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Phytochemical analysis and inhibitory effects of Calligonum polygonoides on pancreatic α-amylase and β-glucosidase enzymes

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Journal of Traditional Chinese Medicine 2022年第3期42卷 426-431页

作者： Mushtaq ahmed Naila Sher Nadia Mushtaq Rahmat ali Khan Department of Biotechnology Faculty of Biological SciencesUniversity of Science&TechnologyBannu 28100KPK-Pakistan Department of Botany Faculty of Biological SciencesUniversity of Science&TechnologyBannu 28100KPKPakistan

OBJECTIVES:To estimate the existence of phytochemicals and then to determine the antidiabetic activity againstα-amylase andβ-glucosidase inhibition in ***:The study was carried out by following standard ***:Phytochemicals analysis indicated the presence of different *** total phenolic content was 6.055 mg GAE/g and the total flavonoid content was 5.706 mg RU/g in the plant *** total saponins,alkaloids,and tannins contents were(0.044%),(2.88%)and(2.862 nm)respectively.α-amylase inhibition activity of Calligonum polygonoides(CP)extract was 70%with IC50 of 610μg/mL and that ofβ-glucosidase inhibition activity was 65%with IC50 of 640μg/***:The findings reported for the first time the antidiabetes-promoting effects of an extract of CP in vitro,thus validating their promising anti-diabetes potential.

关键词： Calligonum polygonoides phytochemicals alpha-amylases beta-glucosidase

Disturbance Evaluation in Power System Based on Machine Learning

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Computers, Materials & Continua 2022年第4期71卷 231-254页

作者： Emad M.ahmed Mohamed A.ahmed Ziad M.ali Imran Khan Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72388Al-JoufSaudi Arabia Department of Electrical Engineering College of EngineeringPrince Sattam bin Abdulaziz UniversityWadi Addawaser11991Saudi Arabia Department of Electrical Engineering Aswan Faculty of EngineeringAswan UniversityAswan81542Egypt Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan

The operation complexity of the distribution system increases as a large number of distributed generators(DG)and electric vehicles were introduced,resulting in higher demands for fast online reactive power *** a power system,the characteristic selection criteria for power quality disturbance classification are not *** classification effect and efficiency needs to be improved,as does the generalization *** order to categorize the quality in the power signal disturbance,this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality ***,a multi-label classification algorithm based on rating is proposed to understand the relationship between the labels and identify the various power quality *** two algorithms are combined to construct a multi-label classification model based on a multi-level extreme learning machine,and the optimal network structure of the multi-level extreme learning machine as well as the optimal multi-label classification threshold are *** proposed method can be used to classify the single and compound power quality disturbances with improved classification effect,reliability,robustness,and anti-noise performance,according to the experimental *** hamming loss obtained by the proposed algorithm is about 0.17 whereas ML-RBF,SVM and ML-KNN schemes have 0.28,0.23 and 0.22 respectively at a noise intensity of 20 *** average precision obtained by the proposed algorithm 0.85 whereas the ML-RBF,SVM and ML-KNN schemes indicates 0.7,0.77 and 0.78 respectively.

关键词： Optimal power flow optimization algorithm deep learning power systems

A Content-Based Medical Image Retrieval Method Using Relative Difference-Based Similarity Measure

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Intelligent Automation & Soft Computing 2023年第8期37卷 2355-2370页

作者： ali ahmed Alaa Omran Almagrabi Omar MBarukab Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz University–RabighRabigh21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz University-RabighRabigh21589Saudi Arabia

Content-based medical image retrieval(CBMIR)is a technique for retrieving medical images based on automatically derived image *** are many applications of CBMIR,such as teaching,research,diagnosis and electronic patient *** methods are applied to enhance the retrieval performance of CBMIR *** new and effective similarity measure and features fusion methods are two of the most powerful and effective strategies for improving these *** study proposes the relative difference-based similarity measure(RDBSM)for *** new measure was first used in the similarity calculation stage for the CBMIR using an unweighted fusion method of traditional color and texture ***,the study also proposes a weighted fusion method for medical image features extracted using pre-trained convolutional neural networks(CNNs)*** proposed RDBSM has outperformed the standard well-known similarity and distance measures using two popular medical image datasets,Kvasir and PH2,in terms of recall and precision retrieval *** effectiveness and quality of our proposed similarity measure are also proved using a significant test and statistical confidence bound.

关键词： Medical image retrieval feature extraction similarity measure fusion method

Deep Learning Framework for Precipitation Prediction Using Cloud Images

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Computers, Materials & Continua 2022年第8期72卷 4201-4213页

作者： Mirza Adnan Baig Ghulam ali Mallah Noor ahmed Shaikh Shah Abdul Latif University Khairpur77150Pakistan

Precipitation prediction(PP)have become one of the significant research areas of deep learning(DL)and machine vision(MV)techniques are frequently used to predict the weather variables(WV).Since the climate change has left significant impact upon weather variables(WV)and continuously changes are observed in temperature,humidity,cloud patterns and other *** cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate,the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall *** of rainfall would provide more meticulous assistance to the farmers to know about the weather conditions and to care their cash *** research proposes a framework to classify the dark cloud patterns(DCP)for prediction of *** framework consists upon three steps to classify the cloud images,first step tackles noise reduction operations,feature selection and preparation of *** step construct the decision model by using convolutional neural network(CNN)and third step presents the performance visualization by using confusion matrix,precision,recall and accuracy *** research contributes(1)real-world clouds datasets(2)method to prepare datasets(3)highest classification accuracy to predict estimated as 96.90%.

关键词： Machine vision SIFT features dark cloud patterns precipitation agriculture

A novel multi-stable sinusoidal chaotic map with spectacular behaviors

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Communications in Theoretical Physics 2023年第11期75卷 3-14页

作者： ahmed M ali ali Sridevi Sriram Hayder Natiq Atefeh Ahmadi Karthikeyan Rajagopal Sajad Jafari Department of Electronics Techniques Babylon Technical InstituteAl-Furat Al-Awsat Technical UniversityBabylon51001Iraq Al-Mustaqbal University College Babylon51001Iraq Centre for Computational Biology Chennai Institute of TechnologyChennai600069Tamil NaduIndia Department of Computer Technology Engineering College of Information TechnologyImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq Department of Biomedical Engineering Amirkabir University of Technology(Tehran Polytechnic)TehranIran Centre for Nonlinear Systems Chennai Institute of TechnologyChennai600069Tamil NaduIndia Department of Electronics and Communications Engineering and University Centre of Research and Development Chandigarh UniversityMohali140413PunjabIndia Health Technology Research Institute Amirkabir University of Technology(Tehran Polytechnic)TehranIran

Chaotic behavior can be observed in continuous and discrete-time *** behavior can appear in one-dimensional nonlinear maps;however,having at least three state variables in flows is *** to the lower mathematical complexity and computational cost of maps,lots of research has been conducted based on *** paper aims to present a novel one-dimensional trigonometric chaotic map that is multi-stable and can act *** proposed chaotic map is first analyzed using a single sinusoidal function;then,its abilities are expanded to a map with a combination of two sinusoidal *** stability conditions of both maps are investigated,and their different behaviors are validated through time series,state space,and cobweb ***,the influence of parameter variations on the maps’outputs is examined by one-dimensional and two-dimensional bifurcation diagrams and Lyapunov exponent ***,the diversity of outputs with varying initial conditions reveals this map’s *** newly designed chaotic map can be employed in encryption applications.

关键词： chaotic map discrete chaos sinusoidal map multi-stability dynamical analysis

Early Diagnosis of Alzheimer’s Disease Based on Convolutional Neural Networks

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Computer Systems Science & Engineering 2022年第10期43卷 305-315页

作者： Atif Mehmood Ahed Abugabah ahmed ali AlZubi Louis Sanzogni College of Technological Innovation Zayed UniversityAbu Dhabi CampusFF2-0-056UAE Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Nathan Campus Griffith UniversityBrisbaneAustralia

Alzheimer’s disease(AD)is a neurodegenerative disorder,causing the most common dementia in the elderly *** AD patients are rapidly increasing in each year and AD is sixth leading cause of death in *** resonance imaging(MRI)is the leading modality used for the diagnosis of *** learning based approaches have produced impressive results in this *** early diagnosis of AD depends on the efficient use of classification *** address this issue,this study proposes a system using two convolutional neural networks(CNN)based approaches for an early diagnosis of AD *** the proposed system,we use segmented MRI *** data samples of three classes include 110 normal control(NC),110 mild cognitive impairment(MCI)and 105 AD subjects are used in this *** data is acquired from the ADNI database and gray matter(GM)images are obtained after the segmentation of MRI subjects which are used for the classification in the proposed *** proposed approaches segregate among NC,MCI,and *** testing both methods applied on the segmented data samples,the highest performance results of the classification in terms of accuracy on NC *** are 95.33%and 89.87%,*** proposed methods distinguish between NC *** and MCI *** patients with a classification accuracy of 90.74%and 86.69%.The experimental outcomes prove that both CNN-based frameworks produced state-of-the-art accurate results for testing.

关键词： Alzheimer’s disease neural networks intelligent systems gray matter

3D static reservoir modelling of Abu Madi paleo-valley in Baltim Field,Offshore Nile Delta Basin,Egypt

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Petroleum Research 2022年第4期7卷 473-485页

作者： Mohammad Abdelfattah Sarhan Tamer Hassan ahmed Saied ali Geology Department Faculty of ScienceDamietta University34517Egypt Qarun Petroleum Company(Apache J.V) New MaadiCairo11742Egypt

The 3D static reservoir modelling provides a good understanding for the hydrocarbon reservoir distri-bution and *** study aimed to construct a static model to study the gas-reservoir potentiality of the Messinian Abu Madi Formation in Baltim Field,offshore Nile Delta *** model was constructed based on the interpretation of the thirty-seven 2D seismic sections besides the analysis of well logs data for five drilled wells(Baltim East-2,Baltim East-3,Baltim East-5,Baltim North-1 and Baltim North-2).The seismic interpretation exposed that the Abu Madi incised valley in Baltim Field is oriented NNW-SSE with width ranges from 5 to 8 km and approximately 32 km in *** reservoir modelling revealed a relatively homogeneous reservoir facies qualities for gas production in two different zones within the Abu Madi *** trapping mechanism for these intervals is represented by pinching out in the two sides of the Abu Madi paleo-valley and bounded by two faults in the northern and southern parts of the study area.

关键词： Abu madi reservoir Baltim field Nile Delta Basin Seismic interpretation Static model Well logging

A Secure and Lightweight Chaos Based Image Encryption Scheme

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Computers, Materials & Continua 2022年第10期73卷 279-294页

作者： Fadia ali Khan Jameel ahmed Fehaid Alqahtani Suliman A.Alsuhibany Fawad ahmed Jawad Ahmad Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Computer Science King Fahad Naval AcademyAl Jubail35512Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Cyber Security Pakistan Navy Engineering CollegeNUSTKarachi 75350Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUnited Kingdom

In this paper,we present an image encryption scheme based on the multi-stage chaos-based image encryption *** method works on the principle of confusion and *** proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing ***,an image(red,green,and blue components)is partitioned into blocks with an equal number of *** block is then processed with Tinkerbell Chaotic Map(TBCM)to get shuffled pixels and shuffled *** Fractal Function(CFF)change the value of pixels of each color component(layer)to obtain a random *** the obtained random sequence,three layers of plain image are ***,with each encrypted layer,Brownian Particles(BP)are XORed that added an extra layer of *** experimental tests including a number of statistical tests validated the security of the presented *** results reported in the paper show that the proposed scheme has higher security and is lightweight as compared to state-of-the-art methods proposed in the literature.

关键词： Chaos fractals fibonacci tinkerbell chaotic map confusion diffusion brownian motion

Hydrogeochemical processes and multivariate analysis for groundwater quality in the arid Maadher region of Hodna,northern Algeria

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Acta Geochimica 2022年第5期41卷 893-909页

作者： Tahar Selmane Mostefa Dougha Mahmoud Hasbaia ahmed Ferhati ali Redjem VESDD Laboratory University of M’sila28000 M’silaAlgeria

This study focused on water quality and hydrogeochemical processes(evolution,origin)in the Maadher region,central Hodna in *** recent decades,the excessive exploitation of this resource due to urbanization,irrigation,and the effect of climate change reaching the countries of northern Africa have caused a decline in water levels and hydrochemical changes in the *** sampling campaign in 2019 based on 13 physicochemical parameters was carried out on the water from 32 boreholes in the study area,compared to data archives of both sampling campaigns in 1967 and *** result revealed that the groundwater as a whole has moderate freshwater quality,due to its total dissolved solids(TDS)content and other dissolved ions of concern(nitrate NO),which exceed WHO *** addition,Piper diagram indicates that the hydrochemical facies of sulfate–chloride–nitrate–calcium(SO–Cl–NO–Catype),which globally characterizes the study area and these elements are the dominant dissolved *** component analysis and hierarchical cluster analysis(HCA)methodologies are applied in order to define the major control factors that affect the hydrochemistry of Maadher *** distinct water groups were found,illustrating a different evolution of salinity(EC and TDS).The HCA indicated an interesting cluster with a distinct contamination signature and most likely with significantly higher sulfate,chloride,and nitrate *** processes also play an important role in the study *** water resource comes from Bousaada Wadi,the exchange at the aquifer depth and the agricultural practices contribute to the deterioration of the quality.

关键词： Groundwater quality Hydrogeochemical processes Multivariate analysis Salinity Mio-Plio-Quaternary aquifer