Ibrahim Abaker Targio Hashem

• Doctor of Philosophy
• Professor (Assistant) at University of Sharjah

Meta-heuristic algorithms aim to achieve near-optimal solutions to complex optimization problems by taking inspiration from nature. The last three decades have seen an increased focus on the use of meta-heuristics in optimization, with the direct result that a great number of new meta-heuristics have been created to tackle challenging real-world si...

The development of computer technology has revolutionized how people live and interact in society. The Internet of Things (IoT) has enabled the development of the Internet of Medical Things (IoMT) to transform healthcare delivery. Artificial intelligence has been used to improve the IoMT. Despite the significance of bibliometric analysis in a resea...

The remarkable miniaturization of Internet of Things (IoT)-based systems and the rise of distributed intelligence are promising research paradigms in the design of smart cities. IoT and distributed intelligence are conjoined. On the one hand, IoT provides a digital connection to everyday physical devices, and on the other hand, distributed intellig...

Backpropagation neural networks are commonly utilized to solve complicated issues in various disciplines. However, optimizing their settings remains a significant task. Traditional gradient-based optimization methods, such as stochastic gradient descent (SGD), often exhibit slow convergence and hyperparameter sensitivity. An adaptive stochastic con...

Based on the results of this research, a new method for separating Arabic offline text is presented. This method finds the core splitter between the “Middle” and “Lower” zones by looking for sharp character degeneration in those zones. With the exception of script localization and the essential feature of determining which direction a starting poin...

Social media have become very popular as the number of users, organizations and research associated continue to increase rapidly. As such, user profiling becomes prominent as it enables the extraction of information and knowledge pertaining to users from their profiles. There is a growing number of current literatures related to social media and us...

In the last decade, the volume of semantic data has increased exponentially, with the number of Resource Description Framework (RDF) datasets exceeding trillions of triples in RDF repositories. Hence, the size of RDF datasets continues to grow. However, with the increasing number of RDF triples, complex multiple RDF queries are becoming a significa...

The recent proliferation of ubiquitous computing technologies has led to the emergence of urban computing that aims to provide intelligent services to inhabitants of smart cities. Urban computing deals with enormous amounts of data collected from sensors and other sources in a smart city. In this article, we investigated and highlighted the role of...

Air pollution has a substantial negative impact on human wellbeing and health. Cardiorespiratory mortality is one of the primary effects of air pollution. In this study, we provide analysis of air pollution, cardiorespiratory mortality and the cardiorespiratory mortality is predicted based on air pollution using tree-based ensemble models. The tree...

New technologies drive educational shifts, transforming offline to online learning. This study investigates e-learning and cloud computing integration to understand synergies and their potential impact. The study addresses two primary research questions: the influence of e-learning on factors like architecture, software, performance, security, hard...

Since the recent outbreak of COVID-19, many scientists have started working on distinct challenges related to mining the available large datasets from social media as an effective asset to understand people’s responses to the pandemic. This study presents a comprehensive social data mining approach to provide in-depth insights related to the COVID-...

A growing amount of research conducted in digital, cooperative with advances in Artificial Intelligence, Computer Vision including Machine learning, has managed to the advance of progressive techniques that aim to detect and process affective information contained in multi-modal evidences. This research intends to bring together for theoreticians a...

Air pollution (AP) has risen as one of the biggest challenges of the 21st century, and it has adverse health effects for humans. The effects of health effects, including cardiorespiratory health effects of various air pollutants, are well documented. This research work presents the modeling and analysis of cardiorespiratory mortality attributed to...

Due to the quick actions of technology, a complicated and huge volume of data deriving from biological sciences are generated which makes string matching patterns a challenging task. This direction has the aim to make the utilization of an individual algorithm for string searching nearly ineffectual as the number of tries and the number of observat...

The Internet of Vehicles (IoV) is a developing technology attracting attention from the industry and the academia. Hundreds of millions of vehicles are projected to be connected within the IoV environments by 2035. Each vehicle in the environment is expected to generate massive amounts of data. Currently, surveys on leveraging deep learning (DL) in...

After the recent outbreak of COVID-19, researchers have risen working on several challenges related to the mining of social data to learn about people’s reactions to the epidemic. Recent studies have largely focused on extracting current themes and inferring broad attitudes, with a particular emphasis on the English language. This study presents va...

Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. One of the major effects of air pollution on health is hospitalizations associated with air pollution. Recently, the estimation and prediction of air pollution–based hospitalization is carried out using artifici...

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learning models and the Internet of Things (IoT) techno...

The COVID-19 pandemic has emerged as the world's most serious health crisis, affecting millions of people all over the world. The majority of nations have imposed nationwide curfews and reduced economic activity to combat the spread of this infectious disease. Governments are monitoring the situation and making critical decisions based on the daily...

The COVID-19 pandemic has emerged as the world's most serious health crisis, affecting millions of people all over the world. The majority of nations have imposed nationwide curfews and reduced economic activity to combat the spread of this infectious disease. Governments are monitoring the situation and making critical decisions based on the daily...

In gastronomic tourism, food is viewed as the central tourist attraction. Specifically, indigenous food is known to represent the expression of local culture and identity. To promote gastronomic tourism, it is critical to have a model for the food business analytics system. This research undertakes an empirical evaluation of recent transfer learnin...

Emerging tools such as Game Based Assessments have been valuable in talent screening and matching soft skills for job selection. However, these techniques/models are rather stand alone and are unable to provide an objective measure of the effectiveness of their approach leading to mismatch of skills. In this research study, we are proposing a Theor...

Deep learning (DL) algorithms have been widely used in various security applications to enhance the performances of decision-based models. Malicious data added by an attacker can cause several security and privacy problems in the operation of DL models. The two most common active attacks are poisoning and evasion attacks, which can cause various pr...

As a result of an increase in the human popula-tion globally, traffic congestion in the urban area is becoming worse, which leads to time-consuming, waste of fuel, and, most importantly, the emission of pollutants. Therefore, there is a need to monitor and estimate traffic density. The emergence of an automatic traffic management system allows us t...

The purpose of smart city is to enhance the optimal utilization of scarce resources and improve the resident’s quality of live. The smart cities employed Internet of Things (IoT) to create a sustainable urban life. The IoT devices such as sensors, actuators, and smartphones in the smart cities generate data. The data generated from the smart cities...

Air pollution has a serious and adverse effect on human health, and it has become a risk to human welfare and health throughout the globe. In this paper, we present the modeling and analysis of air pollution and cardiorespiratory hospitalization. This study aims to investigate the association between cardiorespiratory hospitalization and air pollut...

Online customer reviews have become a popular source of information that influences the purchasing decisions of many prospective customers. However, the rapidly increasing volume of online reviews presents a problem of information overload, which makes it difficult for customers to determine the quality of the reviews. This study defines the helpfu...

PurposeThe classification of mammographic images is an important process in Computer-aided diagnosis (CADx) system for an automatic detection of breast cancer. CADx helps radiologists in providing a second opinion for an accurate diagnosis. Therefore, an intelligent classifier is required in classifying suspicious areas in digital mammograms. A num...

Air pollution is one of the significant causes of mortality and morbidity every year. In recent years, many researchers have focused their attention on the associations of air pollution and health. Air pollution data and health data is used in these studies and feature engineering is used to create and optimize the air quality and health features....

Geographic information system (GIS) is designed to generate maps, manage spatial datasets, perform sophisticated “what if” spatial analyses, visualize multiple spatial datasets simultaneously, and solve location-based queries. The impact of big data is in every industry, including the GIS. The location-based big data also known as big spatial data...

The domain of underwater wireless sensor networks (UWSNs) had received a lot of attention recently due to its significant advanced capabilities in the ocean surveillance, marine monitoring and application deployment for detecting underwater targets. However, the literature have not compiled the state-of-the-art along its direction to discover the r...

Air pollution is strongly tied to climate change. Industrialization and fossil fuel combustion are the main contributors leading to climate change, also being significant sources of air pollution. Malaysia is a developing country with a focus on industrialization. The preference of using private cars is a common practice in Malaysia, resulting in t...

span>Feature engineering (FE) is one of the most important steps in data science research. FE provides useful features to be used later in the study. Due to climate change, the research focus is moving towards air quality estimation and the impacts of air pollution on health in Malaysia. Malaysia has 66 air quality monitoring (AQM) stations, and th...

Recent trends in big data have shown that the amount of data continues to increase at an exponential rate. This trend has inspired many researchers over the past few years to explore new research direction of studies related to multiple areas of big data. The widespread popularity of big data processing platforms using MapReduce framework is the gr...

Dear Editor: This manuscript is already online in techrxiv (https://doi.org/10.36227/techrxiv.12376427.v1), and the co-authors are not correctly associated with the published preprint so we are submitting this again by associating the co-authors. We have also improved the similarity report, the similarity index is 11% of this submission. Thank you....

The increasing volume of online reviews and the use of review platforms leave tracks that can be used to explore interesting patterns. It is in the primary interest of businesses to retain and improve their reputation. Reviewers, on the other hand, tend to write reviews that can influence and attract people’s attention, which often leads to deliber...

Recent technological developments and the availability of enormous amounts of real-time data have played a vital role in the expansion, evolution, and success of smart city projects. Smart data can be used in a variety of smart city applications, but difficulties in managing such data are pushing smart cities toward the adoption of data management...

With the recent advancement of Web 2.0 and the popularity of social media platforms, the volume of User Generated Content (UGC) is rising explosively. Online reviews are rapidly growing and a popular source of UGC, which help customers in evaluating the quality of product and making purchase decisions. However, distilling the required information f...

Social networking websites have been widely used for political awareness and campaigns. With the increasing reliance of political parties and supporters on social media, interesting patterns can be extracted by analyzing social media profiles. The previous approaches perform political analysis used social media data mainly focused on analyzing only...

In recent years, Internet of Things (IoT) has attracted significant attention because of its wide range of applications in various domains. However, security is a growing concern as users of small devices in an IoT network are unable to defend themselves against reactive jamming attacks. These attacks negatively affect the performance of devices an...

Testing and debugging are very important tasks in software development. Fault localization is a very critical activity in the debugging process and also is one of the most difficult and time-consuming activities. The demand for effective fault localization techniques that can aid developers to the location of faults is high. In this paper, a fault...

With easy access to the Internet and the popularity of online review platforms, the volume of crowd-sourced reviews is continuously rising. Many studies have acknowledged the importance of reviews in making purchase decisions. The consumer's feedback plays a vital role in the success or failure of a business. The number of studies on predicting hel...

The journey of data from the state of being valueless to valuable has been possible due to powerful analytics tools and processing platforms. Organizations have realized the potential of data, and they are looking far ahead from the traditional relational databases to unstructured as well as semi-structured data generated from heterogeneous sources...

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big da...

The blockchain is a technology which accumulates and compiles data into a chain of multiple blocks. Many blockchain researchers are adopting it in multiple areas. However, there are still lacks bibliometric reports exhibiting the exploration of an in-depth research pattern in blockchain. This paper aims to address that gap by analyzing the widespre...

With the collection of massive amounts of data every day, big data analytics has emerged as an important trend for many organizations. These collected data can contain important information that may be key to solving wide-ranging problems, such as cyber security, marketing, healthcare, and fraud. To analyze their large volumes of data for business...

Off late, the ever increasing usage of a connected Internet‐of‐Things devices has consequently augmented the volume of real‐time network data with high velocity. At the same time, threats on networks become inevitable; hence, identifying anomalies in real time network data has become crucial. To date, most of the existing anomaly detection approach...

During program testing, software programs may be discovered to contain multiple faults. Multiple faults in a program may reduce the effectiveness of the existing fault localization techniques due to the complex relationship between faults and failures in the presence of multiple faults. In an ideal case, faults are isolated into fault-focused clust...

Approximately 2.5 quintillion bytes of data are emitted on a daily basis, and this has brought the world into the era of “big data”. ANN are known for their effectiveness and efficiency for small datasets, and this era of big data has posed a challenge to the big data analytics using ANN. Recently, much research effort has been devoted to the appli...

Recent trends in big data have shown that the amount of data continues to increase at an exponential rate. This trend has inspired many researchers over the past few years to explore new research direction of studies related to multiple areas in big data. Hadoop is one of the most popular platforms for big data, thus, Hadoop MapReduce is used to st...

The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to eff...

Credit card fraud detection is growing due to the increase and the popularity of online banking. The need to detect fraudulent within credit card has become as a serious problem among the online shoppers. The multi-layer perceptron (MLP) machine learning algorithm is used to identify the credit card fraud. We have used the various parameters of the...

The purpose of this study is to understand the Final Year Project System existences and to find improvement in their workflow process. The observation made was based on a case-study workflow conducted by the final year student. In this paper the proposed systems emit issues of bias and transparency of data involving different examiners and the lack...

The explosive growth of smart objects and their dependency on wireless technologies for communication increases the vulnerability of Internet of Things (IoT) to cyberattacks. Cyberattacks faced by IoT present daunting challenges to digital forensic experts. Researchers adopt various forensic techniques to investigate such attacks. These techniques...

The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifica...

Big data analytics has recently emerged as an important research area due to the popularity of the Internet and the advent of the Web 2.0 technologies. Moreover, the proliferation and adoption of social media applications have provided extensive opportunities and challenges for researchers and practitioners. The massive amount of data generated by...

The increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include r...

Data generation has increased drastically over the past few years due to the rapid development of Internet-based technologies. This period has been called the big data era. Big data offer an emerging paradigm shift in data exploration and utilization. The MapReduce computational paradigm is a well-known framework and is considered the main enabler...

Metaheuristic algorithms have proven to be eeective, robust, and eecient in solving real world optimization, clustering, forecasting, classiication, and other engineering problems. e emergence of extraordinary very large scale data being generated from various sources such as the web, sensors, and social media has led the world to the era of big da...

The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to eff...

The unprecedented proliferation of miniaturized sensors and intelligent communication, computing, and control technologies have paved the way for the development of the Industrial Internet of Things. The IIoT incorporates machine learning and massively parallel distributed systems such as clouds, clusters, and grids for big data storage, processing...

The unabated flurry of research activities dedicated to gaining business insights from a flood of data generated by heterogeneous mobile sources, such as the Internet of Vehicles, sensors, and smartphones, has instigated a new research domain called MBD. At the core of this mobile environment, scalability, cost effectiveness, reliability, analytics...

The explosive growth in the number of devices connected to the Internet of Things (IoT) and the exponential increase in data consumption only reflect how the growth of big data perfectly overlaps with that of IoT. The management of big data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency,...

The detection and recognition and then conversion of the characters in an image into a text are called optical character recognition (OCR). A distinctive type of OCR is used to process Arabic characters, namely, Arabic OCR. OCR is increasingly used in many applications where this process is preferred to automatically perform a process without human...

Image pattern recognition in the field of big data has gained increasing importance and attention from researchers and practitioners in many domains of science and technology. This paper focuses on the usage of image pattern recognition for big data applications. In this context, the taxonomy of image pattern recognition and big data is revealed. T...

Recent years have witnessed tremendous growth in the number of smart devices, wireless technologies, and sensors. In the foreseeable future, it is expected that trillions of devices will be connected to the Internet. Thus, to accommodate such a voluminous number of devices, scalable, flexible, interoperable, energy-efficient, and secure network arc...

Voluminous amounts of data have been produced, since the past decade as the miniaturization of Internet of things (IoT) devices increases. However, such data are not useful without analytic power. Numerous big data, IoT, and analytics solutions have enabled people to obtain valuable insight into large data generated by IoT devices. However, these s...

Tremendous advancements in heterogeneous communication technologies have enabled smart cities objects to interact with each other while ensuring network connectivity. However, these communication technologies cannot provide flawless connectivity in smart cities due to the coexistence of thousands of devices, which brings about several problems. In...

Big data is a potential research area receiving considerable attention from academia and IT communities. In the digital world, the amounts of data generated and stored have expanded within a short period of time. Consequently, this fast growing rate of data has created many challenges. In this paper, we use structuralism and functionalism paradigms...

The expansion of big data and the evolution of Internet of Things (IoT) technologies have played an important role in the feasibility of smart city initiatives. Big data offer the potential for cities to obtain valuable insights from a large amount of data collected through various sources, and the IoT allows the integration of sensors, radio-frequ...

Cloud computing has emerged as a powerful technology to perform massive scale and complex computing that eliminates the need for maintaining expensive computing hardware, dedicated space and software. Moreover, there has been tremendous growth in the scale of the data or “Big Data” that are generated by the use of cloud computing. Big data is a cha...

The continuous increase in computational capacity over the past years has produced an overwhelming flow of data or big data, which exceeds the capabilities of conventional processing tools. Big data signify a new era in data exploration and utilization. The MapReduce computational paradigm is a major enabler for underlying numerous big data platfor...

The rapid growth of emerging applications and the evolution of cloud computing technologies have significantly enhanced the capability to generate vast amounts of data. Thus, it has become a great challenge in this big data era to manage such voluminous amount of data. The recent advancements in big data techniques and technologies have enabled man...

2nd International Conference on Big Data Analysis and Data Mining, J Data Mining Genomics Proteomics

O ver the past few years, the continuous increase in computational capacity has produced an overwhelming flow of data or big data, which exceeds the capabilities of conventional processing tools. Big data offer a new era in data exploration and utilization. The major enabler for underlying many big data platforms is certainly the MapReduce computat...