检索结果-南通市图书馆

An Efficient Indoor Localization Based on Deep Attention Learning Model

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 2637-2650页

作者： Amr Abozeid ahmed I.Taloba Rasha M.abd el-Aziz Alhanoof Faiz Alwaghid Mostafa Salem ahmed elhadad Department of Computer Science College of Science and ArtsJouf UniversityQurayyatSaudi Arabia Information System Department Faculty of Computers and InformationAssiut UniversityEgypt Computer Science Department Faculty of Computers and InformationAssiut UniversityAssiutEgypt Department of Computer Science Faculty of Computers and InformationSouth Valley UniversityQenaEgypt

Indoor localization methods can help many sectors,such as healthcare centers,smart homes,museums,warehouses,and retail malls,improve their service *** a result,it is crucial to look for low-cost methods that can provide exact localization in indoor *** this context,imagebased localization methods can play an important role in estimating both the position and the orientation of cameras regarding an ***-based localization faces many issues,such as image scale and rotation ***,image-based localization’s accuracy and speed(latency)are two critical *** paper proposes an efficient 6-DoF deep-learning model for image-based *** model incorporates the channel attention module and the Scale PyramidModule(SPM).It not only enhances accuracy but also ensures the model’s real-time *** complex scenes,a channel attention module is employed to distinguish between the textures of the foregrounds and *** model adapted an SPM,a feature pyramid module for dealing with image scale and rotation variance ***,the proposed model employs two regressions(two fully connected layers),one for position and the other for orientation,which increases outcome *** on standard indoor and outdoor datasets show that the proposed model has a significantly lower Mean Squared Error(MSE)for both position and *** the indoor 7-Scenes dataset,the MSE for the position is reduced to 0.19 m and 6.25°for the ***,on the outdoor Cambridge landmarks dataset,the MSE for the position is reduced to 0.63 m and 2.03°for the *** to the findings,the proposed approach is superior and more successful than the baseline methods.

关键词： Image-based localization computer vision deep learning attention module VGG-16

Impact of COVID-19 infection during pregnancy on maternal and fetal outcomes

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Reproductive and Developmental Medicine 2023年第2期7卷 108-114页

作者： Mohamed elsibai Anter Nasser Kamal abd el-Aal Mohamed abd Allah Rezk Hussein Fahmy Moawad ahmed Tharwat Abudakika Obstetrics and Gynecology Department Faculty of MedicineElkom CityMenoufia UniversityMenoufiaEgypt Resident of Obstetrics and Gynecology at al-Bagour General Hospital al-Bagour CityMenoufiaEgypt

Objectives:The objective of this study is to assess the impact of coronavirus disease 2019(COVID-19)infection during pregnancy on maternal and fetal outcome in relation to gestational ***:This retrospective study was conducted between May 2020 and July ***-five women infected with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)and hospitalized at a quarantine hospital were ***-four women received prenatal care at the hospital until delivery,while 31 dropped out from the study due to COVID-19 recovery and discharge before ***:COVID-19 was found in 83%of the pregnant women after 20 weeks of *** most common symptoms were cough and *** complications included severe pneumonia and *** maternal mortality rate was 9.2%.Premature rupture of membranes and severe hypertension during labor affected nearly 9%of the pregnant women who completed prenatal care until delivery at the *** labor occurred at a rate of 38.2%.There were seven(20.8%)stillbirths and two cases of infant ***:Hospitalized pregnant women who have coronavirus infection,lymphopenia,and a high C-reactive protein level were at a higher risk of developing severe illness,which can lead to maternal and neonatal complications.

关键词： COVID-19 Hospitals Infant Quarantine Pregnancy outcome Prenatal care Women

Magnetoresistive properties of Ni-doped La_(0.7)Sr_(0.3)MnO_3 manganites

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Rare Metals 2016年第7期35卷 551-558页

作者： ahmed Mohamed ahmed abd el-Moez ahmed Mohamed Medhat abdelrady abdellateef Hassan ahmed abd el-Ghanny Physics Department Faculty of ScienceSohag University

Lao.7Sr0.3Mnl_xNixO3 （x = 0, 0.025, 0.050 and 0.075） ceramics were prepared by the conventional solid-state reaction method. The partial substitution of Mn by Ni2＋ leads to a decrease in cell volume as well as a structural transition from the rhombohedral to the orthorhombic structure. Ni2＋ doping increases the electrical resistivity, decreases the semiconductor-metal transition temperature （Tms） and relatively enhances the room temperature magnetoresistance （MR）, especially in x = 0.025 and around Tins. With respect to conduction mechanism, the small polaron hopping （SPH） and the variable range hopping （VRH） models were used to ex- amine conduction in the semiconducting region.

关键词： Manganites X-ray diffraction Structure electrical resistivity Magnetoresistance

Improved RC6 Block Cipher Based on Data Dependent Rotations

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第1期70卷 1921-1934页

作者： Osama S.Faragallah Ibrahim F.elashry ahmed AlGhamdi Walid el-Shafai S.el-Rabaie Fathi E.abd el-Samie Hala S.el-sayed Mohamed A.elaskily Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electrical Communications Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Informatics Electronic Research Institute(ERI)CairoEgypt

This paper introduces an Improved RC6(IRC6)cipher for data encryption based on data-dependent *** proposed scheme is designed with the potential of meeting the needs of the Advanced Encryption Standard(AES).Four parameters are used to characterize the proposed *** parameters are the size of the word(w)in bits,the number of rounds(r),the length of the secret key(b)in bytes,and the size of the block(L)in *** main feature of IRC6 is the variable number of working registers instead of just four registers as in RC6,resulting in a variable block size for plaintext and *** IRC6 cipher is designed to improve the robustness against attacks by increasing the diffusion for each round and providing greater security with fewer *** effectiveness of the proposed IRC6 scheme is verified against theoretical *** proposed IRC6 scheme depends on full diffusion and confusion mechanisms regardless of the utilized block *** proposed IRC6 scheme saves 70%of the encryption time and 64%of the decryption time of *** simulation results prove that the IRC6 achieves a better encryption/decryption time compared to the ***,the proposed IRC6 is anticipated to fulfill the market needs and system security requirements.

关键词： Cryptography block cipher RC6,IRC6,AES

Anatomical and Molecular Identification of Ornamental Plant Ficus ***

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Phyton-International Journal of Experimental Botany 2023年第5期92卷 1329-1347页

作者： Abtisam Binnoubah Rim Hamdy Osama G.Ragab ahmed M.el-Taher ahmed Abou el-Yazied Fatmah A.Safhi Hala A.elzilal Ashwaq T.Althobaiti Salha M.ALshamrani Diaa.abd el Moneim ahmed el-Banhawy Department of Botany Faculty of ScienceUniversity of SabrathaSabratha999116Libya Department of Botany Faculty of ScienceCairo UniversityGiza12111Egypt Department of Botany and Microbiology Faculty of Science(Boys Branch)Al-Azhar UniversityCairo11884Egypt Department of Agricultural Botany Faculty of AgricultureAl-Azhar UniversityCairo11884Egypt Department of Horticulture Faculty of AgricultureAin Shams UniversityCairo11566Egypt Department of Biology College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Science and Technology College of RanyahTaif UniversityTaif21944Saudi Arabia Department of Biology College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Biology College of ScienceUniversity of JeddahJeddah21959Saudi Arabia Department of Plant Production(Genetic Branch) Faculty of Environmental Agricultural SciencesArish UniversityEl-Arish45511Egypt Department of Botany and Microbiology Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

This present study includes twelve species that represent the Ficus genus,namely;aspera,carica,tinctoria ***,hirta,hispida,neriifolia,palmata,pumila,racemosa,septica,sur,and sycomorus,belonging to the Moraceae *** species samples were collected from various locations in *** study focused on the anatomical and molecular characteristics of mature foliage *** the identification and classification of taxa are highly dependent on the anatomical features of leaves,the anatomical characteristics were recorded in the form of a comparison between the examined plants in the data *** study aims to contribute to the identification of the studied species based on the anatomical details of the matured *** characterization includes the variations in upper and lower epidermal layers that are covered by a thin or thick cuticle;the number of palisade and spongy layers;crystals;secretory elements;lithocysts;the midrib zone has parenchyma associated with mechanical tissue,vascular system,and investigation of trichomes;on the other hand,in the current study,the phylogenetic analysis was conducted by using the ITS and 5.8 S *** the analysis of all the available data,it could be stated that there is an overall agreement with the anatomical character dendrogram.

关键词： ITS trichomes leaf anatomy Ficus moraceae

Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 3687-3703页

作者： ahmed M.Ayoup Ashraf A.M.Khalaf Walid el-Shafai Fathi E.abd el-Samie Fahad Alraddady Salwa M.Serag eldin electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt electronics and electrical Communications Engineering Department Faculty of Electronic EngineeringMenoufia University32952MenoufEgypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of electronics and electrical Communications Engineering Faculty of EngineeringTanta UniversityTantaEgypt

The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric *** paper presents a cancellable multi-biometric identification scheme that includes four stages:biometric data collection and processing,Arnold’s Cat Map encryption,decimation process to reduce the size,and finalmerging of the four biometrics in a single generated ***,a 2D matrix of size 128×128 is created based on Arnold’s Cat Map(ACM).The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more *** decimation is performed to keep the dimensions of the overall cancellable template similar to those of a single template to avoid data ***,some sort of aliasing occurs due to decimation,contributing to the intended distortion of biometric *** hybrid structure that comprises encryption,decimation,andmerging generates encrypted and distorted cancellable *** simulation results obtained for performance evaluation show that the system is safe,reliable,and feasible as it achieves high security in the presence of noise.

关键词： Aliasing technique selective encryption ACM decimation process

Enhanced Robotic Vision System Based on Deep Learning and Image Fusion

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第10期73卷 1845-1861页

作者： E.A.a.abdulkreem ahmed Sedik Abeer D.Algarni Ghada M.el Banby Fathi E.abd el-Samie Naglaa F.Soliman Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafrelsheikh33511Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Image fusion has become one of the interesting fields that attract researchers to integrate information from different image *** is involved in several *** of the recent applications is the robotic *** application necessitates image enhancement of both infrared(IR)and visible *** paper presents a Robot Human Interaction System(RHIS)based on image fusion and deep *** basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured ***,an enhancement model is carried out on the fused image to increase its *** image enhancement models such as fuzzy logic,Convolutional Neural Network(CNN)and residual network(ResNet)pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art *** results prove that the fuzzy logic enhancement gives the best results from the image quality ***,the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.

关键词： Deep learning fuzzy logic image fusion IR images

Efficient Deep Learning Modalities for Object Detection from Infrared Images

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2022年第8期72卷 2545-2563页

作者： Naglaa F.Soliman E.A.a.abdulkreem Abeer D.Algarni Ghada M.el Banby Fathi E.abd el-Samie ahmed Sedik Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a visual search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term Memory(ConvLSTM).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDM SPIHT IoT

An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid el-Shafai Noha A.el-Hag ahmed Sedik Ghada elbanby Fathi E.abd el-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.abdel Samea Department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis