Ahmad Hassanat

Mutah University

Regression, a supervised machine learning approach, establishes relationships between independent variables and a continuous dependent variable. It is widely applied in areas like price prediction and time series forecasting. The performance of regression models is typically assessed using error metrics such as the Mean Squared Error (MSE), Mean Ab...

Background One of the main causes of cancer-related mortality in women is breast cancer [BC]. There were four molecular subtypes of this malignancy, and adjuvant therapy efficacy differed based on these subtypes. Gene expression profiles provide valuable information that is helpful for patients whose prognosis is not clear from clinical markers and...

[This corrects the article DOI: 10.3389/fneur.2023.1270767.].

Background The incidence of microorganisms with extended-spectrum beta-lactamase (ESBL) is on the rise, posing a significant public health concern. The current application of machine learning (ML) focuses on predicting bacterial resistance to optimize antibiotic therapy. This study employs ML to forecast the occurrence of bacteria that generate ESB...

Regression, a supervised machine learning approach, establishes relationships between independent variables and a continuous dependent variable. It is widely applied in areas like price prediction and time series forecasting. The performance of regression models is typically assessed using error metrics such as Mean Squared Error (MSE), Mean Absolu...

The Blockchain is a common data record system that keeps permanent information about all transactions involving two parts. Blockchain consistently and dependably establishes the fictitious possession of each transaction that occurs. Once a transaction has been cryptographically verified and accepted by other participants, it is recorded as a “block...

The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in the initial population is important in determining the final optimal solution. The classic GA using the random population seeding technique is effective and straight...

Accents, or changes in how different people speak the same word/sentence in the same language, pose substantial communication issues in most spoken languages. This is a well-known fact, but how does the accent of one language affect learning/speaking another? In this paper, we look at how Arab accents influence the English language. To that end, we...

Antimicrobial resistance (AMR) is identified as the fourth leading cause of mortality in Jordan. However, there is a scarcity of data addressing the demographics and clinical characteristics associated with AMR against commonly used antibiotics in Western Jordan. To address this knowledge gap, a retrospective analysis was undertaken on the microbio...

Genetic algorithms (GAs) are search algorithms based on population genetics and natural selection concepts. Maintaining population variety in GAs is critical for ensuring global exploration and mitigating the risks of premature convergence. Rapid convergence to local optima is one such challenge in the application of genetic algorithms. To address...

Background Stroke is a significant global health burden and ranks as the second leading cause of death worldwide. Objective This study aims to develop and evaluate a machine learning-based predictive tool for forecasting the 90-day prognosis of stroke patients after discharge as measured by the modified Rankin Score. Methods The study utilized da...

Soil–cement materials are widely used in civil engineering. Previous studies described problems related to errors in ultrasonic measurements of the unconfined compressive strength (UCS) of low-strength soil–cements. In the presented experiments, a standard ultrasonic pulse velocity (UPV) measuring device was equipped with an oscilloscope to extend...

Soil-cement materials are widely used in civil engineering. Previous studies described problems related to errors in ultrasonic measurements of the unconfined compressive strength (UCS) of low-strength soil-cements. In the presented experiments, a standard ultrasonic pulse velocity (UPV) measuring device was equipped with an oscilloscope to extend...

In order to increase the efficiency and effectiveness of sustainable practices, smart sustainability refers to the integration of smart technology with sustainability concepts. The scope of smart sustainability is quite broad and has a wide range of applications related to a number of research areas such as environmental issues, energy, transportat...

Vehicle detection and classification are the most significant and challenging activities of an intelligent traffic monitoring system. Traditional methods are highly computationally expensive and also impose restrictions when the mode of data collection changes. This research proposes a new approach for vehicle detection and classification over aeri...

Fish fecundity is one of the most relevant parameters for the estimation of the reproductive potential of fish stocks, used to assess the stock status to guarantee sustainable fisheries management. Fecundity is the number of matured eggs that each female fish can spawn each year. The stereological method is the most accurate technique to estimate f...

Fish fecundity is one of the most relevant parameters for the estimation of the reproductive potential of fish stocks, used to assess the stock status to guarantee sustainable fisheries management. Fecundity is the number of matured eggs that each female fish can spawn each year. The stereological method is the most accurate technique to estimate f...

This study investigates the classification of Arabic coffee into three major variations (light, medium, and dark) using simulated data gathered from the actual measurements of color information, antioxidant laboratory testing, and chemical composition tests. The goal is to overcome the restrictions of limited real-world data availability and the hi...

The usefulness of the oversampling approach to class-imbalanced structured medical datasets is discussed in this paper. In this regard, we basically look into the oversampling approach’s prevailing assumption that synthesized instances do belong to the minority class. We used an off-the-shelf over-sampling validation system to test this assumption....

Using SEER data, this work seeks to create a machine learning (ML) model to predict lung metastases (LM) and three-month prognostic variables in hepatocellular carcinoma (HCC) patients. The study comprised 34,861 HCC patients, 1,783(5.11%) of whom had lung metastases, and 859 were suitable for the 3-month prognostic model. The ML models were cross-...

Citation: Al-Mahadeen, E.; Alghamdi, M.; Tarawneh, A.S.; Alrowaily, M.A.; Alrashidi, M.; Alkhazi, I.S.; Mbaidin, A.; Alkasasbeh, A.A.; Abbadi, M.A.; Hassanat, A.B. Smartphone User Identification/Authentication Using Accelerometer and Gyroscope Data. Sustainability 2023, 15, 10456. https:// Abstract: With the increasing popularity of smartphones, us...

Background: Hepatocellular carcinoma (HCC) frequently spreads to the bones, and those who do so have a worse prognosis than those who do not. The purpose of this study is to identify the predictors and three-month prognostic indicators of bone metastasis(BM) in patients with HCC and to identify the best machine learning (ML) model for it, which wil...

This research assesses the classification of Arabic coffee into three primary variations (light, medium, and dark) using simulated data based on actual measurements of color information, antioxidant laboratory tests, and chemical composition tests. Two types of simulated data were generated, with the standard deviation of the measures varied. Multi...

With the growing popularity of smartphones, user identification has become an essential component of maintaining security and privacy. This study investigates how smartphone accelerometer data can be used to identify users, and it makes recommendations for the ideal application parts. Accelerometer data from the HMOG public dataset was used to trai...

This presentation shows the achievements of Professor Arafat Awajan during his presidency.

MLCID’23 worship will be organized as part of the 28th IEEE Symposium on Computers and Communications (ISCC), https://2023.ieee-iscc.org/ . and it will include presentations, tutorials, and panel discussions to facilitate knowledge sharing and collaboration among participants. This workshop is peer-reviewed and published as part of the symposium pr...

In this work, we have presented a way to increase the contrast of an image. Our target is to find a transformation that will be image specific. We have used a fuzzy system as our transformation function. To tune the system according to an image, we have used Genetic Algorithm and Hill Climbing in multiple ways to evolve the fuzzy system and conduct...

Blockchain technology has a wide range of applicability in the fields of transportation infrastructure construction and maintenance, transportation big data analysis and application, expressway toll collection, and logistics. The core technology lies in the distributed, decentralized, immutable, and programmable features brought about by consensus....

Big data classification is a challenging task because most known classification methods need a long time and a lot of processing resources to execute such a task and use the vast amount of available data. In this paper, we propose a novel big data classification method that leverages the power of the KNN classifier and the efficiency of the ensembl...

TSP is a well-known combinatorial optimization problem with several practical applications. It is an NP-hard problem, which means that the optimal solution for huge numbers of examples is computationally impractical. As a result, researchers have focused their efforts on devising efficient algorithms for obtaining approximate solutions to the TSP....

Numerous machine learning methods depend on distance measures. In both supervised and unsupervised learning, these distance measures are primarily employed to assess the degree of similarity between data points. One of the most recent distance metrics that comes highly recommended by several academics for its improved performance in machine learnin...

The interface between concrete layers cast at different ages is present both in new construction, e.g., precast beams with cast in place decks, and in rehabilitation, e.g., jacketing of existing beams and columns. The interface strength ensures the element's monolithic behaviour. This strength is mainly determined by the interface surface roughness...

The ancient game of ṭāb is a war and race game. It is played by two teams, each consisting of at least one player. In addition to presenting the game and its rules, the authors develop three versions of the game: human versus human, human versus computer, and computer versus computer. The authors employ a Genetic Algorithm (GA) to help the computer...

The first International Conference on Emerging Trends in Computing and Engineering Applications (ETCEA2022) is a venue for scientists, engineers, and practitioners to share their most recent research findings, ideas, advances, and applications in all fields of computer science .and engineering. Artificial Intelligence, Data Science, Machine learnin...

Description Many relationships important to civil engineering depend on surface roughness (morphology). Examples are the bond strength between concrete layers, the adhesion of a wheel to the pavement, the angle of friction in the soil in contact with a wall surface, and many other cases when we deal with a material with a surface having the charact...

The classic notion of a win–win situation has a key flaw in that it cannot always offer the parties equal amounts of winningsbecause each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We presen...

Biometric technology has received a lot of attention in recent years. One of the most prevalent biometric traits is the finger-knuckle print (FKP). Because the dorsal region of the finger is not exposed to surfaces, FKP would be a dependable and trustworthy biometric. We provide an FKP framework that uses the VGG-19 deep learning model to extract d...

One of the most difficult problems analysts and decision-makers may face is how to improve the forecasting and predicting of financial time series. However, several efforts were made to develop more accurate and reliable forecasting methods. The main purpose of this study is to use technical analysis methods to forecast Jordanian insurance companie...

For the last two decades, oversampling has been employed to overcome the challenge of learning from imbalanced datasets. Many approaches to solving this challenge have been offered in the literature. Oversampling, on the other hand, is a concern. That is, models trained on fictitious data may fail spectacularly when put to real-world problems. The...

There are a plethora of invented classifiers in Machine learning literature, however, there is no optimal classifier in terms of accuracy and time taken to build the trained model, especially with the tremendous development and growth of Big data. Hence, there is still room for improvement. In this paper, we propose a new classification method that...

Since most classifiers are biased toward the dominant class, class imbalance is a challenging problem in machine learning. The most popular approaches to solving this problem include oversampling minority examples and undersampling majority examples. Oversampling may increase the probability of overfitting, whereas undersampling eliminates examples...

Since most classifiers are biased toward the dominant class, class imbalance is a challenging problem in machine learning. The most popular approaches to solving this problem include oversampling minority examples and undersampling majority examples. Oversampling may increase the probability of overfitting, whereas undersampling eliminates examples...

COVID19 detection

For the last two decades, oversampling has been employed to overcome the challenge of learning from imbalanced datasets. Many approaches to solving this challenge have been offered in the literature. Oversampling, on the other hand, is a concern. That is, models trained on fictitious data may fail spectacularly when put to real-world problems. The...

Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiled-persons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully conn...

The classic win-win has a key flaw in that it cannot offer the parties with right amounts of winning because each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure...

The classic win-win has a key flaw in that it cannot offer the parties the right amounts of winning because each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure...

This compressed file contains some of my work and some machine learning methods coded using MS VC++ 2017. For more information, and how to use the code, please see Sharing my code.pdf

A Simulation Model for Forecasting COVID-19 Pandemic Spread using C#

Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiledpersons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully conne...

Biometric recognition based on the full face is an extensive research area. However, using only partially visible faces, such as in the case of veiled-persons, is a challenging task. Deep convolutional neural network (CNN) is used in this work to extract the features from veiled-person face images. We found that the sixth and the seventh fully conn...

The coronavirus pandemic (COVID-19) spreads worldwide during the first half of 2020. As is the case for all countries, the Kingdom of Saudi Arabia (KSA), where the number of reported cases reached more than 392 K in the first week of April 2021, was heavily affected by this pandemic. In this study, we introduce a new simulation model to examine the...

Classifying and modeling texture images, especially those with significant rotation, illumination, scale, and view-point variations, is a hot topic in the computer vision field. Inspired by local graph structure (LGS), local ternary patterns (LTP), and their variants, this paper proposes a novel image feature descriptor for texture and material cla...

Bankruptcy is an issue of interest in the business world since decades. It is a crucial endeavor for survival to predict this phenomenon in periods of economic turmoil and recession. In fact, bankruptcy modeling is challenging due to the complexity of contributing factors and the highly imbalanced distribution of available data sets. This work aims...

Genetic algorithms (GAs) are powerful heuristic search techniques that are used successfully to solve problems for many different applications. Seeding the initial population is considered as the first step of the GAs. In this work, a new method is proposed, for the initial population seeding called the Multi Linear Regression Based Technique (MLRB...

In March 2020, Saudi Arabia reported that the Coronavirus disease (COVID-19) spread to its territory, originating from China. In this study, a new simulation model estimates and forecasts the number of infected subjects with COVID-19 in the upcoming weeks, based on different parameters, in two major cities in Saudi Arabia, namely Riyadh (the capita...

Genetic algorithm (GA) is an efficient tool for solving optimization problems by evolving solutions, as it mimics the Darwinian theory of natural evolution. The mutation operator is one of the key success factors in GA, as it is considered the exploration operator of GA. Various mutation operators exist to solve hard combinatorial problems such as...