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Deep Learning Based Classification of Wrist Cracks from X-ray Imaging

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Computers, Materials & Continua 2022年第10期73卷 1827-1844页

作者： Jahangir Jabbar Muzammil Hussain Hassaan Malik Abdullah Gani Ali haider khan Muhammad Shiraz Department of Computer Science National College of Business Administration&Economics LahoreMultan60000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Faculty of Computing and Informatics University of Malaysia SabahJalan UMSKota Kinabalu88400SabahMalaysia Department of Computer Science Federal Urdu University of ArtsScience and TechnologyIslamabadPakistan

Wrist cracks are the most common sort of cracks with an excessive occurrence *** the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented by crack *** cracks often appear in the human arbitrary bone due to accidental injuries such as ***,many hospitals lack experienced clinicians to diagnose wrist ***,an automated system is required to reduce the burden on clinicians and identify *** this study,we have designed a novel residual network-based convolutional neural network(CNN)for the crack detection of the *** the classification of wrist cracks medical imaging,the diagnostics accuracy of the RN-21CNN model is compared with four well-known transfer learning(TL)models such as Inception V3,Vgg16,ResNet-50,and Vgg19,to assist the medical imaging technologist in identifying the cracks that occur due to wrist *** RN-21CNN model achieved an accuracy of 0.97 which is much better than its competitor`s *** results reveal that implementing a correct generalization that a computer-aided recognition system precisely designed for the assistance of clinician would limit the number of incorrect diagnoses and also saves a lot of time.

关键词： Wrist cracks fracture deep learning X-rays CNN

Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

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Computers, Materials & Continua 2023年第7期76卷 133-150页

作者： Ali haider khan Hassaan Malik Wajeeha Khalil Sayyid Kamran Hussain Tayyaba Anees Muzammil Hussain Department of Software Engineering Faculty of Computer SciencesLahore Garrison UniversityLahorePakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Computer Science&Information Technology University of Engineering and Technology(UET)PeshawarPakistan Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated *** fundus imaging(CFI)is a screening technology that is both effective and *** to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic *** traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of *** addition,they usually only target one or a few different kinds of eye diseases at the same *** this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs ***_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification *** DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right *** then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel *** the attributes have been analyzed,they are integrated to provide a representation at the patient *** the whole process of ODs categorization,the patient-level representation will be *** efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

关键词： Ocular disease multi-label spatial correlation CNN eye disease

Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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Computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid Kamran Hussain Ali haider khan Malek Alrashidi Sajid Iqbal Qazi Mudassar Ilyas Kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

Watering techniques and zero-valent iron biochar pH effects on As and Cd concentrations in rice rhizosphere soils,tissues and yield

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Journal of Environmental Sciences 2021年第2期33卷 144-157页

作者： Md Shafiqul Islam Yali Chen Liping Weng Jie Ma Zulqarnain haider khan Zhongbin Liao Abdoul Salam Issiaka Abdoul Magid Yongtao Li Agro-Environmental Protection Institute/Key Laboratory for Environmental Factors Control of Agro Product Quality Safety Ministry of Agriculture and Rural AffairsTianjin 300191China College of Natural Resources and Environment South China Agricultural UniversityGuangzhou 510642China Chinese Academy of Agricutural Sciences Beijing 100081China Department of Soil Quality Wageningen Universit6700 AAWageningenNetherlands

Zero-valent iron amended biochar(ZVIB)has been proposed as a promising material in immobilizing heavy metals in paddy *** this study,the impacts of p H of ZVIB(p H 6.3 and p H 9.7)and watering management techniques(watering amount in the order of CON(control,5/72)>3/72>1-3/72>3/100>1/72,with 5/72,for example,representing irrigation given to 5 cm above soil surface in 72 hr regular interval)on As and Cd bioavailability for rice and its grain yield(Yield BR)were investigated in a pot *** rice As(As BR)content was irrelative to the watering treatments,while significantly decreased(>50%)with the addition of both ZVIB *** diminutions of brown rice Cd(Cd BR)content as well as the Yield BR were highly dependent on both the soil amendment materials’p H and watering *** all the watering treatments,3/72 treatment(15%less irrigation water than the CON)with ZVIB 6.3 amendment was the optimum fit for simultaneous reduction of As BR(50%)and Cd BR contents(19%)as well as for significant increment(12%)of the Yield *** high pH(9.7)ZVIB application could also efficiently decrease As and Cd contents in brown rice,it might risk grain yield lost if appropriate(e.g.3/72 in our study)watering management technique was not ***,ZVIB would be an environmentally friendly option as an amendment material with proper selection of watering management technique to utilize As and Cd co-contaminated arable soils safely for paddy cultivation.

关键词： Brown rice As Brown rice Cd Grain yield Paddy soils Water management Zero-valent iron biochar

AI-Driven Energy Optimization in UAV-Assisted Routing for Enhanced Wireless Sensor Networks Performance

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Computers, Materials & Continua 2024年第9期80卷 4085-4110页

作者： Syed Kamran haider Abbas Ahmed Noman Mujeeb khan Ali Nauman Sung Won Kim College of Internet of Things(IoT)Engineering Hohai UniversityChangzhou213001China Department of Electrical and Electronics Engineering Beaconhouse International CollegeIslamabad44000Pakistan School of Computer Science and Engineering Yeungnam UniversityGyeongsan38428Republic of Korea

In recent advancements within wireless sensor networks(WSN),the deployment of unmanned aerial vehicles(UAVs)has emerged as a groundbreaking strategy for enhancing routing efficiency and overall network *** research introduces a sophisticated framework,driven by computational intelligence,that merges clustering techniques with UAV mobility to refine routing strategies in *** proposed approach divides the sensor field into distinct sectors and implements a novel weighting system for the selection of cluster heads(CHs).This system is primarily aimed at reducing energy consumption through meticulously planned routing and path *** a greedy algorithm for inter-cluster dialogue,our framework orchestrates CHs into an efficient communication *** comparative analysis,the proposed model demonstrates a marked improvement over traditional methods such as the cluster chain mobile agent routing(CCMAR)and the energy-efficient cluster-based dynamic algorithms(ECCRA).Specifically,it showcases an impressive 15%increase in energy conservation and a 20%reduction in data transmission time,highlighting its advanced ***,this paper investigates the impact of various network parameters on the efficiency and robustness of the WSN,emphasizing the vital role of sophisticated computational strategies in optimizing network operations.

关键词： UAV trajectory clustering next-generation wireless sensor network(NGWSN) energy efficiency mobile sink

Dynamics of organic carbon and nitrogen in deep soil profile and crop yields under long-term fertilization in wheat-maize cropping system

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Journal of Integrative Agriculture 2022年第3期21卷 826-839页

作者： Muhammad QASWAR LI Dong-chu HUANG Jing HAN Tian-fu Waqas AHMED Sehrish ALI Muhammad Numan khan Zulqarnain haider khan XU Yong-mei LI Qian ZHANG Hui-min WANG Bo-ren Ahmad TAUQEER National Engineering Laboratory for Improving Quality of Arable Land/Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural SciencesBeijing 100081P.R.China Key Laboratory of Industrial Ecology and Environmental Engineering School of Environmental Science and TechnologyDalian University of TechnologyDalian 116024P.R.China National Observation Station of Qiyang Agri-Ecology System/Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural SciencesQiyang 426182P.R.China Guangdong Provincial Key Laboratory for Radionuclides Pollution Control and Resources School of Environmental Science and EngineeringGuangzhou UniversityGuangzhou 510006P.R.China Agro-Environmental Protection Institute Ministry of Agriculture and Rural AffairsTianjin 300191P.R.China Institute of Soil Fertilizer and Agricultural Water ConservationXinjiang Academy of Agricultural SciencesUrumqi 830091P.R.China College of Agriculture Henan University of Science and TechnologyLuoyang 471000P.R.China School of Chemical Engineering Dalian University of TechnologyDalian 116024P.R.China

Soil organic carbon(SOC)and nitrogen(N)are two of the most important indicators for agricultural *** primary objective of this study was to investigate the changes in SOC and N in the deep soil profile(up to 100 cm)and their relationships with crop productivity under the influence of long-term(since 1990)fertilization in the wheat-maize cropping *** included CK(control),NP(inorganic N and phosphorus(P)fertilizers),NPK(inorganic N,P and potassium fertilizers),NPKM(NPK plus manure),and M(manure).Crop yield and the properties of topsoil were measured yearly from 2001 to 2009.C and N contents were measured at five different depths in 2001 and *** results showed that wheat and maize yields decreased between 2001 and 2009 under the inorganic fertilizer(NP and NPK)*** average yield between 2001 and 2009 under the NP,NPK,NPKM,and M treatments(compared with the CK treatment)increased by 38,115,383,and 381%,respectively,for wheat and 348,891,2738,and 1845%,respectively,for *** long-term fertilization treatments significantly changed coarse free particulate(cf POC),fine free particulate(ff POC),intramicroaggregate particulate(i POC),and mineral-associated(m SOC)organic carbon *** the experimental years of 2001 and 2009,soil fractions occurred in the following order for all treatments:m SOC>cf POC>i POC>ff *** fractions were higher under the manure application treatments than under the inorganic fertilization *** to the inorganic fertilization treatments,manure input enhanced the stocks of SOC and total N in the surface layer(0–20 cm)but decreased SOC and N in the deep soil layer(80–100 cm).This reveals the efficiency of manure in increasing yield productivity and decreasing risk of vertical loss of nutrients,especially N,compared to inorganic fertilization *** findings provide opportunities for understanding deep soil C and N dynamics,which could help mitigate climate change impact o

关键词： carbon stock nitrogen stock carbon fraction soil profile organic amendments long-term experiment

An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

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Computer Systems Science & Engineering 2024年第2期48卷 529-554页

作者： Irfan haider Muhammad Attique khan Muhammad Nazir Taerang Kim Jae-Hyuk Cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science Hanyang UniversitySeoulKorea

Fruit infections have an impact on both the yield and the quality of the *** a result,an automated recognition system for fruit leaf diseases is *** artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification *** recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature *** work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder *** fruit types have been employed in this work for the validation process,such as apple,grape,and *** the first step,a noisy dataset is prepared by employing the original images to learn the designed framework *** EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy *** that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant *** selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector *** experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

关键词： Fruit disease contrast enhancement augmentation deep learning fusion feature selection classification

Priming mesenchymal stem cells to develop “super stem cells”

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World Journal of Stem Cells 2024年第6期16卷 623-640页

作者： Khawaja Husnain haider Department of Basic Sciences Sulaiman AlRajhi UniversityAlQaseem 52736Saudi Arabia

The stem cell pre-treatment approaches at cellular and sub-cellular levels encompass physical manipulation of stem cells to growth factor treatment,genetic manipulation,and chemical and pharmacological treatment,each strategy having advantages and *** of these pre-treatment protocols are *** editorial is a continuum of Li et al’s published article and Wan et al’s editorial focusing on the significance of pre-treatment strategies to enhance their stemness,immunoregulatory,and immunosuppressive *** have elaborated on the intricacies of the combinative pre-treatment protocol using pro-inflammatory cytokines and *** a well-defined multi-pronged combinatorial strategy of mesenchymal stem cells(MSCs),pre-treatment based on the mechanistic understanding is expected to develop“Super MSCs”,which will create a transformative shift in MSC-based therapies in clinical settings,potentially revolutionizing the *** optimized,the standardized protocols may be used with slight modifications to pre-treat different stem cells to develop“super stem cells”with augmented stemness,functionality,and reparability for diverse clinical applications with better outcomes.

关键词： Cell survival Cell therapy Preconditioning Pre-treatment Stem cells Super stem cells

Fuzzy inference system using genetic algorithm and pattern search for predicting roof fall rate in underground coal mines

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International Journal of Coal Science & Technology 2024年第1期11卷 31-41页

作者： Ayush Sahu Satish Sinha haider Banka Department of CSE IIT(ISM)DhanbadJharkhand826004India Department of Sustainability Adani universityAhmedabadGujrat382421India

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat *** falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation *** a result,a reliable roof fall prediction model is essential to tackle such *** parameters that substantially impact roof falls are ill-defined and intangible,making this an uncertain and challenging research *** National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof *** acquired for 37 mines is limited due to several restrictions,which increased the likelihood of *** logic is a technique for coping with ambiguity,incompleteness,and ***,In this paper,the fuzzy inference method is presented,which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of *** performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error,Mean-Absolute-Error,and coefficient of determination(R_(2)).Based on these criteria,the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

关键词： Underground coal mining Roof fall Fuzzy logic Genetic algorithm