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Deep Semantic and Attentive Network for Unsupervised Video Summarization

ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

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computers, Materials & Continua 2023年第2期74卷 3977-3996页

作者： Billel Meghni Afaf Benamor Oussama Hachana Ahmad Taher Azar Amira Boulmaiz Salah Saad El-Sayed M.El-kenawy Nashwa Ahmad Kamal Suliman Mohamed Fati Naglaa K.Bahgaat Department of Electrical Engineering Badji Mokhtar UniversityLSEM LaboratoryAnnaba23000Algeria Department of Electrical Engineering Biskra UniversityLGEB LaboratoryBiskra07000Algeria Department of Drilling and Rig Mechanics Ksadi Merbah UniversityOuargla30000Algeria College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityBenha13518Egypt Department of Electronics University of Badji MokhtarLERICA LaboratoryAnnaba23000Algeria Delta Higher Institute for Engineering&Technology(DHIET) Mansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Faculty of Engineering Cairo UniversityGiza12613Egypt Department of Communications and Electronics Engineering Faculty of EngineeringCanadian International College(CIC)ElShiekh ZayedEgypt

The integration of wind turbines(WTs)in variable speed drive systems belongs to the main factors causing lowstability in electrical ***,in order to avoid this issue,WTs hybridization with a storage system is a *** paper investigates WT system operating at variable *** system contains of a permanent magnet synchronous generator(PMSG)supported by a battery storage system(BSS).To enhance the quality of active and reactive power injected into the network,direct power control(DPC)scheme utilizing space-vector modulation(SVM)technique based on proportional-integral(PI)control is ***,to improve the rendition of this method(DPC-SVM-PI),the rooted tree optimization technique(RTO)algorithm-based controller parameter identification is used to achieve PI optimal *** compare the performance ofRTO-based controllers,they were implemented and tested along with some other popular controllers under different working *** obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion(THD),overshoot percentage,settling time,rise time,average active power value,overall efficiency,and active power steadystate error.

关键词： Rooted tree optimization(RTO)method direct power control(DPC) wind turbine(WT) proportional integral(PI) PMSG

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Optical Ciphering Scheme for Cancellable Speaker Identification System

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computer Systems science & engineering 2023年第4期45卷 563-578页

作者： Walid El-Shafai Marwa A.Elsayed Mohsen A.Rashwan Moawad I.Dessouky Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi EAbd El-Samie Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Communications Faculty of EngineeringCairo UniversityCairoEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Most current security and authentication systems are based on personal *** security problem is a major issue in the field of biometric *** is due to the use in databases of the original *** biometrics will forever be lost if these databases are *** privacy is the most important goal of cancelable *** order to protect privacy,therefore,cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification *** methodology to achieve non-invertibility is the employment of non-invertible *** work suggests an encryption process for cancellable speaker identification using a hybrid encryption *** system includes the 3D Jigsaw transforms and Fractional Fourier Transform(FrFT).The proposed scheme is compared with the optical Double Random Phase Encoding(DRPE)encryption *** evaluation of simulation results of cancellable biometrics shows that the algorithm proposed is secure,authoritative,and *** encryption and cancelability effects are good and reveal good ***,it introduces recommended security and robustness levels for its utilization for achieving efficient cancellable biometrics systems.

关键词： Cancellable biometrics jigsaw transform FrFT DRPE speaker identification

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Retinal disorder diagnosis based on hybrid deep learning models

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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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Dual Radial-Resonant Wide Beamwidth Circular Sector Microstrip Patch Antennas

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Chinese Journal of Electronics 2023年第4期32卷 710-719页

作者： MAO Xiaohui LU Wenjun JI Feiyan XING Xiuqiong ZHU Lei Jiangsu Key Laboratory of Wireless Communications Nanjing University of Posts and Telecommunications Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau

In this article, a design approach to a radial-resonant wide beamwidth circular sector patch antenna is advanced. As properly evolved from a U-shaped d ipole, a prototype magnetic dipole can be fit in the radial direction of a circular sector patch radiator, with its length set as the positive odd-integer multiples of onequarter wavelength. In this way, multiple TM0m（m = 1,2,...） modes resonant circular sector patch antenna with short-circuited circumference and widened E-plane beamwidth can be realized by proper excitation and perturbations. Prototype antennas are then designed and fabricated to validate the design approach. Experimental results reveal that the E-plane beamwidth of a dual-resonant antenna fabricated on air/Teflon substrate can be effectively broadened to 128°/120°, with an impedance bandwidth of 17.4%/7.1%, respectively. In both cases, the antenna heights are strictly limited to no more than 0.03-guided wavelength. It is evidently validated that the proposed approach can effectively enhance the operational bandwidth and beamwidth of a microstrip patch antenna while maintaining its inherent low profile merit.

关键词： Geometry Patch antennas Perturbation methods Prototypes Magnetic resonance Microstrip antennas Bandwidth

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Reinforcement of Medical Image Security Through Steganography and Encryption Techniques 3

Reinforcement of Medical Image Security Through Steganograph...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Khallaf, Fatma El-Shafai, Walid El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. Menoufia University Faculty of Electronic Engineering Department of Electronics and Communication Engineering Menouf32952 Egypt Ahram Canadian University Faculty of Engineering Department of Electrical Engineering Giza Egypt Prince Sultan University Security Engineering Laboratory Department of Computer Science Riyadh11586 Saudi Arabia

ISBN: (纸本)9798350323511

Patients' data is stored in Electronic Health Records (EHRs) for confidentiality purposes. However, the insecure networks of hospitals and clinics puts patient information at risk. To address this ethical issue, secure communication is crucial. The Digital Imaging and Communications in Medicine (DICOM) standard governs the transmission of EHRs to maintain data integrity and confidentiality. This paper combines cryptography and steganography techniques to transmit medical information and images across hospital networks, securely. The introduced framework comprises encryption of patients' data using DNA-based Advanced Encryption Standard (AES), hiding the information within images using Least Significant Bit (LSB) embedding, compressing the stego images using Discrete Wavelet Transform (DWT), and reversal of the process at the receiver end. Simulation experiments demonstrate that this framework comprising both encryption and steganography outperforms existing methods in securing the medical data. © 2023 IEEE.

关键词： Cryptography

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An Immutable Framework for Smart Healthcare Using Blockchain Technology

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computer Systems science & engineering 2023年第7期46卷 165-179页

作者： Faneela Muazzam A.Khan Suliman A.Alsuhibany Walid El-Shafai Mujeeb Ur Rehman Jawad Ahmad Department of Computer Science Quaid-i-Azam UniversityIslamabad45320Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Science Security Engineering LaboratoryPrince Sultan UniversityRiyadh11586Saudi Arabia James Watt School of Engineering University of GlasgowG128QQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

The advancements in sensing technologies,information processing,and communication schemes have revolutionized the healthcare *** Healthcare Records(EHR)facilitate the patients,doctors,hospitals,and other stakeholders to maintain valuable data and medical *** traditional EHRs are based on cloud-based architectures and are susceptible to multiple cyberattacks.A single attempt of a successful Denial of Service(DoS)attack can compromise the complete healthcare *** article introduces a secure and immutable blockchain-based framework for the Internet of Medical Things(IoMT)to address the stated *** proposed architecture is on the idea of a lightweight private blockchain-based network that facilitates the users and hospitals to perform multiple healthcare-related operations in a secure and trustworthy *** efficacy of the proposed framework is evaluated in the context of service execution time and *** experimental outcomes indicate that the proposed design attained lower service execution time and higher throughput under different control parameters.

关键词： Blockchain technology healthcare applications cybersecurity services IoMT DoS EHR

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Harnessing the power of functionalized biochar:progress,challenges,and future perspectives in energy,water treatment,and environmental sustainability

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Biochar 2024年第1期6卷 407-486页

作者： Muhammad Zubair Yameen Salman Raza Naqvi Dagmar Juchelková Muhammad Nouman Aslam Khan Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering(SCME)National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan. Department of Electronics Faculty of Electrical Engineering and Computer ScienceVŠB-Technical University of Ostrava17.Listopadu 2172/1570800 OstravaPorubaCzech Republic. Department of Engineering and Chemical Sciences Karlstad UniversityKarlstadSweden.

The swift advancement of sustainable energy technologies,coupled with the urgent need to address environmental challenges,has generated considerable interest in the multifaceted applications of biochar materials to promote energy,water,and environmental *** comprehensive review examines recent advancements in the production and applications of functionalized biochar materials,emphasizing their pivotal roles in energy conversion and storage,wastewater treatment,CO_(2)reduction,soil amelioration,and the promotion of carbon neutrality within a circular economy *** functionalization of biochar materials involves surface chemistry and porosity modifications,achieved through techniques like templating,chemical activation,metal impregnation,or heteroatom *** modifications substantially enhance the catalytic activity,energy storage capacity,and cycling stability of biochar materials,making them particularly effective in diverse energy applications such as water splitting,fuel cells,and ***,functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment,proficiently removing pollutants like heavy metals,organic contaminants,and nutrients,thereby facilitating resource recovery from *** review also underscores the potential of functionalized biochar materials in CO_(2)capture and conversion,exploring innovative strategies to augment their CO_(2)adsorption capacity and state-of-the-art catalytic processes for transforming captured CO_(2)into valuable fuels and *** summary,this review offers valuable insights into the recent advancements in biochar research,underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.

关键词： Engineered biochar Sustainable energy technologies Wastewater treatment Carbon reduction Circular economy

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Work in Progress: Remote laboratory Delivery with an At-Home Biomechanical Kinematic Data Acquisition Method 129

Work in Progress: Remote Laboratory Delivery with an At-Home...

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129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022

作者： Sayed, Ahmed M. Electrical Engineering and Computer Science Department MSOE University MilwaukeeWI United States Biomedical Engineering Department Faculty of Engineering Helwan University Helwan Egypt

Under the remote learning mode due to COVID-19, educational laboratory modules lacking the active data acquisition step tend to lose students' engagement and diminish their eagerness to explore further knowledge. Such shortcomings are more profound in practical fields of study, such as Biomechanics. The goal of this paper is to present a remote laboratory delivery and evaluation method where students can apply principles of kinematic and kinetic biomechanical analysis on their own body motions with a computer vision algorithm to interactively solve a motion analysis problem. In this preliminary study, students were given the freedom to choose a specific body motion to be captured and analyzed, such as elbow, knee, wrist, and neck joint movements. Motion specifications included determination of the motion type, and also the starting and ending angular or linear positions. Readily available labels were utilized as passive joint markers. Students were then instructed to video record their joint motions using their laptop cameras. A custom video tracking algorithm specifically designed to track spatial locations was then employed to capture relative positions of the recorded motions. laboratory instructions asked the students to perform kinematic calculations on the algorithm's generated positional data to determine joint velocities and accelerations, and then perform kinetic analyses to estimate the associated muscle forces. laboratory requirements were concluded with a reflection prompt to evaluate the activity's workload and effort perceived by the students. These activities were delivered twice in two different academic terms. Samples of the produced kinematic data using our methods were verified in comparison with a standard physical motion capture system, where similar joint motion descriptive results were observed. Results show that the completion rate of laboratory requirements was 97% in the first term of delivery, and 100% in the second term, as supported by t

关键词： Students

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Early Diagnosis of Osteoporosis: An Artificial Intelligence-Based Framework

Early Diagnosis of Osteoporosis: An Artificial Intelligence-...

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International Conference on Advances in biomedical engineering (ICABME)

作者： Amira J. Zaylaa Alaa Daher Mohammad Ayache Niveen Omeirat Razane Mahmoud Bader Abou Hawili Biomedical Engineering Laboratory Biomedical Engineering Program Electrical and Computer Engineering Faculty of Engineering Beirut Arab University Lebanon

Osteoporosis is a common disease characterized by low bone density and structural deterioration of bone tissue. For a successful course of treatment and fracture avoidance, early diagnosis of this disease is essential. The aim was to provide a novel method for osteoporosis prediction using Artificial Intelligence (AI)-based framework. The purpose was to predict the likelihood of osteoporosis based on the Bone Mineral Density (BMD), along with other characteristics such as age, weight, height, gender, and Body Mass Index (BMI) extracted from medical reports and images collected from a comprehensive medical center in Lebanon. Three machine-learning algorithms were implemented and tested, Logistic Regression (LR), Support Vector Machines (SVM), and Decision Trees (DT). Variety of quantitative statistical metrics were used to evaluate the performance of our framework, upon training and testing our algorithms. The metrics that were employed to evaluate our results included accuracy, precision, sensitivity, and F-score, in addition to the Receiver Operating Characteristic (ROC) Curve and the Area Under the Curve (AUC). Experimental Results demonstrated that both the SVM and LR algorithms achieved the highest accuracy of detection of osteoporosis as compared to existing algorithms applied in this field, with an accuracy of 89%. The sensitivity of diagnosis obtained was 98% by LR and 97% by SVM and surpassed the sensitivity obtained by DT. As such LR showed the best performance. The output of the algorithms could help medical doctors assess patients automatically. These findings demonstrated the potential of AI in osteoporosis prediction and thus prevention, highlighting the significance of early diagnosis. Thereby as a future prospect, choosing carefully the framework is crucial and additional algorithms have to be considered and tested.

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