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Photosynthesis, Growth and Antioxidant Metabolism in Mustard (Brassica juncea L.) Cultivars Differing in Cadmium Tolerance

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Agricultural Sciences in China 2010年第4期9卷 519-527页

作者： Noushina Iqbal Asim Masood Rahat nazar Shabina Syeed Nafees A khan Department of Botany Aligarh Muslim University

Two mustard （Brassica juncea L. Czern and Coss.） cultivars, Pusa Jai Kisan and SS2 differing in cadmium （Cd） tolerance were treated with 0, 25 and 50 umol L-1 Cd to study the physiological basis of difference in Cd tolerance. Cultivar SS2 （Cd sensitive） accumulated greater Cd in leaves than Pusa Jai Kisan （Cd tolerant）. Further, SS2 also exhibited higher contents of thiobarbituric acid reactive substances （TBARS） and H2O2 and electrolyte leakage. However, the activities of antioxidant enzymes, catalase （CAT）, ascorbate peroxidase （APX）, dehydroascorbate reduetase （DHAR）, and glutathione reductase （GR） were higher in Pusa Jai Kisan than those in SS2. Contrarily, the activity of superoxide dismutase （SOD） was higher in SS2 than that in Pusa Jai Kisan and was the greatest at 25 umol L-1 Cd. Treatment of 25 umol L-1 Cd induced the maximum activity of enzymes. However, the activity of GR increased up to 50 umol L-1 Cd in both the cultivars. The non-enzymatic antioxidants ascorbate （AsA） and glutathione （GSH） were higher in Pusa Jai Kisan than that in SS2, whereas dehydroascorbate （DHA） and oxidized glutathione （GSSG） were higher in SS2. Photosynthesis and growth were adversely and maximally decreased by 50 umol L-1 Cd treatment in both the cultivars, but SS2 exhibited greater reductions. The protection of photosynthesis and growth and lesser reduction in Pusa Jai Kisan were associated with its capacity to restrict accumulation of Cd in leaves resulting in lower level of TBARS and H2O2 and electrolyte leakage. Moreover, Pusa Jai Kisan exhibited efficient antioxidant metabolism for removal of Cd-induced reactive oxygen species.

关键词： antioxidant metabolism cadmium oxidative stress photosynthesis

Multiclass Stomach Diseases Classication Using Deep Learning Features Optimization

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Computers, Materials & Continua 2021年第6期67卷 3381-3399页

作者： Muhammad Attique khan Abdul Majid nazar Hussain Majed Alhaisoni Yu-Dong Zhang Seifedine Kadry Yunyoung Nam Department of Computer Science HITEC UniversityTaxila47040Pakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Informatics University of LeicesterLeicesterUK Department of Mathematics and Computer Science Faculty of ScienceBeirut Arab UniversityLebanon Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

In the area of medical image processing,stomach cancer is one of the most important cancers which need to be diagnose at the early *** this paper,an optimized deep learning method is presented for multiple stomach disease *** proposed method work in few important steps—preprocessing using the fusion of ltering images along with Ant Colony Optimization(ACO),deep transfer learning-based features extraction,optimization of deep extracted features using nature-inspired algorithms,and nally fusion of optimal vectors and classication using Multi-Layered Perceptron Neural Network(MLNN).In the feature extraction step,pretrained Inception V3 is utilized and retrained on selected stomach infection classes using the deep transfer learning *** on,the activation function is applied to Global Average Pool(GAP)for feature ***,the extracted features are optimized through two different nature-inspired algorithms—Particle Swarm Optimization(PSO)with dynamic tness function and Crow Search Algorithm(CSA).Hence,both methods’output is fused by a maximal value approach and classied the fused feature vector by *** datasets are used to evaluate the proposed method—CUI WahStomach Diseases and Combined dataset and achieved an average accuracy of 99.5%.The comparison with existing techniques,it is shown that the proposed method shows signicant performance.

关键词： Stomach infections deep features features optimization fusion classication

Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm

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Computers, Materials & Continua 2022年第5期71卷 3513-3531页

作者： Saima Hassan Mojtaba Ahmadieh khanesar nazar Kalaf Hussein Samir Brahim Belhaouari Usman Amjad Wali khan Mashwani Institute of Computing Kohat University of Science and TechnologyKohatPakistan Department of Mechanical Materials and Manufacturing EngineeringFaculty of EngineeringUniversity of NottinghamUK College of Computer Sciences and Mathematics Tikrit UniversityIraq Division of Information and Computing Technology College of Science and EngineeringHamad Bin Khalifa UniversityQatar Department of Computer Science Sir Syed University of Engineering and TechnologyPakistan Institute of Numerical Sciences Kohat University of Science and TechnologyKohatPakistan

The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system(IT2-FLS)is a challenging task in the presence of uncertainty and *** optimization algorithm(GOA)is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature,which has good convergence ability towards *** main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an *** antecedent part parameters(Gaussian membership function parameters)are encoded as a population of artificial swarm of grasshoppers and optimized using its *** of the consequent part parameters are accomplished using extreme learning *** optimized IT2-FLS(GOAIT2FELM)obtained the optimal premise parameters based on tuned consequent part parameters and is then applied on the Australian national electricity market data for the forecasting of electricity loads and *** forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization *** of the performance,on the same data-sets,reveals that the proposed GOAIT2FELM could be a better approach for improving the accuracy of the IT2-FLS as compared to other variants of the optimized IT2-FLS.

关键词： Parameter optimization grasshopper optimization algorithm interval type-2 fuzzy logic system extreme learning machine electricity market forecasting

An Integrated Deep Learning Framework for Fruits Diseases Classification

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Computers, Materials & Continua 2022年第4期71卷 1387-1402页

作者： Abdul Majid Muhammad Attique khan Majed Alhaisoni Muhammad Asfand Eyar Usman Tariq nazar Hussain Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Computer Science Bahria UniversityIslamabad College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

:Agriculture has been an important research area in the field of image processing for the last five *** affect the quality and quantity of fruits,thereby disrupting the economy of a *** computerized techniques have been introduced for detecting and recognizing fruit ***,some issues remain to be addressed,such as irrelevant features and the dimensionality of feature vectors,which increase the computational time of the ***,we propose an integrated deep learning framework for classifying fruit *** consider seven types of fruits,i.e.,apple,cherry,blueberry,grapes,peach,citrus,and *** proposed method comprises several important ***,data increase is applied,and then two different types of features are *** the first feature type,texture and color features,i.e.,classical features,are *** the second type,deep learning characteristics are extracted using a pretrained *** pretrained model is reused through transfer ***,both types of features are merged using the maximum mean value of the serial ***,the resulting fused vector is optimized using a harmonic threshold-based genetic ***,the selected features are classified using multiple *** evaluation is performed on the PlantVillage dataset,and an accuracy of 99%is achieved.A comparison with recent techniques indicate the superiority of the proposed method.

关键词： Fruit diseases data augmentation deep learning classical features features fusion features selection

Classication of COVID-19 CT Scans via Extreme Learning Machin

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Computers, Materials & Continua 2021年第7期68卷 1003-1019页

作者： Muhammad Attique khan Abdul Majid Tallha Akram nazar Hussain Yunyoung Nam Seifedine Kadry Shui-Hua Wang Majed Alhaisoni Department of Computer Science HITEC UniversityTaxila47040Pakistan Department of Electrical Engineering COMSATS University IslamabadWah CampusWah CanttPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Department of Mathematics and Computer Science Faculty of ScienceBeirut Arab UniversityLebanon Department of Mathematics University of LeicesterLeicesterUK College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia

Here,we use multi-type feature fusion and selection to predict COVID-19 infections on chest computed tomography(CT)*** scheme operates in four ***,we prepared a database containing COVID-19 pneumonia and normal CT *** images were retrieved from the Radiopaedia COVID-19 *** images were divided into training and test sets in a ratio of 70:***,multiple features were extracted from the training *** used canonical correlation analysis to fuse the features into single vectors;this enhanced the predictive *** next implemented a genetic algorithm(GA)in which an Extreme Learning Machine(ELM)served to assess GA *** on the ELM losses,the most discriminatory features were selected and saved as an ELM *** images were sent to the model,and the best-selected features compared to those of the trained model to allow nal *** employed the collected chest CT *** best predictive accuracy of the ELM classier was 93.9%;the scheme was effective.

关键词： Coronavirus classical features feature fusion feature optimization prediction

Summarizing Software Artifacts： A Literature Review

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Journal of Computer Science & Technology 2016年第5期31卷 883-909页

作者： Najam nazar Yan Hu He Jiang Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian 116621 China State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China

This paper presents a literature review in the field of summarizing software artifacts, focusing on bug reports, source code, mailing lists and developer discussions artifacts. From Jan. 2010 to Apr. 2016, numerous summarization techniques, approaches, and tools have been proposed to satisfy the ongoing demand of improving software performance and quality and facilitating developers in understanding the problems at hand. Since aforementioned artifacts contain both structured and unstructured data at the same time, researchers have applied different machine learning and data mining techniques to generate summaries. Therefore, this paper first intends to provide a general perspective on the state of the art, describing the type of artifacts, approaches for summarization, as well as the common portions of experimental procedures shared among these artifacts. Moreover, we discuss the applications of summarization, i.e., what tasks at hand have been achieved through summarization. Next, this paper presents tools that are generated for summarization tasks or employed during summarization tasks. In addition, we present different summarization evaluation methods employed in selected studies as well as other important factors that are used for the evaluation of generated summaries such as adequacy and quality. Moreover, we briefly present modern communication channels and complementarities with commonalities among different software artifacts. Finally, some thoughts about the challenges applicable to the existing studies in general as well as future research directions are also discussed. The survey of existing studies will allow future researchers to have a wide and useful background knowledge on the main and important aspects of this research field.

关键词： mining software repositories mining software engineering data machine learning summarizing softwar eartifacts summarizing source code

Boundary layer flow and heat transfer of a micropolar fluid near the stagnation point on a stretching vertical surface with prescribed skin friction

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International Journal of Minerals,Metallurgy and Materials 2011年第4期18卷 502-507页

作者： Kartini Ahmad Roslinda nazar Ioan Pop Centre for Foundation Studies International Islamic University Malaysia46350 Petaling JayaSelangorMalaysia School of Mathematical Sciences Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia Faculty of Mathematics University of ClujR-3400 ClujCP 253Romania

The steady laminar mixed convection boundary layer flow and heat transfer of a micropolar fluid near the stagnation point on a stretched vertical surface with prescribed skin friction were *** governing partial differential equations were transformed into a system of ordinary differential equations,which were then solved numerically using the shooting *** for the stretching velocity,the local Nusselt number,the temperature,and the velocity profiles are presented for various values of the mixed convection parameter λ and material parameter K when the Prandtl number is equal to *** assisting（heated plate） and opposing（cooled plate） flow regions are *** is found that dual solutions exist for both assisting and opposing flows.

关键词： boundary layer flow dual solutions micropolar fluids mixed convection skin friction

Boundary Layer Flow over a Continuously Moving Thin Needle in a Parallel Free Stream

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Chinese Physics Letters 2007年第10期24卷 2895-2897页

作者： Anuar Ishak Rosllinda nazar Ioan Pop School of Mathematical Sciences Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia Faculty of Mathematics University of Cluj R-3400 Cluj CP 253 Romania

We investigate the boundary-layer flow on a moving isothermal thin needle parallel to a moving stream. The governing equations are solved numerically by a finite-difference method. Dual solutions are found to exist wh... 详细信息

关键词： coated conductor buffer layer self-epitaxy CeO2

MHD Flow Towards a Permeable Surface with Prescribed Wall Heat Flux

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Chinese Physics Letters 2009年第1期26卷 169-171页

作者： Anuar Ishak Roslinda nazar Ioan Pop School of Mathematical Sciences Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia Faculty of Mathematics University of Cluj R-3400 Cluj CP 253 Romania

The steady magnetohydrodynamic （MHD） mixed convection flow towards a vertical permeable surface with prescribed heat flux is investigated. The governing partial differential equations are transformed into a system of ordinary differential equations, which is then solved numerically by a finite-difference method. The features of the flow and heat transfer characteristics for different values of the governing parameters are analysed and discussed. Both assisting and opposing flows are considered. It is found that dual solutions exist for the assisting flow, besides the solutions usually reported in the literature for the opposing flow.

关键词： field emission molybdenum dioxide enhancement factor