Mohamed Jmaiel

Digital Research Center of Sfax · Computer Science

This paper presents RL4CEP, a reinforcement learning (RL) approach to dynamically update complex event processing (CEP) rules. RL4CEP uses Double Deep Q-Networks to update the threshold values used by CEP rules. It is implemented using Apache Flink as a CEP engine and Apache Kafka for message distribution. RL4CEP is a generic approach for scenarios...

Defined as an agreement between multiple parties and systematically executed by a computer code, smart contracts enable trust-less execution without a third party. Despite the trusted implementations that smart contracts offer, including those based on standards, different security problems and vulnerabilities arise during their development and exe...

Elasticity is an essential treatment in Cloud environment employed in academic and industrial contexts. The main purpose of elasticity is to reduce the deployment cost while optimizing computing resources. Multiple studies were conducted to tackle classic applications using monolithic architecture deployed with virtual machines (VMs). However, with...

Maximizing the energy saving is one of the most important metrics in 5G and Beyond (B5G) cellular mobile networks. In order to satisfy the diverse requirements of 5G/B5G in dynamic environments, Reinforcement Learning (RL) is proven as a viable approach for solving resource management problems, especially for 5G energy resources. In this paper, we...

Electrocardiogram (ECG) data collection during emergency situations is challenging, making ECG data generation an efficient solution for dealing with highly imbalanced ECG training datasets. In this paper, we propose a novel approach for ECG signal generation using Generative Adversarial Networks (GANs) and statistical ECG data modeling. Our approa...

In this paper, we present a systematic literature review on deep generative models for physiological signals, particularly electrocardiogram, electroencephalogram, photoplethysmogram and electromyogram. Compared to the existing review papers, we present the first review that summarizes the recent state-of-the-art deep generative models. By analysin...

Blockchain-based applications are basically built on smart contracts, which are widely different in regards of the encoded logic and the used standards. When talking about Ethereum standards, ERC-721 is a well-known standard interface developed for Non-Fungible Tokens. Even though it is standard-based contracts that are more and more exploited, pri...

Global digital health inventories can enhance evidence- based decision making, foster collaboration, mitigate duplicated efforts, and facilitate learning from existing experiences among stakeholders in the digital health ecosystem. However, given the diverse range of stakeholders, such as policymakers, solutions developers and investors, and their...

In recent years, deep generative models have gained attention as a promising data augmentation solution for heart disease detection using deep learning approaches applied to ECG signals. In this paper, we introduce a novel approach based on denoising diffusion probabilistic models for ECG synthesis that covers three scenarios: heartbeat generation,...

Access control management in IoT environment faces big challenges. Unfortunately, it is hard to implement current access control standards on smart objects due to the complexity of access control solutions and the limited capacities of IoT devices. The problem becomes harder when these IoT devices belong to different organisations and need to inter...

Service providers provision more and more Internet-of-Things (IoT) services in the cloud for dynamicity and cost-effectiveness purposes. This is made possible thanks to the introduction of edge computing that brings additional computing and resources for analytics close to the data sources and thus enables meeting the low latency requirement. Edge...

Security faces huge challenges in Internet of Things (IoT) environments. In particular, conventional access control standards and models tend to be less tailored for IoT due to the constrained nature of smart objects. Usually, a powerful third party is used to handle the access control logic. However, this third party is lacking in transparency and...

Due to the advancements of deep learning (DL), particularly in the areas of visual object detection and convolutional neural networks (CNN), insect detecetion in images has received a lot of attention from the research community in the last few years. This paper presents a systematic review of the literature on the topic of insect detection as a ca...

Due to the difficulty of collecting electrocardiogram (ECG) data during emergency situations, ECG data generation is an efficient solution for dealing with highly imbalanced ECG training datasets. However, due to the complex dynamics of ECG signals, the synthesis of such signals is a challenging task. In this paper, we present a novel approach for...

The potential of ICTs to make healthcare more accessible, affordable, and effective has led to a proliferation of innovative ideas which are being implemented in LMICs. Many countries do not have repositories of these systems, consequently it is hard to know when efforts are duplicated by different innovations. There are also cases where differen...

Le domaine de la ré-identification de personnes représente un défi dans le sec-teur de la vidéo surveillance puisqu'il rencontre plusieurs problèmes liés à la variations de la posture, de la luminosité et de l'arrière plan. Pour minimiser l'effet de ces variations, nous proposons dans cet article un système de ré-identification multi-flux basé sur...

When dealing with cloud services, there are important security requirements that are highly recommended to be achieved, notably, access control. Cloud services have provided several mechanisms based on traditional solutions for access management. All have ultimately failed as forgery-proof methods. Reality is a word replete with unauthorized access...

Epilepsy is a neurological disorder, characterized by intractable seizures with severe consequences. To predict these seizures, electroencephalogram (EEG) data has to be collected in a continuous manner. EEG signals are recorded through several electrodes fixed on the scalp that can not be worn by a patient in a continuous manner. This paper presen...

On 30 January 2020, the World Health Organization announced a new coronavirus, which later turned out to be very dangerous. Since that date, COVID-19 has spread to become a pandemic that has now affected practically all regions in the world. Since then, many researchers in medicine have contributed to fighting COVID-19. In this context and given th...

This research paper sets forward an autoscaler, called EPMA, (Elastic Platform for Microservice-based Applications). Its main objective corresponds to resource optimization. The basic contributions of EPMA are twofold. First, an analysis module that correctly detects and identifies the root cause of performance degradation while considering a cross...

The explosion of traffic demand combined with increasingly complex heterogeneous network (HetNet) infrastructures, has presented ever more challenges for mobile network operators such as QoS, autonomous network management and energy efficiency (EE). In this paper, we present an energy-efficient solution considering the Self-Organizing Network (SON)...

Person re-identification still facing several challenges related to many factors such as complex poses, occlusion, misalignment and bad detection. Recent works in the literature focus on extracting local information from the human body but most of them rely on full supervision during training. We propose in this paper a new end-to-end trainable neu...

Energy-saving (ES) is becoming one of the most challenging tasks that fifth-generation (5G) tends to tackle. The problem of identifying the optimal set cells to be turned off is nondeterministic polynomial time-hard. In this research article, we use heuristic algorithms to save energy in 5G heterogeneous networks (HetNet). Our approach is based o...

This paper proposes a novel software architecture for developing disease registries. Our proposal consists of five horizontal layers and two transversal layers. It takes into account several aspects of disease registries, such as various sources of data acquisition, security and privacy issues, data analytics, and user management tasks. Several use...

Self-Organizing Network (SON) stands for a key concept characterizing the behavior of the future mobile networks. The evolution of telecom infrastructures towards 5G transforms the network management from the traditional and static processes to automatic and dynamic ones. SON was proposed to offer agile on-demand services to the users through provi...

Globalization pressure on organizations calls for new approaches to survive, grow, and compete. An approach is to allow inter-organizational business processes (IOBP) collaboration where each partner would expose its public know-how without putting its private know-how at-risk nor impeding this collaboration from happening. Private processes would...

The COVID‐19 pandemic has emerged as a highly transmissible disease which has caused a disastrous impact worldwide by adversely affecting the global economy, health, and human lives. This sudden explosion and uncontrolled worldwide spread of COVID‐19 has revealed the limitations of existing healthcare systems regarding handling public health emerge...

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...

The affiliations of the first two volume editors were incorrect. They were corrected to: Chawki Djeddi Larbi Tebessi University Tebessa, Algeria Yousri Kessentini Digital Research Center of Sfax Sfax, Tunisia

In this paper, we focus on the hierarchical multi-label classification task of scientific papers, which consists in assigning to a paper the set of relevant classes, which are organized in a hierarchy. The difficulty of manually constructing sufficient labeled datasets renders challenging the automatic classification task of research papers accordi...

The field of person re-identification remains a challenging topic in video surveillance and public security because it is facing many problems related to the variations of the position, background and brightness scenes. In order to minimize the impact of those variations, we introduce in this work a multi-stream re-identification system based on th...

This book constitutes the refereed proceedings of the 4th Mediterranean Conference on Pattern Recognition and Artificial Intelligence, MedPRAI 2020, held in Hammamet, Tunisia, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 24 revised papers presented were thoroughly reviewed and selected from 72 submissions. The...

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...

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...

Although recognized as effective measures to curb the spread of the COVID19 outbreak, social distancing and home confinement have generated a mental health burden with older adults who are considered to be more vulnerable to psychosocial strains. To date, the application of digital technologies in response to COVID-19 pandemic has been narrowed to...

In service-oriented environments, abstract business processes can be implemented by concrete services to build complex applications. Given global user constraints, service selection allows to identify the best combination of services with respect to the business constraints. Generally, the selection problem is challenging, but it is particularly co...

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...

This paper focuses on the problem of the hierarchical multi‐label classification of research papers, which is the task of assigning the set of relevant labels for a paper from a hierarchy, using reduced amounts of labelled training data. Specifically, we study leveraging unlabelled data, which are usually plentiful and easy to collect, in addition...

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...

In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors. This paper presents a new approach, called Q-Rank, to predict the sen...

The Internet of Medical Things (IoMT) represents a network of implantable or wearable medical devices that continuously collect medical data about the patient’s health status. These data are heavy, sensitive and require high level of security. With the emergence of blockchain technology, researchers are focusing on using blockchain strategies to br...

In response to the researchers need in the bio-medical domain, we opted for automating the bibliographic research stage. In this context, several classification models of supervised machine learning are used. Namely the SVM, Random Forest, Decision Tree, KNN, and Gradient Boosting. In this paper, we conduct a comparative study between experimental...

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...

Cloud is an increasingly popular computing paradigm that provides on-demand services to organizations for deploying their business processes over the Internet as it reduces their needs to plan ahead for provisioning resources. Cloud providers offer competitive pricing strategies (e.g., on-demand, reserved, and spot) specified based on temporal cons...

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 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...