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Phytopharmacological potential of different species of Morus alba and their bioactive phytochemicals:A review

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Asian Pacific Journal of Tropical Biomedicine 2017年第10期7卷 950-956页

作者： fahad hussain Zohaib Rana Hassan Shafique Arif Malik Zahid hussain Institute of Molecular Biology and Biotechnology(IMBB) The University of LahoreRaiwind Road55150LahorePakistan Department of Pharmaceutics Faculty of PharmacyUniversiti Teknologi MARAPuncak Alam CampusBandar Puncak Alam42300SelangorMalaysia

Medicinal plants of Moraceae family have been well-recognized traditionally due to their versatile applications in various fields including agriculture, cosmetic and food as well as in pharmaceutical industries. Their biomedical and medicinal importance is reflected from their broad range of pharmacological activities for treatment of various inflammatory conditions, cancer, infectious diseases, and gastrointestinal disorders. The present review was aimed to summarize and critically discuss the biomedical implications of Morus species, their bioactive compounds, and phytochemicals. Bioactivity guided fractionation of these medicinal plants revealed that different types of bioactive phytochemicals and secondary metabolites such as steroids, saponins, alkaloids, glycosides and phenolic compounds including terpenoids, flavonoids, anthocyanins and tannins were present. The critical analysis of the literature revealed that the aqueous, methanolic, and ethanolic extracts of Morus species and their bioactive compounds exhibit remarkable anti-oxidative,anti-diabetic, anti-stress, nephroprotective, antimicrobial, anti-mutagenic, anticancer,anxiolytic, hepatoprotective, anthelmintic, antimicrobial, immune-modulatory and cholesterol lowering effects. Based on the literature review and bioactivity guided investigation of Morus species and their phytomedicinal effects, we anticipate that these herbal products hold excellent potential for future research.

关键词： Moraceae Phytochemicals Pharmacological activities Anti-inflammatory Immunomodulatory Anticancer

Improved Semi-empirical Model of Proton Exchange Membrane fuel Cell Incorporating fault Diagnostic feature

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1566-1573页

作者： Saad Saleem Khan hussain Shareef Ahmad Asrul Ibrahim Department of Electrical Engineering College of EngineeringUnited Arab Emirates University IEEE Department of Electrical Electronic and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan Malaysia

The membrane water content of the proton exchange membrane fuel cell(PEMfC)is the most important feature required for water management of the PEMfC *** improper management of water in the fuel cell may lead to system *** various faults,flooding and drying faults are the most frequent in the PEMfC *** paper presents a new dynamic semi-empirical model which requires only the load current and temperature of the PEMfC system as the input while providing output voltage and membrane water content as its major *** other PEMfC systems,the proposed dynamic model calculates the internal partial pressure of oxygen and hydrogen rather than using special internal ***,the membrane water content and internal resistances of PEMfC are modelled by incorporating the load current condition and temperature of the PEMfC *** model parameters have been extracted by using a quantum lightening search algorithm as an optimization technique,and the performance is validated with experimental data obtained from the NEXA 1.2 k W PEMfC *** further demonstrate the capability of the model in fault detection,the variation in membrane water content has been studied via the *** proposed model could be efficiently used in prognostic and diagnosis systems of PEMfC fault.

关键词： Proton exchange membrane fuel cell(PEMfC)fault membrane water content modelling optimization quan-tum lightening search algorithm

An Analysis of Integrating Machine Learning in Healthcare for Ensuring Confidentiality of the Electronic Records

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Computer Modeling in Engineering & Sciences 2022年第3期130卷 1387-1422页

作者： Adil hussain Seh Jehad f.Al-Amri Ahmad f.Subahi Alka Agrawal Nitish Pathak Rajeev Kumar Raees Ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025India Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Umm Al-Qura UniversityMakkah21421Saudi Arabia Department of Information Technology Guru Gobind Singh Indraprastha UniversityDelhi110078India Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003India Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

The adoption of sustainable electronic healthcare infrastructure has revolutionized healthcare services and ensured that E-health technology caters efficiently and promptly to the needs of the stakeholders associated with *** the phenomenal advancement in the present healthcare services,the major obstacle that mars the success of E-health is the issue of ensuring the confidentiality and privacy of the patients’data.A thorough scan of several research studies reveals that healthcare data continues to be the most sought after entity by cyber *** approaches and methods have been practiced by researchers to secure healthcare digital ***,there are very few from the Machine learning(ML)domain even though the technique has the proactive ability to detect suspicious accesses against Electronic Health Records(EHRs).The main aim of this work is to conduct a systematic analysis of the existing research studies that address healthcare data confidentiality issues through ML *** guidelines have been practiced as a manual to conduct this *** well-known digital libraries namely IEEE Xplore,Science Direct,Springer Link,ACM Digital Library,Willey Online Library,PubMed(Medical and Bio-Science),and MDPI have been included to performan exhaustive search for the existing pertinent *** of this study depict that machine learning provides a more robust security mechanism for sustainable management of the EHR systems in a proactive fashion,yet the specified area has not been fully explored by the researchers.K-nearest neighbor algorithm and KNIEM implementation tools are mostly used to conduct experiments on EHR systems’log *** and performance measure of practiced techniques are not sufficiently outlined in the primary *** research endeavour depicts that there is a need to analyze the dynamic digital healthcare environment more *** accuracy and effective implementation of

关键词： EHRs healthcare machine learning systematic analysis

Efficient maximum power point tracker based on neural network and sliding-mode control for buck converters

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Clean Energy 2022年第5期6卷 716-725页

作者： hussain Attia Khaled Hossin Department of Electrical and Electronic Engineering American University of Ras Al KhaimahRas Al KhaimahUnited Arab Emirates Department of Mechanical and Industrial Engineering American University of Ras Al KhaimahRas Al KhaimahUnited Arab Emirates

This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation *** design of an intelligent maximum power point tracker(MPPT)supported by a robust sliding-mode(SM)controller is discussed in this *** proposed control scheme is designed to track the MPP and provide a smooth system response by removing the overshoot in the load current during any variation in the connected *** a system is suitable for DC-DC buck converter *** study begins with modelling the buck converter for a continuous current mode *** reference voltage of the tracking system is produced by the proposed neural network(NN)*** proposed intelligent MPPT integrated with an SM controller is simulated in a MATLAB®/Simulink®*** simulation results are analysed to investigate and confirm the satisfaction level of the adopted four-serially connected PV-modules *** system performance is evaluated at a light intensity of 500 W/m^(2) and an ambient temperature of 25°*** only the proposed NN algorithm guarantees the MPP tracking response by delivering 100 W at a resistive load of 13Ω,and 200 W at a load of 6.5Ω,respectively,with 99.77%system ***,this simultaneously demonstrates a current spike of~0.5 A when the load is varied from 50%to 100%.The integrated SM controller demonstrates a robust and smooth response,eliminating the existing current spike.

关键词： photovoltaic panel neural network algorithm MPPT sliding-mode controller buck converter

Contribution of hydro energy production,economic complexity and technological innovation in achieving an environmentally sustainable Asia

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Geoscience frontiers 2024年第5期15卷 515-528页

作者： farah Rana Bilal hussain Abdelmohsen A.Nassani Ayesha hussain Mohamed Haffar Syed Asif Ali Naqvi Department of Economics Government College UniversityFaisalabadPakistan Government Graduate College Gojra Toba Tek SinghPakistan Department of Management College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh 11587Saudi Arabia Department of Home Economics Government College Women University FaisalabadPakistan Department of Management Birmingham Business SchoolUniversity of BirminghamUnited Kingdom

The impact of hydro energy production,economic complexity,urbanization,technological innovation and financial development on environmental sustainability between 1995 and 2017 is examined for a panel of thirteen Asian economies using two environmental proxies—their ecological footprint and CO_(2)*** non-parametric Driscoll-Kraay standard error method and the Dumitrescu-Hurlin panel causality test are applied to the *** findings show that hydro energy production and technological innovation have a significant negative impact on the environment,thus promoting environmental *** complexity significantly lowers environmental sustainability while the non-linear effect of economic complexity favors environmental sustainability;this confirms the existence of an economic-complexity-based inverted-U-shaped environmental Kuznets curve ***,urbanization and financial development significantly decrease environmental *** results of our study confirm the feedback causality between hydro energy production and carbon dioxide *** recommend expansionary policies regarding hydro energy production that are beneficial for substituting fossil fuel *** paves a path towards environmental sustainability in this era of global boiling.

关键词： Hydro energy production Environmental sustainability Global boiling Economic complexity Asian countries Panel corrected standard error

Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color fundus Images

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Computers, Materials & Continua 2023年第7期76卷 133-150页

作者： Ali Haider Khan Hassaan Malik Wajeeha Khalil Sayyid Kamran hussain Tayyaba Anees Muzammil hussain Department of Software Engineering Faculty of Computer SciencesLahore Garrison UniversityLahorePakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Computer Science&Information Technology University of Engineering and Technology(UET)PeshawarPakistan Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CfI)is a screening technology that is both effective and *** to CfIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic *** traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of *** addition,they usually only target one or a few different kinds of eye diseases at the same *** this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs ***_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification *** DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right *** then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel *** the attributes have been analyzed,they are integrated to provide a representation at the patient *** the whole process of ODs categorization,the patient-level representation will be *** efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

关键词： Ocular disease multi-label spatial correlation CNN eye disease

LSTDA: Link Stability and Transmission Delay Aware Routing Mechanism for flying Ad-Hoc Network (fANET)

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Computers, Materials & Continua 2023年第10期77卷 963-981页

作者： farman Ali Khalid Zaman Babar Shah Tariq hussain Habib Ullah Altaf.hussain Daehan Kwak Department of Computer Science and Engineering Sungkyunkwan UniversitySeoul03063South Korea Information Engineering School Chang’an UniversityXi’an710061China College of Technological Innovation Zayed UniversityDubai19282United Arab Emirates School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhou310018China Institute of Computer Science and IT The University of Agriculture PeshawarPeshawer25120Pakistan Department of Computer Science and Technology Kean UniversityUnionNew Jersey07083USA

The paper presents a new protocol called Link Stability and Transmission Delay Aware(LSTDA)for flying Adhoc Network(fANET)with a focus on network corridors(NC).fANET consists of Unmanned Aerial Vehicles(UAVs)that face challenges in avoiding transmission loss and delay while ensuring stable *** proposed protocol introduces a novel link stability with network corridors priority node selection to check and ensure fair communication in the entire *** protocol uses a Red-Black(R-B)tree to achieve maximum channel utilization and an advanced relay *** paper evaluates LSTDA in terms of End-to-End Delay(E2ED),Packet Delivery Ratio(PDR),Network Lifetime(NLT),and Transmission Loss(TL),and compares it with existing methods such as Link Stability Estimation-based Routing(LEPR),Distributed Priority Tree-based Routing(DPTR),and Delay and Link Stability Aware(DLSA)using MATLAB *** results show that LSTDA outperforms the other protocols,with lower average delay,higher average PDR,longer average NLT,and comparable average TL.

关键词： LSTDA routing protocol flying Ad-hoc Network link stability unmanned aerial vehicles maxim priority channel

Deep Learning framework for Classification of Emoji Based Sentiments

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Computers, Materials & Continua 2022年第8期72卷 3145-3158页

作者： Nighat Parveen Shaikh Mumtaz hussain Mahar Shah Abdul Latif University Khairpur77150Pakistan

Recent patterns of human sentiments are highly influenced by emoji based sentiments(EBS).Social media users are widely using emoji based sentiments(EBS)in between text messages,tweets and *** tiny pictures of emoji contains sufficient information to be considered for construction of classification model;but due to the wide range of dissimilar,heterogynous and complex patterns of emoji with similarmeanings(SM)have become one of the significant research areas of machine *** paper proposes an approach to provide meticulous assistance to social media application(SMA)users to classify the EBS *** methodology consists upon three layerswhere first layer deals with data cleaning and feature selection techniques to detect dissimilar emoji patterns(DEP)with similar meanings(SM).In first sub step we input set of emoji,in second sub step every emoji has to qualify user defined threshold,in third sub step algorithm detects every emoji by considering as objects and in fourth step emoji images are cropped,after data cleaning these tiny images are saved as emoji *** second step we build classification model by using convolutional neural networks(CNN)to explore hidden knowledge of emoji *** third step we present results visualization by using confusion matrix and other *** paper contributes(1)data cleaning method to detect EBS;(2)highest classification accuracy for emoji classification measured as 97.63%.

关键词： Deep learning machine vision convolutional neural networks social media emoji based sentiments

Reliability improvement in distribution systems employing an integrated voltage sag mitigation method using binary gravitational search algorithm

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Journal of Central South University 2013年第11期20卷 3002-3014页

作者： Salman Nesrullah Mohamed Azah Shareef.hussain Department of Electrical Electronics and Systems EngineeringFaculty of Engineering and Built EnvironmentUniversiti Kebangsaan Malaysia

A method for improving the level of reliability of distribution systems is presented by employing an integrated voltage sag mitigation method that comprises a two-staged strategy,namely,distribution network reconfiguration(DNR)followed by DSTATCOM ***,an optimal DNR is applied to reduce the propagated voltage sags during the test *** second stage involves optimal placement of the DSTATCOM to assist the already reconfigured *** gravitational search algorithm is used in the process of optimal DNR and in placing *** assessment is performed using the well-known *** simulation results show that the proposed method is efficient and feasible for improving the level of system reliability.

关键词： voltage sag reliability network reconfiguration DSTATCOM gravitational search algorithm