Sadok Ben Ben Yahia

University of Southern Denmark | SDU · Maersk Mc-Kinney Moller Institute

Diabetic retinopathy, a common complication of diabetes, is further exacerbated by factors such as hypertension and obesity. This study introduces the Diabetic Retinopathy Compact Convolutional Transformer (DRCCT) model, which combines convolutional and transformer techniques to enhance the classification of retinal images. The DRCCT model achieved...

Multiple objectives have emerged in tuning protein-protein interaction (PPI) networks, such as identifying cross-species network similarities and predicting protein complexes and functions. Despite the proliferation of tuning methodologies, challenges remain in balancing accuracy and efficiency. In this paper, we introduce GA2Vec, a novel approach...

Purpose The current study intends to use green-driven augmented reality (AR) with gamification application to help students at the Higher Institute of Science and Technology (HIST) in Libya to effectively learn general chemistry concepts successfully and with minimum side effects on individuals and the environment. It also aims to shed light on the...

The integration of fully homomorphic encryption (FHE) in federated learning (FL) has led to significant advances in data privacy. However, during the aggregation phase, it often results in performance degradation of the aggregated model, hindering the development of robust representational generalization. In this work, we propose a novel multimodal...

In the field of Recommender Systems (RS), neural collaborative filtering represents a significant milestone by combining matrix factorization and deep neural networks to achieve promising results. Traditional methods like matrix factorization often rely on linear models, limiting their capability to capture complex interactions between users, items...

The modern labor market faces complex challenges stemming from various factors, such as demographic shifts, the far-reaching impacts of digital and technological evolution, changing job profiles, and job losses due to automation and the green-economy transition. As labor market challenges escalate, it becomes increasingly vital for public employmen...

The technology of connected intelligent objects dedicated to health has become a buzzword in medical circles. It has emerged as a popular trend in the world of health technology, but its growing popularity also raises concerns about security. Sensitive data stored on these devices, such as personal medical information, make them vulnerable to cyber...

Point of Interest (POI) recommender systems (RSs) play a primary role in improving Location-based Social Networks’ user experience. This paper studies the potential usefulness of serendipity in POI recommendations. We first introduce a new POI RS, called Discovery, that attempts to improve the accuracy-serendipity trade-off. The proposed RS aims to...

The widespread deployment of products powered by machine learning models is raising concerns around data privacy and information security worldwide. To address this issue, Federated Learning was first proposed as a privacy-preserving alternative to conventional methods that allow multiple learning clients to share model knowledge without disclosing...

The growing computational demands of artificial intelligence (AI) in addressing climate change raise significant concerns about inefficiencies and environmental impact, as highlighted by the Jevons paradox. We propose an attention-enhanced quantum physics-informed neural networks model (AQ-PINNs) to tackle these challenges. This approach integrates...

Diabetic retinopathy, a common complication of diabetes, is further exacerbated by factors such as hypertension and obesity. This study introduces the Diabetic Retinopathy Convolutional Transformer (DRCT) model, which combines convolutional and transformer techniques to enhance the classification of retinal images. The DRCT model achieved an impres...

Financial market prediction and optimal trading strategy development remain challenging due to market complexity and volatility. Our research in quantum finance and reinforcement learning for decision-making demonstrates the approach of quantum-classical hybrid algorithms to tackling real-world financial challenges. In this respect, we corroborate...

The rate of unplanned hospital readmissions is a relevant indicator of the quality of care provided. From a financial point of view, unplanned readmissions are costly for patients and healthcare providers. Awareness of unplanned readmissions helps to mitigate the growth of healthcare costs. Several predictive models have been proposed to reduce unp...

Data integration is considered a classic research field and a pressing need within the information science community. Ontologies play a critical role in such processes by providing well-consolidated support to link and semantically integrate datasets via interoperability. This paper approaches data integration from an application perspective by loo...

Researchers have long used gravity models to analyze international trade patterns, identify export opportunities, and negotiate trade agreements. Recent research has emphasized the significance of relatedness and product complexity research in developing robust economic development strategies. This paper presents a novel approach, incorporating rel...

Topic detection is the process of identifying the underlying themes or topics present in a set of documents. It has become more critical due to the increase of information electronically available and the necessity to process and filter it. In this respect, we introduce a new approach to detecting topics called ClusART. Thus, we created a three-pha...

This paper addresses the critical gaps within public employment services (PES), with a particular focus on the deficiency in automation and AI-supported intelligent career recommendations. Notably, the advancements in this public sector's domain remain in their early stages, necessitating further exploration and development. The study sheds light o...

Background The pharmaceutical field faces a significant challenge in validating drug target interactions (DTIs) due to the time and cost involved, leading to only a fraction being experimentally verified. To expedite drug discovery, accurate computational methods are essential for predicting potential interactions. Recently, machine learning techni...

In many fields, like aspect category detection (ACD) in aspect‐based sentiment analysis, it is necessary to label each instance with more than one label at the same time. This study tackles the multilabel classification problem in the ACD task for the Arabic language. For this purpose, we used Arabic hotel reviews from the SemEval‐2016 dataset, com...

Urbanization is associated with increasing the temperature of urban areas and phenomena like the Urban Heat Island (UHI). The latter produces a sensible impact on people’s health, quality of life, urban liveability, and even the mortality rate. As a result, reducing high temperatures in cities will improve the quality of life in cities. Overall, th...

Knowledge representation (KR) is vital in designing symbolic notations to represent real-world facts and facilitate automated decision-making tasks. Knowledge graphs (KGs) have emerged so far as a popular form of KR, offering a contextual and human-like representation of knowledge. In international economics, KGs have proven valuable in capturing c...

Asymptotically consistent estimators of a treatment effect under many potential confounders became possible with the latest advancements in doubly-robust causal inference models (e.g., Double ML). In this study, we propose SAFE-TH framework to estimate and explain the heterogeneous treatment effect with partial dependence plots and report it under...

Analyzing and understanding large and complex volumes of biological data is a challenging task as data becomes more widely available. In biomedical research, gene expression data are among the most commonly used biological data. Formal concept analysis frequently identifies deferentially expressed genes in microarray data. Top-K formal concepts are...

Sentiment Analysis (SA) helps automatically and meaningfully discover hotel customers’ satisfaction from their shared experiences and feelings on social media. Several studies were conducted to improve the precision of SA in the hospitality industry. They varied in data preprocessing techniques, feature representation, sentiment classification leve...

Urban traffic congestion is of utmost importance for modern societies due to population and economic growth. Thus, it contributes to environmental problems like increasing greenhouse gas emissions and noise pollution. Improved traffic flow in urban networks relies heavily on traffic signal control. Hence, optimizing cycle timing at many intersectio...

Climatic and micro-climatic phenomena such as summer heat waves and Urban Heat Island (UHI) are increasingly endangering the city's livability and safety. The importance of urban features on the UHI effect encourages us to consider the configuration of urban elements to improve cities' sustainability and livability. Most solutions are viable when a...

Predicting comfort levels in cities is challenging due to the many metric assessment. To overcome these challenges, much research is being done in the computing community to develop methods capable of generating outdoor comfort data. Machine Learning (ML) provides many opportunities to discover patterns in large datasets such as urban data. This pa...

This study aims to examine the effectiveness of the flipped learning approach in a computer principles course at Alasmarya Islamic University, Libya. The reason for this consideration was to evaluate the viability of conven-tional lecture-based educational programmes versus the active learning of computer concepts in flipped classrooms for college...

Call Detail Records (CDRs) are records that provide information about phone conversations and text messages. CDR data has been proved in several studies to give useful information on people's mobility patterns and associations with fine-grained temporal and geographical characteristics. This paper proposes to embed the traces recorded in the CDRs t...

The new digital era brings increasingly massive and complex interdisciplinary projects in various fields. At the same time, the availability of an accurate and reliable database plays a crucial role in achieving project goals. Meanwhile, urban projects and issues usually need to be analyzed to support the objectives of sustainable development of th...

This study seeks to add to the existing literature on SME entity financial distress prediction by estimating models using Logistic Regression, Random Forests, Gradient Boosting (XGBoost and Catboost), and Artificial Neural Networks. Shapley’s Additive Explanations (SHAP) framework is used for modeling result interpretation and validation. Findings...

Phone calls and text messages provide metadata, and Telecom companies record these communications as Call Detail Records (CDR). Using anonymized CDR datasets enables mappings and early decisions in various domains, including public health. Thus, both transmitted and non-transmitted diseases spatio-temporal models may be improved. These CDR data can...

Many industrial sectors are moving toward Industry Revolution (IR) 4.0. In this respect, the Internet of Things and predictive maintenance are considered the key pillars of IR 4.0. Predictive maintenance is one of the hottest trends in manufacturing where maintenance work occurs according to continuous monitoring using a healthiness check for proce...

This paper explores the challenges of today’s labor market service provision in the EU, where, based on our expertise, insufficient scientific inquiry has been conducted. As there are many different focus points and factors to consider in the modern turbulent labor market, we identify the main challenges along with a list of existing scientific dis...

Globally, lower fertility rates combined with increased life expectancy and the transition of “baby boomers” toward retirement have contributed to an aging population in many societies. Ultimately, these demographic developments contain immense societal and economic implications for the public and private sectors. Subsequently, the term “Silver Eco...

The Smart grid designates an innovative technology integrating new information and communication technologies to modernize the energy distribution network and facilitate the transmission of consumption and billing data between production and distribution points. However, the data transmission over the network allows attackers to listen to and subse...

This study investigated the effectiveness of using the Kahoot! game in developing the cognitive achievement and direction of students of pharmacy at Alasmarya Islamic University, Libya. The study design is based on action research. Kahoot! was implemented once at the end of each of three units. The study sample consisted of 30 female students from...

The adoption of ICT in classrooms is very important in order to improve education quality, promote effective management of knowledge, and improve delivery of knowledge in higher education. Some of the Libyan universities have already started using E-learning in classrooms, but many challenges are still hindering that adoption. This paper endeavors...

This study investigated the effectiveness of using the Kahoot! game in developing the cognitive achievement and direction of students of pharmacy at Alasmarya Islamic University, Libya. The study design is based on action research. Kahoot! was implemented once at the end of each of three units. The study sample consisted of 30 female students from...

This research proposal explores how citizen-centered learning and career advancement can benefit from artificial intelligence, occupational classification frameworks, and the concept of proactive services. In the current literature, there are a lot of machine learning methods used in various job and training recommendation systems to tackle scienti...

With more than one billion monthly active users and nearly 100 million photos shared on the platform daily, Instagram has become among the richest sources of information for detecting users’ interests and trends. However, research works on this social network are limited compared to its competitors, e.g., Facebook and Twitter. There is no doubt tha...

For a natural language, morphology is the basic layer over which the higher syntactic and semantic layers are built. Several works relating the Arabic language morphology have been proposed to produce a practical morphological analyzer. However, the latter doesn’t consider the words-agglutination in the same syntagmatic unit. This paper attempts to...

The Internet-of-Things (IoT) edge allows cloud computing services for topology and location-sensitive distributed computing. As an immediate benefit, it improves network reliability and latency by enabling data access and processing rapidly and efficiently near IoT devices. However, it comes with several issues stemming from the complexity, the sec...

In recent years, the development of intelligent transportation systems (ITS) has involved the input of various kinds of heterogeneous data in real time and from multiple sources, which presents several additional challenges. Studies on Data Fusion (DF) have delivered significant enhancements in ITS and demonstrated a substantial impact on its evolu...

Traffic congestion is of utmost importance for modern societies due to population and economic growth. Thus, it contributes to environmental problems like increasing greenhouse gas emissions and noise pollution. Traffic signal control plays a vital role in improving traffic flow in urban networks. Hence, optimizing cycle timing at many intersection...

Call Detail Records (CDRs) provide metadata about phone calls and text message usage. Many studies have shown these CDR data to provide gainful information on people's mobility patterns and relationships with fine-grained aspects, both temporal and spatial elements. This information allows tracking population levels in each country region, individu...

The fifth-generation (5G) mobile network services have made tremendous growth in the Internet of Things (IoT) network. A counters number of battery-powered IoT devices are deployed to serve diverse scenarios, e.g., smart cities, autonomous farming, smart manufacturing, to name but a few. In this context, energy consumption became one of the most cr...

NoSQL stores have become ubiquitous since they offer a new cost-effective and schema-free system. Although NoSQL systems are widely accepted today, Business Intelligence & Analytics (BI&A) wields relational data sources. Exploiting schema-free data for analytical purposes is a challenge since it requires reviewing all the BI&A phases, particularly...

Statistical reasoning was one of the earliest methods to draw insights from data. However, over the last three decades, association rule mining and online analytical processing have gained massive ground in practice and theory. Logically, both association rule mining and online analytical processing have some common objectives, but they have been i...

Artificial Intelligence (AI) in the public and private sectors create new opportunities worldwide. One of such domains where the elements of AI play a critical role are recommendation systems related to finding a new job and offering training suggestions. Based on current literature, only a few attempts are made to implement intelligent recommendat...