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Automatic Finding of Brain-Tumour Group Using CNN Segmentation and Moth-Flame-Algorithm,Selected Deep and Handcrafted Features

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Computers, Materials & Continua 2024年第5期79卷 2585-2608页

作者： Imad Saud Al Naimi syed Alwee Aljunid syed Junid Muhammad lmran ahmad K.Suresh Manic Faculty of Electronic Engineering Technology University Malaysia Perils(UniMAP)Pauh Putra CampusArauPerlis02600Malaysia Department of Electrical and Communication Engineering National University of Science and TechnologyAL HailAL Seeb130Sultanate of Oman Department of Research and Innovation Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)ChennaiTamiNadu602105India

Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in ***’s clinical level screening is usually performed with Magnetic Resonance Imaging(MRI)due to its multi-modality *** overall aims of the study is to introduce,test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans,facilitating improved *** research intends to devise a reliable framework for detecting the BT region in the twodimensional(2D)MRI slice,and identifying its class with improved *** methodology for the devised framework comprises the phases of:(i)Collection and resizing of images,(ii)Implementation and Segmentation of Convolutional Neural Network(CNN),(iii)Deep feature extraction,(iv)Handcrafted feature extraction,(v)Moth-Flame-Algorithm(MFA)supported feature reduction,and(vi)Performance *** study utilized clinical-grade brain MRI of BRATS and TCIA datasets for the *** framework segments detected the glioma(low/high grade)and glioblastoma class *** work helped to get a segmentation accuracy of over 98%with VGG-UNet and a classification accuracy of over 98%with the VGG16 *** study has confirmed that the implemented framework is very efficient in detecting the BT in MRI slices with/without the skull section.

关键词： Brain tumour VGG-UNet VGG16 moth-flame-algorithm classification

Classification and Comprehension of Software Requirements Using Ensemble Learning

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Computers, Materials & Continua 2024年第8期80卷 2839-2855页

作者： Jalil Abbas Arshad ahmad syed Muqsit Shaheed Rubia Fatima Sajid Shah Mohammad Elaffendi Gauhar Ali School of Computer Science and Technology Anhui UniversityHefei230039China School of Computing Sciences Pak Austria FachhochschuleInstitute of Applied Sciences and TechnologyHaripur22620Pakistan Department of Computer Science and IT University of LahoreLahore55150Pakistan Department of Computer Science Emerson UniversityPunjabMultan60000Pakistan EIAS(Emerging Intelligent Autonomous Systems)Data Science Lab Prince Sultan UniversityRiyad12435Saudi Arabia

The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

关键词： Ensemble learning machine learning non-functional requirements requirement engineering accuracy sliding window

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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Computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

Unraveling the therapeutic mechanisms of myristic acid and luteolin 7-rutinoside in oral cancer: insights from network pharmacology and molecular docking analysis

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Pharmacology Discovery 2024年第2期4卷 1-9页

作者： Ansari Vikhar Danish ahmad Misba Ruhi syed Ayaz Ali Qazi Yasar Mohd.Mukhtar Khan Subur W Khan Mohammed Imran Anees Y.B.Chavan College of Pharmacy Dr.Babasaheb Ambedkar Marathwada UniversityAurangabad 431001India Maulana Azad College Dr.Babasaheb Ambedkar Marathwada UniversityAurangabad 431001India

Background:The compound Luteolin-7-rutinoside(L7R)is a flavone derivative of luteolin,predominantly identified in plant species belonging to the families ***,Myristic acid is characterized by its structure as a 14-carbon,unsaturated fatty *** this investigation,we endeavor to elucidate the putative mechanisms underlying the therapeutic effects of Myristic Acid and Luteolin 7-rutinoside in the context of oral cancer treatment,employing network pharmacology coupled with molecular docking ***:The protein targets of Myristic Acid and Luteolin 7-rutinoside were identified through a search on the Swiss Target ***,a compound-target network was constructed using Cytoscape *** associated with OC were retrieved from the OMIM and GeneCards *** overlap between compound targets and OC-related targets was determined,and the resulting shared targets were subjected to protein-protein interaction(PPI)network analysis using the STRING ***,gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were conducted on the identified *** docking were performed to investigate the interactions between the core target and the active ***:The component target network comprises 103 nodes and 102 *** the proteins in the protein-protein interaction(PPI)network,those with higher degrees are TNF,PPARG,and *** through Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways indicates that the treatment of OC with Myristic Acid and Luteolin 7-rutinoside primarily involves the regulation of miRNA transcription and inflammatory *** identified signaling pathways include Pathways in cancer,PPAR signaling pathway,EGFR signaling pathway,and TNF signaling *** docking studies reveal that Luteolin 7-rutinoside and Myristic acid exhibit higher affinity towards TNF,PPARG,TP53,and ***:This study

关键词： myristic acid luteolin 7-rutinoside network pharmacology oral cancer molecular docking

National guidelines for the diagnosis and treatment of hilar cholangiocarcinoma

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World Journal of Gastroenterology 2024年第9期30卷 1018-1042页

作者： Faisal Saud Dar Zaigham Abbas Irfan Ahmed Muhammad Atique Usman Iqbal Aujla Muhammad Azeemuddin Zeba Aziz Abu Bakar Hafeez Bhatti Tariq Ali Bangash Amna Subhan Butt Osama Tariq Butt Abdul Wahab Dogar Javed Iqbal Farooqi Faisal Hanif Jahanzaib Haider Siraj Haider syed Mujahid Hassan Adnan Abdul Jabbar Aman Nawaz Khan Muhammad Shoaib Khan Muhammad Yasir Khan Amer Latif Nasir Hassan Luck ahmad Karim Malik Kamran Rashid Sohail Rashid Mohammad Salih Abdullah Saeed Amjad Salamat Ghias-un-Nabi Tayyab Aasim Yusuf Haseeb Haider Zia Ammara Naveed Department of Hepatopancreatic Biliary Surgery&Liver Transplant Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Hepatogastroenterology and Liver Transplantation Dr.Ziauddin University HospitalKarachi 75600SindhPakistan University of Aberdeen Aberdeen B243FXUnited Kingdom Department of Pathology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Gastroenterology&Hepatology Pakistan Kidney and Liver Institute&Research CentreLahore 54000Pakistan Department of Radiology Aga Khan UniversityKarachi 74800Pakistan Department of Oncology Hameed Latif HospitalLahore 54000Pakistan Division of Hepatopancreatic Biliary Surgery&Liver Transplantation Shifa International HospitalIslamabad 44000Pakistan Department of Hepatopancreatic Biliary Surgery&Liver Transplant Shaikh Zayed Hospital and Post Graduate Medical InstituteLahore 54000Pakistan Department of Medicine Aga Khan University HospitalKarachi 74800Pakistan Department of Liver Transplant Pir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Medicine&Gastroenterology Lifecare Hospital and Research CentrePeshawar 25000Khyber PakhtunkhwaPakistan Department of Hepatopancreatobiliary&Liver Transplant Bahria International HospitalLahore 54000Pakistan Department of Surgery Hepatopancreatobiliary&Liver TransplantDow University of Health SciencesKarachi 74800Pakistan Department of Gastroenterology Hepatology&NutritionPir Abdul Qadir Shah Jeelani Institute of Medical SciencesGambat 66020Pakistan Department of Oncology Dr.Ziauddin HospitalKarachi 74800Pakistan Department of Radiology Rehman Medical InstitutePeshawar 25000Pakistan Army Liver Transplant Unit Pak Emirates Military HospitalRawalpindi 46000Pakistan Department of Gastroenterology Sindh Institute of Urology and TransplantationKarachi 75500Pakistan Rashid Nursing Home and Cancer Clinic Rashid Nursing Home and Cancer ClinicRawalpindi 46000Pakistan Department of Gastroentero

A consensus meeting of national experts from all major national hepatobiliary centres in the country was held on May 26,2023,at the Pakistan Kidney and Liver Institute&Research Centre(PKLI&RC)after initial consultations with the *** Pakistan Society for the Study of Liver Diseases(PSSLD)and PKLI&RC jointly organised this *** effort was based on a comprehensive literature review to establish national practice guidelines for hilar cholangiocarcinoma(hCCA).The consensus was that hCCA is a complex disease and requires a multidisciplinary team approach to best manage these *** coordinated effort can minimise delays and give patients a chance for curative treatment and effective *** diagnostic and staging workup includes high-quality computed tomography,magnetic resonance imaging,and magnetic resonance *** cytology or biopsy utilizing endoscopic retrograde cholangiopancreatography is a mainstay for ***,histopathologic confirmation is not always required before *** ultrasound with fine needle aspiration of regional lymph nodes and positron emission tomography scan are valuable adjuncts for *** only curative treatment is the surgical resection of the biliary tree based on the Bismuth-Corlette *** patients with unresectable hCCA can be considered for liver *** chemotherapy should be offered to patients with a high risk of *** use of preoperative biliary drainage and the need for portal vein embolisation should be based on local multidisciplinary *** with acute cholangitis can be drained with endoscopic or percutaneous biliary *** chemotherapy with cisplatin and gemcitabine has shown improved survival in patients with irresectable and recurrent hCCA.

关键词： Hilar cholangiocarcinoma Bismuth-Corlette classification Memorial Sloan Kettering Cancer Centre Staging Preoperative biliary drainage Portal vein embolisation Surgical resection Hepatectomy

Machine learning empowered COVID-19 patient monitoring using non-contact sensing:An extensive review

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Journal of Pharmaceutical Analysis 2022年第2期12卷 193-204页

作者： Umer Saeed syed Yaseen Shah Jawad ahmad Muhammad Ali Imran Qammer H.Abbasi syed Aziz Shah Research Centre for Intelligent Healthcare Coventry UniversityCoventryCV15FBUK School of Computing Engineering and Built EnvironmentGlasgow Caledonian UniversityGlasgowG40BAUK School of Computing Edinburgh Napier UniversityEdinburghEH114BNUK James Watt School of Engineering University of GlasgowGlasgowG128QQUK

The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),which caused the coronavirus disease 2019(COVID-19)pandemic,has affected more than 400 million people *** the recent rise of new Delta and Omicron variants,the efficacy of the vaccines has become an important *** goal of various studies has been to limit the spread of the virus by utilizing wireless sensing technologies to prevent human-to-human interactions,particularly for healthcare *** this paper,we discuss the current literature on invasive/contact and non-invasive/noncontact technologies(including Wi-Fi,radar,and software-defined radio)that have been effectively used to detect,diagnose,and monitor human activities and COVID-19 related symptoms,such as irregular *** addition,we focused on cutting-edge machine learning algorithms(such as generative adversarial networks,random forest,multilayer perceptron,support vector machine,extremely randomized trees,and k-nearest neighbors)and their essential role in intelligent healthcare ***,this study highlights the limitations related to non-invasive techniques and prospective research directions.

关键词： Artificial intelligence Non-invasive healthcare Machine learning Non-contact sensing COVID-19

Fractional Processing Based Adaptive Beamforming Algorithm

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Computers, Materials & Continua 2023年第7期76卷 1065-1084页

作者： syed Asghar Ali Shah Tariqullah Jan syed Muslim Shah Ruhul Amin Khalil ahmad Sawalmeh Muhammad Anan Department of Electrical Engineering University of Engineering and TechnologyPeshawar25120Pakistan Department of Electrical Engineering Capital University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science Northern Border UniversityArar91431Saudi Arabia Department of Software Engineering Alfaisal UniversityRiyadh11533Saudi Arabia

Fractional order algorithms have shown promising results in various signal processing applications due to their ability to improve performance without significantly increasing *** goal of this work is to inves-tigate the use of fractional order algorithm in the field of adaptive beam-forming,with a focus on improving performance while keeping complexity *** effectiveness of the algorithm will be studied and evaluated in this *** this paper,a fractional order least mean square(FLMS)algorithm is proposed for adaptive beamforming in wireless applications for effective utilization of *** algorithm aims to improve upon existing beam-forming algorithms,which are inefficient in performance,by offering faster convergence,better accuracy,and comparable computational *** FLMS algorithm uses fractional order gradient in addition to the standard ordered gradient in weight *** derivation of the algorithm is provided and supported by mathematical convergence *** is evaluated through simulations using mean square error(MSE)minimization as a metric and compared with the standard LMS algorithm for various *** results,obtained through Matlab simulations,show that the FLMS algorithm outperforms the standard LMS in terms of convergence speed,beampattern accuracy and scatter *** outperforms LMS in terms of convergence speed by 34%.From this,it can be concluded that FLMS is a better candidate for adaptive beamforming and other signal processing applications.

关键词： Adaptive beamforming adaptive array fractional processing least mean square fractional least mean square

Arbuscular mycorrhizal fungi for salinity stress: Anti-stress role and mechanisms

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Pedosphere 2023年第1期33卷 212-224页

作者： Muzafar HDAR syed MRAZVI Narender SINGH ahmad MUSHTAQ Shahnawaz DAR Shabber HUSSAIN Department of Botany Kurukshetra UniversityKurukshetraHaryana 136119India Department of Plant Breeding and Genetics Sher-e Kashmir University of Agricultural Sciences and Technology of Kashmir(SKUAST-K)ShalimarSrinagar 190021India Research Center for Residue and Quality Analysis SKUAST-KShalimarSrinagar 190021India Krishi Vigyan Kendra(KVK)Kargil 11(Zanskar) SKUAST-KShalimarSrinagar 190021India

Salinity stress is considered one of the most harmful environmental plant stresses,as it reduces irrigated land crop production by over 20%***,it is imperative to develop salt-tolerant crops in addition to understanding various mechanisms enabling plant growth under saline stress ***,a novel biological approach that aims to address salinity stress has gained momentum,which involves the use of arbuscular mycorrhizal(AM)fungi in plant-microbe *** has been observed that most terrestrial plant root systems are colonized by AM fungi,which modulate plant growth in multiple *** such interactions,AM fungi obtain organic compounds from the host plant while providing mineral nutrients,including nitrogen,phosphorus,potassium,calcium,and sulfur,to the host *** recent decades,our understanding of the multifunctional roles played by AM fungi has been broadened and advanced,particularly regarding the mediation of mineral nutrients and the alleviation of stress(especially salt stress)in most crop *** uptake of phosphorus and augmented tolerance to salinity result in enhanced plant growth and *** evident anti-stress role of AM fungi and related mechanisms have been described separately,though they need to be analyzed and discussed ***,the present review addresses the major role of AM fungi in mitigating salt stress and their beneficial effects on plant growth and *** mechanisms employed by AM fungi to amplify the salt tolerance of host plants by increased nutrient accession(e.g.,phosphorus,nitrogen,and calcium),physiological changes(e.g.,photosynthetic efficiency,cell membrane permeability,water status,and nitrogen fixation),and biochemical changes(e.g.,the accumulation of different osmolytes such as proline and soluble sugars)are also ***,this review highlights the role of AM fungi in the Na+/H+*** plants,AM fungi inoculation increases the activities of mul

关键词： biochemical and physiological changes osmolytes plant-microbe interaction salt stress sodium accumulation

Hybrid Global Optimization Algorithm for Feature Selection

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Computers, Materials & Continua 2023年第1期74卷 2021-2037页

作者： ahmad Taher Azar Zafar Iqbal Khan syed Umar Amin Khaled M.Fouad Faculty of Computers and Artificial Intelligence Benha UniversityBenha13511Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Technology and Computer Science Nile UniversitySheikh ZaidEgypt

This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm(PLTVACIW-PSO).Its designed has introduced the benefits of Parallel computing into the combined power of TVAC(Time-Variant Acceleration Coefficients)and IW(Inertial Weight).Proposed algorithm has been tested against linear,non-linear,traditional,andmultiswarmbased optimization *** experimental study is performed in two stages to assess the proposed *** I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIWPSO *** based Particle Swarm Optimization(PSO)algorithms,TVAC based PSO algorithms,traditional PSO,Genetic algorithms(GA),Differential evolution(DE),and,finally,Flower Pollination(FP)*** phase II,the proposed PLTVACIW-PSO uses the same 12 known Benchmark functions to test its performance against the BAT(BA)and Multi-Swarm BAT *** phase III,the proposed PLTVACIW-PSO is employed to augment the feature selection problem formedical *** experimental study shows that the planned PLTVACIW-PSO outpaces the performances of other comparable *** from the experiments shows that the PLTVACIW-PSO is capable of outlining a feature subset that is capable of enhancing the classification efficiency and gives the minimal subset of the core features.

关键词： Particle swarm optimization(PSO) time-variant acceleration coefficients(TVAC) genetic algorithms differential evolution feature selection medical data