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MARIE:One-Stage Object Detection Mechanism for Real-Time Identifying of Firearms

Computer Modeling in Engineering & Sciences 2025年第1期142卷 279-298页

作者： Diana Abi-Nader Hassan Harb Ali Jaber Ali Mansour Christophe Osswald nour mostafa Chamseddine Zaki Computer Science Department Faculty of SciencesLebanese UniversityBeirut146404Lebanon College of Engineering and Technology American University of the Middle EastEgaila54200Kuwait Lab-STICC CNRS UMR 6285ENSTA-BretagneBrest29200France

Security and safety remain paramount concerns for both governments and individuals *** today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to ***,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent *** advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying *** paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection *** SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction *** experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy *** these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.

关键词： Firearm and gun detection single shot multi-box detector deep learning one-stage detector MobileNet inception convolutional neural network

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Enhancing Parkinson’s Disease Diagnosis Accuracy Through Speech Signal Algorithm Modeling

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Computers, Materials & Continua 2022年第2期70卷 2953-2969页

作者： Omar M.El-Habbak Abdelrahman M.Abdelalim nour H.Mohamed Habiba M.Abd-Elaty mostafa A.Hammouda Yasmeen Y.Mohamed Mohanad A.Taifor Ali W.Mohamed School of Information Technology and Computer Science Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt

Parkinson’s disease(PD),one of whose symptoms is dysphonia,is a prevalent neurodegenerative *** use of outdated diagnosis techniques,which yield inaccurate and unreliable results,continues to represent an obstacle in early-stage detection and diagnosis for clinical professionals in the medical *** solve this issue,the study proposes using machine learning and deep learning models to analyze processed speech signals of patients’voice *** of these processed speech signals were obtained and experimented on by random forest and logistic regression *** were highly successful,with 90%accuracy produced by the random forest classifier and 81.5%by the logistic regression ***,a deep neural network was implemented to investigate if such variation in method could add to the *** proved to be effective,as the neural network yielded an accuracy of nearly 92%.Such results suggest that it is possible to accurately diagnose early-stage PD through merely testing patients’*** research calls for a revolutionary diagnostic approach in decision support systems,and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians in early diagnosis of PD.

关键词： Early diagnosis logistic regression neural network Parkinson’s disease random forest speech signal processing algorithms

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Virtual orthopedic assessment:Main principles and specific regions

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World Journal of Orthopedics 2021年第9期12卷 672-684页

作者： Khaled M Emara Ramy Ahmed Diab Mohamed Amr Shady Abdelghaffar Mahmoud Mohamed nour Ahmed Abdelsalam Mahmoud Ahmed Elshobaky Mona Farhan mostafa Gemeah Ahmed K Emara Orthopedic Surgery Department Ain Shams UniversityCairo 11566Egypt Orthopedic Surgery Department Bank Ahly HospitalCairo 11566Egypt Department of Health Care Innovation Arizona State UniversityArizonaAZ 85287United States Department of Orthopedic Surgery Cleveland ClinicOhioNY 44195United States

Telemedicine was originally created as a way to treat patients who were located in remote places far away from local health facilities or in areas with shortages of medical *** is still used today to address those problems,and is increasingly becoming a tool for convenient medical *** the emergence of pandemics,telemedicine became almost a mandatory and valuable option for continuing to provide medical care in various *** the threat of pandemic progress has continued for months and may continue for years,it is essential to validate existing tools to maintain clinical assessment and patient treatment to avoid negative consequences of the lack of medical ***,the establishment of a virtual assessment technique that can be conducted effectively is of outmost importance as a way of adapting to the current *** study evaluated the role of telemedicine in the assessment of various orthopedic pathologies by means of a systematic virtual evaluation.

关键词： Telemedicine Virtual assessment Orthopedics Epidemic diseases

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Integrated Control of Meloidogyne Incognita Infesting Tomato Plants Using Callus Powders Derived from Certain Plants Either Alone or in Combination with Oxamyl under Out-Door Conditions

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Journal of Agricultural Science and Technology(A) 2011年第2X期1卷 225-230页

作者： Ahmed H. nour El-Deen A. G. EI-Sherif Fatma A. M. mostafa A. R. Refaei Nematology Research Unit Agricultural Zoology Dept. Fac. of Agric. Mansoura Univ. El-Mansoura DK. 35516 Egypt

The effect of four dried callus powders derived from certain plants, i.e. tomato, Lycopersicon esculentum; periwinkle, Catharanthus roseus; thorne apple, Datura stramonium and oleander, Nerium oleander applied separately or concomitantly with oxamyl at a half of the recommended dose each on tomato seedlings grown in soil naturally heavy infested with M. incognita under field conditions, indicated that dried callus powder derived from N. oleander either alone or mixed with oxamyl significantly surpassed the other tested treatments in improving percentages of increase in whole plant fresh and shoot dry weights as well as increasing numbers and weights of fruits. Concerning other treatments including oxamyl at a half of recommended dose with each tested callus powder, similar results were evident regarding tomato plant growth parameters. C. roseus plus oxamyl achieved the highest percentage of increase in whole plant fresh weight （141.4%） and shoot dry weight （189.7%） and ranked second to N. oleander ＋ oxamyl in this respect over the untreated plants, respectively. One the other hand, among all tested materials single application of either L. esculentum or oxamyl gave the least values of such criteria which averaged 34.4% and 61.7% or 39.5% and 11.2%, respectively. All tested treatments significantly reduced the total number of galls, egg-masses and eggs in egg-masses especially, dried callus powder of N. oleander which applied singly or combined with oxamyl. The least values of reduction percentages of galls and eggs in egg-masses among all treatments were recorded from tomato plant received dried callus powders of L. esculentum applied alone or concomitant with oxamyl.

关键词： Tomato Meloidogyne incognita MS medium callus powders.

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