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Energy-efficient Virtual Machine Allocation Technique Using Flower Pollination Algorithm in Cloud Datacenter:A Panacea to Green Computing

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Journal of Bionic Engineering 2019年第2期16卷 354-366页

作者： mohammed joda usman Abdul Samad Ismail Hassan Chizari Gaddafi Abdul-Salaam Ali Muhammad usman Abdulsalam Yau Gital Omprakash Kaiwartya Ahmed Aliyu Department of Maths Bauchi State University GadauBauchi 81007Nigeria Department of Computer Science Universiti Teknology MalaysiaSkudai Johor 81310Malaysia School of Computing and Technology Park CampusUniversity of Gloucestershire Cheltenham GL50 4SHUK Department of Computer Science Kwame Nkrumah University of Science and TechnologyKumasi 00233Ghana Department of Maths and Computer Federal College of Education Technical GombeGombe 072158Nigeria Department of Maths Abubakar Tafawa Balewa University BauchiBauchi 81027Nigeria Department of Computer and Information Technology Northumbria UniversityNewcastle NE1SSTUK

Cloud computing has attracted significant interest due to the increasing service demands from organizations offloading computationally intensive tasks to ***,datacenter infrastructure comprises hardware resources that consume high amount of energy and give out carbon emissions at hazardous *** cloud datacenter,Virtual Machines(VMs)need to be allocated on various Physical Machines(PMs)in order to minimize resource wastage and increase energy *** allocation problem is *** finding an exact solution is complicated especially for large-scale *** this con text,this paper proposes an Energy-oriented Flower Pollination Algorithm(E-FPA)for VM allocation in cloud datacenter environments.A system framework for the scheme was developed to enable energy-oriented allocation of various VMs on a *** allocation uses a strategy called Dynamic Switching Probability(DSP).The framework finds a near optimal solution quickly and balances the exploration of the global search and exploitation of the local *** considers a processor,storage,and memory constraints of a PM while prioritizing energy-oriented allocation for a set of *** performed on MultiRecCloudSim utilizing planet workload show that the E-FPA outperforms the Genetic Algorithm for Power-Aware(GAPA)by 21.8%,Order of Exchange Migration(OEM)ant colony system by 21.5%,and First Fit Decreasing(FFD)by 24.9%.Therefore,E-FPA significantly improves datacenter performance and thus,enhances environmental sustainability.

关键词： virtualization green computing cloud datacenter energy optimization

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Cross-sectional prevalence and pattern of non-anaemia severe malaria among 2–10 year olds in Sokoto in Northwestern Nigeria

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Frontiers of Medicine 2022年第6期16卷 969-974页

作者： usman Nasir Nakakana Ridwan Muhammad Jega Aliyu Mamman Nauzo Yahya mohammed Ismaila mohammed Ahmed Medical Research Council The Gambia Unit at London School of Hygiene and Tropical MedicineFajara220The Gambia Department of Paediatrics Usmanu Danfodiyo University Teaching HospitalSokoto234Nigeria Department of Paediatrics Federal Medical CentreBirnin Kebbi234Nigeria Department of Microbiology Usmanu Danfodiyo UniversitySokoto234Nigeria Department of Community Medicine Usmanu Danfodiyo University Teaching HospitalSokoto234Nigeria

Malaria is highly prevalent in Nigeria and accounts for approximately 40%of global malaria ***,most reports on severe malaria in Nigeria are from hospital-based studies without accurate information from communities;thus,malaria-related deaths in the community are left *** study aimed to describe the prevalence and pattern of severe malaria in a community in Northwestern Nigeria.A cross-sectional study was conducted among 2–10-year-old children in Sokoto,in August and December 2016,to determine the endemicity of malaria based on Plasmodium falciparum prevalence rate(PfPR2-10)and to describe the disease *** malaria was diagnosed according to the World Health Organisation *** were described using Stata version *** prevalence of non-anaemia severe malaria was higher than expected(2.6%),considering the endemicity pattern which was mesoendemic based on a PfPR2-10 of 34.8%.The mean age of children with severe malaria was 3.73 years,and the male—female ratio was 2:***,54.0%of the patients had hyperparasitaemia.A relatively high prevalence of non-anaemia severe malaria was found in *** finding suggests the need to identify and treat cases in the community using modifications of current strategies,particularly seasonal malaria chemoprophylaxis.

关键词： severe malaria nigeria malaria mortality PfPR2-10 intermediate malaria transmission

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Local-Tetra-Patterns for Face Recognition Encoded on Spatial Pyramid Matching

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Computers, Materials & Continua 2022年第3期70卷 5039-5058页

作者： Khuram Nawaz Khayam Zahid Mehmood Hassan Nazeer Chaudhry Muhammad usman Ashraf usman Tariq mohammed Nawaf Altouri Khalid Alsubhi Department of Software Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electronics Information and BioengineeringPolitecnico di MilanoMilano20122Italy Department of Computer Science University of Management and TechnologySialkotPakistan College of Computer Engineering and Science Prince Sattam bin Abdulaziz UniversityAlkharj16278Saudi Arabia Department of Computer Science Imam Mohammad Ibn Saud Islamic UniversityRiyadh13318Saudi Arabia Department of Computer Science King Abdulaziz UniversityJeddah21589Saudi Arabia

Face recognition is a big challenge in the research field with a lot of problems like misalignment,illumination changes,pose variations,occlusion,and *** a single solution to solve all these problems at a time is a challenging *** have put some effort to provide a solution to solving all these issues by introducing a face recognition model based on local tetra patterns and spatial pyramid *** technique is based on a procedure where the input image is passed through an algorithm that extracts local features by using spatial pyramid matching ***,the input image is recognized using a robust kernel representation method using extracted *** qualitative and quantitative analysis of the proposed method is carried on benchmark image *** results showed that the proposed method performs better in terms of standard performance evaluation parameters as compared to state-of-the-art methods on AR,ORL,LFW,and FERET face recognition datasets.

关键词： Face recognition local tetra patterns spatial pyramid matching robust kernel representation max-pooling

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Two-Mode Biomedical Sensor Build-up:Characterization of Optical Amplifier

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Computers, Materials & Continua 2022年第3期70卷 5487-5501页

作者： usman Masud Fathe Jeribi mohammed Alhameed Faraz Akram Ali Tahir Mohammad Yousaf Naudhani Faculty of Electrical and Electronics Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electrical Communication Engineering University of KasselKassel34127Germany College of Computer Science&Information Technology Jazan UniversityJazan45142Saudi Arabia Faculty of Engineering and Applied Sciences Riphah International UniversityIslamabad44000Pakistan Faculty of Information&Communication Technology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta

Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human *** factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said *** the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their ***,the investigation and technical analysis of the amplifier in the system has been explored in *** algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s *** this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its *** this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.

关键词： Biomedical sensor cavity optomechanics spectroscopy relative intensity noise semiconductor laser diode

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Optimized Evaluation of Mobile Base Station by Modern Topological Invariants

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Computers, Materials & Continua 2023年第1期74卷 363-378页

作者： Khalid Hamid Muhammad Waseem Iqbal Muhammad usman Ashraf Ahmed mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Due to a tremendous increase in mobile traffic,mobile operators have started to restructure their networks to offload their *** directions will lead to fundamental changes in the design of future Fifthgeneration(5G)cellular *** the formal reason,the study solves the physical network of the mobile base station for the prediction of the best characteristics to develop an enhanced network with the help of graph *** number that can be uniquely calculated by a graph is known as a graph *** the last two decades,innumerable numerical graph invariants have been portrayed and used for correlation *** any case,no efficient assessment has been embraced to choose,how much these invariants are connected with a network *** paper will talk about two unique variations of the hexagonal graph with great capability of forecasting in the field of optimized mobile base station topology in setting with physical *** K-banhatti sombor invariants(KBSO)and Contrharmonic-quadratic invariants(CQIs)are newly introduced and have various expectation characteristics for various variations of hexagonal graphs or *** the hexagonal networks are used in mobile base stations in layered,forms called *** review settled the topology of a hexagon of two distinct sorts with two invariants KBSO and CQIs and their reduced *** deduced outcomes can be utilized for the modeling of mobile cellular networks,multiprocessors interconnections,microchips,chemical compound synthesis and memory interconnection *** results find sharp upper bounds and lower bounds of the honeycomb network to utilize the Mobile base station network(MBSN)for the high load of traffic and minimal traffic also.

关键词： Hexagonal networks k-banhatti sombor invariants maple network graph artificial intelligence contraharmonic-quadratic invariants honeycomb

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Recognition of Urdu Handwritten Alphabet Using Convolutional Neural Network (CNN)

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Computers, Materials & Continua 2022年第11期73卷 2967-2984页

作者： Gulzar Ahmed Tahir Alyas Muhammad Waseem Iqbal Muhammad usman Ashraf Ahmed mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science University of South AsiaLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Handwritten character recognition systems are used in every field of life nowadays,including shopping malls,banks,educational institutes,*** is the national language of Pakistan,and it is the fourth spoken language in the ***,it is still challenging to recognize Urdu handwritten characters owing to their cursive *** paper presents a Convolutional Neural Networks(CNN)model to recognize Urdu handwritten alphabet recognition(UHAR)offline and online *** research contributes an Urdu handwritten dataset(aka UHDS)to empower future works in this *** offline systems,optical readers are used for extracting the alphabets,while diagonal-based extraction methods are implemented in online ***,our research tackled the issue concerning the lack of comprehensive and standard Urdu alphabet datasets to empower research activities in the area of Urdu text *** this end,we collected 1000 handwritten samples for each alphabet and a total of 38000 samples from 12 to 25 age groups to train our CNN model using online and offline ***,we carried out detailed experiments for character recognition,as detailed in the *** proposed CNN model outperformed as compared to previously published approaches.

关键词： Urdu handwritten text recognition handwritten dataset convolutional neural network artificial intelligence machine learning deep learning

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Prevalence and risk factors associated with malaria infection among pregnant women in a semi-urban community of north-western Nigeria

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Infectious Diseases of Poverty 2015年第1期4卷 193-197页

作者： Sani Abdullahi Fana mohammed Danladi Abubakar Bunza Sule Aliyu Anka Asiya Umar Imam Shehu usman Nataala Author details 1 Department of Medical Microbiology Faculty of Medical Laboratory ScienceUsmanuDanfodiyo UniversitySokotoNigeria Department of Biological Sciences UsmanuDanfodiyo UniversitySokotoNigeria

Background:Malaria during pregnancy remains a serious public health problem,with substantial risks for the mother,her foetus and the *** aim of this study was to determine the prevalence of malaria and possible risk factors for malaria infection among pregnant women in a semi-urban area in north-western *** women are among the most susceptible to malaria *** of their malaria infection status is an important yardstick to measure the effectiveness of any malaria control ***:We conducted a cross sectional study in the semi-urban area of Argungu,Kebbi State *** hundred and fifty five pregnant women were included in the study after informed verbal consent was *** each participant,the socio-demographic profile,stage of pregnancy and attitude to the use of insecticide-treated nets(ITNs)were investigated using a *** blood samples were collected and thick blood smears were prepared and stained with Giemsa stains to check for malaria *** associations between age,education level and use of ITNs with occurrence of malaria infection during pregnancy were analysed using the chi-square ***:One hundred and six(41.6%)out of 255 pregnant women were infected with malaria parasites,with a mean parasite density of 800 parasitesμl−*** was found that prevalence and parasite density decreased as age *** chi-square test indicated that a lack of education and non-usage of ITNs were significantly associated with malaria ***:Malaria is still a major public health issue among pregnant women mainly due to illiteracy and non-compliance to using *** awareness about malaria preventive measures and early attendance of antenatal care services will help to reduce malaria and,consequently,its associated morbidities and mortalities.

关键词： Malaria Pregnant women Mean parasite density Prevalence Risk factors Giemsa stain Argungu

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Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

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Intelligent Automation & Soft Computing 2023年第4期36卷 169-181页

作者： Muhammad Irfan Khalil Ullah Fazal Muhammad Salman Khan Faisal Althobiani Muhammad usman mohammed Alshareef Shadi Alghaffari Saifur Rahman Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Department of Software Engineering University of MalakandDir LowerPakistan Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan Faculty of Maritime Studies King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science University of Engineering and TechnologyMardan23200Pakistan

The automatic detection of noisy channels in surface Electromyogram(sEMG)signals,at the time of recording,is very critical in making a noise-free EMG *** an EMG signal contaminated by high-level noise is recorded,then it will be useless and can’t be used for any healthcare *** this research work,a new machine learning-based paradigm is proposed to automate the detection of low-level and high-level noises occurring in different channels of high density and multi-channel sEMG signals.A modiﬁed version of mel fre-quency cepstral coefﬁcients(mMFCC)is proposed for the extraction of features from sEMG channels along with other statistical parameters i-e complexity coef-ﬁcient,hurst exponent,and root mean *** state-of-the-art classiﬁers such as Support Vector Machine(SVM),Ensemble Bagged Trees,Ensemble Sub-space Discriminant,and Logistic Regression are used to automatically identify an EMG channel either bad or good based on these extracted ***-based analyses of these classiﬁers have also been considered based on total classi-ﬁcation accuracy,prediction speed(observations/sec),and processing *** proposed method is tested on 320 simulated EMG channels as well as 640 experi-mental EMG *** is used as our main classiﬁer for the detection of noisy channels which gives a total classiﬁcation accuracy of 99.4%for simulated EMG channels whereas accuracy of 98.9%is achieved for experimental EMG channels.

关键词： Machine learning surface electromyography support vector machine classiﬁcation features

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K-Banhatti Sombor Invariants of Certain Computer Networks

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Computers, Materials & Continua 2022年第10期73卷 15-31页

作者： Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad usman Ashraf Ahmed mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Mathematics University of SialkotSialkot51013Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Any number that can be uniquely determined by a graph is called a graph *** the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation ***,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular *** this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or *** study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced *** deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis.

关键词： Bridge networks invariants k-banhatti sombor indices maple network graph molecular graph

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Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

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Computer Systems Science & Engineering 2023年第10期47卷 791-807页

作者： Sundas Rukhsar Mazhar Javed Awan usman Naseem Dilovan Asaad Zebari Mazin Abed mohammed Marwan Ali Albahar mohammed Thanoon Amena Mahmoud Department of Software Engineering University of Management and TechnologyLahore54770Pakistan School of Computer Science The University of SydneySydneyAustralia Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Computer Science Umm Al Qura UniversityMecca24211Saudi Arabia Computer Science Department Faculty of Computers and InformationKafrelsheikh UniversityKafrelsheikhEgypt

Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions,sentiments,and data in the modern ***,a widely used microblogging site where individuals share their thoughts in the form of tweets,has become a major source for sentiment *** recent years,there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or *** or expressions of people about a particular topic,situation,person,or product can be identified from sentences and divided into three categories:positive for good,negative for bad,and neutral for mixed or confusing *** process of analyzing changes in sentiment and the combination of these categories is known as“sentiment analysis.”In this study,sentiment analysis was performed on a dataset of 90,000 tweets using both deep learning and machine learning *** deep learning-based model long-short-term memory(LSTM)performed better than machine learning *** short-term memory achieved 87%accuracy,and the support vector machine(SVM)classifier achieved slightly worse results than LSTM at 86%.The study also tested binary classes of positive and negative,where LSTM and SVM both achieved 90%accuracy.

关键词： COVID-19 artificial intelligence machine learning deep learning sentimental analysis support vector classifier

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