Md Ashraf Uddin

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Jagannath University · Department of Computer Science & Engineering

The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications including continuous Remote Patient Monitoring (RPM). However, the complexity of RPM architectures, the size of datasets generated and limited power capacity of devices make RPM challenging. In this paper, we propose a tier based End-to...

Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentralized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, careful ma...

Health-related data is stored in a number of repositories that are managed and controlled by different entities. For instance, Electronic Health Records are usually administered by governments. Electronic Medical Records are typically controlled by health care providers, whereas Personal Health Records are managed directly by patients. Recently, Bl...

Conventional IoT ecosystems involve data streaming from sensors, through Fog devices to a centralized Cloud server. Issues that arise include privacy concerns due to third party management of Cloud servers, single points of failure, a bottleneck in data flows and difficulties in regularly updating firmware for millions of smart devices from a point...

In today’s digital age, our dependence on IoT (Internet of Things) and IIoT (Industrial IoT) systems has grown immensely, which facilitates sensitive activities such as banking transactions and personal, enterprise data, and legal document exchanges. Cyberattackers consistently exploit weak security measures and tools. The Network Intrusion Detecti...

Skin cancer is a potentially life-threatening disease resulting from DNA damage, where early detection is critical to improving survival rates. This study introduces an advanced hybrid deep learning framework designed to enhance the accuracy of skin cancer classification, distinguishing between benign and malignant lesions. Our approach begins with...

Social media has become a platform for people to express emotions, including happiness and sadness, to their followers. Major Depressive Disorder (MDD), a common mental health disorder, is characterized by sadness and loss of interest in activities, leading to physical, emotional, cognitive, and social suicidal thoughts. Early detection and interve...

Diabetes is a chronic metabolic disease characterized by elevated blood glucose levels and poses significant health risks, such as cardiovascular disease and cognitive damage. Understanding the causes of diabetes is crucial to managing it and preventing complications. The clinical community has a lot of diabetes diagnostic data. Machine learning al...

The rapid expansion of varied network systems, including the Internet of Things (IoT) and the Industrial Internet of Things (IIoT), has led to an increasing range of cyber threats. Ensuring robust protection against these threats necessitates the implementation of an effective Intrusion Detection System (IDS). For more than a decade, researchers ha...

Fraudulent transactions continue to pose a concern for financial institutions and organizations, necessitating the development of effective detection tools. Identification and prevention of fraudulent transactions depend heavily on the detection of credit card fraud. Even though instances of credit card fraud are uncommon, they can nonetheless caus...

Objective Early detection of Parkinson's disease (PD) is essential for halting its progression, yet challenges remain in leveraging deep learning for accurate identification. This study aims to overcome these obstacles by introducing a hybrid deep learning approach that enhances PD detection through a combination of autoencoder (AE) and radial basi...

Financial institutions and businesses face an ongoing challenge from fraudulent transactions, prompting the need for effective detection methods. Detecting credit card fraud is crucial for identifying and preventing unauthorized transactions. While credit card fraud incidents are relatively rare, they can result in substantial financial losses, par...

The deadly hepatitis C virus (HCV) is extremely prevalent and especially not treated quickly, may cause to permanent liver failure, cirrhosis or death. The establishment of prediction models through the application of machine learning techniques is hence effective. The purpose of this investigation is to find efficient machine learning framework th...

Skin cancer is a serious and potentially fatal disease caused by DNA damage. Early detection significantly increases survival rates, making accurate diagnosis crucial. In this groundbreaking study, we present a hybrid framework based on Deep Learning (DL) that achieves precise classification of benign and malignant skin lesions. Our approach begins...

Gallbladder cancer (GBC) is the most frequent cause of disease among biliary tract neoplasms. Identifying the molecular mechanisms and biomarkers linked to GBC progression has been a significant challenge in scientific research. Few recent studies have explored the roles of biomarkers in GBC. Our study aimed to identify biomarkers in GBC using mach...

Objective Brain tumors are a leading global cause of mortality, often leading to reduced life expectancy and challenging recovery. Early detection significantly improves survival rates. This paper introduces an efficient deep learning model to expedite brain tumor detection through timely and accurate identification using magnetic resonance imaging...

Through the advancement of the contemporary web and the rapid adoption of social media platforms such as YouTube, Twitter, and Facebook, for example, life has become much easier when dealing with certain highly personal problems. The far-reaching consequences of online harassment require immediate preventative steps to safeguard psychological welln...

Timely diagnosis of brain tumors using MRI and its potential impact on patient survival are critical issues addressed in this study. Traditional DL models often lack transparency, leading to skepticism among medical experts owing to their "black box" nature. This study addresses this gap by presenting an innovative approach for brain tumor detectio...

The integrity of democratic processes relies on secure and reliable election systems, yet achieving this reliability is challenging. This paper introduces the Post-Quantum Secured Multiparty Computed Hierarchical Authoritative Consensus Blockchain (PQMPCHAC-Bchain), a novel e-voting system designed to overcome the limitations of current Biometric E...

In the present day, the health of the populace is significantly jeopardized by the presence of contaminated water, and the majority of the population is unaware of the distinction between safe and unsafe water consumption. Agricultural, industrial, and other human-induced activities are causing a significant decline in the availability of drinking...

Cancer is a massive public health obligation and a malignant disease that has been blamed for the loss of human life worldwide. The biological facts and connectivity that are associated with cancer, on the other hand, still require deeper clarification. The effect of chronic lymphocytic leukemia (CLL) and hepatitis B virus (HBV) associated hepatoce...

Objective Diabetes is a metabolic disorder that causes the risk of stroke, heart disease, kidney failure, and other long-term complications because diabetes generates excess sugar in the blood. Machine learning (ML) models can aid in diagnosing diabetes at the primary stage. So, we need an efficient ML model to diagnose diabetes accurately. Method...

This paper presents a novel approach to remote patient monitoring using the integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The proposed system is designed to automatically detect and monitor the health status of patients from a remote location. The proposed solution uses a combination of connected devices, cl...

The k-Nearest Neighbors (kNN) method, established in 1951, has since evolved into a pivotal tool in data mining, recommendation systems, and Internet of Things (IoT), among other areas. This paper presents a comprehensive review and performance analysis of modifications made to enhance the exact kNN techniques, particularly focusing on kNN Search a...

The exponential growth of data and increased reliance on interconnected systems have heightened the need for robust network security. Cyber-Attack Detection Systems (CADS) are essential for identifying and mitigating threats through network traffic analysis. However, the effectiveness of CADS is highly dependent on selecting pertinent features. Thi...

Objective Diabetes is a metabolic disorder that causes the risk of stroke, heart disease, kidney failure, and other long-term complications because diabetes generates excess sugar in the blood. Machine learning (ML) models can aid in diagnosing diabetes at the primary stage. So, we need an efficient machine learning model to diagnose diabetes accur...

Acute lymphoblastic leukemia, commonly referred to as ALL, is a type of cancer that can affect both the blood and the bone marrow. The process of diagnosis is a difficult one since it often calls for specialist testing, such as blood tests, bone marrow aspiration, and biopsy, all of which are highly time-consuming and expensive. It is essential to...

Brain tumors significantly impact human health due to their complexity and the challenges in early detection and treatment. Accurate diagnosis is crucial for effective intervention, but existing methods often suffer from limitations in accuracy and efficiency. To address these challenges, this study presents a novel deep learning (DL) approach util...

Human activity recognition (HAR) plays a crucial role in assisting the elderly and individuals with vascular dementia by providing support and monitoring for their daily activities. This paper presents a deep learning (DL)-based approach to HAR, leveraging convolutional neural network (CNN), convolutional long short-term memory (ConvLSTM), and long...

Hypopharyngeal cancer is a disease that is associated with EGFR‐mutated lung adenocarcinoma. Here we utilized a bioinformatics approach to identify genetic commonalities between these two diseases. To this end, we examined microarray datasets from GEO (Gene Expression Omnibus) to identify differentially expressed genes, common genes, and hub genes...

In digital forensics, proper evidence management is crucial for police investigations due to its volatility and improper handling technique. However, to present and utilize the captured digital forensic images, which are typically concrete and admissible in court and a trial, is very challenging. In addition, centralized evidence-gathering, classif...

Handwritten document images need to be processed carefully to understand meaningful information. For useful collection and future reference, nowadays these documents are now protected in digital library. Historical records, cultural artifacts, and literary assets in Bangla scripts are precious things which should be stored in digitized format so th...

In the domain of cyber-physical systems, wireless sensor networks (WSNs) play a pivotal role as infrastructures, encompassing both stationary and mobile sensors. These sensors self-organize and establish multi-hop connections for communication, collectively sensing, gathering, processing, and transmitting data about their surroundings. Despite thei...

Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS) play a critical role in protecting interconnected networks by detecting malicious actors and activities. Machine Learning (ML)-based behavior analysis within the IDS has considerable potential for detecting dynamic cyber threats, identifying abnormalities, and...

Chronic kidney diseases (CKDs) are a significant public health issue with potential for severe complications such as hypertension, anemia, and renal failure. Timely diagnosis is crucial for effective management. Leveraging machine learning within healthcare offers promising advancements in predictive diagnostics. In this paper, we developed a machi...

Nowadays, to accommodate the swift expansion of cloud computing, big data, and other emerging technologies, integrating data center networks and SDN (Software Defined Network) is suggested, which also improves the network management’s convenience and flexibility. As network devices in these data centers continue to increase at a high rate, efficien...

The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of individuals across the planet. It is a highly contagious respiratory disease requiring early and accurate detection to curb its rapid transmission. Initial testing methods primarily revolved around identifying the genetic composition of the coronavirus,...

The Internet of Things (IoT) has recently attracted much interest from researchers due to its diverse IoT applications. However, IoT systems encounter additional security and privacy threats. Developing an efficient IoT system is challenging because of its sophisticated network topology. Effective access control is required to ensure user privacy i...

Leaf diseases pose a significant threat to crop production and profitability, particularly in the case of tomatoes, which are extensively cultivated worldwide. Early detection of these diseases is crucial to prevent significant crop losses. In this study, we propose a novel deep learning-based approach for disease detection and prediction in tomato...

Zoonoses are infectious diseases that spread between humans and vertebrate animals. COVID-19 was a global epidemic and one of the worst zoonotic diseases, costing more people in 2020 than all natural disasters in the last 20 years. Ebola, SARS, MERS, HIV, Lyme disease, Rift Valley fever, and Lassa fever are other prevalent zoonoses. In an epidemic,...

The Internet of Things (IoT) is a transformative technology that is reshaping industries and daily life, leading us towards a connected future that is full of possibilities and innovations. In this paper, we present a robust framework for the application of Internet of Things (IoT) technology in the agricultural sector in Bangladesh. The framework...

An epigenetic modification is DNA N4-methylcytosine (4mC) that affects several biological functions without altering the DNA nucleotides, including DNA conformation, cell development, replication, stability, and DNA structural changes. To prevent restriction enzyme from damaging self-DNA, 4mC performs a critical role in restriction–modification fun...

This research sought to discover relevant gene expression patterns of cancer cells having chronic lymphocytic leukemia(CLL) and head and neck can-cer(HNC). We conducted a comparative genomic study to demonstrate the genetic differences between HNC and CLL. To find the differentially expressed genes (DEGs) in HNC and CLL related datasets obtained fr...

Citation: Khatun, R.; Akter, M.; Islam, M.M.; Uddin, M.A.; Talukder, M.A.; Kamruzzaman, J.; Azad, A.; Paul, B.K.; Almoyad, M.A.A.; Aryal, S.; et al. Cancer Classification Utilizing Voting Classifier with Ensemble Feature Selection Method and Transcriptomic Data. Genes 2023, 14, 1802. https://doi. Abstract: Biomarker-based cancer identification and...

Alzheimer's disease, often known as dementia, is a severe neurodegenerative disorder that causes irreversible memory loss by destroying brain cells. People die because there is no specific treatment for this disease. Alzheimer's is most common among seniors 65 years and older. However, the progress of this disease can be reduced if it can be diagno...

Highlights • We have developed a loan approval prediction model using ensemble machine learning algorithms, which achieves higher performance than a single machine learning algorithm. The proposed model consists of nine machine learning algorithms: Logistic Regression (LR), Support Vector Machine (SVM), Decision Trees (DT), Gaussian Bayesian (GB),...

Cotton is known as ‘white gold’ in the agricultural industry. Agriculture is the primary source of economic income in Bangladesh and the country's economy is heavily dependent on agriculture. The soil and water resources of our country are fertile and the climate is moderate. But numerous diseases affect crop production and cause enormous crop loss...

Agriculture plays a significant role in every nation's economy by producing crops. Plant disease identification is one of the most important aspects of maintaining an agriculturally developed nation. The timely and efficient detection of plant diseases is essential for a healthy and productive agricultural sector and to prevent wasting money and ot...

Microstrip patch antennas are widely utilized in WLAN applications, and body-centric wireless communication relies on multiple network links to get messages through. But the existing antenna size is big with less bandwidth, which increases the cost. This paper has taken a rigorous approach to design an antenna that will provide a single resonant fr...

Social networking platforms give users countless opportunities to share information, collaborate, and communicate positively. The same platform can be extended to a fabricated and poisonous atmosphere that gives an impersonal, harmful platform for online misuse and assault. Cyberstalking is when someone uses an internet system to ridicule, torment,...

Social networking platforms give users countless opportunities to share information, collaborate, and communicate positively. The same platform can be extended to a fabricated and poisonous atmosphere that gives an impersonal, harmful platform for online misuse and assault. Cyberstalking is when someone uses an internet system to ridicule, torment,...

Diabetes is a chronic disease characterized by the inability of the pancreas to produce enough insulin or the body's inability to use insulin efficiently. This disease is becoming increasingly prevalent worldwide and can result in severe complications such as blindness, kidney failure, and stroke. Early detection of diabetes can potentially save mi...