检索结果-南通市图书馆

Crop Discrimination Using field Hyper Spectral Remotely Sensed Data

Advances in Remote Sensing 2013年第2期2卷 63-70页

作者： sayed M. Arafat Mohamed A. Aboelghar Eslam f. Ahmed Agriculture Applications Department National Authority for Remote Sensing and Space Sciences (NARSS)Cairo Egypt

Crop discrimination through satellite imagery is still problematic. Accuracy of crop classification for high spatial resolution satellite imagery in the intensively cultivated lands of the Egyptian Nile delta is still low. Therefore, the main objective of this research is to determine the optimal hyperspectral wavebands in the spectral range of (400 - 2500 nm) to discriminate between two winter crops (Wheat and Clover) and two summer crops (Maize and Rice). This is considered as a first step to improve crop classification through satellite imagery in the intensively cultivated areas in Egypt. Hyperspectral ground measurements of.a.D field Spec3 spectroradiometer was used to monitor the spectral reflectance profile during the period of the maximum growth stage of the four crops. 1-nm-wide was aggregated to 10-nm-wide bandwidths. After accounting for atmospheric windows and/or areas of significant noise, a total of 2150 narrow bands in 400 - 2500 nm were used in the analysis. Spectral reflectance was divided into six spectral zones: blue, green, red, near-inf.a.ed, shortwave inf.a.ed-I and shortwave inf.a.ed-II. One Way ANOVA and Tukey’s HSD post hoc analysis was performed to choose the optimal spectral zone that could be used to differentiate the different crops. Then, linear regression discrimination (LDA) was used to identify the specific optimal wavebands in the spectral zones in which each crop could be spectrally identified. The results of Tukey’s HSD showed that blue, NIR, SWIR-1 and SWIR-2 spectral zones are more sufficient in the discrimination between wheat and clover than green and red spectral zones. At the same time, all spectral zones were quite sufficient to discriminate between rice and maize. The results of (LDA) showed that the wavelength zone (727:1299 nm) was the optimal to identify clover crop while three zones (350:712, 1451:1562, 1951:2349 nm) could be used to identify wheat crop. The spectral zone (730:1299 nm) was the optimal to identify maize

关键词： Hyper Spectral Data Crop Discrimination

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Deep CNN Model for Multimodal Medical Image Denoising

引用

Computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-sayed M.El-Rabaie Taha E.Taha Osama f.Zahran Adel S.El-fishawy Naglaa f.Soliman Amel A.Alhussan fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt 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

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Efficient Deep CNN Model for COVID-19 Classification

引用

Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid El-Shafai Amira A.Mahmoud El-sayed M.El-Rabaie Taha E.Taha Osama f.Zahran Adel S.El-fishawy Mohammed Abd-Elnaby fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in *** Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death *** X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis *** are numerous ways to identify positive COVID-19 *** of the fundamental ways is radiology imaging through CXR,or CT *** comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high ***,automated classification techniques are required to facilitate the diagnosis *** Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical *** deep Convolutional Neural Networks(CNNs)can learn and extract essential f.a.ures from different medical image *** this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is *** activation functions as well as three optimizers are tested and compared for this *** proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train *** performance is tested and investigated on the CT and CXR *** activation functions:Tanh,Sigmoid,and ReLU are compared using a constant learning rate and different batch *** optimizers are studied with different batch sizes and a constant learning ***,a comparison between different combinations of.a.tivation functions and optimizers is presented,and the optimal configuration is ***,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early *** proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR an

关键词： COVID-19 image classification CNN DL activation functions optimizers

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

An Improved Convolutional Neural Network Model for DNA Classification

引用

Computers, Materials & Continua 2022年第3期70卷 5907-5927页

作者： Naglaa.f.Soliman Samia M.Abd-Alhalem Walid El-Shafai Salah Eldin S.E.Abdulrahman N.Ismaiel El-sayed M.El-Rabaie Abeer D.Algarni fathi E.Abd El-Samie Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt

Recently,deep learning(DL)became one of the essential tools in bioinformatics.A modified convolutional neural network(CNN)is employed in this paper for building an integratedmodel for deoxyribonucleic acid(DNA)*** any CNN model,convolutional layers are used to extract f.a.ures followed by max-pooling layers to reduce the dimensionality of f.a.ures.A novel method based on downsampling and CNNs is introduced for f.a.ure *** downsampling is an improved form of the existing pooling layer to obtain better classification *** two-dimensional discrete transform(2D DT)and two-dimensional random projection(2D RP)methods are applied for *** convert the high-dimensional data to low-dimensional data and transform the data to the most significant f.a.ure ***,there are parameters which directly affect how a CNN model is *** this paper,some issues concerned with the training of CNNs have been *** CNNs are examined by changing some hyperparameters such as the learning rate,size of minibatch,and the number of *** and assessment of the performance of CNNs are carried out on 16S rRNA bacterial *** results indicate that the utilization of.a.CNN based on wavelet subsampling yields the best trade-off between processing time and accuracy with a learning rate equal to 0.0001,a size of minibatch equal to 64,and a number of epochs equal to 20.

关键词： DNA classification CNN downsampling hyperparameters DL 2D DT 2D RP

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Vascular Trauma Registry Analysis in Sulaimani Province of Southern Kurdistan

引用

Surgical Science 2015年第8期6卷 369-375页

作者： Aram Baram fahmi H. Kakamad Warzer f. Shali Rebwar sayed-Nouri Department of Surgery School of Medicine Faculty of Medical Sciences University of Sulaimani Sulaymaniyah Iraq Department of Thoracic and Cardiovascular Surgery Sulaimani Teaching Hospital Sulaymaniyah Iraq Department of Thoracic and Cardiovascular Surgery School of Medicine Faculty of Medical Sciences University of Sulaimani Sulaymaniyah Iraq Department of Orthopedics and Trauma Sulaimani DOH Sulaymaniyah Iraq Department Cardiothoracic Surgery Sulaimani DOH Sulaymaniyah Iraq

Background: Vascular injury presents a great challenge to the trauma and vascular surgeons because it needs urgent diagnosis and intervention. Aims: Prospective cohort study is to determine management and outcome of peripheral vascular injuries in a tertiary centre with very poor facilities. Methods: Analysis of peripheral vascular injuries during August 2013 to August 2014. Results: Total of 47 patients (3.4%) from 1377 total trauma admissions had vascular injuries. Penetrating trauma was present in 93.6% of cases. Brachial artery injury was the highest (31.9%), followed by superficial femoral and popliteal arteries (each with 17% incidence). Vein injury occurred in 61.7% of cases. End-to-end anastomosis performed in 76.6% of cases;arterial ligation was done in 14.9% of cases;venous graft was harvested in 6.4% of cases;and arterial wall was repaired in 2.1% of cases. Conclusions: Early intervention is the most important determinant factor of outcome.

关键词： Peripheral Vascular Trauma Hard Signs Soft Signs Long-Term Outcome Surgical Effect Complications

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Al-Biruni Based Optimization of Rainfall forecasting in Ethiopia

引用

Computer Systems Science & Engineering 2023年第6期45卷 2885-2899页

作者： El-sayed M.El-kenawy Abdelaziz A.Abdelhamid fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa Sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

On the Product of Integro Differential Equations and Their Solutions in Direct Sum Spaces

引用

Journal of Mathematics and System Science 2013年第5期3卷 231-245页

作者： Sobhy El-sayed Ibrahim College of Basic Education Department of Mathematics Al-Ardiya area Kuwait

In this paper, we consider a general quasi-differential expressions t1,t2 Tn, each of order n with complex coefficients and their formal adjoints are t1＋,t2＋- x＋ on [0, b） respectively. We show in the direct sum spaces LZ（Ip）, p = 1,2 N of functions defined on each of the separate intervals with the case of one singular end-points and under suitable conditions on the function f that all solutions of the product quasi-integro differential equations are bounded and LZw -bounded on [0,b）.

关键词： Quasi-integro differential equation product differential expressions direct sum spaces bounded and square integrablesolutions.

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

facial Expression Recognition Model Depending on Optimized Support Vector Machine

引用

Computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan fatma M.Talaat El-sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&Information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and Intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

In computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is f.a.ible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(fERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(fERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** fERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,f.a.,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%f1 score.

关键词： facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

A Novel Spectrophotometric Method for Determination of five 1,4-Dihydropyridine Drugs in Their Tablets and Capsules Using Vanillin Reagent

引用

American Journal of.a.alytical Chemistry 2013年第3期4卷 148-157页

作者： Mohamed A. El Hamd sayed M. Derayea Osama Hassan Abdelmageed Hassan f. Askal Department of Pharmaceutical Analytical Chemistry Faculty of Pharmacy Al-Azhar University Assiut Egypt Department of Pharmaceutical Analytical Chemistry Faculty of Pharmacy Assiut University Assiut Egypt Department of Pharmaceutical Analytical Chemistry Faculty of Pharmacy Minia University Minia Egypt Pharmaceutical Chemistry Department Faculty of Pharmacy King Abdulaziz University Jeddah KSA

A selective and new spectrophotometric method is described for determination of five 1,4 dihydropyridine drugs (1,4- DHP);namely nifedipine (NIf), nicardipine (NIC), nimodipine (NIM), felodipine (fEL) and amlodipine (AML). The method is based on a coupling reaction between the cited drugs and vanillin reagent in acidic condition. Under optimized conditions, the red coloured products were measured at 500 nm for NIf, NIC, NIM and fEL or at 479 nm for AML. Molar absorptivities were ranged from 0.575 × 104 - 1.065 × 104 l·mol-1·cm-1, Beer’s law was obeyed at 5 - 70 μg/mL concentration range and the limit of detection was ranged from 0.150 - 1.500 μg/mL. The proposed method was successfully extended to pharmaceutical preparations tablets and capsules and comparison by Student’s t-test and variance ratio f-test showed no significant difference.

关键词： Spectrophotometric Method 1 4-DHP Validated Selective Vanillin Reagent

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Hash Table Assisted Efficient file Level De-Duplication Scheme in SD-IoV Assisted Sensing Devices

引用

Intelligent Automation & Soft Computing 2023年第10期38卷 83-99页

作者： Ghawar Said Ata Ullah Anwar Ghani Muhammad Azeem Khalid Yahya Muhammad Bilal sayed Chhattan Shah Department of Computer Science International Islamic UniversityIslamabad44000Pakistan Department of Computer Science National University of Modern LanguagesIslamabad44000Pakistan Department of Electrical and Electronics Engineering Nisantasi UniversityIstanbul34467Turkey Department of Computer Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea Department of Information and Communication Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea

The Internet of Things(IoT)and cloud technologies have encouraged massive data storage at central ***-defined networks(SDN)support the processing of data and restrict the transmission of duplicate *** is necessary to use a data de-duplication mechanism to reduce communication costs and storage *** State of the art schemes suffer from computational overhead due to deterministic or random tree-based tags generation which further increases as the file size *** paper presents an efficient file-level de-duplication scheme(EfDS)where the cost of creating tags is reduced by employing a hash table with key-value pair for each block of the ***,an algorithm for hash table-based duplicate block identification and storage(HDBIS)is presented based on fingerprints that maintain a linked list of similar duplicate blocks on the same *** tables normally have a consistent time complexity for lookup,generating,and deleting stored data regardless of the input *** experiential results show that the proposed EfDS scheme performs better compared to its counterparts.

关键词： Hash table de-duplication linked list IoT sensing devices

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：