Salem Alelyani

Salem Alelyani
King Khalid University | KKU · College of Computer Science

PhD

About

46
Publications
15,110
Reads
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1,870
Citations
Citations since 2016
38 Research Items
1694 Citations
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2016201720182019202020212022050100150200250300
2016201720182019202020212022050100150200250300

Publications

Publications (46)
Article
This article aims to exploit social exchanges on scientific literature, specifically tweets, to analyse social media users’ sentiments towards publications within a research field. First, we employ the SentiStrength tool, extended with newly created lexicon terms, to classify the sentiments of 6,482,260 tweets associated with 1,083,535 publications...
Article
Full-text available
Rivers are the main sources of freshwater supply for the world population. However, many economic activities contribute to river water pollution. River water quality can be monitored using various parameters, such as the pH level, dissolved oxygen, total suspended solids, and the chemical properties. Analyzing the trend and pattern of these paramet...
Article
Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using 2- D ECG. Numerous studies have proven that ECG can be used to detect human emotions using 1-D ECG; however, ECG is typically captured as 2-D images rather than as 1-D data. There is still no consensus on the effect o...
Preprint
Full-text available
Recent period of pandemic has brought person identification even with occluded face image a great importance with increased number of mask usage. This paper aims to recognize the occlusion of one of four types in face images. Various transfer learning methods were tested, and the results show that MobileNet V2 with Gated Recurrent Unit(GRU) perform...
Conference Paper
Full-text available
Dialect identification is a prior requirement for learning lexical and morphological knowledge a language variation that can be beneficial for natural language processing (NLP) and potential AI downstream tasks. In this paper, we present the first work on sentence-level Modern Standard Arabic (MSA) and Saudi Dialect (SD) identification where we tra...
Article
Human Adaptive Mechatronics (HAM) includes human and computer system in a closed loop. Elderly person with disabilities, normally carry out their daily routines with some assistance to move their limbs. With the short fall of human care takers,mechatronics devices are used with the likes of exoskeleton and exosuits to assist them. The rehabilitatio...
Chapter
Internet of Things (IoT) is the most growing technological branch of computer science. In the current scenario, IoT and green manufacturing (GM) have impacted all the sectors including materials and manufacturing sectors. GM and IoT are two important applications applied in major business domains for the positive results. This study shows the role...
Article
Smart home is a concept that aims to maximize the comfort of occupant while consuming energy as low as possible. The comfort and energy consumption are contradicting factors in smart homes. Enhancing comfort often requires considerable energy. On the other hand, minimizing energy may result in less comfort to the residence. Thus, maximizing comfort...
Article
Diabetic Retinopathy (DR) is the complicatedness of diabetes that happens due to macular degeneration among Type II diabetic patients. The early symptom of this disease is predicted through annual eye checkups. Hence, one can save their vision at an early stage. Later on, it prompts retinal detachment. There is a requirement for awareness among dia...
Article
Full-text available
Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using ECG wave images. Numerous studies have proven that ECG can be used to detect human emotions using numerical data; however, ECG is typically captured as a wave image rather than as a numerical data. There is still no c...
Article
Full-text available
Machine learning is emerging nowadays as an important tool for decision support in many areas of research. In the field of education, both educational organizations and students are the target beneficiaries. It facilitates the educational sector in predicting the student’s outcome at the end of their course and for the students in deciding to choos...
Article
Full-text available
Photovoltaic (PV) systems have become one of the most promising alternative energy sources as they transform the sun’s energy into electricity. This can be achieved frequently without causing any potential harm to the environment. Though their usage in residential places and building sectors has notably increased, PV systems are regarded as unpredi...
Article
Full-text available
Affective computing is a field of study that integrates human affects and emotions with artificial intelligence into systems or devices. A system or device with affective computing is beneficial for the mental health and wellbeing of individuals that are stressed, anguished, or depressed. Emotion recognition systems are an important technology that...
Article
Full-text available
Most existing studies are focused on popular languages like English, Spanish, Chinese, Japanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning model for the sentiments expressed in this under-resourced language. We develop an open-source co...
Article
Full-text available
Machine learning models are built using training data, which is collected from human experience and is prone to bias. Humans demonstrate a cognitive bias in their thinking and behavior, which is ultimately reflected in the collected data. From Amazon’s hiring system, which was built using ten years of human hiring experience, to a judicial system t...
Article
Full-text available
Most existing studies are focused on popular languages like English, Spanish, Chinese, Japanese, and others, however, limited attention has been paid to Urdu despite having more than 60 million native speakers. In this paper, we develop a deep learning model for the sentiments expressed in this under-resourced language. We develop an open-source co...
Article
Class imbalance is a challenging problem especially in a supervised learning setup, as most classification algorithms are designed for balanced class distributions. Although various up-sampling approaches exist for eliminating the class imbalance, however, they do not handle the complexities of sequential data. In this study, using the data of over...
Article
Full-text available
Artificial intelligence (AI) is a broad, umbrella term that encompasses the theory and development of computer systems able to perform tasks normally requiring human intelligence. The aim of this study is to assess the radiology community's attitude in Saudi Arabia toward the applications of AI. Methods: Data for this study were collected using e...
Chapter
This paper introduces a new approach to optimize the cost per unit of product for the Transportation Problem to achieve better outcomes. We present Basic Feasible Solution (BFS) approach compromised of five main steps: (1) Create a Matrix A = mod |Supply(si)-Demand(dj)| (2) Add the cost of each cell of cost matrix C with corresponding elements of M...
Article
In-text citation analysis is one of the most frequently used methods in research evaluation. We are seeing significant growth in citation analysis through bibliometric metadata, primarily due to the availability of citation databases such as the Web of Science, Scopus, Google Scholar, Microsoft Academic, and Dimensions. Due to better access to full...
Preprint
Full-text available
Retinoblastoma is the most prominent childhood primary intraocular malignancy that impacts the vision of children and adults worldwide. In contrasting and comparing with adults it is uveal melanoma. It is an aggressive tumor that can fill and destroy the eye and the surrounding structures. Therefore early detection of retinoblastoma in childhood is...
Article
Full-text available
In the medical field, distinguishing genes that are relevant to a specific disease, let’s say colon cancer, is crucial to finding a cure and understanding its causes and subsequent complications. Usually, medical datasets are comprised of immensely complex dimensions with considerably small sample size. Thus, for domain experts, such as biologists,...
Article
Full-text available
Most of the traditional PID tuning methods are heuristic in nature. The heuristic approach-based tuned PID controllers show only nominal performance. In addition, in the case of a digital redesign approach, mapping of the heuristically-designed continuous-time PID controllers into discrete-time PID controllers and in case of the direct digital desi...
Article
Full-text available
One of the most important concerns in the planning and operation of an electric power generation system is the effective scheduling of all power generation facilities to meet growing power demand. Economic load dispatch (ELD) is a phenomenon where an optimal combination of power generating units is selected in such a way as to minimize the total fu...
Preprint
This article aims to exploit social exchanges on scientific literature, specifically tweets, to analyse social media users' sentiments towards publications within a research field. First, we employ the SentiStrength tool, extended with newly created lexicon terms, to classify the sentiments of 6,482,260 tweets associated with 1,083,535 publications...
Preprint
Full-text available
Citation analysis is one of the most frequently used methods in research evaluation. We are seeing significant growth in citation analysis through bibliometric metadata, primarily due to the availability of citation databases such as the Web of Science, Scopus, Google Scholar, Microsoft Academic, and Dimensions. Due to better access to full-text pu...
Preprint
Full-text available
In the medical field, distinguishing genes that are relevant to a specific disease, let's say colon cancer, is crucial to finding a cure and understanding its causes and subsequent complications. Usually, medical datasets are comprised of immensely complex dimensions with considerably small sample size. Thus, for domain experts, such as biologists,...
Preprint
Full-text available
In the medical eld, distinguishing genes that are relevant to a specific disease, let's say colon cancer, is crucial to finding a cure and understanding its causes and subsequent complications. Usually, medical datasets are comprised of immensely complex dimensions with considerably small sample size. Thus, for domain experts, such as biologists, t...
Article
Full-text available
Altmetrics are often praised as an alternative or complement to classic bibliometric metrics, especially in the social sciences discipline. However, empirical investigations of altmetrics concerning the social sciences are scarce. This study investigates the extent to which economic research is shared on social media platforms with an emphasis on m...
Article
We propose a new metric called ‘alt-index’, which is analagous to the h-index, but uses altmetrics data to measure both the volume and social media activity of scientific literature. The dataset includes over 1.1 million papers and their associated altmetrics score. A correlation analysis of the h-index and alt-index is conducted at three different...
Article
Full-text available
Purpose The purpose of this paper is to present a novel approach for mining scientific trends using topics from Call for Papers (CFP). The work contributes a valuable input for researchers, academics, funding institutes and research administration departments by sharing the trends to set directions of research path. Design/methodology/approach The...
Conference Paper
In the realm of crime, cybercrimes have become the most threatening of its kind due to the vast approaches of hacking, the ability to do so with relative anonymity, and the increased complexity of subsequent investigations. The misconceptions about cybercrimes and the lack of awareness are causing significant numbers of people to underestimate the...
Conference Paper
The rapid advancement of wearable devices and smartphones, allowed practitioners and specialists to keep track of physical, biological and behavioral activities. Nowadays, this self tracking, a.k.a. quantified self (QS), is widely used in big data science due to the large volume of data being generated from these devices. The wearable devices that...
Conference Paper
Increasing attention has been focused on the stability of selected features or selection stability, which is becoming a new measure in determining the effectiveness of a feature selection algorithm besides the learning performance. A recent study has shown that data characteristics play a significant role in selection stability. Hence, the solution...
Conference Paper
Ensemble feature selection is known for its robustness and generalization of highly accurate predictive models. In this paper, we use different filter-based feature selection methods in an ensemble manner to improve face recognition. The goal is to distinguish human faces from avatar faces. Our approach was able to achieve very high accuracy, 99%,...
Conference Paper
Real-world datasets commonly present high dimensional data, which means an increased amount of information. However, this does not always imply an improvement in learning technique performance. Furthermore, some features may be correlated or add unexpected noise, thereby reducing data clustering performance. This has motivated the development of fe...
Conference Paper
Feature selection is an effective technique to reduce the dimensionality of a data set and to select relevant features for the domain problem. Recently, stability of feature selection methods has gained increasing attention. In fact, it has become a crucial factor in determining the goodness of a feature selection algorithm besides the learning per...
Conference Paper
In realm, feature selection is an effective means for handling high-dimensional data that becomes increasingly abundant. The stability of a feature selection algorithm is becoming crucial for determining the fitness of the algorithm. Below, we review existing methods of stability assessment and analyse how they assess the stability of a feature sel...

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Project (1)
Project
The use of artificial intelligence (AI) is increasing in various sectors of photovoltaic (PV) systems, due to the increasing computational power, tools and data generation. This project uses artificial intelligence and machine learning methods to predict the generated power. In this study, we used machine learning (ML)-based algorithms to predict the generated power of a PV system for residential buildings.