Publishing and Printing College Shanghai 200093China Zhangjiang Laboratory Shanghai 200120China Department of Electronic Engineering Faculty of EngineeringThe Islamia University of Bahawalpur63100PunjabPakistan

Sentiment analysis depends on individuals’comments and opinions on *** from social media platforms like Twitter,Quora,or Facebook poses challenges due to informal language,including acronyms,misspellings,and ambiguous ***,hyperparameters in machine learning models significantly impact *** address these issues,we propose advanced feature engineering techniques in Natural Language Processing(NLP)and hyperparameter optimization to enhance prediction accuracy and generalization *** study employs Naïve Bayes,Logistic Regression(LR),Multi-layer Perceptron(MLP),and Support Vector Machine(SVM)to classify sentiments in tweets about Elon Musk’s potential acquisition of *** dataset,consisting of 100,000 tweets,is fetched using the Twitter representational state transfer application programming interface(REST API).We outline a sentiment analysis procedure to classify unstructured Twitter data,identify influential keywords,and categorize sentiments as Positive,Negative,or *** a hybrid Lexicon NLP approach,we extract contextually significant emotionally charged words and assign sentiment *** optimization via automated search methods ensures alignment with classifier performance *** achieved an impressive accuracy rate of 97%.Cross-validation minimizes random variations,providing a reliable assessment of the model’s generalization capabilities,and demonstrating the method’s accuracy in predicting sentiments with larger new unseen standard datasets,and varying sentiment.

关键词： Hybrid lexicon Logistic regression(LR) Machine learning Natural language processing(NLP)

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Physiological and psychological effects of spotlight in a limited space

Physiological and psychological effects of spotlight in a li...

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AIAA Science and technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Yoshino, Karin Takahashi, Masaki School of Science for Open and Environmental Systems Keio University Kanagawa Yokohama223-8522 Japan Faculty of Science and Technology Department of System Design Engineering Keio University Kanagawa Yokohama223-8522 Japan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In a limited space, such as pressurized rovers, insufficient personal space is a source of stress for astronauts. The aim of this study is to mitigate effects caused by personal space invasions. The proposed system for that problem is using a spotlight system that automatically adjusts based on vital sign feedback. In this study, experiments with human subjects to test the effects of spotlight exposure are conducted. Specifically, respiration signal was measured to investigate the relationship between respiration, distance and the spotlight in a limited space. The results suggest that changes in respiration may reflect the effects of spatial distance, suggesting that respiration may serve as an indicator of personal spatial discomfort. Furthermore, the usefulness of spotlight lighting in confined spaces was demonstrated through its effects on breathing, demonstrating its potential to enhance comfort by adjusting lighting based on vital sign. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Lighting

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Reinforced Residual Encoder–Decoder Network for Image Denoising via Deeper Encoding and Balanced Skip Connections

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Big Data and Cognitive Computing 2025年第4期9卷 82-82页

作者： Boucherit, Ismail Kheddar, Hamza Laboratory of Advanced Electronic Systems Department of Electrical Engineering Faculty of Technology University of Medea Medea26000 Algeria

Traditional image denoising algorithms often struggle with real-world complexities such as spatially correlated noise, varying illumination conditions, sensor-specific noise patterns, motion blur, and structural distortions. This paper presents an enhanced residual denoising network, R-REDNet, which stands for Reinforced Residual Encoder–Decoder Network. The proposed architecture incorporates deeper convolutional layers in the encoder and replaces additive skip connections with averaging operations to improve feature extraction and noise suppression. Additionally, the method leverages an iterative refinement approach, further enhancing its denoising performance. Experiments conducted on two real-world noisy image datasets demonstrate that R-REDNet outperforms current state-of-the-art approaches. Specifically, it attained a peak signal-to-noise ratio of 44.01 dB and a structural similarity index of 0.9931 on Dataset 1, and it obtained a peak signal-to-noise ratio of 46.15 dB with a structural similarity index of 0.9955 on Dataset 2. These findings confirm the efficiency of our method in delivering high-quality image restoration while preserving fine details. © 2025 by the authors.

关键词： Signal to noise ratio

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Enhancing Power Quality in Grid Connected PV systems: Investigating the Influence of Solar Irradiance on Harmonic Mitigation and Control Techniques Using Hysteresis and PI Controllers 4th

Enhancing Power Quality in Grid Connected PV Systems: Inves...

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4th International Conference on Electronic engineering and Renewable Energy systems, ICEERE 2024

作者： Oukili, Mohamed Melhaoui, Mustapha Chennani, Mohammed Ouchbel, Taoufik Electrical Systems Energy Efficiency and Telecommunications Laboratory Faculty of Sciences and Technologies Cadi Ayyad University Marrakesh Morocco Electrical Engineering and Maintenance Laboratory Higher School of Technology Mohammed I University Oujda Morocco

ISBN: (纸本)9789819606436

This paper proposes the utilization of a Parallel Active filter (PAF) controlled by two different methods, proportional-integral (PI) and hysteresis controllers, in combination with L-filter, in order to enhance the power quality by eliminating the harmonic component generated by photovoltaic gen-erators in electrical grid. A PQ theory is used to extract the harmonic component of the injected current into the power grid. However, the quality of injected current is influenced by the solar irradiance levels. Hence, this study aims to investigate the influence of solar irradiance on the Total Harmonic Distortion of the injected current (THDi) and to conduct a comparative analysis of hysteresis and PI controllers in Grid-Connected PV systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Solar irradiance

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A Design Study on Integrated Complex Coefficient Filters with Peripheral Circuits for Accurate Frequency Response Measurement

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and systems 2025年第1期145卷 16-24页

作者： Shouno, Kazuhiro Sato, Lina Fukagawa, Kanta Tanimoto, Hiroshi Muto, Cosy Division of Information Engineering University of Tsukuba 1-1-1 Tennoudai Ibaraki Tsukuba305-8573 Japan Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master’s Program in Computer Science University of Tsukuba Japan Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan Faculty of Education Nagasaki University 1-14 Bunkyo-machi Nagasaki852-8521 Japan

This paper proposes a measurement technique for an integrated complex filter. The proposed method is based on two measurement methods with integrated circuitry for calibration. It is accomplished by applying square waves to an FUT (Filter Under Test) instead of sinusoidal waves or by superposing transfer characteristics obtained by applying a single sinusoidal wave to an FUT. In both of the above methods, the output signal connected to the external measurement equipment via a 50 Ω coaxial cable and so on. In this case, the output signal of the FUT should be amplified by internal or external amplifiers, which degrades the response. However, it is cancelled out by the proposed calibration circuitry with some analog switches. In addition to the above, for the RC polyphase filter, the source resistance and the load capacitance degrade the measurement results and their effect is discussed. The validity of the proposal is confirmed through computer simulation for a third-order RCPF whose passband is 8–40 MHz fabricated by Phenitec 0.6 µm CMOS process. It is shown that the measurement error is −1.10 dB for the square-wave method and −1.00 dB and −0.43 degrees for the superposition method at 40 MHz. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Capacitance

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Correction: Online channel selection within a capital-constrained green supply chain under government subsidies

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Environment, Development and Sustainability 2025年 1-10页

作者： Qiu, Yuzhuo Wang, Shu Pardalos, Panos M. School of Business Nanjing University of Information Science & Technology Nanjing China Department of Industrial and Systems Engineering Faculty of Engineering University of Florida Gainesville USA

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Development of Automatic Cartesian Robot Cannabis Seeder using LabVIEW

Development of Automatic Cartesian Robot Cannabis Seeder usi...

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International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications engineering (ECTI-NCON)

作者： Rujipan Kosarat Keattipoom Sangwai Anan Wongjan Department of Software Engineering Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand Department of Electronic Engineering and Automatic Control Systems Faculty of Engineering Rajamangala University of Technology Lanna Chiangmai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This article describes the invention of autonomous cannabis seeding equipment to reduce contamination and planting time. The automated cannabis seeder employs an NI myRIO control board to operate a y-axis stepper motor attached to a ball screw to move along the breadth of each row of 14 seed trays. Soil drilling and burial Drill all holes at the same depth. This promotes seed germination and lowers human-seed germ contamination. These 7 soil drill heads and 7 seeders use 3D printers to design and shape the workpiece. An 800-watt air pump smokes the cannabis seeds. Linear electric motors function in two rows in the z-axis. The buffer reverses the drowning process from row 14 to the first row, starting from the 3rd row and continuing through the final series of steps until 14 rows in the y-axis are complete. The hardware controls all program activities in LabVIEW. We tested the automated cannabis seeding machine 100 times on average, sowing cannabis seeds into 98 seed trays and dropping 93 seeds at 94.80% efficiency in 10.38 minutes. A 16 percent faster machine than human work is available.

关键词： Technological innovation Motor drives Shape Soil Pulse width modulation Three-dimensional printing Seeds (agriculture) Printers Robots Contamination

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Evaluation of the physical properties of local wheat husk ash and its effects on the compressive strength of hardened cement paste

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Discover Chemistry 2025年第1期2卷 1-14页

作者： Farhat, Masuoda Al Madani, Mohammed A. Abdullah, Taha Embaya, Mohammed Saeed, Abdulla Saleh, Abdulla Fenniche, Fares Khane, Yasmina Materials and Corrosion Engineering Department Sebha University Sabhā Libya Chemical Engineering Department Sebha University Sabhā Libya Process Engineering Department Faculty of Science and Technology Ghardaïa University Bounoura Algeria Materials Energy Systems Technology and Environment Laboratory Faculty of Sciences and Technology University of Ghardaïa Ghardaïa Algeria Faculty of Sciences and Technology University of Ghardaïa Ghardaïa Algeria

The dehusking of wheat results in the significant annual production of wheat husk, an agricultural byproduct. This waste is often burned outdoors to generate energy, with the resulting ash (wheat husk ash, WHA) typically disposed of in landfills, leading to environmental harm. To mitigate the negative environmental impact, this research explores the potential of utilizing wheat husk ash to enhance the mechanical properties of cement paste. The study involved the partial replacement of Portland cement in the mixture with varying proportions of wheat husk ash (0, 5, 10, 15, 20, 25 and 30%) to produce WHA blended cement with sample with 0% as the control, and examined the compressive strength of hardened cement paste (HCP) at different curing ages (3, 7, 14, and 28 days). Chemical water tests revealed that the water-to-cement ratio required for standard HCP increased linearly with the proportion of WHA in the mix. Additionally, it was found that the bulk density of HCP decreased as the percentage of WHA increased. Compressive strength tests of the HCP samples yielded promising results, particularly with 15% (30.04) and 20% (28.73) WHA replacement. The compressive strength improved by approximately 14% with 15% WHA replacement and by 10% with 20% WHA replacement. In conclusion, the incorporation of wheat husk ash (WHA) at optimal percentages in cement mixtures enhances the compressive strength of hardened cement paste, particularly after full curing. This study highlights not only the mechanical improvements achieved through WHA integration but also its potential to significantly reduce the carbon footprint of cement production, demonstrating a dual advantage of improved material performance and environmental sustainability.

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Phase Distribution of the Large-Scale Scattered Field from the Sea Surface

Phase Distribution of the Large-Scale Scattered Field from t...

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European Conference on Antennas and Propagation, EuCAP

作者： Giacomo Melloni Torbjörn Ekman Department of Electronic Systems Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Trondheim Norway

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

A new phase distribution model of the scattered field from the sea surface is proposed, combining Geometrical-based Stochastic Channel Modeling (GSCM) and the Effective Roughness (ER) approaches. The presented model applies to the large-scale roughness of the sea surface. Assuming the sea surface elevation follows a Normal distribution, a phase relation model is derived, capturing the statistical correlation between distinct scattering points across the surface. The phase correlation function is derived from the sea surface's autocorrelation function (ACF), highlighting the influence of sea state parameters on the resulting phase distribution. The model demonstrates a strong dependence of the phase distribution on the characteristics of sea conditions and is applicable to any surface with a correlated Normal distributed roughness profile.

关键词： Sea surface Wind speed Scattering Stochastic processes Gaussian distribution Sea state Radio propagation Predictive models Surface roughness Rough surfaces

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