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Risk Factors Categorizations of Ischemic Heart Disease in South-Western Bangladesh

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Data Intelligence 2024年第3期6卷 834-868页

作者： M.raihan Sami Azam Laboni Akter md.Mehedi Hassan Ryana Quadir Asif Karim Saikat Mondal Arun More Department of Computer Science and Engineering North Western UniversityKhulna 9100Bangladesh Faculty of Science and Technology Charles Darwin UniversityNT 0909Australia Departmentof Biomedical Engineering Khulna University of Engineering&TechnologyKhulnaBangladeh Computer Science and Engineering Discipline Khulna UniversityKhulna 9208Bangladesh Department of Computer Science and Engineering Daffodil International University(DIU)Bangladesh Department of Cardiology Ter Institute of Rural Health and ResearchMurud-413510India

Ischemic heart disease(IHD)is one of the leading causes of death ***,different geographic regions show different variations of the risk factors of this disease based on the different lifestyles of *** study examines the current IHD condition in southern Bangladesh,a Southeast Asian middle-income *** main approach to this research is an al-based proposal of a reduced set of the greatest impact clinical traits that may cause *** approach attempts to reduce IHD morbidity and mortality by early detection of risk factors using the reduced set of clinical ***,diagnostic,and symptomatic features were considered for analysing this clinical *** pre-processing utilizes several machine learning techniques to select significant features and make meaningful interpretations.A proposed voting mechanism ranked the selected 138 features by their impact *** this regard,diverse patterns in correlations with variables,including age,sex,career,family history,obesity,etc.,were calculated and explained in terms of voting *** the 138 risk factors,three labels were categorized:high-risk,medium-risk,and low-risk features;19 features were regarded as high,25 were medium,and 94 were considered low impactful *** research's technological methodology and practical goals provide an innovative and resilient framework for addressing IHD,especially in less developed cities and townships of Bangladesh,where the general population's socioeconomic conditions are often *** data collection,pre-processing,and use of this study's complete and comprehensive IHD patient dataset is another innovative *** believe that other relevant research initiatives will benefit from this work.

关键词： Ischemic heart disease Machine learning CVD Data categorization Medical data

Improving Prediction Efficiency of Machine Learning Models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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Computers, Materials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim md.Niamat Ullah Akhund Waleed M.al-Nuwaiser Department of Computer Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

关键词： Internet of sensing things(IoST) machine learning hyperparameter optimization cardiovascular disease prediction execution time analysis performance analysis wilcoxon signed-rank test

Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah md.Siraj Bander ali Saleh al-rimy Sultan Noman Qasem Tawfik al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection Systems(CIDS).Existing adaptive CIDS solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDS(Adaptive Cloud Intrusion Detection System)-*** novel Adaptive CIDS framework leverages the Pruned Exact Linear Time(PELT)algorithm and a Support Vector Machine(SVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature Selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HSO-SU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)Surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training Set:Labeled network traffic data forms the training set used to train the SVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing Set:The testing set evaluates ACIDS-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDS-PELT using the NSL-KDD benchmark *** results demonstrate that ACIDS-PELT outperf

关键词： Adaptive cloud IDS harmony search distributed denial of service(DDoS) PELT machine learning SVM ISOTCID NSL-KDD

Tuberculosis-diabetes comorbidities: Mechanistic insights for clinical considerations and treatment challenges

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World Journal of Diabetes 2024年第5期15卷 853-866页

作者： md Abdul alim al-Bari Nicholas Peake Nabil Eid Department of Pharmacy University of RajshahiRajshahi 6205Bangladesh Biosciences and Chemistry and Biomolecular Research Centre Sheffield Hallam UniversitySheffield S11WBUnited Kingdom Department of Anatomy Division of Human BiologySchool of MedicineInternational Medical UniversityKuala Lumpur 57000Malaysia

Tuberculosis(TB)remains a leading cause of death among infectious diseases,particularly in poor *** infections,multidrug-resistant and ex-tensively drug-resistant TB strains,as well as the coexistence of chronic illnesses such as diabetes mellitus(DM)greatly aggravate TB morbidity and ***[particularly type 2 DM(T2DM)]and TB have converged making their control even more *** contemporary global epidemics,TB-DM behaves like a syndemic,a synergistic confluence of two highly prevalent diseases.T2DM is a risk factor for developing more severe forms of multi-drug resistant-TB and TB recurrence after preventive *** a bidirectional relationship exists between TB and DM,it is necessary to concurrently treat both,and promote recommendations for the joint management of both *** are also some drug-drug interactions resulting in adverse treatment outcomes in TB-DM patients including treatment failure,and *** addition,autophagy may play a role in these ***,the TB-DM comorbidities present several health challenges,requiring a focus on multidisciplinary collaboration and integrated strategies,to effectively deal with this double *** effectively manage the comorbidity,further screening in affected countries,more suitable drugs,and better treatment strategies are required.

关键词： Diabetes mellitus Tuberculosis Coinfections Comorbidity Drug-drug interactions Autophagy Treatment challenges

An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1689-1710页

作者： md.Abdur Rahim Fahmid al Farid Abu Saleh Musa Miah Arpa Kar Puza md.Nur alam md.Najmul Hossain Sarina Mansor Hezerul Abdul Karim Department of Computer Science and Engineering Pabna University of Science and TechnologyPabna6600Bangladesh Faculty of Engineering Multimedia UniversityCyberjaya63100Malaysia Department of Computer Science and Engineering Bangladesh Army University of Science and TechnologySaidpur5311Bangladesh Department of Mathematics Pabna University of Science and TechnologyPabna6600Bangladesh Department of Electrical Electronic and Communication EngineeringPabnaUniversity of Science and TechnologyPabna6600Bangladesh Department of Electrical and Communication Engineering Pabna University of Science and TechnologyPabna6600Bangladesh

Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde

关键词： Bengali handwriting(BHW) person identification convolutional neural network(CNN) BiLSTM

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin md.al Mehedi Hasan Abu Saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

Anomaly-Based Intrusion DetectionModel Using Deep Learning for IoT Networks

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 823-845页

作者： Muaadh A.alsoufi Maheyzah md Siraj Fuad A.Ghaleb Muna al-Razgan Mahfoudh Saeed al-Asaly Taha alfakih Faisal Saeed Faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research Group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,F1 of 99.9%,False Positive Rate(FPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

Privacy-Preserving Information Fusion Technique for Device to Server-Enabled Communication in the Internet of Things:A Hybrid Approach

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Computers, Materials & Continua 2024年第7期80卷 1305-1323页

作者： Amal al-Rasheed Rahim Khan Tahani alsaed Mahwish Kundi Mohamad Hanif md.Saad Mahidur R.Sarker Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science AbdulWali Khan University MardanMardan23200Pakistan Faculty of Computing and Informatics University Malaysia SabahKota KinabaluSabah88400Malaysia Applied College Taibah UniversityMadinah41477Saudi Arabia Maynooth International Engineering College Maynooth UniversityCo KildareW23 X021Irland Department of Mechanical Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Institute of Visual Informatics Universiti Kebangsaan MalaysiaBangiSelangor43600Malaysia University of Design Innovation and Technology(UDIT)Av.Alfonso XIII97Madrid28016Spain

Due to the overwhelming characteristics of the Internet of Things(IoT)and its adoption in approximately every aspect of our lives,the concept of individual devices’privacy has gained prominent attention from both customers,i.e.,people,and industries as wearable devices collect sensitive information about patients(both admitted and outdoor)in smart healthcare *** addition to privacy,outliers or noise are among the crucial issues,which are directly correlated with IoT infrastructures,as most member devices are resource-limited and could generate or transmit false data that is required to be refined before processing,i.e.,***,the development of privacy-preserving information fusion techniques is highly encouraged,especially those designed for smart IoT-enabled *** this paper,we are going to present an effective hybrid approach that can refine raw data values captured by the respectivemember device before transmission while preserving its privacy through the utilization of the differential privacy technique in IoT *** window,i.e.,δi based dynamic programming methodology,is implemented at the device level to ensure precise and accurate detection of outliers or noisy data,and refine it prior to activation of the respective transmission ***,an appropriate privacy budget has been selected,which is enough to ensure the privacy of every individualmodule,i.e.,a wearable device such as a smartwatch attached to the patient’s *** contrast,the end module,i.e.,the server in this case,can extract important information with approximately the maximum level of ***,refined data has been processed by adding an appropriate nose through the Laplace mechanism to make it useless or meaningless for the adversary modules in the *** proposed hybrid approach is trusted from both the device’s privacy and the integrity of the transmitted information *** and analytical results ha

关键词： Internet of things information fusion differential privacy dynamic programming Laplace function

The link between intracellular calcium signaling and exosomal PD-L1 in cancer progression and immunotherapy

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Genes & Diseases 2024年第1期11卷 321-334页

作者： md Rakibul alam md Mizanur Rahman Zhiguo Li Department of Toxicology and Cancer Biology College of MedicineUniversity of KentuckyLexingtonKY 40506USA Department of Medicine(Nephrology) Faculty of Medicine and DentistryUniversity of AlbertaEdmontonAlberta T6E2H7Canada

Exosomes are small membrane vesicles containing microRNA,RNA,DNA fragments,and proteins that are transferred from donor cells to recipient *** cells release exo-somes to reprogram the factors associated with the tumor microenvironment(TME)causing tu-mor metastasis and immune *** evidence revealed that cancer cell-derived exosomes carry immune inhibitory molecule program death ligand 1(PD-L1)that binds with re-ceptor program death protein 1(PD-1)and promote tumor progression by escaping immune ***,some FDA-approved monoclonal antibodies are clinicallyused for cancer treatment by blocking PD-1/PD-L1 *** notable treatment outcomes,some pa-tients show poor drug *** PD-L1 plays a vital role in lowering the treatment response,showing resistance to PD-1/PD-L1 blockage therapy through recapitulating the ef-fect of cell surface *** enhance therapeutic response,inhibition of exosomal PD-L1 is *** signaling is the central regulator of tumorigenesis and can regulate exosome biogenesis and secretion by modulating Rab GTPase family and membrane fusion ***-mune checkpoints are also connected with calcium signaling and calcium channel blockers like amlodipine,nifedipine,lercanidipine,diltiazem,and verapamil were also reported to suppress cellular PD-L1 ***,to enhance the PD-1/PD-L1 blockage therapy response,the reduction of exosomal PD-L1 secretion from cancer cells is in our therapeutic *** this review,we proposed a therapeutic strategy by targeting calcium signaling to inhibit the expression of PD-L1-containing exosome levels that could reduce the anti-PD-1/PD-L1 therapy resistance and increase the patient's drug response rate.

关键词： Calcium signaling CD8^(+)T cells Exosomal PD-L1 Exosomes biogenesis Immunosuppression Immunotherapy