M. AKHROUF Samir

Prof

Directory of teachers

Department

Informatics Department

Research Interests

Identification Biométrique Enseignement à distance Analyse des réseaux sociaux Synthèse d'images

Contact Info

University of M'Sila, Algeria

Email : samir.akhrouf@univ-msila.dz

On the Web:

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Recent Publications

2024-12-10

Parallel Association Rules Mining Using GPUs and Reptile Search Algorithm

This paper proposes a novel approach to accelerate association rule mining using the Reptile Search Algorithm (RSA) in conjunction with GPU-based parallel processing. Traditional association rule mining techniques can be computationally expensive, especially with large datasets. By utilizing the inherent parallelism of Graphics Processing Units (GPUs), we significantly speed up the fitness evaluation process, a core component of the Reptile Search Algorithm. Our results show a marked improvement in the performance of RSA on large datasets, making it feasible for real-time or large scale applications such as market basket analysis, healthcare for drug interaction analysis, and web usage mining. We also analyze the impact of various GPU optimizations and present a comparison with CPU-based execution.
Citation

M. AKHROUF Samir, kameleddine.heraguemi@univ-msila.dz, , (2024-12-10), "Parallel Association Rules Mining Using GPUs and Reptile Search Algorithm", [international] The Sixth International Symposium on Informatics and Its Applications (ISIA) , Université Mohamed Boudiaf M'Sila

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2024-10-01

Improving plant disease classification using realistic data augmentation

Recently, several studies have used deep convolutional neural networks (DCNN) for plant disease classification based on leaf symptoms images. Most of these studies use the PlantVillage dataset, which contains simple images with simple backgrounds. This has led to classifiers achieving high accuracy in academic settings but underperforming in practical scenarios where images taken by farmers are much more complex. In this paper, we propose a data augmentation (DA) method that transforms simple images from the PlantVillage dataset into more complex images, thereby bridging the gap between academic results and practical performance. Our technique focuses on making the images more realistic by generating images containing multiple leaves and complex backgrounds, such as soil. To evaluate the impact of our proposed method, we trained DCNN models using various augmentation methods and tested them on a dataset containing highly complex images comparable to those taken by farmers, posing a substantial challenge. The experimental results showed that models trained on images generated by our method outperformed traditional data augmentation methods, such as geometric transformations. Moreover, our method is competitive with Generative Adversarial Networks (GANs) without requiring any training phase.
Citation

M. AKHROUF Samir, wassim.benabbas@univ-bba.dz, mohamed.brahimi@ensia.edu.dz, bilal.fortas@univ-bba.dz, , (2024-10-01), "Improving plant disease classification using realistic data augmentation", [national] Multimedia Tools and Applications , Springer Nature

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2024-08-23

An efficient explainable deep neural network classifier for diabetic retinopathy detection

Early detection of Diabetic Retinopathy (DR) is crucial for effective intervention, particularly given its often
asymptomatic nature in initial stages. Automated detection systems offer significant advantages, such as
improving screening efficiency, extending healthcare accessibility to remote regions, and facilitating proactive
disease management. Introducing an innovative framework for retinal image analysis that combines explainable deep learning, hybrid feature extraction, and advanced data augmentation to optimize performance and interpretability for clinical applications. The xDNN model, trained on the MESSIDOR-2 dataset, achieved an average recall of 98%, precision of 98.2%, F1-score of 98%, and accuracy of 98.2%. When extensively trained on the APTOS 2019 dataset, the model delivered outstanding results with an average precision, recall, and F1-score of 99%, and an accuracy of 99.7%. Additionally, the model’s performance on the IDRID dataset was remarkable, with average precision, recall, F1-score, and accuracy all reaching 99%. Noteworthy is our method impressive average AreaUnder the Curve (AUC) of 99.8%, affirming its consistent and exceptional performance across all classes of diabetic retinopathy. This underscores the xDNN Classifier’s potential as a valuable tool for precise and reliable diabetic retinopathy detection. It holds substantial promise for elevating clinical diagnosis and enhancing treatment outcomes within the field of ophthalmology.
Citation

M. AKHROUF Samir, oualid.mecili@univ-bba.dz, hadj.barkat@gmail.com, attia.abdelouahab@gmail.com, farid.nouioua@gmail.com, , (2024-08-23), "An efficient explainable deep neural network classifier for diabetic retinopathy detection", [national] International Journal of Computers and Applications , Taylor and Francis

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2024-06-01

Reptile Search Algorithm for Association Rule Mining

Association rule mining (ARM) is a very popular, engaging, and active research area in data mining. It seeks to find valuable
connections between different attributes in a defined dataset. ARM, which describes it as an NP-complete problem, creates a fertile field
for optimization applications. The Reptile Search Algorithm (RSA) is an innovative evolutionary algorithm. It yanks stimulation from
the encircling and hunting conducts of crocodiles. It is a well-known optimization technique for solving NP-complete issues. Since its
introduction by Abualigah et al. in 2022, the approach has attracted considerable attention from researchers and has extensively been
used to address diverse optimization issues in several disciplines. This is due to its satisfactory execution speed, efficient convergence
rate, and superior effectiveness compared to other widely recognized optimization methods. This paper suggests a new version of the
reptile search algorithm for resolving the association rules mining challenge. Our proposal inherits the trade-off between local and
global search optimization issues demonstrated by the Reptile search algorithm. To illustrate the power of our proposal, a sequence of
experiments is taken out on a varied, well-known, employing multiple comparison criteria. The results show an evident dominance of
the proposed approach in the front of the famous association rules mining algorithms as well as Bees Swarm Optimization (BSO), Bat
Algorithm (BA), Whale Optimization Algorithm (WOA), and others regarding CPU time, fitness criteria, and the quality of generated
rules.
Citation

M. AKHROUF Samir, kameleddine.heraguemi@univ-msila.dz, , (2024-06-01), "Reptile Search Algorithm for Association Rule Mining", [national] International Journal of Computing and Digital Systems , University of Bahrain

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2024-05-13

Analysis Study of Participant Selection Methods in Federated Learning

To the best of current knowledge, the performance of federated learning predominantly depends on the efficiency of the aggregation server scheme utilized to consolidate model parameters received from distributed local devices. However, in practical scenarios, the global server often faces single-point failures due to four major issues: 1) variations in data distribution settings, such as independent identical distribution (IID) or non-independent identical distribution; 2) communication overhead; 3) limitations in hardware and resource storage availability; and 4) diverse participant participation behaviors. To address the latter concern, limited research has endeavored to establish a correlation between these heterogeneous settings and federated learning performance by analyzing different aspects of participant behavior. Inspired by the absence of a definitive verdict regarding the relationship between the global server and participant behavior, this paper investigates the aspect of participant selection methods and conducts a detailed comparative study among various participant selection methods
Citation

M. AKHROUF Samir, brahim.bouderah@univ-msila.dz, , (2024-05-13), "Analysis Study of Participant Selection Methods in Federated Learning", [international] ICEEAC’2024 , Setif university

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2024-05-08

مخاطر استعمال منصات التواصل الاجتماعي

في عالمنا المتسارع اليوم، أصبحت منصات التواصل الاجتماعي وسيلة أساسية للتواصل والتفاعل بين الناس. فهي تتيح لنا الاتصال بأصدقائنا وعائلتنا، والتعرف على ثقافات جديدة، والمشاركة في المناقشات والأفكار المختلفة.
Citation

M. AKHROUF Samir, (2024-05-08), "مخاطر استعمال منصات التواصل الاجتماعي", [national] اليوم التحسيسي ضد الأخطار المتعلقة باستعمال وسائل التواصل الاجتماعي الأربعاء 08 ماي 2024 , Université Mohamed Boudiaf M'Sila

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2024-04-24

Efficient Machine Learning Approach for Diabetes Mellitus Disease Prediction

Diabetes mellitus, a widely recognized chronic disease often termed a silent killer, disrupts insulin production, leading to elevated blood sugar levels and complications affecting organs including the eyes, kidneys, and nerves. Despite significant research interest, diabetes classification-based machine learning methods suffer from low performance due to missing data and imbalanced class data. Thus, this paper introduces a new method for Diabetes Mellitus classification for Imbalanced data with Missing values (DMIM). The proposed approach involves these key steps. Firstly, missing values are preprocessed using the Isolation Forest method that provides data normalization. Then, an adaptive synthetic sampling technique, Smote T-link, is employed to counter the impact of class imbalance. Finally, we utilized a Random Forest (RF) classifier and conducted experiments on the Pima Indians diabetes dataset from the University of California. Our proposed approach yielded highly accurate predictions, as evidenced by impressive performance metrics such as an Area Under the Curve (AUC) of 97.2%, Specificity (SP) of 91.7%, and Recall (Rec) of 92.3%, Further comparison between other ML methods including k-nearest Neighbors, Decision Trees, Random Forest, AdaBoost, Naive Bayes, XGBoost, Extra Trees. The results demonstrate the effectiveness and superiority of our proposed method and improved diabetes classification performance compared to existing techniques.
Citation

M. AKHROUF Samir, mecilioualid@gmail.com, hadj.barkat@gmail.com, farid.nouioua@gmail.com, attia.abdelouahab@gmail.com, , (2024-04-24), "Efficient Machine Learning Approach for Diabetes Mellitus Disease Prediction", [international] Conference: 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS) , El OUED Algérie

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2023-12-06

A Conceptual Framework for Identifying Influential Users in Online Social Networks for Viral Marketing

The emergence of so many online social networks (OSNs), such as Twitter, YouTube...etc, has significantly altered the global landscape of human connections and interactions. OSNs have become an integral part of people’s lives and have led to an explosion in the volume and variety of information available for research and analysis. In social network analysis (SNA), Influential user identification in OSN involves detecting users who have a significant impact on information dissemination and network dynamics is a fundamental research task. It plays an important role in different domains such as political movements, health applications, innovation dissemination, news spreading, and viral marketing. In this paper, we introduce a theoretical framework for identifying influential users based on both structural and behavioral factors of online social networks. We first present the problem statement and provide a review of pertinent background knowledge. Subsequently, our proposed framework is explained and discussed.
Citation

M. AKHROUF Samir, Baabcha Halima, Meriem Laifa, , (2023-12-06), "A Conceptual Framework for Identifying Influential Users in Online Social Networks for Viral Marketing", [international] THE 6TH INTERNATIONAL HYBRID CONFERENCE ON INFORMATICS AND APPLIED MATHEMATICS IAM’23 , Guelma Algeria

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2023-10-03

Influencers Detection in Online Social Network

Online social networks (OSNs) have become an integral part of people's daily lives, resulting in a vast amount and diversity of information available for research and analysis. Detecting influential users is a significant research topic in social network analysis (SNA), and it‘s played a crucial role in information dissemination within OSNs. It has various applications, including viral marketing. In this short paper, we describe our thesis subject by explaining the context, research objectives, and motivations. Subsequently, we present our proposed approach and research methodology.
Citation

M. AKHROUF Samir, Baabcha Halima, Laifa Meriem, , (2023-10-03), "Influencers Detection in Online Social Network", [national] The 1st National Conference on New Educational Technologies and Informatics NCNETI'23 , Guelma Algeria

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2023-07-15

A Survey on Using Evolutionary Approaches-Based High-Utility Itemsets Mining

Frequently item-sets mining, also known as FIM, is a data mining technique used to extract useful knowledge from datasets. FIM is plagued by a number of issues, including high storage charges, a huge time and memory consumption. Classical FIM algorithms suffer with the great number of generated itemsets which contains useless items. And presupposes that all itemsets have the same importance. To deal with these limitations, high-utility itemsets (HUI) is proposed, which are as subset of FIM with the consideration of Utility or profit measure. In the last decade, evolutionary approaches become a trend to solve HUIs mining problem (EA). This paper explores the use of evolutionary techniques in HUIs mining. Moreover, we present an evolutionary techniques-based HUIs mining classification including single objective, multi-objective and Hybrid optimization techniques. This article provides a comparative examination of methodologies and discusses theoretical features of a wide variety of algorithms that are inspired by nature.KeywordsHUIs miningBio-inspired algorithmsEvolutionary approaches
Citation

M. AKHROUF Samir, Abderrahim Boukhalat, Kameleddine Heraguemi, Mouhamed Benouis, Bouderah brahim, , (2023-07-15), "A Survey on Using Evolutionary Approaches-Based High-Utility Itemsets Mining", [international] Artificial Intelligence Doctoral Symposium , Alger

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2023

SATISFACTION OF STUDENTS AND TEACHERS WITH BLENDED LEARNING DURING COVID-19 PANDEMIC: AN ALGERIAN CASE STUDY

The conversation on the effectiveness of blended learning experience in Algerian higher education has not received the necessary attention compared to developed countries. Moreover, there is a scarcity of research that discusses the impact and benefits of the pandemic-induced changes in Algerian higher education. The primary goal of this paper is to initiate a deeper conversation about blended learning in Algerian Higher Education using an exploratory research method based on empirical evidence and quantitative data. It examines teachers’ and students’ satisfaction with blended teaching and learning at Algerian universities since the start of Covid-19. There was a total of 782 students and 82 teachers involved with valid questionnaire responses, from two different Algerian public universities. The data were examined using descriptive and inferential statistical analysis, such as independent t-test, Mann-Whitney U-test, Kruskal-Wallis test, and one-way ANOVA. The results indicate low satisfaction with blended learning on both sides: students and teachers. Furthermore, the data do not suggest differences in satisfaction between teachers and students, either in terms of the program taught or the university to which they belong. However, there were significant differences among students based on their age and their level of study. The paper also discusses the values, benefits, and restrictions of the mandatory blended learning approach applied by the Algerian ministry since March 2020. Implications and recommendations for both practitioners and researchers are additionally addressed in this study to make informed pedagogical choices in the future.
Citation

M. AKHROUF Samir, Meriem Laifa, Mohdeb Djamila, Belazzoug Mouhoub, , (2023), "SATISFACTION OF STUDENTS AND TEACHERS WITH BLENDED LEARNING DURING COVID-19 PANDEMIC: AN ALGERIAN CASE STUDY", [national] International Journal of Learning Technology , Inderscience

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Blended Learning in Algeria: Assessing Students’ Satisfaction and Future Preferences Using SEM and Sentiment Analysis

Given the still-existing restrictions of COVID-19, blended learning is undoubtedly becoming a better-fitting strategy for higher education institutions in underprivileged countries. Acknowledging the current changes in higher education, this study aims to investigate the elements that influence students’ satisfaction and their future preferences regarding blended learning in Algeria. A total of 782 questionnaires were collected from different Algerian universities. A structural Equation Modeling (SEM) analysis was conducted to investigate the relationship among the latent variables of the proposed theoretical model. Moreover, an unsupervised sentiment analysis approach was applied to analyze the qualitative data received as feedback from the participants. The results show that students perceived ease of use and perceived usefulness of blended learning had a significant positive impact on their satisfaction. Similarly, satisfaction had a positive influence on students’ future preferences regarding blended learning. In turn, students’ perceived ease of use and usefulness indirectly affected their future preferences, mediated by satisfaction. Additionally, qualitative data echoed students’ eagerness to adopt more advanced learning technologies and what obstacles currently stand in their way. The contribution of this study is to reflect the current situation of blended learning adoption in developing countries and to support future curriculum planning and development. It can also help teachers, students, and policymakers to make better decisions and recommendations for an improved and more sustainable learning and teaching environment in the future.
Citation

M. AKHROUF Samir, Meriem Laifa, Roya Imani Giglou, , (2023), "Blended Learning in Algeria: Assessing Students’ Satisfaction and Future Preferences Using SEM and Sentiment Analysis", [national] Innovative Higher Education , Springer Nature

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Artificial Orca Algorithm for Solving University Course Timetabling Issue

Timetabling problems for university courses (UCTP) is one of the most traditional challenges many researchers have emphasized for a long time. This issue belongs to NP-Hard problems, which are hard to solve with classical algorithms due to their complexity. Swarm intelligence has become a trend to solve NP-hard problems and real-life issues. This paper proposes a new-based Artificial Orca Algorithm (AOA) solver for university course timetabling problems. In order to evaluate our proposal, A series of are carried out on Ghardaia University Timetabling data, and the performance of the proposed approach is evaluated and compared with other algorithms developed to solve the same problem. The results show a clear superiority of our proposal over the others in terms of execution time and result in quality.KeywordsUniversity course timetablingArtificial Orca Algorithm (AOA)Metaheuristics
Citation

M. AKHROUF Samir, (2023), "Artificial Orca Algorithm for Solving University Course Timetabling Issue", [national] Artificial Intelligence: Theories and Applications , Springer Sham

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Fast approach for link prediction in complex networks based on graph decomposition

Social networks such as Facebook, Twitter, etc. have dramatically increased recently. These databases are massive and their use is time-consuming. In this work, we present an optimal calculation in graph mining for link prediction to reduce the runtime. For that purpose, we propose a novel approach that operates on the connected components of a network instead of the whole network. Thanks to this decomposition, we show that the results of all link prediction algorithms using local and path-based similarity measures can be achieved with much fewer computations and hence within a much shorter runtime. We show that this gain depends on the distribution of nodes in components and may be captured by the Gini and the variance measures. We propose a parallel architecture of the link prediction process based on the connected component's decomposition. To validate this architecture, we have carried out an experimental study on a wide range of well-known datasets. The obtained results clearly confirm the efficiency of exploiting the decomposition of the network into connected components in link prediction.
Citation

M. AKHROUF Samir, (2023), "Fast approach for link prediction in complex networks based on graph decomposition", [national] Evolving Systems , Springer Nature

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2022

Score level fusion of major and minor finger knuckle patterns based symmetric sum-based rules for person authentication

This paper present a novel system for person authentication based on score level fusion of Minor and Major dorsal finger knuckle patterns. In the proposed method, the adaptive single scale retinex method is used to extract the reflectance and the illumination of Major and Minor traits respectively, also the binarized statistical image features method is used to extract normalized histogram features. Furthermore, the Cosine Mahalanobis distance is used in the matching stage. Moreover, a multi-biometric system-based score level fusion has been proposed. In an attempt to enhance performance recognition, the symmetric sum-based rules based on triangular norms are applied. The system is evaluated on the publically Minor/Major knuckle database. Experiments conducted on this database achieved good results. Besides, the proposed system outperforms the previous methods given in the state of the art.
Citation

M. AKHROUF Samir, Hammouche Rabah, Attia Abdelouahab, , (2022), "Score level fusion of major and minor finger knuckle patterns based symmetric sum-based rules for person authentication", [national] Evolving Systems , Springer Nature

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Gabor Filter Bank with Deep Autoencoder based Face Recognition System

These days, face recognition systems are widely being employed in various daily applications such as smartphone unlocking, tracking school attendance, secure online bank transactions, smarter border control, to name a few. In spite of the remarkable progress, face recognition systems still suffer from occlusions, light variations, camera types, and their resolutions. Face recognition is still a dynamic research field. In this paper, we propose an efficient face recognition system based on the Gabor filter bank and a deep learning method known as Sparse AutoEncoder (SAE). The main aim of the proposed system is to improve the features extracted by the Gabor filter bank using the SAE method. Then, these enhanced features are subjected to features reduction using principal component analysis and linear discriminant analysis (PCA+LDA) technique. Finally, the matching stage is accomplished via cosine Mahalanobis distance. Experiments on seven publicly available databases (i.e., JAFFE, AT&T, Yale, Georgia Tech, CASIA, Extended Yale, Essex) show that the proposed system can achieve promising results with the combination of Gabor and SAE, as well as outperform previously proposed methods.
Citation

M. AKHROUF Samir, Hammouche Rabah, Attia Abdelouahab, Akhtar Zahid, , (2022), "Gabor Filter Bank with Deep Autoencoder based Face Recognition System", [national] Expert Systems with Applications , ScienceDirect

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A fuzzy connective score fusion technique for 2D and 3D palmprint authentication system

Palmprint recognition systems have been extensively studied over the past two decades because of their unique, accurate, and stable biometric features. Many researchers have investigated the two-dimensional (2D) palmprint recognition that contains texture information, but the 2D palmprint image does not contain three-dimensional (3D) depth information. To beat the limitations associated with a 2D palmprint recognition system; this paper proposes using both 2D and 3D palmprint features for a personal recognition system. The BSIF and GIST descriptors are utilized for feature extraction from the 2D and 3D palmprint. Then, the PCA + LDA technique is used to reduce the dimensionality of feature vectors. Next, the matching process is done using the Cosine distance. Finally, a score-level fusion was applied to get a final matching score using a fuzzy connective method based on the linear combination of triangular norms (T-norms and T-conforms). Also, the proposed method is compared to several techniques of score fusion, including Sum, Min, Max, and Symmetric Sum based on triangular norms. The system was evaluated on the publicly available Hong Kong-PolyU 2D + 3D palmprint database, and the results show the proposed system's efficiency.
Citation

M. AKHROUF Samir, Attia Abdelouahab, Rabah Hammouche, Zahid Akhthar, , (2022), "A fuzzy connective score fusion technique for 2D and 3D palmprint authentication system", [national] Evolving Systems , Springer Nature

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Toward a New Recursive Model to Measure Influence in Subscription Social Networks: A Case Study Using Twitter

This chapter presents a new version of one of the models that we have proposed to measure the influence of web users on social networks like Facebook. The new version enhanced the previous one through the incorporation of two substantial modules, namely, the global impression that the postings of the potential influencer get from his followers and the entropy which manifests the quantity of information carried by those postings. The comparison of our model with the precedent version and the PageRank benchmark has shown the effectiveness of our updates and the importance of incorporating the entropy and the global impression factors in its formulation.
Citation

M. AKHROUF Samir, (2022), "Toward a New Recursive Model to Measure Influence in Subscription Social Networks: A Case Study Using Twitter", [national] International Conference on Managing Business Through Web Analytics , Springer Sham

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2021

User Similarity and Trust in Online Social Networks: An Overview

During the last decade, traditional interpersonal relationships have been replaced by online communications due to the rapid evolution of online social networks. Trust plays an important role in enhancing interactions and ensuring security in such online communications. The decision to trust a user or not depends on a number of factors such as the similarity between users. The concept of user similarity is used in various fields for different aims. This paper presents an overview of the user similarity concept in an online trust-related context. We present various similarity metrics used by researchers in this field, and we provide a literature classification, including characteristics, data, and applications based on existing well-established studies. Finally, we review related work that focuses on both similarity and trust in online social networks.
Citation

M. AKHROUF Samir, Zouaoui Aya, Laifa Meriem, , (2021), "User Similarity and Trust in Online Social Networks: An Overview", [international] International Conference on “Managing Business through Web Analytics" ICMBWA2020, , Université Djilali Bounaama – Khemis Miliana,

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Social Influence Analysis in Online Social Networks for Viral Marketing: A Survey

The advent of online social networks has been one of the most exciting events in the last years. Their richness in content can be leveraged for analysis; the richness of this network provides unprecedented opportunities for data analytics. Social influence analysis is one of the major research topics in social networks analysis. It can be used in many applications including viral marketing. Modeling influences diffusion and influence maximization in social networks is an important challenging in the area of social network analysis. Furthermore the identification of influential nodes in a social network. There is an abundance of research that has been done regarding influence in online
social networks for various applications, especially in a viral marketing context. In this paper, a survey of the most and recent important methods for influence modeling, maximization, and influential nodes detection. We aim to guide novice researchers by providing them with the leading works on social influence analysis in the context of viral marketing.
Citation

M. AKHROUF Samir, Baabcha Halima, Laifa Meriem, , (2021), "Social Influence Analysis in Online Social Networks for Viral Marketing: A Survey", [international] International Conference on “Managing Business through Web Analytics" ICMBWA2020, , Université Djilali Bounaama – Khemis Miliana,

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A Recursive Model to Measure Influence in Subscription Networks: A Case Study using Twitter.

This paper presents a new version of one of the models that we have proposed to measure the influence of web users in social networks like Facebook. The new version enhanced the previous one through the incorporation of two substantial modules, namely the global impression that the postings of the potential influencer get from his followers and the entropy which manifests the quantity of information carried by those postings. The comparison of our model with the precedent version and the PageRank benchmark has shown the effectiveness of our updates and the importance of incorporating the entropy and the global impression factors in its formulation.
Citation

M. AKHROUF Samir, (2021), "A Recursive Model to Measure Influence in Subscription Networks: A Case Study using Twitter.", [international] International Conference on “Managing Business through Web Analytics" ICMBWA2020, , Université Djilali Bounaama – Khemis Miliana,

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2020

Machine Learning and Deep Learning: Recent Overview in Medical Care

Medical care has always presented quite wide ranged and challenging problems. However, machine learning techniques and methods as well as deep learning never stopped evolving and tackling those challenges issued by medicine, medical and health care. In order to have a more close up look on how machine learning and deep learning has been affecting medical care in general, we review in this paper some machine learning and deep learning techniques used in a variety of medical care sections such as medical imaging, medical decision, diagnostic, medical records and big data, and disease prediction.
Citation

M. AKHROUF Samir, Nour El-Houda Chalabi, Abdelouahab Attia, , (2020), "Machine Learning and Deep Learning: Recent Overview in Medical Care", [international] Internet of Things, Infrastructures and Mobile Applications, Proceedings of the 13th IMCL Conference , springer , Greece

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A SURVEY ON MACHINE AND DEEP LEARNING FOR DETECTION OF DIABETIC RETINOPATHY

Diabetic Retinopathy (DR) is one of the mainly causes of visual loss worldwide. In fact, DR is leading source of impaired vision in people between 25 and 74 years old. DR exists in wide ranged and its detection is a challenging problem. The gradual deterioration of retina leads to DR with several types of lesions, including hemorrhages, exudates, micro aneurysms, etc. Early detection and diagnosis can prevent and save the vision of diabetic patients or at least the progression of DR can be slowed down. The manual diagnosis and analysis of fundus images to substantiate morphological changes in micro aneurysms, exudates, blood vessels, hemorrhages, and macula are usually time-consuming and monotonous task. It can be made easy and fast with the help of computer-aided system based on advanced machine learning techniques that can greatly help doctors and medical practitioners. Thus, the main focus of this paper is to provide a summary of the numerous methods designed for discovering hemorrhages, microaneurysms and exudates are discussed for eventual recognition of non-proliferative diabetic retinopathy. This survey will help the budding researchers, scientists, and practitioners in the field.
Citation

M. AKHROUF Samir, Abdelouahab Attia, Zahid Akhtar, Sofiane Maza, , (2020), "A SURVEY ON MACHINE AND DEEP LEARNING FOR DETECTION OF DIABETIC RETINOPATHY", [national] JOURNAL ON IMAGE AND VIDEO PROCESSING , ICTACT

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A NOVEL SYSTEM BASED ON PHASE CONGRUENCY AND GABOR - FILTER BANK FOR FINGER KNUCKLE PATTERN AUTHENTICATION

The authentication of individuals based on Finger Knuckle print (FKP) is a very interesting system in the biometric community. In this paper, we introduce a biometric authentication system based on the FKP trait which consists of four stages. The first one is the extraction of the Region of Interest (ROI). The Phase Congruency method with Gabor filters bank descriptors has been used in the feature extraction stage. Then to enhance the performance of the proposed scheme the Principle Component Analysis (PCA) + Linear Discriminant Analysis (LDA) method has been used in the dimensionality reduction stage. Finally, cosine Mahalanobis distance has been used in the matching stage. Experiments were conducted on the FKP PolyU Database which are publicly available. The reported results with comparison to previous methods prove the effectiveness of the proposed scheme, as well as the given system can achieve very high performance in both the identification and verification modes.
Citation

M. AKHROUF Samir, Hammouche Rabah, Attia Abdelouahab, , (2020), "A NOVEL SYSTEM BASED ON PHASE CONGRUENCY AND GABOR - FILTER BANK FOR FINGER KNUCKLE PATTERN AUTHENTICATION", [national] ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING , JOURNAL ON IMAGE AND VIDEO PROCESSING

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2019

Special Session Call for Papers Social Networks and Mobile Applications for Health care (SNMAH)

In the last decade advances in wireless technology led to the emergence of a wide range of applications in healthcare, mobile health care, social networking, etc.
Among these applications, health care, mobile health and smart health are considered the most promising and most important, this is mainly due to their positive impact on the quality of life of patients.
Furthermore, mobile health care technology helps improve the quality of care administered to patients providing clinical and critical care in ways that help them follow-up their disease. Therefore, patients can be treated and cared for from anywhere, at any time. In addition mobility helps patients track their recovery with remote monitoring tools and follow what doctors prescribed.
Thus we can conclude that this area of research is very interesting and this is why we intend to propose this special session in order to gather researchers in the field of mobile health care, give them the opportunity to share their ideas and conceptual approaches and finally discuss the recent advances in this field.
Citation

M. AKHROUF Samir, (2019), "Special Session Call for Papers Social Networks and Mobile Applications for Health care (SNMAH)", [international] IMCL 2019 , Thessaloniki Greece

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دور المنح الدراسية في تحسين العملية التعليمية الجامعية

دور المنح الدراسية في تحسين العملية التعليمية الجامعية
Citation

M. AKHROUF Samir, Benfradj Zouina, , (2019), "دور المنح الدراسية في تحسين العملية التعليمية الجامعية", [international] المؤتمر العربي الدولي التاسع لضمان جودة التعليم العالي , Beyrouth Liban

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The use of Big Data and Data Analytics in the prevention, the diagnosis and the monitoring of long-term diseases

Diabetes is a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin that is produced. The constant hyperglycemia of diabetes is related to long-haul harm, brokenness, and failure of various organs, particularly the eyes, kidneys, nerves, heart, and veins. This last can be monitoring by doctors over the internet and especially social net- works.In this context, having a healthcare social media strategy is no longer optional, it’s a requirement. With the right strategy, social media will become a powerful tool to build trust, reach more patients, and spread valuable medical information. Furthermore, advances in mobile technology and the widespread use of smartphones and tablets will make an improvement in healthcare services at a rapid pace.In this paper, we propose a system that supports a community of diabetes people, their families and friends, doctors, nutritionist and anyone who might need or offer help and support to the community. Our objective is to develop a system that can predict, diagnose and monitor the diabetes or support diabetes self- management using machine learning algorithms and Big Data.
Citation

M. AKHROUF Samir, Mecili Oualid, Barkat Hadj, Nouioua Farid, Malek Rachid, , (2019), "The use of Big Data and Data Analytics in the prevention, the diagnosis and the monitoring of long-term diseases", [international] IMCL 2019 , Thessaloniki Greece

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Machine learning & Deep learning: Recent Overview in Medical Care

Medical care has always presented quite wide ranged and challenging problems. However, machine learning techniques and methods as well as deep learning never stopped evolving and tackling those challenges issued by medicine, medical and health care. In order to have a more close up look on how machine learning and deep learning has been affecting medical care in general, we review in this paper some machine learning and deep learning techniques used in a variety of medical care sections such as medical imaging, medical decision, diagnostic, medical records and big data, and disease prediction.
Citation

M. AKHROUF Samir, Chalabi Nour El Houda, Attia Abdelouaheb, , (2019), "Machine learning & Deep learning: Recent Overview in Medical Care", [international] IMCL 2019 , Thessaloniki Greece

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A fast minutiae-based fingerprint-matching algorithm using a dynamic descriptor and virtual minutiae insertion

Most minutiae-based matching techniques use local static descriptor to emphasize their discrimination power between ambiguous minutiae features. Despite the improvements shown by these methods, still some challenging problems limit their performance in particular the presence of spurious (added) minutiae and the missing of genuine minutiae. The added/missed minutiae problem misleads the matching process and complicates the correspondence decision. A general countermeasure of most existing matching algorithms is to add a global matching consolidation step that results in augmented time complexity.
In this work, a dynamic minutiae-based descriptor is described. Its particularity resides in its ability to adjust a minutia features according to the correspondent minutia context in the second print. The minutiae of the input fingerprint are arranged to get a global stable geometric structure called minutiae-based polysegment structure (MPS). It permits to detect added/missed minutia once compared to another MPS structure. Whenever the matching algorithm detects an added minutia in an MPS, it inserts a virtual minutia in the second to update the minutia descriptor context and, hence, let propagating the similarity. This increases the chance to maximize the number of genuine paired minutiae. Furthermore, the MPS structure reduces enormously the minutiae space to be tested; the matching algorithm complexity is near O(n log(n)). Experiments of the proposed algorithm are conducted on the public database FVC2002.
Citation

M. AKHROUF Samir, Belhadj Foudil, , (2019), "A fast minutiae-based fingerprint-matching algorithm using a dynamic descriptor and virtual minutiae insertion", [international] ICPAR 2019 International Conference on Pattern Analysis and Recognition , Tebessa

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2018

Forgiveness and repairing the broken trust in digital age

As online communications are taking over traditional ones, new perspectives are needed to understand the effect of this shift on people’s interactions and behavior. In this short paper, we focus on the aspect of repairing broken relationships after a transgression or a conflict that occurs in an online environment, where we specifically highlight the importance of studying forgiveness in the context in which the conflict occurs. We also provide a brief discussion of possible paths for such research.
Citation

M. AKHROUF Samir, Laifa Meriem, Belayadi Yahia, Boubetra Djamel, , (2018), "Forgiveness and repairing the broken trust in digital age", [international] IAJC 2018 , Orlando USA

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Social Networking for Obesity Prevention and Eradication for Algerian teenagers

Obesity can be classified as one of the most dangerous diseases in the world, as the number of obese people keeps on increasing. Obesity is related to many chronic diseases such as cancer, type 2 diabetes and heart disease, also to many factors such as eating habits and inactivity. This last can be caused by people’s addiction to Internet and especially social networks. This research introduces a new approach in the daily fight against obesity, by proposing a system that supports a community of overweight people, obese people, their families and friends, physicians, and anyone who might need help and support from this community or who can offer help to members of the community. In addition to the new system proposed a specific purpose social network to support this community was developed in order to help them discuss their problems, express their specific needs, share their experiences and motivate other members by sharing their experience with obesity… etc.
Citation

M. AKHROUF Samir, Benathmane Abdelkrim, Bouchachi Ramzi, Belayadi Yahia, , (2018), "Social Networking for Obesity Prevention and Eradication for Algerian teenagers", [national] , Springer, Cham

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Forgiveness Predictors and Trust in a Digital Age

This article describes how interpersonal relationships structures and standards are evolving. By focusing on a social network context, this study examined different factors that can affect forgiveness decision of a victim of an online offense. In addition, it inspected whether the decrease of trust after an online-related offense can be affected by forgiveness. 323 participants took part in this study by completing a questionnaire that recorded different measurements. Structural equation modeling was used as the main technique for data analysis, and AMOS was used as a tool. Surprisingly, while empathy and commitment had no significant direct effect, results showed that the severity of the offense, its frequency and pretransgression trust are the main factors that influence forgiveness. Moreover, a victim's trust towards the transgressor decreased much more in the absence of forgiveness than in its presence. A valuable contribution of this article is in the prospect for related future research as well as the potential for applications that explore new techniques to facilitate forgiveness in the digital age.
Citation

M. AKHROUF Samir, Laifa Meriem, Roya Imani Giglou, Maameri Ramdane, , (2018), "Forgiveness Predictors and Trust in a Digital Age", [national] IJTHI , IGI Global

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Forgiveness and trust dynamics on social networks

Social media users can easily be offended or hurt on those platforms, which leads to discomfort and health issues such as stress and anxiety. Forgiveness plays an important role to maintain healthy online relationships, which is the central constituent of social dynamics, from cooperation to social cohesion. While most prior studies have focused on analyzing forgiveness factors in offline settings using statistical methods, this study offers a new perspective using a two-staged approach whereby a research model was tested using structural equation modeling (SEM), and then the results were used as inputs for artificial neural network (ANN) and fuzzy logic (FL) models. An agent-based simulation was then performed to shed light on a possible use of the implemented models. Combining ANN and FL provided more accurate prediction results. In addition, simulation experiments call attention to the potential benefits of forgiveness in maintaining connectedness in a social network. The main purpose of this investigation was to evaluate the applicability of soft computing techniques on forgiveness prediction. Instead of relying on data mining techniques, we looked into questions that can improve our understanding of how society works in a digital age. In addition, this study provides an interesting example of a different and insightful way of doing computational social science that is useful to both researchers and practitioners.
Citation

M. AKHROUF Samir, Meriem Laifa, Ramdane Maamri, , (2018), "Forgiveness and trust dynamics on social networks", [national] Adaptive Behavior , SAGE Journals

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2016

A modern classroom response system for Bordj Bou Arreridj University

One of the biggest challenges teachers are facing is the inability of students to interact with each other. The instructor may ask for students' opinion, their ideas and whether they agree or disagree on a given problem or statement, without getting any feedback. However, some students have communication difficulties, and those who can have the correct answer may feel uncomfortable, and therefore the class will miss a good learning opportunity. Our objective is to create real-time multiple choice question system with an interactive and fun learning environment to increase the productivity of the maximum number of students.
Citation

M. AKHROUF Samir, Mebarkia Mohamed Khalil, Cap Clemens H, Belayadi Yahia, Boubetra Djamel, , (2016), "A modern classroom response system for Bordj Bou Arreridj University", [international] IMCL 2016 , San Diego USA

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A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks

This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.
Citation

M. AKHROUF Samir, Hamza Loucif, , Abdelhak Boubetra, , (2016), "A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks", [national] New Review of Hypermedia and Multimedia , Taylor and Francis online

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2015

Online Social Trust: an Overview

There is a wealth of information created every day through computer-mediated communications. Trust is an important component to sustain successful interactions and to filter the overflow of information. The concept of trust is widely used in computer science in various contexts and for different aims. This variety can confuse or mislead new researchers who are interested in trust concept but not familiar enough with it to find relevant related work to their projects. Therefore, we give in this paper an overview of online trust by focusing on its social aspect, and we classify important reviewed work in an attempt to guide new researchers in this domain and facilitate the first steps of their research projects. Based on previous trust surveys, we considered the following criteria: (1) trust dimension and its research purpose, (2) the trusted context and (3) the application domain in which trust is applied.
Citation

M. AKHROUF Samir, Laifa Meriem, Maamri Ramdane, , (2015), "Online Social Trust: an Overview", [international] IPAC 2015 , Batna Algérie

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An Overview of Forgiveness in the Digital Environment

We live in an interdisciplinary world, and we participate in an interplay between society and technology. In online settings, trust is required to back up successful interactions and to filter the overflow of information. However, trust is dynamic and very sensitive; it can be strengthened by positive experiences and destroyed by negative ones. Thus, we chose forgiveness as a way to repair broken trust relationships in computer-mediated communications. We believe that forgiveness benefits can improve online users' experiences by repairing broken relationships and encourage cooperation. In this paper, we present an overview about forgiveness research and we hope to put the first basic stones to drive more attention to this complicated concept in the digital environment.
Citation

M. AKHROUF Samir, Laifa Meriem, Maamri Ramdane, , (2015), "An Overview of Forgiveness in the Digital Environment", [international] IPAC 2015 , Batna Algérie

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Trust and Forgiveness in Virtual Teams: A Study in Algerian E-Learning Context

E- learning is gaining more popularity due to the technological development and the personalization it offers for learners and organizations. Most e-learning platforms support group work and collaboration between learners, which is a desirable educational practice. Thus, virtual team members must be flexible to achieve their goals in a cooperative environment. In order to improve learners experiences, and to encourage collaboration between them, we propose and validate a theoretical model that predicts the effect of trust on learners' forgiveness when a conflict occurs in a virtual team.
Citation

M. AKHROUF Samir, Meriem Laifa, ; Roya Imani Giglou, Ramdane Maamri, , (2015), "Trust and Forgiveness in Virtual Teams: A Study in Algerian E-Learning Context", [international] IMCL 2015 , Thessaloniki Greece

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Dihya: an Intelligent Learning Object Repository

The aim of this paper is to develop an Intelligent Learning Object Repository for computer science educational institutions at first glance, in order to facilitate the accessibility to different Learning Objects and therefore, enhance their reusability, interoperability, while taking advantage of their granularity/aggregation features. This LOR will give teachers the possibility to design courses that may include one or many LOs, second, the courses that depends on each other are linked together as nodes to form a graph that represents the global learning experience. Finally, it is to integrate a recommendation system which recommends to students the best paths to follow during a learning experience using the multi-agents approach where the recommender agent uses the A star pathfinding technique.
Citation

M. AKHROUF Samir, Abdelbasset Rouabah, Larbi Selmani, Yahia Belayadi, , (2015), "Dihya: an Intelligent Learning Object Repository", [international] IMCL 2015 , Thessaloniki Greece

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BBA virtual laboratory through m-learning

A significant development in virtual labs has been made in the last few years. The main reason for that is: the rapid development of technology, especially the internet, the huge growth of computer networks, the large use of personal computers and mobile devices. The World Wide Web with its different web services offers users a new way of learning; by giving the possibility of sharing and managing resources online and performing experiments through the web. This paper describes the use of BBA1 virtual laboratory through mobile devices. It will introduce the different tools available and will present some of the virtual experiments by giving an example of its usage in the virtual mobile laboratory.
Citation

M. AKHROUF Samir, Adel Merabet, Djamel Boubetra, Foudil Belhadj, Selmani Larbi, Abdelhak Boubetra, , (2015), "BBA virtual laboratory through m-learning", [international] IMCL 2015 , Thessaloniki Greece

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Secure Fingerprint-based authentication and non-repudiation services for mobile learning systems

Most of the solutions proposed to the security and privacy issues in mobile learning systems are generally inherited from those developed in e-learning systems and network communication background. However, the implication of the mobile devices in m-learning can reveal more private data and requires far more challenges. In this paper, we exploit the richness of mobile devices in sensors to propose a fingerprint-based strategy that provides a secure authentication, communication and non-repudiation scheme for mobile learning using recent advances in cancelable biometrics. The proposed scheme covers all the learning system steps starting b y subscription, communication and assessments.
Citation

M. AKHROUF Samir, Belhadj Foudil, Ait Aoudia Samy, , (2015), "Secure Fingerprint-based authentication and non-repudiation services for mobile learning systems", [international] IMCL2015 , Thessaloniki Greece

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Efficient fingerprint singular points detection algorithm using orientation-deviation features

Accurate singular point (SP) detection is an important factor in fingerprint (FP) recognition systems. We propose an algorithm to detect SPs in FP images. Our idea is based on the observation that the orientation field (OF) at the regions containing SPs has high variation, whereas in the other regions, it is smooth. Thus, a pixel-wise descriptor that comprises orientation-deviation (OD)-based features is proposed to measure the OF variation in the local neighborhood of a pixel which we call OF energy. Candidate SPs are characterized by locations where the OF energy function has local gradual maxima. Furthermore, the OD-based descriptor exhibits some advanced topological properties, in particular the descriptor profile tendency, which are highly correlated with the SP type. These properties are used to filter out some spurious SPs. A second refining step based on an extended Poincaré index is then applied to keep only genuine SPs with their information. The proposed algorithm has the ability to accurately detect the classical singularities as well as the arch-type SP. Experiments conducted over the public databases FVC2002 db1 and db2 confirm its accuracy and reliability with a reduced false alarm rate in comparison to other proposed methods.
Citation

M. AKHROUF Samir, Belhadj Foudil, Harous Saad, Ait Aoudia Samy, , (2015), "Efficient fingerprint singular points detection algorithm using orientation-deviation features", [national] Journal of Electronic Imaging , SPIE Digital Library

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2014

Virtual Simulation on the Web

E-learning is becoming more and more used by students and teachers in higher education. It is
a new way of performing practical works and acquiring knowledge in many fields, especially in
technology. Gathering ressourses and sharing their usage is very beneficial for educational
institutions and will reduce the cost of training.

In this paper we present the architecture of a platform we are developing in our university for
the purpose of distance learning. This platform is a part of a TEMPUS project for linking three
e-labs situated in three maghrebian countries, namely Algeria, Morocco and Tunisia.
The platform is mainly dedicated to our students and can be accessed remotely via internet.
We will present its architecture, focusing on the web interface and we will see that we use web
services for access control and for simulations. The last will be performed by tools such as
AMS and TCAD from Silvaco.
Citation

M. AKHROUF Samir, Adel Merabet, Djamel Boubetra, Larbi Selmani, Abdelhak Boubetra, , (2014), "Virtual Simulation on the Web", [international] IAJC-ISAM International Conference , Orlando USA

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Towards Content Based Image Retrieval with Personalized Semantic Spaces

Towards Content Based Image Retrieval with Personalized Semantic Spaces
Citation

M. AKHROUF Samir, Tekkali Aicha, Rima Merrouche, Anas Y Boubas, Saad Harous, , (2014), "Towards Content Based Image Retrieval with Personalized Semantic Spaces", [international] International Conference on Computer Vision and Image Analysis, ICCVIA’2014 , Ras Al Khaimah UNITED ARAB EMIRATES.

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A Biometric Identification Course for eSience Virtual Lab

Determining the identity of a person automatically is still an actual problem. There is an urgent need to have automatic and reliable authentication systems in order to combat fraud and meet the requirements for different areas ranging from international border stations to accessing personal information. Biometrics is an alternative to the old methods of identification. It involves identifying persons from their physical or behavioral characteristics. Face, fingerprint, iris, etc, are examples of physical characteristics. This course aims to introduce first basic concepts related to the recognition of individuals, based on their physiological or behavioral biometric characteristics, to students and allow them to study the key techniques to achieve reliable systems for biometric recognition. In This paper we will present the architecture of the course which will be held on a virtual laboratory. The course objective is to give the student different skills which are necessary in this field of study. The course is divided in several parts; each one will present a specific topic and will provide different notions in order to let students understand theoretical concepts by practicing.
Citation

M. AKHROUF Samir, Larbi Selmani, Djamel Boubetra, Mostefai Messaoud, , (2014), "A Biometric Identification Course for eSience Virtual Lab", [national] Lecture Notes on Software Engineering , LNSE

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BBA Lab a Virtual Laboratory for Distant Learning

Nowadays distant learning is gaining more and more popularity due to the technological development and the flexibility it offers for the students. All around the world we see universities conceiving their distant learning platforms in order to offer to their students this service and help them study at their own pace. In this paper we describe BBA lab a draft of the distant lab of Bordj Bou Arreridj University. It is dedicated mainly to students in the field of electrical engineering and computer science. Bordj Bou Arreridj University is involved in a project which is financed by the Eurepean Community and aims to link three distant Elabs, the Algerian Elab, developed by Constantine 1 and Bordj Bou Arreridj Universities, the Moroccan and the Tunisian Elabs.
Citation

M. AKHROUF Samir, Djamel Boubetra, Jean Jacques Charlot, Larbi Slimani, Boubetra Abdelhak, Adel Merabet, , (2014), "BBA Lab a Virtual Laboratory for Distant Learning", [national] International Journal of Information and Education Technology , IJIET

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Web Services for Virtual Simulation

Great development in distance learning has been made in the last two decades facilitated by the rapid evolution of technology, the huge development of computer networks and the large use of internet and personal computers. The World Wide Web with its different web services offers learners and teachers’ new ways of learning and teaching; students can study at their own pace and perform practical tasks remotely.
We, at the University of Bordj Bou Arreridj, are involved in the eSience (rESeau maghrébIn de laboratoirEs à distance) project which aims to link three elabs around the Maghreb countries namely Algeria, Tunisia and Morocco. The project is coordinated by the University of Bordeaux 1, France with the participation of many European partners. These elabs will propose practical and theoretical teaching units that will be part of their degree program.
In this paper we present our university’s platform architecture, focusing on the web interface. First we introduce the service broker, which allows students to communicate and use the various platforms of the network. Second we present the simulation server and give an example of its usage.
Citation

M. AKHROUF Samir, Adel Merabet, Ayoub Maza, Djamel Boubetra, Larbi Selmani, Abdelhak Boubetra, , (2014), "Web Services for Virtual Simulation", [national] International Journal of Online and Biomedical Engineering , IJOE

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2013

Social Network Analysis and Information Propagation

Social media and Social Network Analysis (SNA) acquired a huge popularity and represent one of the most important social and computer science phenomena of recent years. One of the most studied problems in this research area is influence and information propagation. The aim of this paper is to analyze the information diffusion process and predict the influence (represented by the rate of infected nodes at the end of the diffusion process) of an initial set of nodes in two networks: Flickr user’s contacts and YouTube videos users commenting these videos. These networks are dissimilar in their structure (size, type, diameter, density, components), and the type of the relationships (explicit relationship represented by the contacts links, and implicit relationship created by commenting on videos), they are extracted using NodeXL tool. Three models are used for modeling the dissemination process: Linear Threshold Model (LTM), Independent Cascade Model (ICM) and an extension of this last called Weighted Cascade Model (WCM). Networks metrics and visualization were manipulated by NodeXL as well. Experiments results show that the structure of the network affect the diffusion process directly. Unlike results given in the blog world networks, the information can spread farther through explicit connections than through implicit relations.
Citation

M. AKHROUF Samir, Laifa Meriem, Belayadi Yahia, , (2013), "Social Network Analysis and Information Propagation", [international] International Journal of Future Computer and Communication , IJFCC , Malaysia

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2012

Construction et génération d’un graphe AoA en tenant compte des contraintes temporelles

Le problème d’ordonnancement consiste à organiser dans le temps
un ensemble d’activités, de façon à satisfaire un ensemble de contraintes et
optimiser le résultat. La contrainte temporelle touche au problème central de
l’ordonnancement et le modifie, donc il n’aura plus ses caractéristiques. Notre
travail consiste, pour résoudre ce problème, à modéliser par les graphes ce type
de contraintes et le ramener à un problème classique d’ordonnancement ;
ensuite appliquer une nouvelle technique de transformation d’un graphe AoN
(Activities on Nodes) qui est unique avec un nombre important d’arcs et non
préféré par les praticiens de gestion de projet vers un graphe AoA (Activities on
Arcs) avec moins d’arcs et plus souhaitable. Le papier contient des concepts sur
les graphes adjoints et un exemple illustratif de la méthode proposée.
Citation

M. AKHROUF Samir, Benhocine Abdelhamid, , (2012), "Construction et génération d’un graphe AoA en tenant compte des contraintes temporelles", [international] Colloque sur l'Optimisation et les Systèmes d'Information COSI'2012 , Tlemcen Algérie

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Generating Pert Network with Temporal Constraints

A scheduling problem is organizing in time a set of activities, so as to satisfy a set of constraints and optimize the result. The temporal constraint modifies the project scheduling, therefore in loses its characteristics. Our objective is to solve this problem by finding the various types of temporal constraints then modeling them by using graphs. Furthermore we apply a technique for transforming an AoN graph (Activities on Nodes) which is unique and contains a significant number of arcs. This graph is not preferred by practitioners of project management. We transform the AoN graph into an AoA graph (Activities on Arcs) which contains fewer arcs and is preferred by practitioners of project management. In this paper we present some concepts of line graphs and an illustrative example of the proposed method.
Citation

M. AKHROUF Samir, (2012), "Generating Pert Network with Temporal Constraints", [national] Studia Univ. BABES-BOLYAI, INFORMATICA , Studia University BABES-BOLYAI, INFORMATICA

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A New multimodal Biometric identification approach

Several authors have shown that multimodality was a highly efficient solution for biometric identification and allows to increase performance and reliability. Indeed, the acquisition of multiple biometric features makes it much more difficult for an impostor to spoof the system with artificially developed samples. However, we do not get these benefits for free: multimodal biometric systems are less profitable and have significant effects on their users. Some of them may indeed lead a non acceptance by their users, in particular when it comes to privacy issues that may result when acquiring data at multiple levels. That is why it is always important to explore the possibility of finding new systems that could be accepted by users and which are fully reliable than the previous ones. In this paper we present a new approach for speaker biometric identification. This approach is a user friendly platform which adds a new modality, namely a virtual character, which will be easily accepted by users. The virtual character [6] will first put the users in a comfortable position and simultaneously acquire the information necessary for their identification. Then, it will guide them step by step until the end of the process of identification. The users are put in the best conditions which will facilitate their participation and acceptance to be identified.
Citation

M. AKHROUF Samir, Belayadi Yahia, , (2012), "A New multimodal Biometric identification approach", [national] International Journal of Computer Science Issues , IJCSI

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Social Network Analysis and Information propagation: A case study using Flickr and YouTube networks

Social media and Social Network Analysis (SNA) acquired a huge popularity and represent one of the most important social and computer science phenomena of recent years. One of the most studied problems in this research area is influence and information propagation. The aim of this paper is to analyze the information diffusion process and predict the influence (represented by the rate of infected nodes at the end of the diffusion process) of an initial set of nodes in two networks: Flickr user’s contacts and YouTube videos users commenting these videos. These networks are dissimilar in their structure (size, type, diameter, density, components), and the type of the relationships (explicit relationship represented by the contacts links, and implicit relationship created by commenting on videos), they are extracted using NodeXL tool. Three models are used for modeling the dissemination process: Linear Threshold Model (LTM), Independent Cascade Model (ICM) and an extension of this last called Weighted Cascade Model (WCM). Networks metrics and visualization were manipulated by NodeXL as well. Experiments results show that the structure of the network affect the diffusion process directly. Unlike results given in the blog world networks, the information can spread farther through explicit connections than through implicit relations.
Citation

M. AKHROUF Samir, (2012), "Social Network Analysis and Information propagation: A case study using Flickr and YouTube networks", [international] International Conference on Information and Multimedia Technology (ICIMT 2012) , Kuala Lumpur, Malaysia

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2011

Speaker dependent threshold’s estimation for GMM-UBM speaker verification systems

In real applications of speaker verification [1] based on GMM-UBM method, the size of training data varies from a speaker to another; the choice of a common threshold of verification will reduce the performance of the system when we only have short records of training data. In this paper we first describe speaker verification using adapted gaussian mixture models based on Reynolds works [2] and the performance obtained by this method. We then propose a new method to estimate a speaker-dependent threshold and the results obtained by this approach.
Citation

M. AKHROUF Samir, Mehemel Bachir, Mehemmel Abbas, , (2011), "Speaker dependent threshold’s estimation for GMM-UBM speaker verification systems", [international] International Conference on Software and Information Management , Chengdu, China

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A Multi-Modal Recognition System Using Face and Speech

Nowadays Person Recognition has got more and more interest especially for security reasons. The recognition performed by a biometric system using a single modality tends to be less performing due to sensor data, restricted degrees of freedom and unacceptable error rates. To alleviate some of these problems we use multimodal biometric systems which provide better recognition results. By combining different modalities, such us speech, face, fingerprint, etc., we increase the performance of recognition systems. In this paper, we study the fusion of speech and face in a recognition system for taking a final decision (i.e., accept or reject identity claim). We evaluate the performance of each system differently then we fuse the results and compare the performances.
Citation

M. AKHROUF Samir, Belayadi Yahia, Mostefai Messaoud, Chahir Youssef, , (2011), "A Multi-Modal Recognition System Using Face and Speech", [national] International Journal of Computer Science Issues , IJCSI

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2010

Towards an Intelligent Multimodal Biometric Identification System

The goal of this project is to bring together and
integrates the work of the laboratory team members in order to
get a practical realization of an Intelligent Multimodal
Biometric Identification System. This last exploits the vocal and
visual properties of a person to carry out, her or his,
identification. To improve classification performance, the
system will have a virtual character module which can
exchange information with the person to be identified according
to a random survey (based on information provided previously).
Our first objective is to equip our laboratory with a powerful
access control system able to identify the members of the lab
and follows them where ever they go helping them with all kind
of information they may be in need to.
Citation

M. AKHROUF Samir, Abderraouf. Bouziane, A. Hacine. Gharbi, Messaoud Mostefai, Youssef Chahir, , (2010), "Towards an Intelligent Multimodal Biometric Identification System", [national] International Journal of Computer Science and Electrical Engineering , IACSIT

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2009

Face Recognition Using PCA and DCT

Research in the field of face recognition knew considerable progress during these last years. Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition. For these methods, the images of faces are seen like points in a space of very great dimensions. The basic idea is to encode the initial data to pass to another space of dimensions much more reduced while preserving as much useful information. This paper presents a hybrid method combining principal components analysis (PCA) and the discrete cosine transform (DCT).
Citation

M. AKHROUF Samir, Sehili Mohamed Amine, Chekhchoukh Abdeslam, Chahir Youssef, Mostefai Messaoud, , (2009), "Face Recognition Using PCA and DCT", [international] 2009 Fifth International Conference on MEMS NANO, and Smart Systems , Dubai UAE

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J2EE : Etude de cas d’une Application Web 3 tiers.

J2EE : Etude de cas d’une Application Web 3 tiers.
Citation

M. AKHROUF Samir, Benziouche Hamza, , (2009), "J2EE : Etude de cas d’une Application Web 3 tiers.", [international] ICAI09 , Bordj Bou Arreridj Algérie

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Interpolation Intercoupe Markovienne pour la Reconnaissance 3D des Images Médicales Anisotropiques.

Interpolation Intercoupe Markovienne pour la Reconnaissance 3D des Images Médicales Anisotropiques.
Citation

M. AKHROUF Samir, Belhadj Foudil, Ait Aoudia Samy, , (2009), "Interpolation Intercoupe Markovienne pour la Reconnaissance 3D des Images Médicales Anisotropiques.", [international] ICAI09 , Bordj Bou Arreridj Algérie

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A Study of an Online Auction Implementation

A Study of an Online Auction Implementation
Citation

M. AKHROUF Samir, Messaoud Mostefai, Bouziane Abderraouf, , (2009), "A Study of an Online Auction Implementation", [international] ICAI09 , Bordj Bou Arreridj Algérie

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Développement d'un système d'identification biométrique multimodale

Développement d'un système d'identification biométrique multimodale
Citation

M. AKHROUF Samir, Bouziane Abderraouf, Hacine Gharbi Abdennour, Mostefai Messaoud, , (2009), "Développement d'un système d'identification biométrique multimodale", [international] ICAI09 , Bordj Bou Arreridj Algérie

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2008

CMMS*net: A distributed and object-oriented Data Manipulation Language using CORBA

CMMS*net: A distributed and object-oriented Data Manipulation Language using CORBA
Citation

M. AKHROUF Samir, Bouziane Abderraouf, Mostefai Messaoud, , (2008), "CMMS*net: A distributed and object-oriented Data Manipulation Language using CORBA", [international] 2nd International Conference on Electrical Engineering Design and Technologies , Hammamet Tunisia

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Effecient Face Location Operator based on motion detection techniques

Effecient Face Location Operator based on motion detection techniques
Citation

M. AKHROUF Samir, Mostefai Messaoud, Bouziane Abderraouf, , (2008), "Effecient Face Location Operator based on motion detection techniques", [international] 2nd International Conference on Electrical Engineering Design and Technologies , Hammamet Tunisia

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Development of A New Face tracking Operator

Development of A New Face tracking Operator
Citation

M. AKHROUF Samir, Mostefai Messaoud, Bouziane Abderraouf, , (2008), "Development of A New Face tracking Operator", [international] ICEE08 , Oran Algérie

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2007

Les Graphes Adjoints dans le Problème Centrale d'Ordonnancement

Les Graphes Adjoints dans le Problème Centrale d'Ordonnancement
Citation

M. AKHROUF Samir, Boubetra Abdelhak, , (2007), "Les Graphes Adjoints dans le Problème Centrale d'Ordonnancement", [national] Colloque International d'Analyse non Linéaire et Applications , Université de Sétif Algérie

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A Study of Free Form Deformations and their Applications

In this communication we will present the different methods used for free form deformation over different types of models.
Citation

M. AKHROUF Samir, Boubetra Adelhak, Fares Nour El Houda, , (2007), "A Study of Free Form Deformations and their Applications", [international] Conférence Internationale sur la productique , Université Ferhat Abbas, Sétif

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A specification tool for simulating a manufacturing system component

The proposed approach seeks to develop a combined simulation tool based on Petri nets, the producer consumer computing model and the simulation techniques. This tool is designated for simulating manufacturing systems. Such an approach offers an adequate platform to carry out simulation in parallel to take advantage of that, plus the experts of the Petri nets will find a strategy to make simulations not far from their concepts of modelling.
Citation

M. AKHROUF Samir, Boubetra Abdelhak, Belayadi Yahia, , (2007), "A specification tool for simulating a manufacturing system component", [national] Journal of Advances in Computer Science and Engineering , Pushpa Publishing House

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2005

Inside a descrete event simulation

Inside a descrete event simulation
Citation

M. AKHROUF Samir, Abdelhak Boubetra, , (2005), "Inside a descrete event simulation", [international] Congrès International en Informatique Appliquée , Bordj Bou Arreridj Algérie

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