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Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

Computers, Materials & Continua 2023年第4期75卷 785-798页

作者： Kamalrulnizam Bin Abu Bakar fatima Tul Zuhra Babangida Isyaku Fuad A.Ghaleb Faculty of Computing Universiti Teknologi MalaysiaJohor Bahru81310Malaysia Faculty of Science and Technology Shaheed Benazir Bhutto University Sanghar CampusPakistan Faculty of Computing and Information Technology Sule Lamido UniversityKafin HausaP.M.B.048Nigeria

The Internet of Medical Things (IoMT) emerges with the visionof the Wireless Body Sensor Network (WBSN) to improve the health monitoringsystems and has an enormous impact on the healthcare system forrecognizing the levels of risk/severity factors (premature diagnosis, treatment,and supervision of chronic disease i.e., cancer) via wearable/electronic healthsensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy playsa very significant role in the detection of gastric cancer. Convolutional NeuralNetwork (CNN) has been widely used to diagnose gastric cancer based onvarious feature extraction models, consequently, limiting the identificationand categorization performance in terms of cancerous stages and gradesassociated with each type of gastric cancer. This paper proposed an optimizedAI-based approach to diagnose and assess the risk factor of gastric cancerbased on its type, stage, and grade in the endoscopic images for smarthealthcare applications. The proposed method is categorized into five phasessuch as image pre-processing, Four-Dimensional (4D) image conversion,image segmentation, K-Nearest Neighbour (K-NN) classification, and multigradingand staging of image intensities. Moreover, the performance of theproposed method has experimented on two different datasets consisting ofcolor and black and white endoscopic images. The simulation results verifiedthat the proposed approach is capable of perceiving gastric cancer with 88.09%sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively.

关键词： Artificial intelligence internet of things internet of medical things wireless body sensor network wireless endoscopic capsule gastric cancer

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New uses for an old remedy:Digoxin as a potential treatment for steatohepatitis and other disorders

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World Journal of Gastroenterology 2023年第12期29卷 1824-1837页

作者： fatima Jamshed Farzaneh Dashti Xinshou Ouyang Wajahat Z Mehal Bubu A Banini Section of Digestive Diseases Yale School of MedicineNew HavenCT 06510United States Griffin Hospital-Yale University DerbyCT 06418United States West Haven Veterans Medical Center West HavenCT 06516United States

Repurposing of the widely available and relatively cheap generic cardiac glycoside digoxin for non-cardiac indications could have a wide-ranging impact on the global burden of several *** the past several years,there have been significant advances in the study of digoxin pharmacology and its potential noncardiac clinical applications,including anti-inflammatory,antineoplastic,metabolic,and antimicrobial *** holds promise in the treatment of gastrointestinal disease,including nonalcoholic steatohepatitis and alcoholassociated steatohepatitis as well as in obesity,cancer,and treatment of viral infections,among other *** this review,we provide a summary of the clinical uses of digoxin to date and discuss recent research on its emerging applications.

关键词： Digoxin Cardiac glycosides Oxidative stress Nonalcoholic steatohepatitis Alcohol-associated steatohepatitis Sterile inflammation

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Multi-Modality and Feature Fusion-Based COVID-19 Detection Through Long Short-Term Memory

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Computers, Materials & Continua 2022年第9期72卷 4357-4374页

作者： Noureen fatima Rashid Jahangir Ghulam Mujtaba Adnan Akhunzada Zahid Hussain Shaikh Faiza Qureshi Center of Excellence for Robotics Artificial Intelligenceand BlockchainDepartment of Computer ScienceSukkur IBA UniversitySukkurPakistan Department of Computer Science COMSATS University Islamabad–Vehari CampusPakistan Faculty of Computing and Informatics University Malaysia SabahKota Kinabalu88400Malaysia Department of Mathematics Sukkur IBA UniversitySukkurPakistan

The Coronavirus Disease 2019(COVID-19)pandemic poses the worldwide challenges surpassing the boundaries of country,religion,race,and *** current benchmark method for the detection of COVID-19 is the reverse transcription polymerase chain reaction(RT-PCR)***,this testing method is accurate enough for the diagnosis of ***,it is time-consuming,expensive,expert-dependent,and violates social *** this paper,this research proposed an effective multimodality-based and feature fusion-based(MMFF)COVID-19 detection technique through deep neural *** multi-modality,we have utilized the cough samples,breathe samples and sound samples of healthy as well as COVID-19 patients from publicly available COSWARA *** set of experimental analyses were performed to evaluate the performance of our proposed *** useful features were extracted from the aforementioned modalities that were then fed as an input to long short-term memory recurrent neural network algorithms for the classification *** set of experimental analyses were performed to evaluate the performance of our proposed *** experimental results showed that our proposed approach outperformed compared to four baseline approaches published *** believe that our proposed technique will assists potential users to diagnose the COVID-19 without the intervention of any expert in minimum amount of time.

关键词： Covid-19 detection long short-term memory feature fusion deep learning audio classification

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Physical Layer Authentication Using Ensemble Learning Technique in Wireless Communications

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Computers, Materials & Continua 2022年第12期73卷 4489-4499页

作者： Muhammad Waqas Shehr Bano fatima Hassan Shanshan Tu Ghulam Abbas Ziaul Haq Abbas Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan School of Engineering Edith Cowan UniversityJoondalup Perth6027WA Australia Faculty of Electrical Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan

Cyber-physical wireless systems have surfaced as an important data communication and networking research *** is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking *** to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and *** methods use physical layer authentication(PLA),themost promising solution to detect ***,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency *** methods perform well but only in stationary *** have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile *** features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify *** authentication of the received signal is considered a binary classification *** transmitted data is labeled as legitimate information,and spoofing data is illegitimate ***,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing *** detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are *** proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.

关键词： Physical layer authentication machine learning cyber-physical systems security

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B^(2)C^(3)NetF^(2):Breast cancer classification using an end‐to‐end deep learning feature fusion and satin bowerbird optimization controlled Newton Raphson feature selection

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1374-1390页

作者： Mamuna fatima Muhammad Attique Khan Saima Shaheen Nouf Abdullah Almujally Shui‐Hua Wang Department of Computer Science HITEC UniversityTaxilaPakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Mathematics University of LeicesterLeicesterUK

Currently,the improvement in AI is mainly related to deep learning techniques that are employed for the classification,identification,and quantification of patterns in clinical *** deep learning models show more remarkable performance than the traditional methods for medical image processing tasks,such as skin cancer,colorectal cancer,brain tumour,cardiac disease,Breast cancer(BrC),and a few *** manual diagnosis of medical issues always requires an expert and is also ***,developing some computer diagnosis techniques based on deep learning is *** cancer is the most frequently diagnosed cancer in females with a rapidly growing *** is estimated that patients with BrC will rise to 70%in the next 20 *** diagnosed at a later stage,the survival rate of patients with BrC is ***,early detection is essential,increasing the survival rate to 50%.A new framework for BrC classification is presented that utilises deep learning and feature *** significant steps of the presented framework include(i)hybrid contrast enhancement of acquired images,(ii)data augmentation to facilitate better learning of the Convolutional Neural Network(CNN)model,(iii)a pre‐trained ResNet‐101 model is utilised and modified according to selected dataset classes,(iv)deep transfer learning based model training for feature extraction,(v)the fusion of features using the proposed highly corrected function‐controlled canonical correlation analysis approach,and(vi)optimal feature selection using the modified Satin Bowerbird Optimization controlled Newton Raphson algorithm that finally classified using 10 machine learning *** experiments of the proposed framework have been carried out using the most critical and publicly available dataset,such as CBISDDSM,and obtained the best accuracy of 94.5%along with improved computation *** comparison depicts that the presented method surpasses the current state‐ofthe‐art approache

关键词： artificial intelligence artificial neural network deep learning,medical image processing,multi‐objective optimization

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Lowering fasting blood glucose with non-dialyzable material of cranberry extract is dependent on host genetic background,sex and diet

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Animal Models and Experimental Medicine 2023年第3期6卷 196-210页

作者： fatima Amer-Sarsour Rana Tarabeih Itzhak Ofek Fuad A.Iraqi Department of Clinical Microbiology and Immunology Sackler Faculty of MedicineTel-Aviv UniversityTel-AvivIsrael

Background:Type 2 diabetes(T2D)is a polygenic metabolic disease,character-ized by high fasting blood glucose(FBG).The ability of cranberry(CRN)fruit to regulate glycemia in T2D patients is well ***,a cohort of 13 lines of the genetically diverse Collaborative Cross(CC)mouse model was assessed for the effect of non-dialyzable material(NDM)of cranberry extract in lowering fasting blood ***:Eight-week-old mice were maintained on either a standard chow diet(con-trol group)or a high-fat diet(HFD)for 12 weeks,followed by injections of intraperi-toneal(IP)NDM(50 mg/kg)per mouse,three times a week for the next 6 *** FBG(mg/dl)was measured bi-weekly and percentage changes in FBG(%FBG)between weeks 0 and 12 were ***:Statistical analysis showed a significant decrease in FBG between weeks 0 and 12 in male and female mice maintained on ***,a non-significant in-crease in FBG values was observed in male and female mice maintained on HFD dur-ing the same *** administration of NDM during the following 6 weeks,the results show a variation in significant levels of FBG lowering between lines,male and female mice and under the different ***:The results suggest that the efficacy of NDM treatment in lowering FGB depends on host genetic background(pharmacogenetics),sex of the mouse(phar-macosex),and diet(pharmacodiet).All these results support the need for follow-up research to better understand and implement a personalized medicine approach/uti-lization of NDM for reducing FBG.

关键词： chow diet(CHD) collaborative cross(CC)mouse model fasting blood glucose(FBG) high-fat diet(HFD) non-dialyzable material(NDM)of cranberry extract type 2 diabetes(T2D)

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Decentralized solar-powered cooling systems for fresh fruit and vegetables to reduce post-harvest losses in developing regions:a review

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Clean Energy 2023年第3期7卷 635-653页

作者： Waseem Amjad Anjum Munir fatima Akram Aditya Parmar Marcelo Precoppe Furqan Asghar Faisal Mahmood Department of Energy Systems Engineering University of Agriculture FaisalabadFaisalabadPakistan Department of Agricultural&Biological Engineering Purdue UniversityWest LafayetteINUSA Natural Resources Institute University of GreenwichChatham MaritimeChathamME44TBUK

The availability of on-farm storage and processing is a critical challenge facing small farmers,which hinders agricultural *** per cent of the food produced globally is lost after harvest,with the proportion being exceptionally high in low-and middle-income countries due to a lack of on-farm handling and storage *** cold-storage solutions have not taken off at the smallholder level,mainly due to a lack of availability and access to reliable grid ***,off-grid decentralized solar-powered cold-storage units can play a vital role in preserving the produce at production sites and enhancing livelihood and rural development with a minimal carbon *** maintain low temperatures at every step of the agricultural value chain,known as the‘cold chain’,several technology vendors aim to improve the shelf life and user ***-scale farmers,which account for two-thirds of all food losses,are another group they focus *** study examines the existing situation,importance and potential opportunities of decentralized cold-storage systems for fresh fruit and *** addition to economic,social,technological and environmental limitations,this study examines the triumphs and challenges of incorporating solar-energy-powered cold storage into developing *** the private sector,NGOs and some government agencies are working to promote decentralized cold-storage facilities,relatively little has been done so far to have a significant influence on post-harvest losses and food *** are still knowledge gaps on decentralized cold-storage *** primary operational constraint is the economic situation of end users and the lack of financing alternatives for smallholder farmers.

关键词： post-harvest losses solar energy on-farm cold storage GHG emission

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On the Derivation of Subject wh-Words and Theory of Cartography

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Fudan Journal of the Humanities and Social Sciences 2023年第3期16卷 329-357页

作者： Marwan Jarrah Mutasim Al-Deaibes fatima Al Qaisiya Department of English Language and Literature School of Foreign LanguagesThe University of JordanAmmanJordan Khalifa University Abu DhabiUAE

In this article,we examine the syntactic derivation of subject wh-words in Jordanian ***,we provide empirical evidence that questions with a subject wh-word are syntactically derived by overt movement of the given subject wh-word to the left *** empirical evidence is based on the position of the subject wh-words to the left of the high IP adverbials,including epistemic adverbials and evidentials,as well as the position of the subject wh-words relative to topical ***,we examine the intriguing ban on the use of subject wh-words in VSO sentences although non-interrogative subjects are permitted to occur in such clauses,and other wh-words may appear in their thematic positions(given the appropriate context).We show that this ban results from the effects of a proposed economy-driven condition that disallows the use of an expletive(to fill Spec,TP)while the thematic subject is available(in Spec,vP).Additionally,we show that this ban results from the interactions of the effects of criterial freezing and the conditions that licence elements in the low IP area.

关键词： Criterial freezing Expletives Jordanian Arabic The low IP area Wh-movement

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Recycled materials in railroad substructure: an energy perspective

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Railway Engineering Science 2022年第3期30卷 304-322页

作者： Buddhima Indraratna Yujie Qi Rakesh Sai Malisetty Sinniah KNavaratnarajah fatima Mehmood Miriam Tawk Transport Research Centre School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyNSW 2007Australia Department of Civil Engineering Faculty of EngineeringUniversity of PeradeniyaPeradeniyaSri Lanka School of Civil Mining and Environmental EngineeringUniversity of WollongongWollongongNSW 2522Australia College of Engineering and Technology American University of the Middle EastEgailaKuwait

Given that the current ballasted tracks in Australia may not be able to support faster and significantly heavier freight trains as planned for the future,the imminent need for innovative and sustainable ballasted tracks for transport infrastructure is *** the past two decades,a number of studies have been conducted by the researchers of Transport Research Centre(TRC)at the University of Technology Sydney(UTS)to investigate the ability of recycled rubber mats,as well as waste tyre cells and granulated rubber to improve the stability of track substructure including ballast and subballast *** paper reviews four applications of these novel methods,including using recycled rubber products such as CWRC mixtures(i.e.,mixtures of coal wash(CW)and rubber crumbs(RC))and SEAL mixtures(i.e.,mixtures of steel furnace slag,CW and RC)to replace subballast/capping materials,tyre cells reinforcements for subballast/capping layer and under ballast mats;and investigates the energy dissipation capacity for each application based on smallscale cyclic triaxial tests and large-scale track model *** has been found that the inclusion of these rubber products increases the energy dissipation effect of the track,hence reducing the ballast degradation efficiently and increasing the track ***,a rheological model is also proposed to investigate the effect of different rubber inclusions on their efficiency to reduce the transient motion of rail track under dynamic *** outcomes elucidated in this paper will lead to a better understanding of the performance of ballast tracks upgraded with resilient rubber products,while promoting environmentally sustainable and more affordable ballasted tracks for greater passenger comfort and increased safety.

关键词： Ballast degradation Recycled rubber Energy dissipation Laboratory testing Rheological model

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Convolutional Neural Network-Based Classificationof Multiple Retinal Diseases Using Fundus Images

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Intelligent Automation & Soft Computing 2023年第6期36卷 2607-2622页

作者： Aqsa Aslam Saima Farhan Momina Abdul Khaliq fatima Anjum Ayesha Afzaal Faria Kanwal Lahore College for Women University Lahore54000Pakistan

Use of deep learning algorithms for the investigation and analysis of medical images has emerged as a powerful *** increase in retinal dis-eases is alarming as it may lead to permanent blindness if left ***-tion of the diagnosis process of retinal diseases not only assists ophthalmologists in correct decision-making but saves time *** researchers have worked on automated retinal disease classification but restricted either to hand-crafted fea-ture selection or binary *** paper presents a deep learning-based approach for the automated classification of multiple retinal diseases using fundus *** this research,the data has been collected and combined from three distinct *** images are preprocessed for enhancing the *** layers of the convolutional neural network(CNN)are used for the automated feature extraction and classification of 20 retinal *** is observed that the results are reliant on the number of *** binary classification(healthy ***),up to 100%accuracy has been *** 16 classes are used(treating stages of a disease as a single class),93.3%accuracy,92%sensitivity and 93%specificity have been obtained *** 20 classes(treating stages of the disease as separate classes),the accuracy,sensitivity and specificity have dropped to 92.4%,92%and 92%respectively.

关键词： Classification convolutional neural network fundus images medical image diagnosis retinal diseases

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