Mamoon Rashid

Several deep learning networks are developed to identify the complex atrophic patterns of Alzheimer's disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one. Even though these functions are analyzed individually, group activations and their interpretations are still not explored...

Introduction: Acute lymphoblastic leukemia (ALL) is a severe illness that affects children and adults, and it can be fatal when left untreated. This leukemia strikes children and adolescents suddenly, often claiming their lives within just a few weeks after diagnosis. To diagnose ALL, hematologists investigate blood slides and bone marrow samples....

A complicated neurodevelopmental illness known as Autism Spectrum Disorder (ASD) impacts behavior, speech, and social interaction. For early diagnosis and intervention, it is essential to classify people with ASD accurately. The hybrid Parcellation Mapping approach for the extraction of connectivity measures is used in this study to analyze the ABI...

Functional Magnetic Resonance Imaging (fMRI) is presently one of the most popular techniques for analysing the dynamic states in brain images using various kinds of algorithms. From the last decade, there is an exponential rise in the use of the machine and deep learning algorithms of artificial intelligence for analysing fMRI data. However, it is...

Postpartum haemorrhage (PPH) is the loss of blood above 500 ml during vaginal or caesarean deliveries. It is difficult to find a PPH in an earlier stage, so pregnant women are exposed to excess blood loss that makes them suffer and die. Antenatal practices help in identifying risk factors, and modern technology is used to overcome the risk. Still,...

Neuroblastoma (NB) is a childhood malignancy associated with high cancer-related mortality and disability, remaining a persistent challenge in paediatric oncology. High-risk NB tumours often metastasize, resulting in survival rates below 50%. Early detection and accurate risk stratification are thus essential for improving patient prognosis and the...

Unmanned Aerial Vehicles (UAVs) are enabled to be fast and flexible in managing traffic compared to the conventional methods. However, in emergencies, this system takes more time to identify and clear the traffic because of fixed time control. To overcome this problem, an automated intelligent traffic monitoring and controlling system is designed u...

Background Lung cancer has the highest global fatality rate, with diagnosis primarily relying on histological tissue sample analysis. Accurate classification is critical for treatment planning and patient outcomes. Methods This study develops a computer-assisted diagnosis system for non-small cell lung cancer histology classification, utilizing th...

Brain tumors are abnormal growths of brain cells that can be benign (non-tumor) or malignant (tumor). These tumors can arise from different types of brain cells and occur in various brain regions. Timely detection is crucial for reducing the severity and improving prognosis. However, the traditional human examination suffers in early tumor detectio...

Electronic health records (EHR) are essential for making informed patient care decisions., but missing data can hinder decision-making. This study addresses the issue of missing data, specifically under the Missing at Random (MAR) mechanism, which is common in real-world datasets. While statistical methods are traditionally used for data imputation...

Dyslexia, a neurodevelopmental disorder, significantly impacts the learning ability of young children, often going undetected until later stages of education. Early detection of this disease is essential so that the impact can be significantly reduced by prompt intervention. But because of the reliance on labour-intensive procedures and limited sca...

Introduction Mobile devices have become an integral part of our digital lives, facilitating various tasks and storing a treasure trove of sensitive information. However, as more people utilize mobile devices, sophisticated cyber threats are emerging to elude traditional security measures. Method The use of evasion techniques by malicious actors pr...

Histopathological image analysis is a specialised area of medical imaging that involves the careful examination and interpretation of tissue samples to diagnose and investigate diseases. We begin by reviewing the traditional methods of histopathological image analysis and their limitations, setting the stage for the necessity of computational appro...

In the realm of medical datasets, particularly when considering diabetes, the occurrence of data incompleteness is a prevalent issue. Unveiling valuable patterns through medical data analysis is crucial for early and precise medical predictions. However, the quality of data and the proper handling of missing data hold significant significance. To a...

The design revolutionizes medication management with its intelligent features, ensuring accuracy, convenience, and patient safety. The innovative design transforms healthcare delivery, ensuring better adherence and improved outcomes.

Dyslexia is a complex learning disorder that affects neurological nerves in the brain and makes reading and writing difficult; therefore, early diagnosis for effective interventions becomes important. This study demonstrates how quickly dyslexia can be identified by introducing an advanced convolutional neural network model developed for detecting...

Background Feature selection is a vital process in data mining and machine learning approaches by determining which characteristics, out of the available features, are most appropriate for categorization or knowledge representation. However, the challenging task is finding a chosen subset of elements from a given set of features to represent or ext...

This chapter analyzes the relationships that cities have with digital technologies. "Smart Cities" are at the crossroads between the development of information and communication technologies in the city and the affirmation of a new paradigm of sustainable urban development. To assess the social impact of smart cities on citizens, an empirical study...

Medical imaging informatics play an important role in the effectiveness of present-day healthcare systems. Advancement of artificial intelligence, big data analytics, and internet of things technologies contribute greatly to various healthcare applications. Artificial intelligence techniques are contributing to improvements with traditionally human...

Generating data at an abundant scale has become a boon nowadays, as we see the shining side of its features and practicality but, data quality, integrating it with other physical, cloud systems, or storing this data could be impenetrable. Every sector including finance, retail, government, and technology produces giant lofts of data every year. But...

Artificial intelligence (AI) has the potential to help diagnose autism, a neurodevelopmental condition that affects communication, social interaction, and behaviour, which is often diagnosed through clinical observation and standardised assessments. This chapter explores different methods and methodologies that are commonly used to identify and tre...

Routing and security are critical considerations when designing a communication network for Flying Adhoc Networks (FANET). However, the rapid topological changes and high mobility of aerial vehicles make it difficult to maintain a stable network. Moreover, cross-layer routing is required, as it makes the best routing decisions by using dependence p...

We introduce the Multi-objective Java Macaque Algorithm for tackling complex multi-objective optimization (MOP) problems. Inspired by the natural behavior of Java Macaque monkeys, the algorithm employs a unique selection strategy based on social hierarchy, with multiple search agents organized into multi-group populations. It includes male replacem...

This provides remarkable image recognition, ensuring precise identification of even the tiniest hemorrhages in medical images. Built on a scalable architecture, this device seamlessly integrates into healthcare networks, accommodating facilities of all sizes and adapting to the ever-evolving demands of the medical field.

Atrial fibrillation easily leads to stroke, cerebral infarction and other complications, which will seriously harm the life and health of patients. Traditional deep learning methods have weak anti-interference and generalization ability. Therefore, we propose a new-fashioned deep residual-dense network via bidirectional recurrent neural network (RN...

Cloud computing is the most widely adapted computing model to process scientific workloads in remote servers accessed through the internet. In the IaaS cloud, the virtual machine (VM) is the execution unit that processes the user workloads. Virtualization enables the execution of multiple virtual machines (VMs) on a single physical machine (PM). Vi...

The objective is to print the living tissues of the patients from a computer model and create totally functional human skin.

In itemset mining, the two vital goals that must be resolved from a multi-objective perspective are frequency and utility. To effectively address the issue, researchers have placed a great deal of emphasis on achieving both objectives without sacrificing the quality of the solution. In this work, an effective itemset mining method was formulated fo...

This article discusses the importance of cross-platform UX/UI designs and frameworks and their effectiveness in building web applications and websites. Third-party libraries (TPL) and plug-ins are also emphasized, as they can help developers quickly build and compose applications. However, using these libraries can also pose security risks, as a vu...

Artificial Intelligence (AI) integrated with Blockchain distributed ledger technology (BDLT) has become the most attractive research area in the domain of renewable energy and related power automations. However, the increased use of renewable energy-enabled devices raised various challenging problems, such as smart grid-based control management, po...

The central remote servers are essential for storing and processing data for cloud computing evaluation. However, traditional systems need to improve their ability to provide technical data security solutions. Many data security challenges and complexities await technical solutions in today's fast-growing technology. These complexities will not be...

Functional Magnetic Resonance Imaging (fMRI) is the popular technique where it is possible to capture neural activity in brain regions when subjected to different stimuli. However, due to fMRI datasets’ high dimensional and sparse nature, the best features’ selection plays an essential role in providing the best classification accuracy in fMRI mode...

Knee osteoarthritis is a challenging problem affecting many adults around the world. There are currently no medications that cure knee osteoarthritis. The only way to control the progression of knee osteoarthritis is early detection. Currently, X-ray imaging is a central technique used for the prediction of osteoarthritis. However, the manual X-ray...

This article addresses the problem of converting a single-objective combinatorial problem into a multi-objective one using the Pareto front approach. Although existing algorithms can identify the optimal solution in a multi-objective space, they fail to satisfy constraints while achieving optimal performance. To address this issue, we propose a mul...

The degree of openness of the socially aware recommendation systems and the possibility of the attackers injecting vast numbers of fake profiles biases the prediction of the system. Most classical shilling attack discovery mechanisms rely on artificially derived features, generally determined from user-generated data. Moreover, these baseline appro...

In the realm of image processing and pattern recognition, writing with gestures in the air has grown in popularity and difficulty over the past few years. It contributes significantly to the creation of automation processes and can improve human-machine communication in a range of systems. Many studies focus on cutting-edge methods and techniques t...

The rapid progress in emerging communication technologies, enhancing the next generation visible light communication (VLC) and passive optical network (PON) as a promising candidate for highly demanding sophisticated services and applications. The next generation hybrid PONVLC network provides high data rate, capacity, security, mobility, flexibili...

The human brain is made up of millions of neurons, each of which plays a crucial part in directing the behaviour of the human body in response to internal/external motor-impulses. These neurons will act as data conduits between the brain and the body. Studying brain signals or images may help us better understand the cognitive behaviour of the brai...

Breast cancer is one of the most common cancer types. This is the second-leading cause of cancer-related death in women. It ranked 2 nd according to available data lung cancers is the only one causing more causalities. It’s critical to receive a breast cancer diagnosis quickly. The MIAS data set is used in this study to examine machine learning-bas...

One of the medical field’s most researched issues is cancer diagnosis. Many researchers have concentrated on performance enhancement and achieving successful outcomes. One of the most lethal forms of cancer is breast cancer. A significant issue in cancer diagnosis research is the diagnosis of this cancer. A kind of artificial intelligence called ma...

In the livestock industry, wireless sensor networks (WSNs) play a significant role in monitoring many fauna health statuses and behaviors. Energy preservation in WSNs is considered one of the critical, complicated tasks since the sensors are coupled to constrained resources. Therefore, the clustering approach has proved its efficacy in preserving e...

Deep learning has stretched out its roots even more in our daily lives. As a society, we are witnessing small changes in lifestyle such as self-driving cars, Google Assistant, Netflix recommendations, and spam email detection. Similarly, deep learning is also evolving in healthcare, and today many doctors often use it more comfortably. Using deep l...

Deep learning has stretched out its roots even more in our daily lives. As a society, we're witnessing small changesin lifestyle such as self-driving cars, Google Assistant, Netflix recommendations, and spam email detection. Similarly, deep learning is also evolving in healthcare, and today many doctors often use it more comfortably. Using deep lea...

Resting-state functional connectivity has been widely used for the past few years to forecast Alzheimer’s disease (AD). However, the conventional correlation calculation does not consider different frequency band features that may hold the brain atrophies’ original functional connectivity relationships. Previous works focuses on low-order neurodyna...

Vehicle-to-everything (V2X) in networks is a communication technology that allows vehicles to communicate with their surroundings. Traffic congestion and unawareness of the travel of emergency vehicles (EVs) lead to delays in reaching the destination of the EV. In order to overcome this time delay, we propose a jitter-to-highly reliable (J2H) appro...

This paper proposes a noble image segment technique to differentiate between large malignant cells called centroblasts vs. centrocytes. A new approach is introduced, which will provide additional input to an oncologist to ease the prognosis. Firstly, a H&E-stained image is projected onto L*a*b* color space to quantify the visual differences. Second...

The Internet of Medical Things (IoMT) is an extended version of the Internet of Things (IoT). It mainly concentrates on the integration of medical things for servicing needy people who cannot get medical services easily, especially rural area people and aged peoples living alone. The main objective of this work is to design a real time interactive...

The framework for aqua farming database collection and the real-time monitoring of different working functions of aqua farming are essential to enhance and digitalize aqua farming. Data collection and real-time monitoring are attained using cutting-edge technologies, and these cutting-edge technologies are useful for the conservation and advancemen...

Fog computing is an emerging research domain to provide computational services such as data transmission, application processing and storage mechanism. Fog computing consists of a set of fog server machines used to communicate with the mobile user in the edge network. Fog is introduced in cloud computing to meet data and communication needs for Int...

Parkinson’s disease (PD) is a neurodegenerative disease that impacts the neural, physiological, and behavioral systems of the brain, in which mild variations in the initial phases of the disease make precise diagnosis difficult. The general symptoms of this disease are slow movements known as ‘bradykinesia’. The symptoms of this disease appear in m...

Detection of intrusions is a system that is competent in detecting cyber-attacks and network anomalies. A variety of strategies have been developed for IDS so far. However, there are factors that they lack in performance, creating scope for further research. The current trend shows that the Deep Learning (DL) technique has been proven better than t...

The swarm-based Artificial Bee Colony (ABC) algorithm has a significant range of applications and is competent, compared to other algorithms, regarding many optimization problems. However, the ABC’s performance in higher-dimension situations towards global optima is not on par with other models due to its deficiency in balancing intensification and...

Recent innovations in digital image capturing techniques facilitate the capture of stationary and moving objects. The images can be easily captured via high-end digital cameras, mobile phones and other handheld devices. Most of the time, captured images vary compared to actual objects. The captured images may be contaminated by dark, grey shades an...

All witnessed the terrible effects of the COVID-19 pandemic on the health and work lives of the population across the world. It is hard to diagnose all infected people in real time since the conventional medical diagnosis of COVID-19 patients takes a couple of days for accurate diagnosis results. In this paper, a novel learning framework is propose...

Economic Load Dispatch (ELD) belongs to a non-convex optimization problem that aims to reduce total power generation cost by satisfying demand constraints. However, solving the ELD problem is a challenging task, because of its parity and disparity constraints. The Pigeon-Inspired Optimizer (PIO) is a recently proposed optimization algorithm, which...

Unmanned Aerial Vehicle (UAV) integrated Heterogeneous Network (HetNet) is currently considered as one of the promising technologies. This technology helps in fulfilling high demands of bandwidth, volume, and range as per user needs. In this paper, the work is carried out by authors to assure high security for the users in such a network by incorpo...

A Wireless Sensor Network (WSN) is a group of autonomous sensors that are distributed geographically. However, sensor nodes in WSNs are battery-powered, and the energy drainage is a significant issue. The clustering approach holds an imperative part in boosting the lifespan of WSNs. This approach gathers the sensors into clusters and selects the cl...

Nowadays, much research leverages the clustering to mine commercial patterns from data in enterprise systems. However, previous methods cannot fully consider local structures and global topology of data, which may cause the degradation of clustering performance. To address the challenges, a deep multimodal adversarial cycle-consistent network (DMAC...

According to United Nations (UN) 2030 agenda, the pollution detection system needs to be improved for the establishment of fresh air to obtain healthy life of living things. There are many reasons for the pollution and one of the reasons for pollution is from the emissions of the vehicles. Currently digital technologies such as the Internet of Thin...

Vehicle identification and classification are some of the major tasks in the areas of toll management and traffic management, where these smart transportation systems are implemented by integrating various information communication technologies and multiple types of hardware. The currently shifting era toward artificial intelligence has also motiva...

The nurse scheduling problem (NSP) is an NP-Hard combinatorial optimization scheduling problem that allocates a set of shifts to the group of nurses concerning the schedule period subject to the constraints. The objective of the NSP is to create a schedule that satisfies both hard and soft constraints suggested by the healthcare management. This wo...

The advent of fog computing as an extension of cloud-enabling technology has moved from the hub of the internet framework to the unmanned aerial vehicle (UAV)-enabled control and management of drone-based data. The key objectives are to improve the computation and processing of drone-based resource constraints and deliver the data to the outsourced...

Dyslexia is among the most common neurological disorders in children. Detection of dyslexia therefore remains an important pursuit for the research works across various domains which is illustrated by the plethora of work presented in diverse scienti c articles. e work presented herein attempted to utilize the potential of a uni ed gaming test of s...

Twitter is a platform where people express their opinions and come with regular updates. At present, it has become a source for many organizations where data will be extracted and then later analyzed for sentiments. Many machine learning algorithms are available for twitter sentiment analysis which are used for automatically predicting the sentimen...

Medical imaging informatics plays an important role in the effectiveness of present-day radiology in healthcare systems. The advancement of artificial intelligence (AI), big data analytics, and the Internet of Things technologies greatly contribute to various healthcare applications. Artificial intelligence techniques have replaced human-based syst...

Authentication, authorization, and data access control are playing major roles in data security and privacy. The proposed model integrated the multi-factor authentication–authorization process with dependable and non-dependable factors and parameters based on providing security for tenants through a hybrid approach of fully homomorphic encryption m...

Deep learning-based machine learning models have shown significant results in speech recognition and numerous vision-related tasks. The performance of the present speech-to-text model relies upon the hyperparameters used in this research work. In this research work, it is shown that convolutional neural networks (CNNs) can model raw and tonal speec...

Twitter is a platform where people express their opinions and come with regular updates. At present, it has become a source for many organizations where data will be extracted and then later analyzed for sentiments. Many machine learning algorithms are available for twitter sentiment analysis which are used for automatically predicting the sentimen...

There are several popular books published in Healthcare Computational Informatics like Computational Bioengineering and Bioinformatics (2020), Springer; Health Informatics (2017), Springer; Health Informatics Vision: From Data via Information to Knowledge (2019), IOS Press; Data Analytics in Biomedical Engineering and Healthcare (2020), Elsevier. H...

The useful constructs in terms of dynamic features of programming languages bring the developers convenience and flexibility, but can also lead to the risks in the software maintenance. Evaluating whether the use of such features affects the maintenance can be significant for both practitioners as well as researchers, yet a very little amount of wo...

The rapid development of technology has empowered us to achieve resilient infrastructure to establish a sustainable ecosystem. The construction site is one of the highest risk jobs for accident-related fatalities and injuries globally. From the previous studies, it is concluded that untrained or inexperienced workers were responsible for 40% of wor...

Remote sensing image object detection is widely used in civil and military fields. The important task is to detect objects such as ships, planes, airports, harbours and so on, and then it can obtain object category and position information. It is of great significance to use remote sensing images to observe the densely arranged and directional targ...

The healthcare system is literally losing patients due to improper diagnosis, accidents, and infections in hospitals alone. To address these challenges, the authors are proposing the drug prediction model that will act as informative guide for patients and help them for taking right medicines for the cure of particular disease. In this chapter, the...

Artificial Intelligence and Blockchain technologies have infiltrated all areas of our lives, from manufacturing to healthcare systems. Cybersecurity is an industry that has been significantly affected by these technologies and in future we expect more advancement in this industry by the application of these technologies. Artificial Intelligence and...

In the medical field, due to their economic and clinical benefits, there is a growing interest in minimally invasive surgeries and microscopic surgeries. These types of surgeries are often recorded during operations, and these recordings have become a key resource for education, patient disease analysis, surgical error analysis, and surgical skill...