Faiez Gargouri

University of Sfax | US · Higher Institute of Computer Sceince and Multimedia of Sfax (ISIM)

Data is expanding at a rapid pace these days, and dealing with it has become incredibly challenging. Since they allow for the storage of various data structures, NoSQL graph databases are becoming more popular. Nonetheless, due to their schema-less nature, improper data migration and manipulation during the query phase might result in significant d...

Currently, the blooming growth of social networks such as Facebook, Twitter, Instagram, etc., has generated and is still generating a big amount of data, which can be regarded as a gold mine for business analysts and researchers where several insights that are useful and essential for effective decision making have to be provided. However, multiple...

The evolution of different techniques for exploring cerebral activity and the development of signal processing and analysis methods have enabled a better understanding of the dynamic cerebral mechanisms in favor of fine diagnosis and characterization of certain diseases such as dementia and epilepsy. Integration of functional magnetic resonance ima...

As the amount of information exceeds the management and storage capacity of traditional data management systems, several domains need to take into account this growth of data, in particular the decision-making domain known as Business Intelligence (BI). Since the accumulation and reuse of these massive data stands for a gold mine for businesses, se...

Over the last few years, NoSQL databases have been a key for several problems for storing Big Data sources as well as implementing data warehouses (DW). With decisional systems, NoSQL column-oriented structure can provide relevant results for storing a multidimensional structure, where the relational databases cannot be able to handle the semi-stru...

This research article aims to apply the Business Process Model and Notation (BPMN) for the representation of Sensitive Business Processes (SBPs). Therefore, we propose a new extension “BPMN4SBP” explicitly integrate all the relevant issues and aspects relevant at the coupling of the business process modeling (BPM) domain and the knowledge managemen...

The description of the audiovisual documents aims essentially at providing meaningful and explanatory information about their content. Despite the multiple efforts made by several researchers to extract descriptions, the lack of pertinent semantic descriptions always persists. We introduce, in this paper, a new approach to improve the semantic desc...

Temporal data (TD) in Semantic Web are affected by different types of imperfections principally conflict. In the literature, most of the proposed approaches deal with perfect TD. However, to our knowledge, there is no approach to dealing with conflicting TD. In this paper, we propose an approach to represent and reason about quantitative conflictin...

This research article proposes a conceptual solution for the Sensitive Business Processes (SBPs). It aims at systematically developing a valid and rigorous BPMN extension, called “BPMN4SBP”, supporting the multi-dimensional modeling of SBPs (i.e., the knowledge, functional, organizational, behavioral, informational and intentional dimensions). The...

Artificial neural networks (ANNs) are being widely used in supervised machine learning to analyze signals or images for many applications. Using an annotated learning database, one of the main challenges is to optimize the network weights. A lot of work on solving optimization problems or improving optimization methods in machine learning has been...

The digitalization of health data and the innovative eHealth technologies has created a new paradigm shift from traditional medicine methods to a new predictable, individualized medicine based on patient-centric approaches. The emerging fields of predictive and precision medicine are evolutionary methods to treat the disease based on the patient's...

Dealing with imperfect temporal data entries in the context of Collective and Personal Memory applications is an imperative matter. Data are structured semantically using an ontology called “Collective Memo Onto”. In this paper, we propose an approach that handles temporal data imperfections in OWL 2. We reduce to four types of imperfection defined...

Efficient and accurate early prediction of Alzheimer's disease (AD) based on the neuroimaging data has attracted interest from many researchers to prevent its progression. Deep learning networks have demonstrated an optimal ability to analyse large-scale multimodal neuroimaging for AD classification. The most widely used architecture of deep learni...

Personalised medicine is a new approach that ensure a tolerant and optimal diagnosis for the patient basing on his own data and its profile information such as life style, medical history, genetic data, behaviours, and his environment. These data is vital to predict the potential disease progression. Extracting insights from these heterogeneous dat...

Enterprise Information System (EIS) must cover the interoperability criteria inside its “application view” scope. Nevertheless, the urbanization approach, on which we rely to implement this EIS, has to deal with “horizontal fit” and “traversal fit” problems: lack of intra and inter-applicative communications problems. To overcome these deficiencies...

The urbanization approach, on which we rely to implement an Information System (IS), has to deal with “vertical fit” problems: lack of flexibility and lack of interoperability. To overcome this failure, we show in this paper our solutions to reduce the gap between business and technical infrastructures of any IS, particularly the Bid Process Inform...

Enterprise Information Systems (EIS) supporting business processes are to be characterized by integrity, flexibility, and interoperability. Nevertheless, the urbanization approach, on which we rely to implement business and technical infrastructures levels of any EIS, has to deal with “three fit” problems: “vertical fit” problems – concerning the b...

The Accurate and the early detection of the neurodegenerative brain disorders such as the Alzheimer’s disease(AD) is crucial today for an effective patient care and prevention of disease progression. Computer Assisted Diagnosis (CAD) based on the neuroimaging data is an active research that was enhanced recent years by the deep learning methods. Br...

In supervised Machine Learning (ML), Artificial Neural Networks (ANN) are commonly utilized to analyze signals or images for a variety of applications. They are increasingly performing as a strong tool to establish the relationships among data and being successfully applied in science due to their generalization ability, noise and fault tolerance....

Augmented, Virtual and Mixed Reality Technology (AR / VR / MR) - also known as xR technology - is one of the key technologies of digital transformation. Thanks to the existing powerful immersive hardware systems, complex technical and natural systems can be digitally represented in a realistic virtual environment. This enables users to completely i...

Extended Reality technology (xR) contains Augmented, Virtual and Mixed Reality Technology (AR / VR / MR) is one of the key technologies of digital transformation. Thanks to the existing powerful immersive hardware systems, complex technical and natural systems can be digitally represented in a realistic virtual environment. This enables users to co...

The extraction of description is important in audio-visual document retrieval. Although various approaches were proposed, extracting semiotic description that reflect the content knowledge remains a challenging task. This paper proposes an approach for describing external and a semiotic description of audio-visual document. The main objective is to...

Since December 2019, we have detected the appearance of a new virus called COVID-19, which has spread, throughout the world. Everyone today, has given major importance to this new virus. Although we have little knowledge of the disease, doctors and specialists make decisions every day that have a significant impact on public health. There are many...

Reading and interpreting the medical image still remains the most challenging task in radiology. Through the important achievement of deep Convolutional Neural Networks (CNN) in the context of medical image classification, various clinical applications have been provided to detect lesions from Magnetic Resonance Imaging (MRI) and Computed Tomograph...

The massive use of ontologies generates a large amount of semantic data. To facilitate their management, persistent solutions for storing and querying these semantic data loads have been proposed. This gave rise to a new type of databases, called ontology-based databases (OBDB). In recent years, the need for data and real-time services has increase...

Enterprise Information System (EIS) must cover the interoperability criteria inside its “application view” scope. Nevertheless, the urbanization approach, on which we rely to implement this EIS, has to deal with “horizontal fit” and “traversal fit” problems: lack of intra and inter-applicative communications problems. To overcome these deficiencies...

Typically, to implement a data warehouse, we have to extract the data from relational databases, XML files, etc., which are very used by companies. Since today’s data are generated from social media, GPS data, sensor data, surveillance data, etc., which are maintained in NoSQL databases, we are talking about big data warehouses (BDW). Hence, there...

With the proliferation of textual data on the web, efficient access to pertinent information to meet user’s needs becomes an important problem in information retrieval field. Semantic relationships between terms plays an important role in information retrieval field in order to disambiguate document content.

Modern graph database management systems use graph structures for semantic queries with nodes, edges, and properties to connect to and store information. Due to their schema-less nature, inappropriate data migration and manipulation can lead to severe data loss during the data query process. Data migration in graph databases strongly depends on gra...

Latest research studies on multi-dimensional design have combined business data with User-Generated Content (UGC). They have integrated new analytical aspects, such as user’s behavior, sentiments, opinions or topics of interest, to ameliorate decisional analysis. In this paper, we deal with the complexity of designing topics dimension schema due to...

Dealing with temporal data imperfections in Semantic Web is still under focus. In this paper, we propose an approach based on the possibility theory to represent and reason about time intervals that are simultaneously uncertain and imprecise in OWL2. We start by calculating the possibility and necessity degrees related to the imprecision and uncert...

Temporal data given by Alzheimer's patients are mostly uncertain. Many approaches have been proposed to handle certain temporal data and lack uncertain ones. This paper proposes an approach to represent and reason about quantitative time intervals and points and qualitative relations between them. It is suitable to handle certain and uncertain temp...

Background: The COVID-19 lockdown could engender disruption to lifestyle behaviors, thus impairing mental wellbeing in the general population. This study investigated whether sociodemographic variables, changes in physical activity, and sleep quality from pre- to during lockdown were predictors of change in mental wellbeing in quarantined older ad...

Nowadays, the virtual learning environment has become an ideal tool for professional self-development and bringing courses for various learner audiences across the world. There is currently an increasing interest in researching the topic of learner dropout and low completion in distance learning, with one of the main concerns being elevated rates o...

Performance is one of the major topics for organizations seeking continuous improvements. Evidently, evaluating the performance of business process model is a necessary step to reduce time, cost and to indicate whether the company goals are successfully achieved or not. In the literature, several researchers refers to different techniques that aim...

This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021. The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems...

Aims Prognosis of lung mathology severity after Covid-19 infection using chest X-ray time series Background We have been inspired by methods analysing time series of images in remote sensing for change detection. During the current Covid-19 pandemic, our motivation is to provide an automatic tool to predict severity of lung pathologies due to Covi...

Symptoms of psychological distress and disorder have been widely reported in people under quarantine during the COVID-19 pandemic; in addition to severe disruption of peoples' daily activity and sleep patterns. This study investigates the association between physical-activity levels and sleep patterns in quarantined individuals. An international Go...

The number of audiovisual documents available on the web is exponentially increasing due to the rise of the number of videos produced every day. The recent progress in audiovisual documents field has made it possible to popularize the exchange of these documents in many domains. More generally, the interest in the indexing potential of audiovisual...

Background Public health recommendations and government measures during the COVID-19 pandemic have enforced restrictions on daily-living. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on mental health and emotional wellbeing is undefined. Therefore, an international online survey (ECLB-COVI...

This work proposes a deep learning algorithm based on the Convolutional Neural Network (CNN) architecture to detect HepatoCellular Carcinoma (HCC) from liver DCE-MRI (Dynamic Contrast-Enhanced MRI) sequences. The Deep Learning technique is an artificial intelligence technique (AI) that tries to imitate the human brain work in the training data and...

In this paper, we propose an ontology-based approach for representing and reasoning about certain and uncertain temporal data. It handles temporal data in terms of quantitative time intervals and points and the qualitative relations between them (e.g., “before”). It includes three parts. (1) We extend the 4D-fluents approach with certain ontologica...

The emergence of the Internet of Things (IoT) in the medical field has led to the massive deployment of a myriad of medical connected objects (MCOs). These MCOs are being developed and implemented for remote healthcare monitoring purposes including elderly patients with chronic diseases, pregnant women, and patients with disabilities. Accordingly,...

Public health recommendations and governmental measures during the new coronavirus disease (COVID-19) pandemic have enforced numerous restrictions on daily living including social distancing, isolation, and home confinement. While these measures are imperative to mitigate spreading of COVID-19, the impact of these restrictions on psychosocial healt...

Although recognised as effective measures to curb the spread of the COVID-19 outbreak, social distancing and self-isolation have been suggested to generate a burden throughout the population. To provide scientific data to help identify risk factors for the psychosocial strain during the COVID-19 outbreak, an international cross-disciplinary online...

Enterprise Information Systems supporting business processes are to be characterized by integrity, flexibility, and interoperability. Nevertheless, the “three fit” problems (considered in the current paper) obstruct the achievement of those desired features both at the business-infrastructure and technical-infrastructure EIS levels: “vertical fit”...

Making the most from virtual learning environments captivates researchers, enhancing the learning experience and reducing the withdrawal rate. In that regard, this article presents a framework for a withdrawal prediction model for the data of the Open University, one of the largest distance-learning institutions. The main contributions of this work...

COVID-19 pandemic have resulted in numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifestyles at home is undefined. Therefore, an international online survey was launche...

Background: Public health recommendations and governmental measures during the COVID-19 pandemic have resulted in numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifest...

Background Public health recommendations and governmental measures during the COVID-19 pandemic have enforced numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to mitigate spreading of COVID-19, the impact of these restrictions on psychosocial health is undefined....

Background: Although recognised as effective measures to curb the spread of the COVID-19 outbreak, social distancing and self-isolation, have been suggested to generate burden throughout the population. To provide scientific data to help identify risk-factors for the psychosocial strain during the COVID-19 outbreak, an international cross-discipli...

Background: Public health recommendations and government measures during the COVID-19 pandemic have enforced restrictions on daily living, which may include social distancing, remote work/school, and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on mental health and emoti...

Background Public health recommendations and governmental measures during the COVID-19 pandemic have enforced numerous restrictions on daily living including social distancing, isolation and home confinement. While these measures are imperative to abate the spreading of COVID-19, the impact of these restrictions on health behaviours and lifestyle a...

Humanity is facing nowadays a dramatic pandemic episode with the Coronavirus propagation over all continents. The Covid-19 disease is still not well characterized, and many research teams all over the world are working on either therapeutic or vaccination issues. Massive testing is one of the main recommendations. In addition to laboratory tests, i...

Humanity is facing nowadays a dramatic pandemic episode with the Coronavirus propagation over all continents. The Covid-19 disease is still not well characterized, and many research teams all over the world are working on either ther- apeutic or vaccination issues. Massive testing is one of the main recommendations. In addition to laboratory tests,...

Nowadays, the use of the Internet of Things (IoT) in diverse applications becomes very popular. Accordingly, a proliferation of objects with remote sensing, actuation, analysis, and sharing capabilities will be interconnected on top of heterogeneous communication networks. Their deployment contexts are continuously changed, which imply a change in...

Owing to the absolute significance of the business process management, companies have become thoroughly oriented toward a good modeling of the business processes. Although the business process modeling is a substantial part in workflow automation, business process designers often misunderstand domain concepts or relationships due to their lack of p...

Big Data emerged after a big explosion of data from the Web 2.0, digital sensors, and social media applications such as Facebook, Twitter, etc. In this constant growth of data, many domains are influenced, especially the decisional support system domain, where the integration of processes should be adapted to support this huge amount of data to imp...

Before talking about the security tools we must first think about what we should protect and how we should distinguish information that seems to be sensitive and identifiable among heterogeneous data that spread over several sources like Facebook, twitter and several other suppliers of big data. Thus, in this paper we proved a method of identifying...

Big volumes of data cannot be processed by traditional warehouses and OLAP servers which are based on RDBMS solutions. As an alternative solution, Not only SQL (NoSQL) databases are becoming increasingly popular as they have interesting strengths such as scalability and flexibility for an OLAP system. As NoSQL database offer great flexibility, they...

The past few years has seen the rapid growth of educational data mining approaches for the analysis of data obtained from the virtual learning environments (VLE). However, due to the open and online characteristics of VLEs, vast majority of learners may enroll and drop a course freely, resulting in high dropout rates problem. One of the key element...

As one of NoSQL data models, graph oriented databases are highly recommended to store and manage interconnected data. Used as back-end for today applications, NoSQL databases come with the challenge of effectively managing data evolution. In fact, NoSQL graph oriented databases offer a great flexibility. Usually such flexibility helps developers to...

Based on the assumption that users generally tend to use entities proposed by friends rather than strangers and that trust among friends significantly correlates with user’s trends, we decided to refer to research conducted on the evolving field of social trust computation. Although many models were proposed to analyze computational trust for vario...

Enterprise Information System (EIS) must cover the interoperability criterion between its business and technical infrastructures. Nevertheless, the “vertical fit” problems, which has deduced from the business infrastructure handicap the exploitation of this criterion. To overcome this failure, we propose in this paper our solutions to reduce the ga...

Ontology, as a useful knowledge engineering technique, has been widely used for reducing ambiguity and helping with information sharing. It is considered originally to be clear, comprehensive, and with well-defined format. It characterizes several domains purposes description through structured and formalized languages. In various areas of research...

Today eHealth is an emerging area becoming increasingly reliant upon medical information and communication technology. The implementation of an eHealth strategy is important today to meet health goals, notably: promoting the effectiveness of medical data treatment and data retrieval, and improving the information flow between doctors and patients....

Social trust-based recommendation systems are currently based on the computation of the level of trust in users' interactions or on a combination of trust and similarity scores while generating recommendations. In this research paper, we propose a framework for a recommender system that is based on users' preferences on the one hand and on the opin...