Iyad Abu Doush

• Ph.D. Computer Science
• Professor (Full) at Yarmouk University

Aim and objective This study explored the relationship between air pollution and rheumatoid arthritis (RA), focusing on how specific air quality components affect RA disease activity as measured by Disease Activity Score 28 (DAS28). Methods The research involved Data were obtained from six air‐monitoring stations across Kuwait, and RA patient info...

Background Rheumatoid arthritis (RA) is a common condition treated with biological disease-modifying anti-rheumatic medicines (bDMARDs). However, many patients exhibit resistance, necessitating the use of machine learning models to predict remissions in patients treated with bDMARDs, thereby reducing healthcare costs and minimizing negative effects...

This paper addresses the pressing need to evaluate the maturity and performance metrics of generative AI tools dedicated to accessibility in product development. The problem lies in the lack of standardized methods for assessing the maturity of generative AI tools tailored to accessibility needs and the absence of universally accepted performance m...

The multilayer perceptron (MLP) neural network is a widely adopted feedforward neural network (FNN) utilized for classification and prediction tasks. The effectiveness of MLP greatly hinges on the judicious selection of its weights and biases. Traditionally, gradient-based techniques have been employed to tune these parameters during the learning p...

The quality of the output produced by the multi-layer perceptron neural network depends on the careful selection of its weights and biases. The gradient descent technique is commonly used for choosing MLP’s optimal configuration, but it can suffer from being stuck in local optima and slow convergence toward promising regions in the search space. In...

This paper proposes a novel nature-inspired swarm-based optimization algorithm called elk herd optimizer (EHO). It is inspired by the breeding process of the elk herd. Elks have two main breeding seasons: rutting and calving. In the rutting season, the elk herd splits into different families of various sizes. This division is based on fighting for...

The Multi-Layer Perceptron Neural Network (MLP) is the commonly used Feedforward Neural Network (FNN) for tackling classification and prediction problems. The efficiency of MLP relies on the appropriate selection of its weights and biases. Usually, a gradient-based technique is used for tuning the selection of these parameters during the learning p...

Brain Computer Interface (BCI) has demonstrated significant effectiveness in optimizing the usability of mobile applications, particularly in the realm of mobile gaming. With the increasing popularity of video games, they offer an opportune platform for exploring novel control interfaces for mobile devices. This paper introduces the Mobile Gaming E...

Air pollution poses a serious threat to public health and for the environment, thus predicting air quality is very crucial for the health and well-being of individuals and the environment. Economic development drives rapid industrialization and urbanization, which are significant sources of air pollution in developing countries. Kuwait’s rapid urba...

Equilibrium optimizer (EO) is a recent optimization method inspired by the physical equation of the mass balance that provides the conservation of mass entering, leaving, and generating in a control volume and the system always reaches an equilibrium point. It is a fast-growing algorithm that has been adopted by several researchers due to its succe...

This paper proposes binary versions of artificial rabbits optimization (ARO) for feature selection (FS) with medical diagnosis data. ARO is a recent swarm-based optimization algorithm that mimics rabbits’ natural survival tactics and eating habits. It was modeled in an optimization context to tackle optimization problems of continuous search spaces...

The success of the supervised learning process for feedforward neural networks, especially multilayer perceptron neural network (MLP), depends on the suitable configuration of its controlling parameters (i.e., weights and biases). Normally, the gradient descent method is used to find the optimal values of weights and biases. The gradient descent me...

The success of the Multi-Layer Perceptron Neural Network (MLP) relies on carefully configuring its weights and biases to promising values. The gradient descent technique is usually used to select the optimal MLP configuration. Such a technique can stuck in local optima and its convergence towards promising regions in the search space is slow. Harri...

Web accessibility automatic evaluation tools (WAET) are used to evaluate the conformance of the web content to the web content accessibility guidelines (WCAG) success criteria (SC). This paper aims to identify performance criteria that can be used to compare between automatic web accessibility evaluation tools (WAET), determine which SC can be auto...

Software Fault Prediction (SFP) is an important process to detect the faulty components of the software to detect faulty classes or faulty modules early in the software development life cycle. In this paper, a machine learning framework is proposed for SFP. Initially, pre-processing and re-sampling techniques are applied to make the SFP datasets re...

This paper reviews the latest versions and applications of sparrow search algorithm (SSA). It is a recent swarm-based algorithm proposed in 2020 rapidly grew due to its simple and optimistic features. SSA is inspired by the sparrow living style of foraging and the anti-predation behavior of sparrows. Since its establishment, it has been utilized fo...

The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from the hunting behavior of wolf packs. GWO’s appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable, flexible, and robust. Its efficacy has been demon...

The butterfly optimization algorithm (BOA) is a recent successful metaheuristic swarm-based optimization algorithm. The BOA has attracted scholars’ attention due to its extraordinary features. Such as the few adaptive parameters to handle and the high balance between exploration and exploitation. Accordingly, the BOA has been extensively adapted fo...

The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub. These two principles are mathematically modeled in the optimization context to handle local search, exploitation, and exploration search concepts. The LO is...

The COVID-19 pandemic increases the reliance on video conferencing applications for learning. Accessible video conferencing applications with good learning features can help people with visual impairment when they participate in online classes. This paper investigates the accessibility limitations and the available learning features of the top two...

This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer to tackle economic load dispatch (ELD) problems. ELD is an important problem in power systems that is tackled by finding the optimal schedule of the generation units that minimize fuel conceptions under a set of constraints. Due to the...

In this paper, the learning process of multilayer perceptron (MLP) neural network is boosted using hybrid metaheuristic optimization algorithms. Normally, the learning process in MLP requires suitable settings of its weight and bias parameters. In the original version of MLP, the gradient descent algorithm is used as a learner in MLP which suffers...

Bat-inspired algorithm (BA) is a robust swarm intelligence algorithm that finds success in many problem domains. The ecosystem of bat animals inspires the main idea of BA. This review paper scanned and analysed the state-of-the-art researches investigated using BA from 2017 to 2021. BA has very impressive characteristics such as its easy-to-use, si...

In this paper, a modified version of the Multi-objective Grey Wolf Optimizer (MGWO), known as linked-based GWO (LMGWO), is proposed for the Appliances Energy Scheduling Problem (AESP). The proposed LMGWO is utilized by combining the MGWO searching mechanism with a novel strategy, called neighbourhood selection strategy, to improve local exploitatio...

This paper proposes an island neighboring heuristics harmony search algorithm (INHS) to tackle the blocking flow-shop scheduling problem. The island model is used to diversify the population and thus enhance the algorithm performance. The proposed method distributes the individuals in the population into different islands or sub-population. Then th...

In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. Many FS-based swarm intelligence algorithms have been used to tackle FS. However, the door is st...

Since the start of the coronavirus 2019 (COVID-19) outbreak, governments across the world have mobilized to inform citizens on the virus spread details, nation-level processes, and best health measures and practices to be taken. A large percentage of the media posted through the COVID-19 crisis has been graphical, which raised the question of wheth...

The Coronavirus herd immunity optimizer (CHIO) is a new human-based optimization algorithm that imitates the herd immunity strategy to eliminate of the COVID-19 disease. In this paper, the coronavirus herd immunity optimizer (CHIO) is modified to tackle a discrete power scheduling problem in a smart home (PSPSH). PSPSH is a combinatorial optimizati...

In evolutionary computation, systematically structuring the population is used to manage the evolution process. Thus controlling the amount of diversity during the algorithm search. Island-based, hierarchical-based, and cellular automata are the most popular structured population models utilized for evolutionary algorithms to improve their diversit...

This article evaluates the accessibility computer laboratories, libraries, and web sites of five different institutions of higher education in Jordan. The evaluation is performed using a questionnaire and by expert visiting these institutions of higher education to check their accessibility according to a set of universal standard collected from th...

Intuitive user interface design is of utmost importance to mobile applications, especially when dealing with new technologies like Augmented Reality (AR). In this paper, a user study for evaluating AR 3D furniture arrangement mobile application user experience is presented. In our gesture design, we used one hand to ease the use of the application....

COVID‐19 is the disease evoked by a new breed of coronavirus called the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Recently, COVID‐19 has become a pandemic by infecting more than 152 million people in over 216 countries and territories. The exponential increase in the number of infections has rendered traditional diagnosis techni...

Feature selection is an essential stage in many data mining and machine learning and applications that find the proper subset of features from a set of irrelevant, redundant, noisy and high dimensional data. This dimensional reduction is a vital task to increase classification accuracy and thus reduce the processing time. An optimization algorithm...

In this paper, the β-hill climbing optimizer is hybridized with the flower pollination algorithm (FPA) as a local refinement operator for global optimization problems. The proposed method is called HyFPAβ-hc. Such hybridization aims to enhance the balance between exploration and exploitation processes during the search, thus improving the quality o...

In this review paper, JAYA algorithm, which is a recent population-based algorithm is intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. Initially, the optimization model and convergence characteristi...

People with communication impairment need an alternative communication channel to complete daily activities. Augmentative and alternative communication (AAC) systems can help provide a communication medium to support such users. The involvement of speech and language pathologists (SLPs) who work in rehabilitation centers can help develop better sol...

In this paper, a new nature-inspired human-based optimization algorithm is proposed which is called coronavirus herd immunity optimizer (CHIO). The inspiration of CHIO is originated from the herd immunity concept as a way to tackle coronavirus pandemic (COVID-19). The speed of spreading coronavirus infection depends on how the infected individuals...

DNA microarray technology is the fabrication of a single chip to contain a thousand genetic codes. Each microarray experiment can analyze many thousands of genes in parallel. The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate b...

Evolutionary multi-objective optimization (EMO) refers to the domain in which an evolutionary algorithm is applied to tackle an optimization problem with multiple objective functions. The literature is rich with many approaches proposed to solve multi-objective problems including the NSGA-II, MOEA/D, and MOPSO algorithms. The proposed approaches in...

The purpose of the International Conference on Computer-Human Interaction Research and Applications (CHIRA) is to bring together professionals, academics and students who are interested in the advancement of research and practical applications of interaction design & human-computer interaction. Five parallel tracks will be held, covering different...

This paper proposes an efficient version of artificial bee colony (ABC) algorithm based on the island model concepts. The new version is called the island artificial bee colony (iABC) algorithm. It uses the structured population concept by applying the island model to improve the diversification capabilities of ABC. In the island model, the populat...

Harmony Search Algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algori...

In this paper, a new nature-inspired human-based optimization algorithm is proposed which called Coronavirus Herd Immunity Optimizer (CHIO). The inspiration of CHIO is originated from the herd immunity concept as a way to tackle coronavirus pandemic (COVID-19). The speed of spreading coronavirus infection depends on how the infected individuals dir...

The advancements in Internet of things (IoT) technology is quickly transforming the world into a smart network of interoperable devices. Traditional devices are becoming ubiquitous, pervasive, connected, and wearable IoT gadgets. The purpose of this investigation is to develop a smart Child Pocket Monitoring and Protection System (ChildPOPS). Child...

The aim of this paper is to automatically compose new pleasing music from randomly generated notes without human intervention. To achieve this goal, Genetic Algorithm was implemented to generate random notes. The Neural Network was trained on a set of melodies to learn their regularity of patterns and then it is used as a fitness evaluator for the...

At the present time, 15% of the growing world population is estimated to have disabilities and special needs. Disabilities can seriously limit participation in regular life activities, such as controlling home facilities, using transportation services, joining social events, accessing educational contents, to name but a few. With the advancement in...

Harmony search algorithm with multi-parent crossover (HSA-MPC) is a hybrid algorithm that relies on benefiting from the crossover operation to combine more than one harmony to generate a new harmony. The picked harmonies are taken from an archive pool with best harmonies. In a previous study, the algorithm proves its efficiency when compared to oth...

Quality has become a fundamental requirement for success and sustainability of websites. This study discusses the evaluation of some e-Learning websites as one of the main sources of information to administrators, students and teachers in the educational systems. This article investigates the quality of e-learning websites in the Middle East in ter...

Artificial Immune Systems (AIS) is a well-known nature inspired and population based algorithm that proved its effectiveness for solving engineering and practical real-world problems. AIS can adapt to learning, has many models for different immune systems, which can be used to tackle different kinds of optimisation problems, and it can also be hybr...

Nowadays, the Web is used as a medium for providing different kinds of services for people. The needs of people with disabilities have to be taken into consideration when developing E-government. The objective of this work is to evaluate the Web accessibility issues facing people with disabilities in Kuwait in an attempt to identify problems, enhan...

Nowadays, the Web is used as a medium for providing different kinds of services for people. The needs of people with disabilities have to be taken into consideration when developing E-government. The objective of this work is to evaluate the Web accessibility issues facing people with disabilities in Kuwait in an attempt to identify problems, enhan...

The flow shop scheduling with blocking is considered an important scheduling problem which has many real-world applications. This paper proposes a new algorithm which applies heuristic techniques in harmony search algorithm (HSA) to minimize the total flow time. The proposed method is called modified harmony search algorithm with neighboring heuris...

Tourists that visit multiple locations need to have prior knowledge about interesting and attractive destinations. Selecting the most suitable tour plan for any tourist is not an easy task. Building a schedule of proposed destinations may allow the tourist to navigate between these destinations efficiently based on his/her time and budget. This pap...

Flower pollination algorithm (FPA) is a recent swarm-based evolutionary algorithm that was inspired by the biological evolution of pollination of the flowers. It deals with a panmictic population of pollens (or solutions) at each generation, using global and local pollination operators, to improve the whole population at once. Like other evolutiona...

Tourists that visit multiple locations need to have prior knowledge about interesting and attractive destinations. Selecting the most suitable tour plan for any tourist is not an easy task. Building a schedule of proposed destinations may allow the tourist to navigate between these destinations efficiently based on his/her time and budget. This pap...

Memory problems usually appear because of aging or may happen because of a brain injury. Such problems prevent the person from performing daily activities. In this paper, the authors propose a framework to develop a smartphone solution to detect and recognize the user context. In order to build the context detection framework, the authors compare t...

Accessibility of university online services is a major issue for undergraduate and graduate students with disabilities. Online registration makes people with disabilities more independent to register courses, add, drop courses, or see courses without depending on others. Yet, many people with disabilities in Jordan face major challenges to register...

In evolutionary multi-objective optimization, an evolutionary algorithm is used to solve an optimization problem having multiple, and usually conflicting objective functions. Previous proposed approaches to solve multi-objective optimization problems include NSGA-II, MOEA/D, MOPSO, and MOHS/D algorithms. In our previous work, we enhanced the perfor...

In evolutionary multi-objective optimization, an evolutionary algorithm is invoked to solve an optimization problem involving concurrent optimization of multiple objective functions. Many techniques have been proposed in the literature to solve multi-objective optimization problems including NSGA-II, MOEA/D and MOPSO algorithms. Harmony Search (HS)...

The number of students with disabilities attending universities is increased, and several challenges face them in higher education institutions. This study aims to determine accessibility needs of computer laboratories, libraries and websites for students with disabilities at Jordanian universities and colleges. The sample consists of staff in comp...

In this research, we propose an Arabic printed OCR dataset. To the best of our knowledge, there is no Arabic OCR dataset that is available to be used by the research community with its ground truth with a size that is suitable to build a robust Arabic OCR. The proposed dataset is extracted randomly from Wikipedia to have different topics. It consis...

Optical character recognition (OCR) is the process of recognizing characters automatically from scanned documents for editing, indexing, searching, and reducing the storage space. The resulted text from the OCR usually does not match the text in the original document. In order to minimize the number of incorrect words in the obtained text, OCR post...

The patient admission scheduling (PAS) problem is an optimization problem in which we assign patients automatically to beds for a specific period of time while preserving their medical requirements and their preferences. In this paper, we present a novel solution to the PAS problem using the harmony search (HS) algorithm. We tailor the HS to solve...

This article evaluates the accessibility computer laboratories, libraries, and web sites of five different institutions of higher education in Jordan. The evaluation is performed using a questionnaire and by expert visiting these institutions of higher education to check their accessibility according to a set of universal standard collected from th...

In this paper, the problem of economic load dispatch (ELD) is tackled using a recently introduced local search-based method called \(\beta \)-hill climbing optimizer. In a power system, the ELD problem is tackled by arranging a set of generation units’ outputs in a specific order to minimize the cost of the operating fuel and to match the power sys...

This work implements the Firefly algorithm (FA) to find the best decision hyper-plane in the feature space. The proposed classifier uses a cross-validation of a 10-fold portioning for the training and the testing phases used for classification. Five pattern recognition binary benchmark problems with different feature vector dimensions are used to d...

This paper provides a thorough evaluation of a set of six important Arabic OCR systems available in the market; namely: Abbyy FineReader, Leadtools, Readiris, Sakhr, Tesseract and NovoVerus. We test the OCR systems using a randomly selected images from the well known Arabic Printed Text Image database (250 images from the APTI database) and using a...

The multi-reservoir systems optimization problem requires defining a set of rules to recognize the water amount stored and released in accordance with the system constraints. Traditional methods are not suitable for complex multi-reservoir systems with high dimensionality. Recently, metaheuristic-based algorithms such as evolutionary algorithms and...

Different attack and defence techniques have been evolved over time as actions and reactions between black-hat and white-hat communities. Encryption, polymorphism, metamorphism and obfuscation are among the techniques used by the attackers to bypass security controls. On the other hand, pattern matching, algorithmic scanning, emulation and heuristi...

Guided by the eagerness to fulfill business objectives, quality assurance has become one of the highlighted topics in software engineering. With the rise of globalization and free markets, software users are becoming increasingly powerful with their ability to buy or reject computer software. While there is agreement over achieving quality, there i...

Maximum Satisfiability problem is an optimization variant of the Satisfiability problem (SAT) denoted as MAX-SAT. The aim of this problem is to find Boolean variable assignment that maximizes the number of satisfied clauses in the Boolean formula. In case the number of variables per clause is equal or greater than three, then this problem is consid...

A good library is one that has all of its resources accessible to all kinds of people, e.g. people with print disabilities. For this purpose, librarians try to provide books in several types of formats to accommodate different users. For example, e-books and digital talking books (DTB) are now available and can be used by a wider spectrum of users....

A good library is one that has all of its resources accessible to all kinds of people, e.g. people with print disabilities. For this purpose, librarians try to provide books in several types of formats to accommodate different users. For example, e-books and digital talking books (DTB) are now available and can be used by a wider spectrum of users....

Community structure means the existence of densely connected subgroups in the networks. It is a surprising property that appears in complex and naturally constructed networks. We are proposing a novel heuristic approach to the community detection problem. In this paper, the community detection problem is solved using the intelligent water drop heur...

To begin with, this research defines Software Quality Prediction System (SQPS) as a system composed of a Classification Algorithm (CA) and a Software Quality Measurement Model (SQMM). Machine Learning applications in software quality measurement are expanding as research intensifies in two directions, the first direction focuses on improving the pe...

Abstract Arabic language is one of six United Nations official languages. Arabic language processing, in particular speech synthesis, is a challenging task due to the inherent complexity of the language text and characters and because each letter may have up to seven different sounds. In this paper, we provide subjective and objective evaluation fo...

Banknote recognition means classifying the currency (coin and paper) to the correct class. In this paper, we developed a dataset for Jordanian currency. After that we applied automatic mobile recognition system using a smartphone on the dataset using scale-invariant feature transform (SIFT) algorithm. This is the first attempt, to the best of the a...