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Application of Intuitionistic Z-Numbers in Supplier Selection

Intelligent Automation & Soft Computing 2023年第1期35卷 47-61页

作者： Nik muhammad Farhan Hakim Nik Badrul alam Ku muhammad Naim Ku Khalif Nor Izzati Jaini Centre for Mathematical Sciences College of Computing and Applied SciencesUniversiti Malaysia PahangLebuhraya Tun RazakGambangKuantan26300PahangMalaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA PahangJengka CampusBandar Tun Abdul Razak Jengka26400PahangMalaysia

Intuitionistic fuzzy numbers incorporate the membership and non-membership *** contrast,Z-numbers consist of restriction components,with the existence of a reliability component describing the degree of certainty for the *** combination of intuitionistic fuzzy numbers and Z-numbers produce a new type of fuzzy numbers,namely intuitionistic Z-numbers(IZN).The strength of IZN is their capability of better handling the uncertainty compared to Zadeh's Z-numbers since both components of Z-numbers are charac-terized by the membership and non-membership functions,exhibiting the degree of the hesitancy of *** paper presents the application of such numbers in fuzzy multi-criteria decision-making problems.A decision-making model is proposed using the trapezoidal intuitionistic fuzzy power ordered weighted average as the aggregation function and the ranking function to rank the *** proposed model is then implemented in a supplier selection *** obtained ranking is compared to the existing models based on *** results show that the ranking order is slightly different from the existing *** analysis is performed to validate the obtained *** sensitivity analysis result shows that the best supplier is obtained using the proposed model with 80%to 100%consistency despite the drastic change of criteria *** Z-numbers play a very important role in describing the uncertainty in the decision makers’opinions in solving decision-making problems.

关键词： Intuitionistic Z-number fuzzy decision making ranking function supplier selection sensitivity analysis

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Rice molecular markers and genetic mapping:Current status and prospects

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Journal of Integrative Agriculture 2017年第9期16卷 1879-1891页

作者： Ghulam Shabir Kashif Aslam Abdul Rehman Khan muhammad Shahid Hamid Manzoor Sibgha Noreen Mueen alam Khan muhammad Baber muhammad Sabar Shahid Masood Shah muhammad Arif National Institute for Biotechnology and Genetic Engineering(NIBGE) Faisalabad 38000Pakistan Biotechnology Program Environmental SciencesCOMSA TS Institute of Information TechnologyAbbottabad 22010Pakistan Institute of Molecular Biology and Biotechnology Bahauddin Zakariya UniversityMultan 60000Pakistan Rice Research Institute Kala Shah Kaku 39020Pakistan Department of Bioinformatics and Biotechnology Government College UniversityFaisalabad 38000Pakistan Institute of Pure and Applied Biology Bahauddin Zakariya UniversityMultan 60000Pakistan Department of Plant Breeding and Genetics The Islamia University of BahawalpurBahawalpur 63100Pakistan National Center for Soybean Improvement Nanjing Agricultural UniversityNanjing 210095P.R.China

Dramatic changes in climatic conditions that supplement the biotic and abiotic stresses pose severe threat to the sustainable rice production and have made it a difficult task for rice molecular breeders to enhance production and productivity under these stress factors. The main focus of rice molecular breeders is to understand the fundamentals of molecular pathways involved in complex agronomic traits to increase the yield. The availability of complete rice genome sequence and recent improvements in rice genomics research has made it possible to detect and map accurately a large number of genes by using linkage to DNA markers. Linkage mapping is an effective approach to identify the genetic markers which are co-segregating with target traits within the family. The ideas of genetic diversity, quantitative trait locus（QTL） mapping, and marker-assisted selection（MAS） are evolving into more efficient concepts of linkage disequilibrium（LD） also called association mapping and genomic selection（GS）, respectively. The use of cost-effective DNA markers derived from the fine mapped position of the genes for important agronomic traits will provide opportunities for breeders to develop high-yielding, stress-resistant, and better quality rice cultivars. Here we focus on the progress of molecular marker technologies, their application in genetic mapping and evolution of association mapping techniques in rice.

关键词： genetic mapping molecular markers maker assisted selection Oryza sativa L quantitative trait loci

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Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

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Computers, Materials & Continua 2022年第6期71卷 4199-4220页

作者： Sami Ullah Khan Babar Nazir muhammad Hanif Akhtar Ali Sardar alam Usman Habib Department of Computer Science COMSATS UniversityAbbottabad CampusPakistan Faculty of Computer Science and Engineering Ghulam Ishaq Khan(GIK)Institute of Engineering Sciences and Technology TopiPakistan IFahja Pvt Limited PeshawarPakistan Department of Computer Science National University of Computer and Emerging Sciences IslamabadChiniot-Faisalabad CampusPakistan

The cloud service level agreement(SLA)manage the relationship between service providers and consumers in cloud *** is an integral and critical part of modern era IT vendors and communication *** to low cost and flexibility more and more consumers delegate their tasks to cloud providers,the SLA emerges as a key aspect between the consumers and *** monitoring of Quality of Service(QoS)attributes is required to implement SLAs because of the complex nature of cloud *** other factors,such as user reliability,satisfaction,and penalty on violations are also taken into ***,there is no such policy of cloud SLA monitoring to minimize SLA *** this work,we have proposed a cloud SLA monitoring policy by dividing a monitoring session into two parts,for critical and non-critical *** critical and non-critical parameters will be decided on the interest of the consumer during SLA *** will help to shape a new comprehensive SLA based Proactive Resource Allocation Approach(RPAA)which will monitor SLA at runtime,analyze the SLA parameters and try to find the possibility of SLA *** also have implemented an adaptive system for allocating cloud IT resources based on SLA violations and *** have defined two main components of SLA-PRAA i.e.,(a)Handler and(b)Accounting and Billing *** have also described the function of both components through *** experimental results validate the performance of our proposed method in comparison with state-of-the-art cloud SLA policies.

关键词： Energy consumption penalty calculation proactive resource allocation service level agreement(SLA)monitoring SLA violation detection

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Convolutional Neural Network for Histopathological Osteosarcoma Image Classification

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Computers, Materials & Continua 2021年第12期69卷 3365-3381页

作者： Imran Ahmed Humaira Sardar Hanan Aljuaid Fakhri alam Khan muhammad Nawaz Adnan Awais Center of Excellence in Information Technology Institute of Management SciencesPeshawarPakistan Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)RiyadhSaudi Arabia

Osteosarcoma is one of the most widespread causes of bone cancer globally and has a high mortality *** diagnosis may increase the chances of treatment and survival however the process is time-consuming(reliability and complexity involved to extract the hand-crafted features)and largely depends on pathologists’*** Neural Network(CNN—an end-to-end model)is known to be an alternative to overcome the aforesaid ***,this work proposes a compact CNN architecture that has been rigorously explored on a Small Osteosarcoma histology Image Dataaseet(a high-class imbalanced dataset).Though,during training,class-imbalanced data can negatively affect the performance of ***,an oversampling technique has been proposed to overcome the aforesaid issue and improve generalization *** this process,a hierarchical CNN model is designed,in which the former model is non-regularized(due to dense architecture)and the later one is regularized,specifically designed for small histopathology ***,the regularized model is integrated with CNN’s basic architecture to reduce *** results demonstrate that oversampling might be an effective way to address the imbalanced class problem during *** training and testing accuracies of the non-regularized CNN model are 98%&78%with an imbalanced dataset and 96%&81%with a balanced dataset,*** regularized CNN model training and testing accuracies are 84%&75%for an imbalanced dataset and 87%&86%for a balanced dataset.

关键词： Convolutional neural network histopathological image classification osteosarcoma computer-aided diagnosis

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Landslide inventory and susceptibility assessment using multiple statistical approaches along the Karakoram highway,northern Pakistan

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Journal of Mountain Science 2021年第3期18卷 583-598页

作者： Mian Luqman HUSSAIN muhammad SHAFIQUE alam Sher BACHA CHEN Xiao-qing CHEN Hua-yong National Centre of Excellence in Geology University of PeshawarPeshawar 25130Pakistan Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China

China-Pakistan Economic Corridor(CPEC)is a framework of regional connectivity,which will not only benefit China and Pakistan but will have positive impact on Iran,Afghanistan,India,Central Asian Republic,and the *** surrounding area in CPEC is prone to frequent disruption by geological hazards mainly landslides in northern *** landslide inventory and susceptibility assessment are rarely available to utilize for landslide mitigation *** study aims to utilize the high-resolution satellite images to develop a comprehensive landslide inventory and subsequently develop landslide susceptibility maps using multiple *** very high-resolution(VHR)satellite images are utilized to develop a landslide inventory using the visual image classification techniques,historic records and field observations.A total of 1632 landslides are mapped in the *** statistical models i.e.,frequency ratio,artificial neural network,weights of evidence and logistic regression were used for landslide susceptibility modeling by comparing the landslide inventory with the topographic parameters,geological features,drainage and road *** developed landslides susceptibility maps were verified using the area under curve(AUC)*** prediction power of the model was assessed by the prediction rate *** success rate curves show 93%,92.8%,92.7%and 87.4%accuracy of susceptibility maps for frequency ratio,artificial neural network,weights of evidence and logistic regression,*** developed landslide inventory and susceptibility maps can be used for land use planning and landslide mitigation strategies.

关键词： Landslides Inventory map Susceptibility assessment Northern Pakistan CPEC

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An investigation of the effects of synthesized zinc oxide nanoparticles on the properties of water-based drilling fluid

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Petroleum Research 2022年第1期7卷 131-137页

作者： muhammad Hasibul Ahasan MdFazla Alahi Alvi Nayem Ahmed Md.Saiful alam Department of Petroleum and Mining Engineering Shahjalal University of Science and TechnologySylhet3114Bangladesh

The deterioration of drilling fluid properties during deep drilling causes problems like inefficient cutting removal,fluid invasion,and shale swelling,which increases non-productive time(NPT)and *** nanoparticles(NPs)based drilling fluid are introduced to address these impediments since these particles prove their advantages in different stages of petroleum exploration and *** developments are concerned with the use of commercial zinc oxide(ZnO)NPs in inorganic KCl salt-based drilling fluid,although application of KCl in drilling fluid arouses environmental *** this study,ZnO NPs prepared in the laboratory are used in water-based drilling fluid(WBDF)to assess the effect of nanoparticles on the properties of drilling fluid at two temperature conditions of 40C and 80C.A base mud is formulated,and ZnO NPs with five different concentrations of 0.05,0.1,0.5,1.0,and 2.0 wt%are mixed with the base *** experimental analysis shows that NPs improve the rheological properties of *** the concentration of NPs was 0.1 wt%,the yield point increased by 61.54%at 40C,and when the concentration of NPs was 0.05 wt%,the yield point increased by 60%at 80***,when the concentration of NPs is 0.05 wt%,10-sec gel strengths are enhanced by 25%and 50%at 40C and 80C,*** API low-pressure low-temperature(LPLT)filter volume is not significantly affected by the addition of NPs in ***,mud cake thickness continuously reduces with the increase of NPs *** result reveals that a superior rheological improvement is achieved at low NPs concentration(0.05 wt%)at higher temperature.

关键词： Drilling fluids Zinc oxide Nanoparticles Rheology Mud cake thickness

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Disease Diagnosis System Using IoT Empowered with Fuzzy Inference System

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Computers, Materials & Continua 2022年第3期70卷 5305-5319页

作者： Talha Mahboob alam Kamran Shaukat Adel Khelifi Wasim Ahmad Khan Hafiz muhammad Ehtisham Raza muhammad Idrees Suhuai Luo Ibrahim A.Hameed Department of Computer Science and Information Technology Virtual University of PakistanLahorePakistan School of Information and Physical Sciences The University of NewcastleAustralia Department of Computer Science and Information Technology Abu Dhabi UniversityAbu DhabiUnited Arab Emirates School of Computer Science National College of Business Administration&EconomicsLahorePakistan Sir Syed College of Computer Science University of Engineering and TechnologyLahorePakistan Department of Data Science University of the PunjabLahorePakistan Department of ICT and Natural Sciences Norwegian University of Science and TechnologyTrondheimNorway

Disease diagnosis is a challenging task due to a large number of associated *** in the diagnosis process arises frominaccuracy in patient attributes,missing data,and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated *** paper aims to demonstrate an integrated view of deploying smart disease diagnosis using the Internet of Things(IoT)empowered by the fuzzy inference system(FIS)to diagnose various *** Fuzzy Systemis one of the best systems to diagnose medical conditions because every disease diagnosis involves many uncertainties,and fuzzy logic is the best way to handle *** proposed system differentiates new cases provided symptoms of the ***,it becomes a time-sensitive task to discriminate symptomatic *** proposed system can track symptoms firmly to diagnose diseases through IoT and FIS smartly and *** coefficients have been employed to predict and compute the identified disease’s severity for each sign of *** study aims to differentiate and diagnose COVID-19,Typhoid,Malaria,and *** study used the FIS method to figure out the disease over the use of given data related to correlating with input *** tool is utilised for the implementation of *** procedure on the aforementioned given data presents that affectionate disease can derive from the *** results of our proposed method proved that FIS could be utilised for the diagnosis of other *** study may assist doctors,patients,medical practitioners,and other healthcare professionals in early diagnosis and better treat diseases.

关键词： Disease diagnosis system COVID-19 healthcare biomedical rules extraction

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A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health

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Computers, Materials & Continua 2023年第5期75卷 4553-4571页

作者： Md.Moddassir alam Md Mottahir alam muhammad Moinuddin Mohammad Tauheed Ahmad Jabir Hakami Anis Ahmad Chaudhary Asif Irshad Khan Tauheed Khan Mohd Department of Health Information Management and Technology University of Hafr Al-BatinSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing AbdulazizJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems King Abdul Aziz UniversityJeddahSaudi Arabia College of Medicine King Khalid UniversityAbhaSaudi Arabia Department of Physics College of ScienceJazan UniversityP.O.Box.114Jazan45142Saudi Arabia Department of Biology College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Math and Computer Science Augustana CollegeIL61201United States

Artificial Intelligence(AI)is finding increasing application in healthcare *** learning systems are utilized for monitoring patient health through the use of IoT sensor,which keep track of the physiological state by way of various health ***,early detection of any disease or derangement can aid doctors in saving patients’***,there are some challenges associated with predicting health status using the common algorithms,such as time requirements,chances of errors,and improper *** propose an Artificial Krill Herd based on the Random Forest(AKHRF)technique for monitoring patients’health and eliciting an optimal prescription based on their health *** begin with,various patient datasets were collected and trained into the system using IoT *** a result,the framework developed includes four processes:preprocessing,feature extraction,classification,and result ***,preprocessing removes errors,noise,and missing values from the dataset,whereas feature extraction extracts the relevant ***,in the classification layer,we updated the fitness function of the krill herd to classify the patient’s health status and also generate a *** found that the results fromthe proposed framework are comparable to the results from other state-of-the-art techniques in terms of sensitivity,specificity,Area under the Curve(AUC),accuracy,precision,recall,and F-measure.

关键词： Healthcare system health monitoring clinical decision support internet of things artificial intelligence machine learning diagnosis

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Inclined magnetic field and variable viscosity effects on bioconvection of Casson nanofluid slip flow over non linearly stretching sheet

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Propulsion and Power Research 2022年第4期11卷 565-574页

作者： Noman Sarwar muhammad Imran Asjad Sajjad Hussain Md.Nur alam Mustafa Inc Department of Mathematics University of Management and TechnologyLahore54770Pakistan School of Aerospace and Mechanical Engineering Nanyang Technological University639798Singapore Department of Mathematics Pabna University of Science and TechnologyPabna-6600Bangladesh Department of Mathematics Science FacultyFirat University23119ElazigTurkey

In pursuit of improved thermal transportation,the slip flow of Casson nanofluid is considered in the existence of an inclined magnetic field and radiative heat flux flow over a nonlinear stretching *** viscosity of the fluid is considered as a function of temperature along with the convective thermal boundary *** solutions are obtained via Runge-Kutta along with the shooting technique method for the chosen boundary values *** see the physical insights of the problem,some graphs are plotted for various flow and embedded parameters on temperature function,micro-organism distribution,velocity,and volume fraction of nanoparticles.A decline is observed in the velocity and the temperature for Casson *** and Brownian motion incremented the temperature *** is also found that thermal transportation can be enhanced in the presence of nanoparticles and the bioconvection of *** results are useful in the various sectors of engineering and for heat exchangers working in various technological *** main findings of the problem are validated and compared with those in the existing literature as a limiting case.

关键词： Variable viscosity Bioconvection Inclined field Casson fluid Nonlinearly Stretching sheet Convective boundary Velocity slip Varying viscosity

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Artificial Intelligence Based Reliable Load Balancing Framework in Software-Defined Networks

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Computers, Materials & Continua 2022年第1期70卷 251-266页

作者： Mohammad Riyaz Belgaum Fuead Ali Zainab Alansari Shahrulniza Musa muhammad Mansoor alam M.S.Mazliham Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Majan University College Muscat710Oman Institute of Business Management KarachiPakistan Malaysia France Institute Universiti Kuala LumpurKuala Lumpur43650Malaysia

Software-defined networking(SDN)plays a critical role in transforming networking from traditional to intelligent *** increasing demand for services from cloud users has increased the load on the *** efficient system must handle various loads and increasing needs representing the relationships and dependence of businesses on automated measurement systems and guarantee the quality of service(QoS).Themultiple paths from source to destination give a scope to select an optimal path by maintaining an equilibrium of load using some best ***,the requests need to be transferred to reliable network *** address SDN’s current and future challenges,there is a need to know how artificial intelligence(AI)optimization techniques can efficiently balance the *** study aims to explore two artificial intelligence optimization techniques,namely Ant Colony Optimization(ACO)and Particle Swarm Optimization(PSO),used for load balancing in ***,we identified that a modification to the existing optimization technique could improve the performance by using a reliable link and node to form the path to reach the target node and improve load ***,we propose a conceptual framework for SDN futurology by evaluating node and link reliability,which can balance the load efficiently and improve QoS in SDN.

关键词： Ant colony optimization load balancing particle swarm optimization quality of service reliability software-defined networking

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