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On Some Modified Methods on Fractional Delay and Nonlinear IntegroDifferential Equation

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Sound & Vibration 2021年第4期55卷 263-279页

作者： a.a.soliman K.R.Raslan A.M.Abdallah Department of Mathematics Faculty of ScienceArish UniversityAL-ArishEgypt Department of Mathematics Faculty of ScienceAL-Azhar UniversityCairo GovernorateEgypt Basic Science Department Higher Technological Institute10th of Ramadan CityEgypt

The fundamental objective of this work is to construct a comparative study of some modified methods with Sumudu transform on fractional delay integro-differential *** existed solution of the equation is very accuratel... 详细信息

关键词： Convergence stability fractional integro-differential equation

Semantic Pneumonia Segmentation and Classification for Covid-19 Using Deep Learning Network

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Computers, Materials & Continua 2022年第10期73卷 1141-1158页

作者： M.M.Lotfy Hazem M.El-Bakry M.M.Elgayar Shaker El-Sappagh G.Abdallah M.I a.a.soliman Kyung Sup Kwak Department of Mathematics Faculty of ScienceArish UniversityArish45511Egypt Department of Information Systems Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Department of Information Technology Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Centro Singular de Investigación en Tecnoloxías Intelixentes(CiTIUS) Universidade de Santiago de CompostelaSantiago de Compostela15705Spain Information Systems Department Faculty of Computers and Artificial IntelligenceBenha UniversityBenha13512Egypt Department of Information and Communication Engineering Inha UniversityIncheon22212Korea

Early detection of the Covid-19 disease is essential due to its higher rate of infection affecting tens of millions of people,and its high number of deaths also by 7%.For that purpose,a proposed model of several stages was *** first stage is optimizing the images using dynamic adaptive histogram equalization,performing a semantic segmentation using DeepLabv3Plus,then augmenting the data by flipping it horizontally,rotating it,then flipping it *** second stage builds a custom convolutional neural network model using several pre-trained ***,the model compares the pre-trained data to the new output,while repeatedly trimming the best-performing models to reduce complexity and improve memory *** experiments were done using different techniques and ***,the proposed model achieved an average accuracy of 99.6%and an area under the curve of 0.996 in the Covid-19 *** paper will discuss how to train a customized intelligent convolutional neural network using various parameters on a set of chest X-rays with an accuracy of 99.6%.

关键词： SARS-COV2 COVID-19 pneumonia deep learning network semantic segmentation smart classification

Robust Malicious Executable Detection Using Host-Based Machine Learning Classifier

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Computers, Materials & Continua 2024年第4期79卷 1419-1439页

作者： Khaled soliman Mohamed Sobh Ayman M.Bahaa-Eldin Department of Computer and Systems Engineering Ain Shams UniversityCairo11517Egypt Department of Computer Engineering Technology ElSewedy University of TechnologyCairo44629Egypt

The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust Malicious ExecutableDetection (RMED) using Host-based Machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RMED *** most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RMED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.

关键词： Portable executable malware intrusion detection cybersecurity zero-day threats Host IntrusionDetection System(HIDS) machine learning Anomaly-based Intrusion Detection System(AIDS) deep learning

Assessment of plant diversity of endemic species of the Saharo-Arabian region in Egypt

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Journal of Arid Land 2024年第7期16卷 1000-1021,I0002-I0044页

作者： Asmaa S ABO HATAB Yassin M AL-SODANY Kamal H SHALTOUT soliman A HAROUN Mohamed M EL-KHALAFY Botany and Microbiology Department Faculty of ScienceKafrelsheikh UniversityKafrelsheikh 33511Egypt Botany Department Faculty of ScienceTanta UniversityTanta 31527Egypt

Savanna, semi-deserts, and hot deserts characterize the Saharo-Arabian region, which includes Morocco, Mauretania, Algeria, Tunisia, Libya, Egypt, Palestine, Kuwait, Saudi Arabia, Qatar, Bahrain, the United Arab Emirates, Oman, Yemen, southern Jordan, Syria, Iraq, Iran, Afghanistan, Pakistan, and northern India. Its neighboring regions, the Sudano-Zambezian region belonging to the Paleotropical Kingdom and the Mediterranean and Irano-Turanian regions included in the Holarctic Kingdom, share a large portion of their flora with the Saharo-Arabian region. Despite the widespread acknowledgment of the region's global importance for plant diversity, an up to date list of the Saharo-Arabian endemics is still unavailable. The available data are frequently insufficient or out of date at both the whole global and the national scales. Therefore, the present study aims at screening and verifying the Saharo-Arabian endemic plants and determining the phytogeographical distribution of these taxa in the Egyptian flora. Hence, a preliminary list of 429 Saharo-Arabian endemic plants in Egypt was compiled from the available literature. Indeed, by excluding the species that were recorded in any countries or regions outside the Saharo-Arabian region based on different literature, database reviews, and websites, the present study has reduced this number to 126 taxa belonging to 87 genera and 37 families. Regarding the national geographic distribution, South Sinai is the richest region with 83 endemic species compared with other eight phytogeographic regions in Egypt, followed by the Isthmic Desert(the middle of Sinai Peninsula, 53 taxa). Sahara regional subzone(SS1) distributes all the 126 endemic species, Arabian regional subzone(SS2) owns 79 taxa, and Nubo-Sindian subzone(SS3) distributes only 14 endemics. Seven groups were recognized at the fourth level of classification as a result of the application of the two-way indicator species analysis(TWINSPAN) to the Saharo-Arabian endemic sp

关键词： endemism phytogeographical regions Saharo-Arabian floristic region Egyptian flora plant diversity two-way indicator species analysis(TWINSPAN)

Organ and function preservation in gastrointestinal cancer: Current and future perspectives on endoscopic ablation

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World Journal of Gastrointestinal Endoscopy 2024年第6期16卷 282-291页

作者： Youssef Yousry soliman Megan soliman Shravani Reddy James Lin Toufic Kachaamy Department of Gastroenterology City of Hope PhoenixGoodyearAZ 85338United States Department of Medicine Medical ConsultingGoodyearAZ 85395United States Department of Gastroenterology University of California IrvineIrvineCA 92697United States Department of Gastroenterology City of Hope National Medical CenterDuarteCA 91010United States

The escalating prevalence of gastrointestinal cancers underscores the urgency for transformative *** treatment costs amount to billions of dollars annually,combined with the risks and comorbidities associated with invasive *** highlights the importance of less invasive alternatives with organ preservation being a central aspect of the treatment *** current standard of care typically involves neoadjuvant systemic therapy followed by surgical *** is a growing interest in organ preservation approaches by way of minimizing extensive surgical *** ablation has proven to be useful in precursor lesions,as well as in palliative cases of unrese-ctable *** recently,there has been an increase in reports on the utility of adjunct endoscopic ablative techniques for downstaging disease as well as contributing to non-surgical complete clinical *** expansive field within endoscopic oncology holds great potential for advancing patient *** addressing challenges,fostering collaboration,and embracing technological advancements,the gastrointestinal cancer treatment paradigm can shift towards a more sustainable and patient-centric future emphasizing organ and function *** editorial examines the evolving landscape of endoscopic ablation strategies,emphasizing their potential to improve patient *** briefly review current applications of endoscopic ablation in the esophagus,stomach,duodenum,pancreas,bile ducts,and colon.

关键词： Gastrointestinal cancer Endoscopic ablation Organ preservation Complete clinical response Neoadjuvant therapy Endoscopic oncology Palliative treatment

A Hybrid Cybersecurity Algorithm for Digital Image Transmission over Advanced Communication Channel Models

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Computers, Materials & Continua 2024年第4期79卷 201-241页

作者： Naglaa F.soliman Fatma E.Fadl-Allah Walid El-Shafai Mahmoud I.Aly Maali Alabdulhafith Fathi E.Abd El-Samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The efficient transmission of images,which plays a large role inwireless communication systems,poses a significant challenge in the growth of multimedia ***-quality images require well-tuned communication *** Single Carrier Frequency Division Multiple Access(SC-FDMA)is adopted for broadband wireless communications,because of its low sensitivity to carrier frequency offsets and low Peak-to-Average Power Ratio(PAPR).Data transmission through open-channel networks requires much concentration on security,reliability,and *** data need a space away fromunauthorized access,modification,or *** requirements are to be fulfilled by digital image watermarking and *** paper ismainly concerned with secure image communication over the wireless SC-FDMA systemas an adopted communication *** introduces a robust image communication framework over SC-FDMA that comprises digital image watermarking and encryption to improve image security,while maintaining a high-quality reconstruction of images at the receiver *** proposed framework allows image watermarking based on the Discrete Cosine Transform(DCT)merged with the Singular Value Decomposition(SVD)in the so-called DCT-SVD *** addition,image encryption is implemented based on chaos and DNA *** encrypted watermarked images are then transmitted through the wireless SC-FDMA *** linearMinimumMean Square Error(MMSE)equalizer is investigated in this paper to mitigate the effect of channel fading and noise on the transmitted *** subcarrier mapping schemes,namely localized and interleaved schemes,are compared in this *** study depends on different channelmodels,namely PedestrianAandVehicularA,with a modulation technique namedQuadratureAmplitude Modulation(QAM).Extensive simulation experiments are conducted and introduced in this paper for efficient transmission of encrypted watermarked *** addition,different variants of SC-FDMA bas

关键词： Cybersecurity applications image transmission channel models modulation techniques watermarking and encryption

A review of concrete bridge surface defect detection based on deep learning

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Optoelectronics Letters 2024年

作者： LIAO Yanna HUANG Chaoyang Abdel-Hamid soliman School of Electronic Engineering， Xi'an University of Posts and Telecommunications School of Digital， Technology， Innovation and Business， Staffordshire University

The detection of surface defects in concrete bridges using deep learning is of significant importance for reducing operational risks， saving maintenance costs， and driving the intelligent transformation of bridge defect detection. In contrast to the subjective and inefficient manual visual inspection， deep learning-based algorithms for concrete defect detection exhibit remarkable advantages， emerging as a focal point in recent research. This paper comprehensively analyzes the research progress of deep learning algorithms in the field of surface defect detection in concrete bridges in recent years. It introduces the early detection methods for surface defects in concrete bridges and the development of deep learning. Subsequently， it provides an overview of deep learning-based concrete bridge surface defect detection research from three aspects: image classification， object detection， and semantic segmentation. The paper summarizes the strengths and weaknesses of existing methods and the challenges they face. Additionally， it analyzes and prospects the development trends of surface defect detection in concrete bridges.

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Engineering nanomedicines for immunogenic eradication of cancer cells:Recent trends and synergistic approaches

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Acta Pharmaceutica Sinica B 2024年第6期14卷 2475-2504页

作者： Ahmed O.Elzoghby Omar Samir Hagar E.Emam Ahmed soliman Riham M.Abdelgalil Yomna M.Elmorshedy Kadria A.Elkhodairy Mahmoud L.Nasr Division of Engineering in Medicine and Division of Renal Medicine Department of MedicineBrigham and Women's HospitalHarvard Medical SchoolBoston 02115MAUSA Cancer Nanotechnology Research Laboratory(CNRL) Faculty of PharmacyAlexandria UniversityAlexandria 21521Egypt

Resistance to cancer immunotherapy is mainly attributed to poor tumor immunogenicity as well as the immunosuppressive tumor microenvironment(TME)leading to failure of immune *** therapeutic strategies including chemotherapy,radiotherapy,photodynamic,photothermal,magnetic,chemodynamic,sonodynamic and oncolytic therapy,have been developed to induce immunogenic cell death(ICD)of cancer cells and thereby elicit immunogenicity and boost the antitumor immune ***,many challenges hamper the clinical application of ICD inducers resulting in modest immunogenic ***,we outline the current state of using nanomedicines for boosting ICD of cancer ***,synergistic approaches used in combination with ICD inducing nanomedicines for remodeling the TME via targeting immune checkpoints,phagocytosis,macrophage polarization,tumor hypoxia,autophagy and stromal modulation to enhance immunogenicity of dying cancer cells were *** further highlight the emerging trends of using nanomaterials for triggering amplified ICD-mediated antitumor immune *** reticulum localized ICD,focused ultrasound hyperthermia,cell membrane camouflaged nanomedicines,amplified reactive oxygen species(ROS)generation,metallo-immunotherapy,ion modulators and engineered bacteria are among the most innovative *** challenges,merits and demerits of ICD inducer nanomedicines were also discussed with shedding light on the future role of this technology in improving the outcomes of cancer immunotherapy.

关键词： Immunogenic cell death Immunogenic eradication Nanomedicines Drug delivery Cancer immunotherapy Antitumor immunity T cells Tumor associated antigens Synergistic immune response

基三众核架构中基于同步哈密顿环的无死锁策略

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计算机研究与发展 2024年

作者：李春峰 Karim soliman 计卫星石峰北京理工大学计算机学院北京师范大学人工智能学院

确保片上网络（network-on-chip，NoC）中的数据传输无死锁，是NoC为多处理器片上系统（multi-processor system-on-chip，MPSoC）提供可靠通信服务的前提，决定了NoC甚至MPSoC的可用性.现有的通用防死锁策略难以发挥出特定拓扑结构自... 详细信息

确保片上网络（network-on-chip，NoC）中的数据传输无死锁，是NoC为多处理器片上系统（multi-processor system-on-chip，MPSoC）提供可靠通信服务的前提，决定了NoC甚至MPSoC的可用性.现有的通用防死锁策略难以发挥出特定拓扑结构自身特点和优势，甚至可能会增加网络延迟、功耗以及硬件复杂性.另外，由于路由级和协议级死锁存在显著差异，现有无死锁方案较难同时解决这2类死锁问题，影响了MPSoC的可靠性.利用基三众核架构（Triplet-based many-core architecture，TriBA）中拓扑结构自身具有的哈密顿特性提出了基于同步哈密顿环的无死锁策略，该策略依据拓扑结构自身的对称轴和哈密顿边对数据传输进行分类，预防了协议级死锁并提高了数据传输速度；同时使用循环链表技术判断同一缓冲区内数据同步传输方向，消除了路由级死锁并降低了数据传输延迟.在优化前瞻路由算法基础上，设计了基于同步哈密顿环的无死锁路由机制（Hamiltonian shortest path routing，HamSPR）.GEM5仿真结果表明，与TriBA现有方法相比，HamSPR在合成流量下的平均数据包延迟和功耗分别降低了18.78% ～ 65.40% 和6.94% ～ 34.15%，吞吐量提高了8.00% ～ 59.17%；在PARSEC测试集下的应用运行时间和平均数据包延迟分别最高实现了16.51%和42.75%的降低.与2D-Mesh架构相比，TriBA在PARSEC测试集下的应用性能实现了1% ～ 10%的提升.

关键词：众核处理器片上网络基三众核架构哈密顿特性路由算法死锁预防