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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1387-1404页

作者： Hao Qi mohamed Sharaf Andres Annuk Adrian Ilinca mohamed A.mohamed College of Electrical and New Energy China Three Gorges UniversityYichang443002China Department of Industrial Engineering College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia Institute of Forestry and Engineering Estonian University of Life SciencesTartu51006Estonia Department of Mechanical Engineering école de Technologie SupérieureMontréalQC H3C 1K3Canada Electrical Engineering Department Faculty of EngineeringMinia UniversityMinia61519Egypt

Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and *** this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is ***,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the ***-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in ***,peak-hour loads are shifted using price demand response guidance in the context of time-of-day ***,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with *** simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.

关键词： Energy harvesting integrated energy systems optimum scheduling time-of-use pricing demand response geothermal energy

Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

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Digital Communications and Networks 2024年第2期10卷 404-415页

作者： mohamed Abdel-Basset Hossam Hawash Nour Moustafa Imran Razzak mohamed Abd Elfattah Faculty of Computers and Informatics Zagazig UniversityZagazigSharqiyah44519Egypt School of Engineering and Information Technology University of New South Wales@ADFACanberraACT2600Australia Deakin University Geelong Waurn Ponds CampusAustralia Computer Science Department Misr Higher Institute for Commerce and ComputersMansoura35511Egypt

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber *** complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning *** Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT *** though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d *** is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other *** paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d ***-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each *** PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 *** empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

关键词： Privacy preservation Federated learning Deep learning Fog computing Smart cities

Life Threatening Stridor Due to Primary Laryngeal Tuberculosis

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International Journal of Otolaryngology and Head & Neck Surgery 2024年第1期13卷 62-69页

作者： Siti Aisyah mohamed Azreen Zaira abu Bakar Mawaddah Azman Otorhinolaryngology Department Hospital Ampang Selangor Malaysia Otorhinolaryngology Department Faculty of Medicine Universiti Kebangsaan Malaysia Kuala Lumpur Malaysia Otorhinolaryngology Department Hospital Kuala Lumpur Kuala Lumpur Malaysia

Tuberculosis is a potentially serious infectious disease. In otorhinolaryngology practice, lymph node infection is the most common site of predilection followed by the larynx. Laryngeal tuberculosis (LTB) typically presents with dysphagia, odynophagia and hoarseness. We reported a case of primary LTB presenting with acute upper airway obstruction and respiratory distress mimicking acute supraglottitis which requires emergency tracheostomy. Therefore, in acute upper airway obstruction, the appropriate initial investigation should be done to rule out TB to make sure early treatment can be given and it may prevent complications of disease to the patient. .

关键词： Extra-Pulmonary Granulomatous Infection Malignancy Upper Airway

A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

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Computers, Materials & Continua 2024年第7期80卷 119-138页

作者： mohamed Karray Nesrine Triki mohamed Ksantini ESME ESME Research LabIvry Sur Seine94200France CEM Lab ENISUniversity of SfaxSfax3038Tunisia

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the *** Sign Recognition System(TSRS)is one of themost important components *** the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing ***,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed ***,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured ***,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise *** addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting *** rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,***,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

关键词： Driving automation advanced driver assistance systems(ADAS) traffic sign recognition(TSR) artificial intelligence ensemble learning belief functions voting method

Comparison between seismic analysis of twisting and regular 52-story towers considering soil-structure interaction

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Earthquake Engineering and Engineering Vibration 2024年第3期23卷 663-675页

作者： mohamed Naguib Abouelsaad Mohammed Shaaban Salah El Bagalaty mohamed E.El Madawy Structural Engineering Department Faculty of EngineeringMansura UniversityMansoura 35511Egypt Faculty of Engineering Delta University for Science and TechnologyGamasa 35712Egypt

A dynamic analysis of both twisting and regular towers is carried out to determine the results of considering soil-structure interaction(SSI)on high-rise *** addition,the difference between the seismic performance of using twisting towers over regular ones is *** twisting tower is a simulation of the Evolution Tower(Moscow).The towers’skeletons consist of RC elements and rest on a reinforced concrete piled-raft *** soil model is considered as multi-layered with the same soil properties as the zone chosen for the analysis(New Mansoura City,Egypt).The only difference between both towers is their shape in *** whole system is modelled and analyzed in a single step as one full 3D model,which is known as the direct approach in *** analyses are carried out using finite-element software(Midas GTS NX).Dynamic output responses due to three records of seismic loads are proposed and presented in some *** on the results,it is concluded that SSI has a considerable effect on the dynamic response of tall buildings mainly because of the foundation flexibility,as it leads to lengthening the vibration period,increasing the story drift and the base shear for both cases.

关键词： soil-structure interaction seismic analysis twisting towers base shear story drift finite element method Midas GTS NX

A Multi-Task Deep Learning Framework for Simultaneous Detection of Thoracic Pathology through Image Classification

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Journal of Computer and Communications 2024年第4期12卷 153-170页

作者： nada Al Zahrani Ramdane Hedjar mohamed Mekhtiche mohamed Bencherif Taha Al Fakih Fattoh Al-Qershi Muna Alrazghan Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Department of Information System College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Department of Software Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

Thoracic diseases pose significant risks to an individual's chest health and are among the most perilous medical diseases. They can impact either one or both lungs, which leads to a severe impairment of a person’s ability to breathe normally. Some notable examples of such diseases encompass pneumonia, lung cancer, coronavirus disease 2019 (COVID-19), tuberculosis, and chronic obstructive pulmonary disease (COPD). Consequently, early and precise detection of these diseases is paramount during the diagnostic process. Traditionally, the primary methods employed for the detection involve the use of X-ray imaging or computed tomography (CT) scans. Nevertheless, due to the scarcity of proficient radiologists and the inherent similarities between these diseases, the accuracy of detection can be compromised, leading to imprecise or erroneous results. To address this challenge, scientists have turned to computer-based solutions, aiming for swift and accurate diagnoses. The primary objective of this study is to develop two machine learning models, utilizing single-task and multi-task learning frameworks, to enhance classification accuracy. Within the multi-task learning architecture, two principal approaches exist soft parameter sharing and hard parameter sharing. Consequently, this research adopts a multi-task deep learning approach that leverages CNNs to achieve improved classification performance for the specified tasks. These tasks, focusing on pneumonia and COVID-19, are processed and learned simultaneously within a multi-task model. To assess the effectiveness of the trained model, it is rigorously validated using three different real-world datasets for training and testing.

关键词： Pneumonia Thoracic Pathology COVID-19 Deep Learning Multi-Task Learning

Exact and heuristic formulae to compute the geodetic height from the ellipse equation

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Geodesy and Geodynamics 2024年第2期15卷 150-155页

作者： mohamed Eleiche Ahmed Hamdi Mansi Construction Department Faculty of EngineeringEgyptian Russian UniversityCairoEgypt Istituto Nazionale di Geofisica e Vulcanologia Sezione di PisaPisaPlItaly

The conversion of the cartesian coordinates of a point to its geodetic equivalent coordinates in reference to the geodetic ellipsoid is one of the main challenges in *** ellipse equation in the meridian plane significantly influences the value of the geodetic *** research analyzes this influence and how it can contribute to their *** study investigates the mathematical relation between them and presents an exact formula relating to the geodetic height and the ellipse *** addition,a heuristic formula for the relation between the geodetic height and the ellipse equation is proposed,which is independent of the geodetic latitude and has a relative accuracy better than 99.9 %.The calculation is stable,and the cost is low.

关键词： Ellipse equation Geodetic height Heuristic geodetic height

Impact of lifestyle interventions on pathogenesis of nonalcoholic fatty liver disease

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World Journal of Gastroenterology 2024年第20期30卷 2633-2637页

作者： Wafaa mohamed Ezzat Department of Internal Medicine Medical Research and Clinical Studies InstituteNational Research CenterGiza 12311Egypt

This editorial builds on the article titled“Establishment and validation of an adherence prediction system for lifestyle interventions in non-alcoholic fatty liver disease”by Zeng et *** carried out a critical examination of nonalcoholic fatty liver disease(NAFLD)pathogenesis and how lifestyle interventions could facilitate disease resolution,particularly highlighting that non-alcoholic steatohepatitis(NASH)is a severe form of *** discussion details that weight loss is a pivotal factor in disease outcomes:A 3%-5%reduction is enough for resolution in 50%of non-obese individuals,while a 7%-10%reduction achieves similar benefits in obese individuals,as demonstrated by magnetic resonance ***,the editorial underscores that such lifestyle changes are instrumental not only in resolving NAFLD but also in reversing hepatic steatosis and *** insights,derived from the research,emphasize the critical role of personalized lifestyle modifications in halting the progression of NAFLD to NASH and even reversing fibrosis,thus offering a template for effective patient management.

关键词： Nonalcoholic fatty liver disease Non-alcoholic steatohepatitis Diet Physical activity Life style

Enteric neuropathy in diabetes:Implications for gastrointestinal function

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World Journal of Gastroenterology 2024年第22期30卷 2852-2865页

作者： Mona mohamed Ibrahim Abdalla Department of Human Biology School of MedicineInternational Medical UniversityBukit Jalil 57000Kuala LumpurMalaysia

Diabetes,commonly known for its metabolic effects,also critically affects the enteric nervous system(ENS),which is essential in regulating gastrointestinal(GI)motility,secretion,and *** development of diabetes-induced enteric neuropathy can lead to various GI dysfunctions,such as gastroparesis and irregular bowel habits,primarily due to disruptions in the function of neuronal and glial cells within the ENS,as well as oxidative stress and *** editorial explores the pathophysiological mechanisms underlying the development of enteric neuropathy in diabetic ***,it discusses the latest advances in diagnostic approaches,emphasizing the need for early detection and intervention to mitigate GI complications in diabetic *** editorial also reviews current and emerging therapeutic strategies,focusing on pharmacological treatments,dietary management,and potential neuromodulatory ***,this editorial highlights the necessity of a multidisciplinary approach in managing enteric neuropathy in diabetes,aiming to enhance patient quality of life and address a frequently overlooked complication of this widespread disease.

关键词： Diabetic neuropathy Gastrointestinal Insulin resistance Diabetes Enteric nervous system Enteric neuropathy

Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： mohamed Abdel-Basset Hossam Hawash mohamed Abouhawwash S.S.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion