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Deep Transfer Learning Based Detection and Classification of Citrus Plant Diseases

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Computers, Materials & Continua 2023年第7期76卷 895-914页

作者： Shah Faisal kashif Javed Sara Ali Areej Alasiry Mehrez Marzougui Muhammad Attique Khan Jae-Hyuk Cha Department of Robotics and Artificial Intelligence SMME NUSTIslamabadPakistan College of Computer Science King Khalid UniversityAbha61413Saudi Arabia Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Citrus fruit crops are among the world’s most important agricultural products,but pests and diseases impact their cultivation,resulting in yield and quality *** vision and machine learning have been widely used to detect and classify plant diseases over the last decade,allowing for early disease detection and improving agricultural *** paper presented an automatic system for the early detection and classification of citrus plant diseases based on a deep learning(DL)model,which improved accuracy while decreasing computational *** most recent transfer learning-based models were applied to the Citrus Plant Dataset to improve classification *** transfer learning,this study successfully proposed a Convolutional Neural Network(CNN)-based pre-trained model(EfficientNetB3,ResNet50,MobiNetV2,and InceptionV3)for the identification and categorization of citrus plant *** evaluate the architecture’s performance,this study discovered that transferring an EfficientNetb3 model resulted in the highest training,validating,and testing accuracies,which were 99.43%,99.48%,and 99.58%,*** identifying and categorizing citrus plant diseases,the proposed CNN model outperforms other cuttingedge CNN model architectures developed previously in the literature.

关键词： Citrus diseases classification deep learning transfer learning efficientNetB3 mobileNetV2 ResNet50 InceptionV3

Prevalence of gastric varices and results of sclerotherapy with N-butyl 2 cyanoacrylate for controlling acute gastric variceal bleeding

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World Journal of Gastroenterology 2007年第8期13卷 1247-1251页

作者： Khalid Mumtaz Shahid Majid Hasnain A Shah kashif Hameed Ashfaq Ahmed Saeed Hamid Wasim Jafri Section of Gastroenterology Aga Khan University HospitalKarachiPakistan

AIM： To study the prevalence, predictors and control of bleeding following N-butyl 2 cyanoacrylate （NBC） sclerotherapy of gastric varix （GV）. METHODS： We analyzed case records of 1436 patients with portal hypertension, who underwent endoscopy during the past five years for variceal screening or upper gastrointestinal （GI） bleeding. Fifty patients with bleeding GV underwent sclerotherapy with a mean of 2 mL NBC for control of bleeding. Outcome parameters were primary hemostasis （bleeding control within the first 48 h）, recurrent bleeding （after 48 h of esophagogastro-duodenoscopy） and in-hospital mortality were analyzed. RESULTS： The prevalence of GV in patients with portal hypertension was 15% （220/1436） and the incidence of bleeding was 22.7% （50/220）. Out of the 50 bleeding GV patients, isolated gastric varices （IGV-Ⅰ） were seen in 22 （44%）, gastro-oesophageal varices （GOV） on lesser curvature （GOV-Ⅰ） in 16 （32%）, and GOV on greater curvature （GOV-Ⅱ） in 15 （30%）. IGV-Ⅰ was seen in 44% （22/50） patients who had bleeding as compared to 23% （39/170） who did not have bleeding （P 〈 0.003）. Primary hernostasis was achieved with NBC in all patients. Re-bleeding occurred in 7 （14%） patients after 48 h of initial sclerotherapy. Secondary hemostasis was achieved with repeat NBC sclerotherapy in 4/7 （57%）. Three patients died after repeat sclerotherapy, one during transjugular intrahepatic portosystemic stem shunt （TIPSS）, one during surgery and one due to uncontrolled bleeding. Treatment failure-related mortality rate was 6% （3/50）. CONCLUSION： GV can be seen in 15% of patients with portal hypertension and the incidence of bleeding is 22.7%. NBC is highly effective in controlling GV bleeding. In hospital mortality of patients with bleeding GV is 6%.

关键词： Gastric varices Portal hypertension N-butyl cyanoacrylate Bleeding Sclerotherapy

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

Early selection of bread wheat genotypes using morphological and photosynthetic attributes conferring drought tolerance

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Journal of Integrative Agriculture 2019年第11期18卷 2483-2491页

作者： Hafiz Ghulam Muhu-Din Ahmed Abdus Salam khan LI Ming-ju Sultan Habibullah Khan Muhammad kashif Department of Plant Breeding and Genetics University of Agriculture FaisalabadFaisalabad 38000Pakistan Institute of Agricultural Environment and Resources Yunnan Academy of Agricultural SciencesKunming 650205P.R.China Center of Agricultural Biotechnology and Biochemistry University of Agriculture FaisalabadFaisalabad 38000Pakistan

Genetic diversity is the base of any genetic improvement breeding program aimed at stress *** variability among breeding materials is of primary importance in the achievements of a good crop ***,105 wheat genotypes were screened against drought stress using factorial completely randomized design at seedling stage to determine the genetic diversity and traits association conferring drought *** of variances revealed that all the studied parameters differed significantly among all genotypes,indicating the significance genetic variability existed among all genotypes for studied *** 10 best performance genotypes G1,G6,G11,G16,G21,G26,G39,G44,G51,and G61 were screened as drought tolerant,while five lowest performance genotypes G3,G77,G91,G98,and G105 were screened as drought *** length,chlorophyll a,chlorophyll b,and carotenoid contents were significantly correlated among themselves which exhibited the importance of these indices for rainfed areas in future wheat breeding *** length exhibited non-significant and negative association with other studied traits,and its selection seems not to be a promising criteria for this germplasm for drought *** performance genotypes under drought stress conditions will be useful in future wheat breeding program and early selection will be effective for developing high yielding and drought tolerant wheat varieties.

关键词： drought photosynthesis chlorophyll wheat seedling carotenoid

Thermal Conductivity of Complex Plasmas Using Novel Evan-Gillan Approach

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Communications in Theoretical Physics 2018年第6期69卷 704-710页

作者： Aamir Shahzad Syed Irfan Haider Muhammad kashif Muhammad Shahzad Shifa Tariq Munir Mao-Gang He Molecular Modeling and Simulation Laboratory Department of PhysicsGovernment College University Faisalabad(GCUF)Allama Iqbal RoadFaisalabad 38040Pakistan Key Laboratory of Thermo-Fluid Science and Engineering Ministry of Education(MOE)Xi'an Jiaotong UniversityXi'an 710049China

The thermal conductivity of complex fluid materials （dusty plasmas） has been explored through novel Evan-Gillan homogeneous non-equilibrium molecular dynamic （HNEMD） algorithm. The thermal conductivity coefficient obtained from HNEMD is dependent on various plasma parameters （T,k）. The proposed algorithm gives accurate results with fast convergence and small size effect over a wide range of plasma parameters. The cross microscopic heat energy current is discussed in association with variation of temperature （1/Г） and external perturbations （Pz）. The thermal conductivity obtained from HNEMD simulations is found to be very good agreement and more reliable than previously known numerical techniques of equilibrium molecular dynarnic, nonequilibrium molecular dynamic simulations. Our new investigations point to an effective conclusion that the thermal conductivity of complex dusty plasmas is dependent on an extensive range of plasma coupling （P） and screening parameter （k） and it varies by the alteration in these parameters. It is also shown that a different approach is used for computations of thermal conductivity in 2D complex plasmas and can be appropriate method for behaviors of complex systems.

关键词： complex dusty plasma homogenous nonequilibrium molecular dynamics canonical ensemble scaling law thermal conductivity Yukawa liquids

Pore Characteristics of the Fine-Grained Tight Reservoirs in the Yabulai Basin, Northwestern China

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Acta Geologica Sinica(English Edition) 2018年第3期92卷 1170-1192页

作者： ZHANG Shaomin CAO Yingchang Jens JAHREN ZHU Rukai MAO Zhiguo XI Kelai kashif MUHAMMAD Helge HELLEVANG School of Geosciences China University of Petroleum (East China) Qingdao 266580 Shandong China Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and TechnologyQingdao 266071 Shandong China Department of Geosciences University of Oslo Blindern 0316 Oslo Norway Research Institute of Petroleum Exploration & Development Beijing 100083 China

This work investigated the pore structure characteristics and reservoir features of the finegrained tight reservoirs in the lower member of the Xinhe Formation(J2x1) in the Xiaohu subsag,Yabulai Basin based on core samples through various techniques. Interbedded silt/fine sandstones and mudstones are developed in the study area. Scanning electron microscopy(SEM) images were used to delineate different types of pores, including primary intergranular pores, secondary intergranular and intragranular pores, organic pores and fractures. The pore types were distinguished by pore size, pore area, location and formation process. The pore radii of the fine-grained rocks range from 1 nm to 1.55μm, mainly concentrated between 5 and 300 nm by low pressure N2adsorption and MICP analyses. The pore structure parameters of pore throat size and pore throat sorting coefficient are both positively correlated with porosity, while pore throat sorting coefficient has a negative correlation with permeability. The pore structures of the studied samples are much related to the mineral type and content and grain size, followed by TOC content. In these rocks with relatively low TOC and low maturity, the rigid minerals protect pores with pressure shadow from collapse, and dissolution-related pores contribute a lot to inorganic porosity. In contrast, these rocks with abundant TOC contain a large number of organic pores. The permeability of the fine-grained tight reservoir is mainly dominated by larger pore throats, while a large number of small pores(mostly <0.1 μm) contribute considerably to porosity. These results have deepened our understanding of the interbedded fine-grained tight reservoirs and can be applicable to fine-grained reservoirs in a similar setting.

关键词： pore characteristics reservoir property fine-grained tight reservoirs Xinhe Formation Yabulai Basin China

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

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Computers, Materials & Continua 2021年第2期66卷 1595-1612页

作者： kashif Iqbal Sagheer Abbas Muhammad Adnan Khan Atifa Ather Muhammad Saleem Khan Areej Fatima Gulzar Ahmad School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Sciences GC UniversityLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Comsats University IslamabadLahore CampusLahore54000Pakistan

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of ***-based target detection and object classification have been improved due to the development of deep learning *** fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise,well-engineered,and complete detection of objects,scene or *** target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion *** this study we examined to solve these problems described by(1)extracting region-of-interest in the images(2)vehicle detection based on instance segmentation,and(3)building deep learning model based on the key features obtained from input parking *** build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking *** augmentation techniques were performed using edge detection,cropping,refined by rotating,thresholding,resizing,or color augment to predict the region of bounding boxes.A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling,training,validating and testing on parking video frames through *** results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6%than previous reported ***,this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space *** results are verified using Python,TensorFlow,OpenCV computer simulation frameworks.

关键词： Smart parking-lot detection deep convolutional neural network data augmentation region-of-interest object detection

Sustainable food industrial waste management through single cell protein production and characterization of protein enriched bread

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Food Bioscience 2022年第2期46卷 639-646页

作者： Muhammad kashif Iqbal Khan Muhammad Asif Zafar Ullah Razzaq Akmal Nazir Abid Aslam Maan Department of Food Engineering University of AgricultureFaisalabadPakistan National Institute of Food Science and Technology University of AgricultureFaisalabadPakistan Department of Food Science College of Agriculture and Veterinary MedicineUnited Arab Emirates UniversityAl AinUnited Arab Emirates

Production of single cell protein(SCP)from food waste is one of the promising approaches for excellent waste *** the present study,SCP was produced through submerged fermentation using selected food wastes(banana peel,citrus peel,carrot pomace and potato peel).During process optimization,combinations of various temperature and nitrogen sources were studied for optimum SCP yield(g/100g).The results indicated that maximum SCP yield was obtained at 30℃ for 7 days on potato peels,whereas citrus and banana peels exhibited the lowest SCP yield at the same process *** SCP compositional analysis indicated that the amount of non-essential amino acids was significantly higher than wheat ***,SCP enriched bread was prepared by adding SCP at different concentrations(0,4,8,and 12%).The organoleptic properties indicated that SCP addition up to 4%was acceptable to prepare protein enriched ***,SCP may be effectively used for food waste management and food security.

关键词： Fruit waste Food security Single cell protein Bread Protein deficiency Malnourishment

Validation of an Optimized Spectrophotometric Method for the Selective Determination of Labetalol Hydrochloride

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Chinese Journal of Chemistry 2005年第12期23卷 1611-1617页

作者： RAHMAN, Nafisur SINGH, Manisha HODA, Nasrul Md ZAIDI, S.M. kashif R. BANU, Naheed Analytical Research Laboratory Department of Chemistry Aligarh Muslim University Aligarh-202 002 India Department of Biochemistry Faculty of Life Science Aligarh Muslim Universtty Aligarh-202002 India

A simple sensitive and economical method for the determination of labetalol hydrochloride has been proposed, based on the reaction of labetalol with sodium nitroprusside and hydroxylamine hydrochloride in sodium dihydrogen phosphate-sodium hydroxide buffer solution of pH 12. The green-blue color produced due to the formation of a nitroso derivative has been measured at 695 nm. The Beer＇s range was obeyed in the concentration range of 2-51 μg·mL^-1 with molar absorptivity of 0.48 × 10^4 L·mol^-1·cm^-1. Rigorous statistical analyses were performed for the validation of the method. A detailed investigation of the selectivity of the method has been done to find it to be highly selective for the determination of labetalol hydrochloride in the presence of its acidic degradation product and common excipients of formulations. The proposed method was successfully applied to the determination of labetalol hydrochloride in the laboratory prepared dosage forms. Comparison of the means of the proposed procedure with a reference method using point as well as interval hypotheses showed no statistically significant difference. The developed method was extended to investigate its applicability to biological samples.

关键词： labetalol hydrochloride sodium nitroprusside hydroxylamine hydrochloride biological sample