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Journal of Rare Earths 2019年第2期37卷 193-197页

作者： Muhammad Ayub Iftikhar Hussain Gul khalid nawaz Khurram Yaqoob Thermal Transport Laboratory School of Chemical and Materials Engineering (SCME) National University of Sciences and Technology (NUST)

In the current research work Ba_(1-x)La)xMn)yFe_(12-y)O_(19) hexa-ferrite nanoparticles of different compositions were synthesized using chemical co-precipitation technique. The structural properties were explored using X-ray diffractions(XRD), scanning electron microscopy(SEM) and Fourier transmission infrared spectroscopy(FTIR). XRD indexed pattern confirms the formation of M-type hexagonal phase. The crystallite size of synthesized samples ranges from 13 to 34 ± 2 nm. FTIR peaks observe also confirmed the presence of metaloxygen bond of the desired product. The position of peak at 467 cm^(-1) corresponds to A_2 u vibration for octahedral Fe(4+)-O and peak position E1 u corresponds to vibration of Fe(3+)O4 octahedral bonds. The band v_1 in range(677-559 cm^(-1)) and v_2 in frequency range(356-419 cm^(-1)) are associated to A and B *** properties of all compositions were measured with frequency. The dielectric constant, loss and tangent loss decrease from 26 to 9, 25 to 2 and 0.94 to 0.14, respectively with frequency. DC electrical resistivity is increased with dopant concentration increasing from 2.15 × 10~4 to 1.92 ×10~5 Ω·cm.

关键词： Co-precipitation Electrical properties Dielectric X-ray diffraction Rare earths

Early Detection of Diabetic Retinopathy Using Machine Intelligence throughDeep Transfer and Representational Learning

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Computers, Materials & Continua 2021年第2期66卷 1631-1645页

作者： Fouzia nawaz Muhammad Ramzan khalid Mehmood Hikmat Ullah Khan Saleem Hayat Khan Muhammad Raheel Bhutta Department of Computer Science and Information Technology University of SargodhaSargodha40100Pakistan and School of Systems and TechnologyUniversity of Management and TechnologyLahore54782Pakistan Department of Computer Science COMSATS University IslamabadWah CampusIslamabadPakistan University Hospital Birmingham BirminghamUK Shifa International Hospital IslamabadPakistan Department of Computer Science and Engineering Sejong UniversitySeoulKorea

Diabetic retinopathy (DR) is a retinal disease that causes irreversible *** occurs due to the high blood sugar level of the patient, and it is clumsy tobe detected at an early stage as no early symptoms appear at the initial level. To preventblindness, early detection and regular treatment are needed. Automated detectionbased on machine intelligence may assist the ophthalmologist in examining thepatients’ condition more accurately and efficiently. The purpose of this study is toproduce an automated screening system for recognition and grading of diabetic retinopathyusing machine learning through deep transfer and representational *** artificial intelligence technique used is transfer learning on the deep neural network,Inception-v4. Two configuration variants of transfer learning are applied onInception-v4: Fine-tune mode and fixed feature extractor mode. Both configurationmodes have achieved decent accuracy values, but the fine-tuning method outperformsthe fixed feature extractor configuration mode. Fine-tune configuration modehas gained 96.6% accuracy in early detection of DR and 97.7% accuracy in gradingthe disease and has outperformed the state of the art methods in the relevant literature.

关键词： Diabetic retinopathy artificial intelligence automated screening system machine learning deep neural network transfer and representational learning

Identification of Anomaly Scenes in Videos Using Graph Neural Networks

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Computers, Materials & Continua 2023年第3期74卷 5417-5430页

作者： khalid Masood Mahmoud M.Al-Sakhnini Waqas nawaz Tauqeer Faiz Abdul Salam Mohammad Hamza Kashif Department of Software Engineering Lahore Garrison UniversityLahore54000Pakistan School of Business Skyline University CollegeSharjahUAE Al-Madinah International University–Faculty of Computer and Information Technology Kuala LumpurMalaysia College of Computer and Information Systems Islamic University of MadinahMadinahKingdom of Saudi Arabia School of IT Skyline University CollegeSharjahUAE Faculty of Engineering Computing and Science(FECS)-Swinburne University of TechnologySarawak Department of General Education Skyline University CollegeUniversity City of SharjahUAE Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan

Generally,conventional methods for anomaly detection rely on clustering,proximity,or *** themassive growth in surveillance videos,outliers or anomalies find ingenious ways to obscure themselves in the network and make conventional techniques *** research explores the structure of Graph neural networks(GNNs)that generalize deep learning frameworks to graph-structured *** node in the graph structure is labeled and anomalies,represented by unlabeled nodes,are predicted by performing random walks on the node-based graph *** to their strong learning abilities,GNNs gained popularity in various domains such as natural language processing,social network analytics and *** detection is a challenging task in computer vision but the proposed algorithm using GNNs efficiently performs the identification of *** Graph-based deep learning networks are designed to predict unknown objects and *** our case,they detect unusual objects in the form of malicious *** edges between nodes represent a relationship of nodes among each *** case of anomaly,such as the bike rider in Pedestrians data,the rider node has a negative value for the edge and it is identified as an *** encoding and decoding layers are crucial for determining how statistical measurements affect anomaly identification and for correcting the graph path to the best possible *** show that the proposed framework is a step ahead of the traditional approaches in detecting unusual activities,which shows a huge potential in automatically monitoring surveillance *** autonomous monitoring of CCTV,crime control and damage or destruction by a group of people or crowd can be identified and alarms may be triggered in unusual activities in streets or public *** suggested GNN model improves accuracy by 4%for the Pedestrian 2 dataset and 12%for the Pedestrian 1 dataset compared to a few state-of the-art techniq

关键词： Graph neural network deep learning anomaly detection auto encoders

Adaptive Multi-Cost Routing Protocol to Enhance Lifetime for Wireless Body Area Network

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Computers, Materials & Continua 2022年第7期72卷 1089-1103页

作者： Muhammad Mateen Yaqoob Waqar Khurshid Leo Liu Syed Zulqarnain Arif Imran Ali Khan Osman khalid Raheel nawaz Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan Department of OTEHM Manchester Metropolitan UniversityManchesterUK

Wireless Body Area Network(WBAN)technologies are emerging with extensive applications in several *** is a fascinating domain of WBAN for smart monitoring of a patient’s *** important factor to consider in WBAN is a node’s *** the lifetime of nodes is critical to address many issues,such as utility and *** routing protocols have addressed the energy conservation problem but considered only a few parameters,thus affecting their ***,most of the existing schemes did not consider traffic prioritization which is critical in *** this paper,an adaptive multi-cost routing protocol is proposed with a multi-objective cost function considering minimum distance from sink,temperature of sensor nodes,priority of sensed data,and maximum residual energy on sensor *** performance of the proposed protocol is compared with the existing schemes for the parameters:network lifetime,stability period,throughput,energy consumption,and path *** is evident from the obtained results that the proposed protocol improves network lifetime and stability period by 30%and 15%,respectively,as well as outperforms the existing protocols in terms of throughput,energy consumption,and path loss.

关键词： Multi-cost routing protocol network lifetime wireless body area network adaptive routing residual energy clustering poisson distribution

Antihyperglycemic effect of methanol extract of Tamarix aphylla L. Karst (Saltcedar) in streptozocin–nicotinamide induced diabetic rats

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Asian Pacific Journal of Tropical Biomedicine 2017年第7期7卷 619-623页

作者： rooh ullah shafiq ahmed tariq naeem khan nawaz sharif zia ud din khalid mansoor department of pharmacology institute of basic medical sciences khyber medical university

Objective: To evaluate the antihyperglycemic potential of Tamarix aphylla(T. aphylla)leaves in STZ–NIC induced diabetes in Wister Albino ***: Acute toxicity study was done to check the toxicity of T. aphylla(L. Karst)methanol extract. T. aphylla leaves extract was administered intraperitoneally(100 mg,250 mg and 400 mg/kg body weight per day) to diabetic Wister rats for 21 days. The various parameters were studied including fasting blood glucose levels, haemoglobin and glycosylated ***: The treatment groups with the extract at three dose levels expressively abridged the intensities of blood glucose and Glycosylated Haemoglobin. The earlier detected reduced level of plasma haemoglobin of the diabetic rats was raised to near normalcy with treatment of ***: The results of the current study confirm that the leaves extract of T. aphylla are nontoxic and have antidiabetic nature.

关键词： Tamarix aphylla leaves Diabetes Streptozotocin Antidiabetic potential Insulin secretion

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

Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning

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Intelligent Automation & Soft Computing 2023年第5期36卷 1915-1930页

作者： Rab nawaz Bashir Imran Sarwar Bajwa Muhammad Waseem Iqbal Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel ABahaddad khalid Ali Almarhabi Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science and IT Islamia University BahawalpurPakistan Department of Software Engineering Superior University Lahore54000Pakistan 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

Soil salinity is a serious land degradation issue in *** is a major threat to agriculture *** irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation *** the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)*** relationship between environmental conditions and ET rate is hard to be deﬁned by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)***-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity *** proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)*** validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm *** applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.

关键词： Leaching fraction saline soil evapotranspiration machine learning calibrated evapotranspiration artiﬁcial intelligence blaney criddle method

Physicochemical,rheological and antioxidant profiling of yogurt prepared from non-enzymatically and enzymatically hydrolyzed potato powder under refrigeration

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Food Science and Human Wellness 2023年第1期12卷 69-78页

作者： Ishtiaq Ahmad Zhouyi Xiong Hanguo Xiong Rana Muhammad Aadil Nauman khalid Allah Bakash Jvaid Lakhoo Zia-ud-din Asad nawaz Noman Walayat Rao Sanaullah Khan College of Food Science and Technology Huazhong Agricultural UniversityWuhan 430070China Fisheries Research Institute Wuhan Academy of Agricultural SciencesWuhan 430207China National Institute of Food Science and Technology University of AgricultureFaisalabad 38000Pakistan Schools of Food and Agricultural Sciences University of Management and TechnologyLahore 54000Pakistan College of Food Science and Technology Zhejiang University of TechnologyHangzhou 310014China

Evidences show that the storage period greatly affects the quality of *** this study,three types of yogurt:control yogurt(CY),non-hydrolyzed potato powder yogurt(PPY)and enzymatically hydrolyzed potato powder yogurt(EHPPY)were prepared at 42℃ for 5 h and stored for 28 days at 4℃.The yogurts were evaluated for quality characteristics at different storage *** differences in pH values,titratable acidities and viable counts were detected in all three types of yogurt during ***,compared to other yogurts,EHPPY exhibited desirable water holding capacity,throughout the storage *** from this,sensory properties and antioxidant activities(2-diphenyl-1-picryl-hydrazyl(DPPH)free radical scavenging activity and ferric reducing antioxidant power(FRAP))of EHPPY were also significantly improved during the storage ***,the storage(G’)and loss(G”)modulus of PPY,EHPPY were lower than CY at 4℃ while a hysteresis loop was shown by all yogurts at the temperature range of 4-50℃ indicating higher G’(elasticity)than G”(viscosity).Based on our findings,EHPP could be an important functional ingredient in improving the quality and storage stability of yogurt for its production at an industrial level.

关键词： Storage stability Potato powder Yogurt Rheology Microbiology Antioxidant activity

BN-GEPSO:Learning Bayesian Network Structure Using Generalized Particle Swarm Optimization

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Computers, Materials & Continua 2023年第5期75卷 4217-4229页

作者： Muhammad Saad Salman Ibrahim M.Almanjahie AmanUllah Yasin Ammara nawaz Cheema Air University Islamabad44000Pakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia

At present Bayesian Networks(BN)are being used widely for demonstrating uncertain knowledge in many disciplines,including biology,computer science,risk analysis,service quality analysis,and *** they suffer from the problem that when the nodes and edges increase,the structure learning difficulty increases and algorithms become *** solve this problem,heuristic optimization algorithms are used,which tend to find a near-optimal answer rather than an exact one,with particle swarm optimization(PSO)being one of *** is a swarm intelligence-based algorithm having basic inspiration from flocks of birds(how they search for food).PSO is employed widely because it is easier to code,converges quickly,and can be parallelized *** use a recently proposed version of PSO called generalized particle swarm optimization(GEPSO)to learn bayesian network *** construct an initial directed acyclic graph(DAG)by using the max-min parent’s children(MMPC)algorithm and cross relative average *** used to create a population for theGEPSO optimization ***,we propose a velocity update procedure to increase the efficiency of the algorithmic search *** of the experiments show that as the complexity of the dataset increases,our algorithm Bayesian network generalized particle swarm optimization(BN-GEPSO)outperforms the PSO algorithm in terms of the Bayesian information criterion(BIC)score.

关键词： Bayesian network structure learning particle swarm optimization

Ranked-Set Sampling Based Distribution Free Control Chart with Application in CSTR Process

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Computer Modeling in Engineering & Sciences 2023年第6期135卷 2091-2118页

作者： Ibrahim M.Almanjahie Zahid Rasheed Majid Khan Syed Masroor Anwar Ammara nawaz Cheema Department of Mathematics College of ScienceKing Khalid UniversityAbha62529Saudi Arabia Statistical Research and Studies Support Unit King Khalid UniversityAbha62529Saudi Arabia School of Mathematics and Statistics Xi’an Jiaotong University ChinaXi’an710049China Department of Mathematics Women University of Azad Jammu and KashmirBagh12500Pakistan Government Post Graduate College Haripur22620Pakistan Department of Statistics University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Mathematics Air UniversityIslamabad44000Pakistan

Nonparametric(distribution-free)control charts have been introduced in recent years when quality characteristics do not follow a specific *** the sample selection is prohibitively expensive,we prefer ranked-set sampling over simple random sampling because ranked set sampling-based control charts outperform simple random sampling-based control *** this study,we proposed a nonparametric homogeneously weighted moving average based on theWilcoxon signed-rank test with ranked set sampling(NPHWMARSS)control chart for detecting shifts in the process location of a continuous and symmetric *** Carlo simulations are used to obtain the run length characteristics to evaluate the performance of the proposed NPHWMARSS control *** proposed NPHWMARSS control chart’s performance is compared to that of parametric and nonparametric control *** control charts include the exponentially weighted moving average(EWMA)control chart,Wilcoxon signed-rank with simple random sampling based the nonparametric EWMA control chart,the nonparametric EWMA sign control chart,Wilcoxon signed-rank with ranked set sampling-based the nonparametric EWMA control chart,and the homogeneously weighted moving average control *** findings show that the proposed NPHWMARSS control chart performs better than its competitors,particularly for the small ***,an example is presented to demonstrate how the proposed scheme can be implemented practically.

关键词： Nonparametric control charts run-length ranked set sampling Wilcoxon signed-rank