Hana Sulieman

• American University of Sharjah

Language choice or preference, that is the deliberate selection of language(s) for different purposes in different contexts, situations and domains, is a complex sociolinguistic phenomenon as it is usually motivated by numerous sociolinguistic factors. This study investigates language choice between Arabic and English during automated teller machin...

Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). To evaluate FSAs effectively, controlled environments are required, and the use of synthetic datasets offers significant advantages....

Accurate forecasting is one of the keys to the efficient use of the limited existing energy resources and plays an important role in sustainable development. While most of the current research has focused on energy price forecasting, very few studies have considered medium-term (monthly) electricity generation. This research aims to fill this gap b...

Feature selection is an important and active field of research in machine learning and data science. Our goal in this paper is to propose a collection of synthetic datasets that can be used as a common reference point for feature selection algorithms. Synthetic datasets allow for precise evaluation of selected features and control of the data param...

It has been shown that while feature selection algorithms are able to distinguish between relevant and irrelevant features, they fail to differentiate between relevant and redundant and correlated features. To address this issue, we propose a highly effective approach, called Nested Ensemble Selection (NES), that is based on a combination of filter...

Ultrasound (US) has numerous uses in the medical field, including imaging, tumor ablation, and lithotripsy; another interesting application of US in cancer therapy is as an external trigger in targeted drug delivery. Cancer-targeted drug delivery involves delivering chemotherapeutic drugs to tumor sites with a high degree of precision, which would...

The rise in crime rates in many parts of the world, coupled with advancements in computer vision, has increased the need for automated crime detection services. To address this issue, we propose a new approach for detecting suspicious behavior as a means of preventing shoplifting. Existing methods are based on the use of convolutional neural networ...

This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic stability assessment is achieved. The selected rese...

Abstract: Targeted liposomes triggered by ultrasound are a promising drug delivery system as they potentially improve the clinical outcomes of chemotherapy while reducing associated side effects. In this work, a comprehensive model fitting was performed for a large dataset of liposomal release profiles with seven targeting moieties (albumin, cRGD,...

Targeted liposomes triggered by ultrasound are a promising drug delivery system as they potentially improve the clinical outcomes of chemotherapy while reducing associated side effects. In this work, a comprehensive model fitting was performed for a large dataset of liposomal release profiles with seven targeting moieties (albumin, cRGD, estrone, h...

Knowledge of antibiotics and awareness of microbial resistance are essential for appropriate antibiotic consumption. This study aimed to develop and validate a measure of antibiotic knowledge and consumption (AKCT) and to make it available in the Arabic language and context. The tool was developed and applied on individuals ≥ 18 years, with mastery...

Feature selection is an important and active field of research in machine learning and data science. Our goal in this paper is to propose a collection of synthetic datasets that can be used as a common reference point for feature selection algorithms. Synthetic datasets allow for precise evaluation of selected features and control of the data param...

CALL FOR PAPERS: We are pleased to announce that the 9th International Conference on Modeling, Simulation and Applied Optimization will be held in Marrakesh, Morocco on April 26th-28th 2023 (www.icmsao.org/). ICMSAO provides a venue for engineers, mathematicians, and scientists from all over the world to share their latest research results in the f...

To mitigate the curse of dimensionality in high-dimensional datasets, feature selection has become a crucial step in most data mining applications. However, no feature selection method consistently delivers the best performance across different domains. For this reason and in order to improve the stability of the feature selection process, ensemble...

Signal data often contains missing values. Effective replacement (imputation) of the missing values can have significant positive effects on processing the signal. In this paper, we compare three commonly employed methods for estimating missing values in time series data: forward fill, backward fill, and mean fill. We carry out a large scale experi...

Background Diabetes distress (DD) has broad-ranging effects on type 2 diabetes (T2DM) management and outcomes. DD research is scarce among ethnic minority groups, particularly Arabic-speaking immigrant communities. To improve outcomes for these vulnerable groups, healthcare providers, including pharmacists, need to understand modifiable predictors...

The COVID-19 pandemic has impelled the majority of schools and universities around the world to switch to remote teaching. One of the greatest challenges in online education is preserving the academic integrity of student assessments. The lack of direct supervision by instructors during final examinations poses a significant risk of academic miscon...

Background Diabetes distress (DD) has broad-ranging effects on type 2 diabetes (T2DM) management and outcomes. DD research is scarce among ethnic minority groups, particularly Arabic-speaking immigrant communities. To improve outcomes for these vulnerable groups, healthcare providers, including pharmacists, need to understand modifiable predictors...

Cryptocurrency has become the leading method for peer-to-peer electronic cash system. It uses cryptography to secure financial transactions. Recently, several researchers have attempted to understand the behaviors of cryptocurrency exchange rates. In this paper, we introduce a new location–scale family of distributions to understand the distributio...

Although replaced by the internet-based TOEFL (iBT), the paper-based TOEFL (PBT) was still used in some countries until July 2017. This natural experiment investigates a case where, November 2006–May 2009, a testing center in the Middle East did not follow TOEFL time interval protocol at that time, with 1,575 test takers allowed to attempt paper TO...

In the past decade, big data has become increasingly prevalent in a large number of applications. As a result, datasets suffering from noise and redundancy issues have necessitated the use of feature selection across multiple domains. However, a common concern in feature selection is that different approaches can give very different results when ap...

Experimental designs based on the classical D-optimal criterion minimize the volume of the linear-approximation inference regions for the parameters using local sensitivity coefficients. For nonlinear models, these designs can be unreliable because the linearized inference regions do not always provide a true indication of the exact parameter infer...

The COVID-19 pandemic has galvanized the machine learning community to create new solutions that can help in the fight against the virus. The body of literature related to applications of machine learning and artificial intelligence to COVID-19 is constantly growing. The goal of this article is to present the latest advances in machine learning res...

The market for cryptocurrencies has experienced extremely turbulent conditions in recent times, and we can clearly identify strong bull and bear market phenomena over the past year. In this paper, we utilise algorithms for detecting turnings points to identify both bull and bear phases in high-frequency markets for the three largest cryptocurrencie...

This paper aims to study the relations between construction enterprises’ project management capabilities and organizational performance. A questionnaire survey was administered to 89 Saudi construction contracting organization administrative members. Data were obtained from 32 projects that were held during the last two years and were analyzed usin...

In this paper we propose a novel approach for feature selection in machine learning. The approach based on the Sobol sensitivity analysis which a variance-based technique which determines the contribution of each feature and their interactions to the overall variance of the target variable. Similar to wrappers, Sobol sensitivity is a model-based ap...

This work presents invited contributions from the second "International Conference on Mathematics and Statistics" jointly organized by the AUS (American University of Sharjah) and the AMS (American Mathematical Society). Addressing several research fields across the mathematical sciences, all of the papers were prepared by faculty members at univer...

Students from different majors taking statistics course view their statistics learning experience differently. In this work, a survey of 440 undergraduate students from various majors who took an introductory statistics course at the American University of Sharjah (AUS) in Fall 2012 or earlier semesters was conducted. Analysis of the survey data sh...

Objectives No previous studies have investigated patients' expectations of, or interest in, using primary care pharmacy services in the UAE. The study investigated primary care services that patients would use if they were provided through community pharmacies.MethodsA questionnaire was developed in English and translated to Arabic. Participants we...

D-optimal experimental designs for precise parameter estimation are designs which minimize the determinant of the variance-covariance matrix of the parameter estimates based on the conventional parametric sensitivity coefficients. These coefficients are local measures of sensitivity defined by the first-order derivative of system model function wit...

Objectives The aim of this study was to assess pregnancy outcomes after cervical cerclage. Methods A retrospective analysis of all cervical cerclages placed at Al Qassimi Hospital from 2004 to 2008 was performed. The primary outcome of interest was prolongation of pregnancy beyond 36 wks. Secondary outcomes were premature rupture of membranes, bir...

Background: Patient satisfaction has become an integral component of the quality of healthcare services. It has been used for the purpose of performance assessment, reimbursement, and quality management of health service delivery. It has been suggested that patient satisfaction could be a predictor of health-related behavior. Objectives: To deve...

To identify the type and frequency of services provided through community pharmacies in the United Arab Emirates (UAE). A survey was conducted using an anonymous questionnaire distributed by hand to 700 community pharmacies. Items included information about the pharmacists and pharmacies, type of products sold, type and extent of enhanced services...

Skin testing can be a useful diagnostic tool to identify patients who are allergic to penicillin. Procedures for skin testing in the United Arab Emirates have not been standardized. The aim of this study was to examine the current practice of antibiotic skin testing in a tertiary hospital in the United Arab Emirates (UAE). This was a prospective cr...

In nonlinear parameter estimation local sensitivity assessment; conventionally measured by the first-order derivative of the predicted response with respect to a parameter of interest fails to provide a representative picture of the prediction sensitivity in the presence of significant parameter co-dependencies and/or nonlinearities. In this articl...

This article presents a comparative analysis of three derivative-based parametric sensitivity approaches in multi-response regression estimation: marginal sensitivity, profile-based approach developed by [Sulieman, H., McLellan, P.J., Bacon, D.W., 2004, A Profile-based approach to parametric sensitivity in multiresponse regression models, Computati...

Purpose The purpose of this study is to examine students' perception of end‐of‐semester Student Evaluations of Teaching (SET), and to explore the extent to which SET are biased by non‐instructional factors. Design/methodology/approach A survey questionnaire about the end‐of‐semester SET was designed and administered to 819 students selected from a...

A sample of 221 women who delivered at Al Qassimi Hospital, Sharjah, United Arab Emirates, were included in this prospective study to identify breastfeeding patterns at day 1, 1 month, and 6 months postpartum. The exclusive breastfeeding rate was 76.5% on day 1, 48.4% at 1 month, and 13.3% at 6 months. At 6 months, 16.1% had stopped breastfeeding....

Molecular weight distributions (MWDs) are inherently functional observations in which differential weight fraction is expressed as a function of chain length. Conventional approaches for analyzing and predicting MWDs include discretization and treatment as multi-response estimation problems, characterization using moments, and detailed mechanistic...

The profile-based sensitivity measure proposed by Sulieman et al. (Technometrics 43(4) (2001) 425) for single-response nonlinear models is extended to the case of multiresponse parameter estimation based on the Box–Draper estimation criterion. The profile-based sensitivity measure for the parameters in the multiresponse case is a vector-valued meas...

Predictions from a nonlinear regression model are subject to uncertainties propagated from the estimated parameters in the model. Parameters exerting the strongest influence on model predictions can be identified by a sensitivity analysis. In this article, a new parametric sensitivity measure is introduced, based on the profiling algorithm develope...

The study examines job satisfaction among information technology professionals' in Dubai and its relation to monetary compensation and involvement in strategic management among UAE nationals and expatriates. 148 information technology professionals in Dubai were surveyed via online administered survey. A significant relation was found between job s...