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Les villes petites et moyennes dans un monde globalisé
(Université d'Oum El Bouaghi, 2021) Bousmaha, Ahmed
Electronics, artifical intelligence and new technologies
(University of Oum El Bouaghi, 2021) Lashab, Mohamed
The Electronics and New Technologies Laboratory (LENT) is organizing the first international conference on electronics, artificial intelligence and new technologies (ICEAINT'21), this will be held at the University of Larbi Ben M’hidi, Oum El Bouaghi. The conference will cover all the research activities of the laboratory; moreover, the conference will include different axes of electronics, computer science and new technologies likely to interest all researchers in these fields. The ICEAINT'21 aims to bring together academic researchers and industrial scientists to exchange new ideas, original research results and practical development experiences on all aspects dealing with the different themes of the conference.
أعمال المؤتمر العلمي الدولي الافتراضي الثاني حول مساهمة العلوم البيوطبية في تطويرالأداء الرياضي النخبوي أيام 29-30 ماي2021
(جامعة أم البواقي, 2021) مالك, رضا
تهدف الدراسة إلى التعرف على أثر كل من التدريب المتقطع والتدريب الفتر ي على السرعة الهوائية القصوى وقدرة الاسترجاع لدى لاعب ي كر ة القدم أكابر.ولهذا الغ رض استخدمنا المنهج التجريبي، على عينة متكونة من 40 لاعبا، مقسمة إلى عينتي ن 20 لاعبا من كل فريق. وقد تم اختياره ا بشكل قصدي من نادي أمل شلغوم العبد ونادي 2020 . لجم ع / شباب ميلة للموسم الرياض ي 2019 Polar و جهاز GPS البيانات استخدمنا جهاز والاختبارات البدنية بعد جمع النتائج ومعالجته ا إحصائيا تم التوصل إلى أ ن التدريب المتقطع أكثر فعالية من التدريب الفتري في تطوير السرعة الهوائية القصوى قدرة الاسترجاع لدى لاعب ي كر ة القدم أكابر. The study aims to identify the effect of both intermittent training and interval training on the maximum air speed and recovery ability of senior football players. For this purpose, we used the experimental method, on a sample of 40 players, divided into two samples, 20 players from each team. She was intentionally selected from Amal Shalghoum Al-Abed Club and Mila Youth Club for the 2019/2020 sports season. To collect the data, we used GPS, Polar and physical tests. After collecting the results and processing them statistically, it was concluded that intermittent training is more effective than interval training in developing the maximum aerobic speed and recovery capacity of senior football player
تدويل التعليم المحاسبي
(جامعة ام البواقي, 2021) جفال, خالد
Dynamique des villes en algerie. Application du Critere de la taille des villes selon le modele Hierarchique de la loi de zipf
(Université D’Oum El Bouaghi, 2021-04-02) Bousmaha, Ahmed; Boulkaibet, Aissa; Kouba, Yacine
Les objectifs de cet article est de proposer une analyse de la croissance urbaine et le phénomène de l’urbanisation dont l’originalitéréide dans l'élargissement de la strate des centres déjà urbains ou en voie d'urbanisation entre 1954 et 2008, une période marquée par des changements économiques, sociaux et politiques importants. Ce papier décrit la croissance urbaine en Algérie à partir d'une base de données du recensement général de la population et de l’habitat (RGPH), de l’Office National des Statistiques (O NS), d’une part. D’autres parts, nous abordons, via l’application du critèe de la taille des villes, la distribution rang-taille selon le modèle hiérarchique de « la loi de Zipf » dans l’éude du systèe urbain algéien. The objectives of this article are to propose an analysis of urban growth and the phenomenon of urbanization, the originality of which lies in the expansion of the stratum of centers already urban or in the process of urbanization between 1954 and 2008, a period marked by significant economic, social and political changes. This paper describes urban growth in Algeria based on a database of the General Census of Population and Housing (RGPH), of the National Statistical Office (O NS), on the one hand. On the other hand, we approach, through the application of the criterion of the size of cities, the distribution rang-size according to the hierarchical model of "Zipf's law" in the study of the Algerian urban system.
Achieving the quality of accounting learning outcomes: an Algerian perspective
(University of Oum El Bouaghi, 2021-05-10) Rimouche, Kaoutar; Himrane, Mohammed
This paper aims to demonstrate the efforts made by the International Accounting Education Standards Board (IAESB) in achieving the quality of the accounting learning outcomes and to explore the reality of accounting education in Algerian. We based on the comparative method in order to compare between the content of universities' accounting programs and the International Accounting Education Standard (2). Considering that the accounting educational system in universities should emphasize serving students and ensure that they will be able to practice the accounting profession in the future, and that accounting education should seek to adapt to the trend of professional accounting development. We have concluded that there is almost a perfect match between what Algerian universities apply and what the International Federation of accountant’s committee approved, but the problem lies in achieving the learning outcomes with the required quality as stated in the IES2 تهدف هذه الورقة إلى إظهار الجهود التي يبذلها المجلس الدولي لمعايير تعليم المحاسبة (IAESB) في تحقيق جودة مخرجات تعلم المحاسبة واستكشاف واقع تعليم المحاسبة في الج ا زئر. حيث اعتمدنا على المنهج المقارن لمقارنة بي ن محتوى برامج المحاسبة بالجامعات ومعيار تعليم المحاسبة الدولي (2). مع الأخذ في الاعتبار أن النظام التعليمي المحاسبي في الجامعات يجب أن يركز على خدمة الط لب والتأكد من أنهم سيكونون قادرين على ممارسة مهنة المحاسبة في المستقبل، وأن التعليم المحاسبي يجب أن يسعى للتكيف مع اتجاه تطوير المحاسبة المهنية. لقد توصلنا إلى أن هناك تطابقًا تامًا تقريبًا بين ما تقدمه الجامعات الجزائرية وما أقرته لجنة المحاسبين الفيدرالية الدولية، لكن المشكلة تكمن في تحقيق مخرجات التعلم بالجودة المطلوبة كما هو مذكور في .IES2
Accounting Education: a theoretical overview
(University of Oum El Bouaghi, 2021-05-10) Khalfallah, Zakarya
The main purpose of this paper is to highlight the Accounting Education as a real asset that must continually evolve in order to best prepare future professionals on accounting for the new requirements imposed by technology and globalization. To do this, a descriptive methodological approach has been deployed to present Accounting Education Standards (IESs), which are developed by the International Accounting Education Standards Board (IAESB). These standards are influencing Accounting Education and training worldwide. The goal of the IESs is to ensure that economic decision makers can rely on the competence of professional accountants regardless of the country where the accountants received their education and training. Two major lessons emerge from this study. On the one hand, that the organizational structure, globalization and technology impact the skills needs of the accountancy profession and, on the other hand, there is a gap between the training provided and the needs of the profession. تستهدف هذه الورقة البحثية تسليط الضوء على التعليم المحاسبي كأداة حقيقية يجب أن تتطور باستمرار من أجل إعداد أفضل المهنيين المحاسبين في المستقبل، وذلك بهدف الاستجابة للمتطلبات الجديدة التي تفرضها التكنولوجيا والعولمة؛ وقد اعتمدت الورقة البحثية في تحقيق أهدافها على المنهج الوصفي التحليلي من خلال تقديم والتي تم تطويرها من قبل مجلس معايير تعليم ،(IESs) معايير التعليم المحاسبي حيث تؤثر هذه المعايير على التعليم المحاسبي ، (IAESB) المحاسبة الدولي والتدريب في جميع أنحاء العالم، كما تهدف إلى ضمان أن صناع القرار الاقتصادي يمكنهم الاعتماد على كفاءة المحاسبين بغض النظر عن الدولة التي تلقوا فيها تعليمهم وتدريبهم.
An extended artificial bee colony with skyline operator for solving the QoS uncertainty-aware web service composition under interval QoS properties
(University of Oum El Bouaghi, 2021-05-25) Seghir, Fateh; Ghizlane, Khababa
In this paper, we provide an extended artificial bee colony (EABC) algorithm with skyline operator for solving the QoS uncertainty-aware web service composition (IQSC) problem, where the uncertain QoS properties have been expressed as intervals numbers. At first, we formulate the addressed problem as an interval constrained single-objective optimization model. Then we employ the skyline operator to reduce the search space of IQSC. Whereas, the EABC algorithm has been performed to solve IQSC in a reduced search space more effectively and efficiently. To validate the performance and efficiency of the proposed approach, we present the experimental comparisons to an existing skyline-based PSO algorithm on an interval extended version of the public QWS dataset.
A Survey on Identity-based Key Management Schemes in Mobile Ad hoc networks
(University of Oum El Bouaghi, 2021-05-25) Gasmi, Kenza; Bourouis, Abdelhabib; Benaboud, Rohallah
Mobile Ad hoc networks attract more attention over the years, but the security matter of this type of network makes it hard to achieve all of their advantages. Cryptographic key management is the cornerstone for building any robust network security solution. Identity-based cryptography is a promising solution that resists well the key escrow problem which is suitable for Mobile Ad hoc networks. In this paper, we give an overview of the most important identity-based encryption schemes proposed in the last decade; combined with other techniques to enhance it and provide better results for Mobile Ad hoc networks. Hence, we give a comparative analysis to highlight their advantages and weaknesses. This work gives insights into a recent research to point out its interesting features, take advantages of its strength, ovoid its weaknesses and to lay out the future directions in this area.
A comparative study of perceptual hashing algorithms: Application on fingerprint images
(University of Oum El Bouaghi, 2021-05-25) Hamadouche, Maamar; Zebbiche, Khalil; Guerroumi, Mohamed; Tebbi, Hanane; Zafoune, Youcef
Perceptual image hashing has been broadly used in the literature to authenticate images or to identify similar contents for image copy detection. It can be used to improve the security of fingerprint-based identification systems, especially to guarantee the authenticity of fingerprint images. In this paper, a comparative study of the most used techniques in the field of perceptual hashing is provided, aiming at evaluating their performance when applied to fingerprint images. The study includes five techniques, namely: A-Hash, D-Hash, P-Hash, WHash and SVD-Hash. The performance has been assessed in terms of perceptual robustness, discrimination capability and authentication characteristics, through extensive experiments. The obtained results are promising and show that overall both the A-Hash and P-Hash performed well when compared to other evaluated techniques.
2nd International Conference on Computer Science's Complex Systems and their Applications
(University of Oum El Bouaghi, 2021-05-25) Marir, Toufik; Bourouis, Abdelhabib; Benaboud, Rohallah
Bandwidth Provision through Disjoint Multipath RPL in the IoMT
(University of Oum El Bouaghi, 2021-05-25) Kettouche, Souhila; Maimour, Moufida; Derdouri,Lakhdar
Internet of Multimedia Things (IoMT) is one extensively current topic of the Internet of Things (IoT) due to the immersive growth of multimedia applications in several fields. In LowPower and Lossy Networks (LLNs) where sensor nodes are a key component, providing a satisfactory quality of service (QoS) as well as a user quality of experience (QoE) for such applications is a challenging task. In fact, high bandwidth and substantial computation resources are required. To provide sufficient bandwidth to handle these high data rate applications, we propose to extend RPL to enable for simultaneous use of disjoint multiple paths. This is done on top of the already maintained DODAG structure with the least induced overhead. Furthermore, we suggest applying a low-complexity encoding method on the captured images. Based on both QoS and QoE metrics, we evaluate the performance of our disjoint multipath RPL (DM-RPL) for real video clip transmission using the IoTLAB testbed. Our results show that multipath provides more bandwidth as the PDR is increased. Video quality is further improved thanks to the adopted data reduction at the source. All of this translates into less energy being consumed.
Biometric Image Encryption Scheme based on Modified Double Random Phase Encoding System
(University of Oum El Bouaghi, 2021-05-25) Yahi, Amina; Bekkouche, Tewfik; Diffellah, Nacira; Daachi, Mohamed El Hossine
In this paper, an opto-digital encryption scheme based on a modified Double Random Phase Encoding (DRPE) system is proposed. Two biometric modalities are used in this work which is the face and the corresponding finger print of the same person. Firstly the face biometric image is encrypted chaotically using the permutation-diffusion architecture. Then obtained encrypted face is multiplied element by element by a constructed mask formed by injecting the finger print image within the phase of this mask. The obtained result will be transformed into a frequency domain by the two-dimensional. Fourier transform or any of its derivatives, resulting complex image is exactly the encrypted biometric image. Experiment computer simulations confirm the efficiency of this work in terms of histogram analysis, loss data and sensitivity test when compared with existing works.
An Improved Binary Particle Swarm Optimization of RFM’s for ALSAT2 Imagery
(University of Oum El Bouaghi, 2021-05-25) Mezouar , Oussama; Meskine, Fatiha; Boukerch, Issam
Rational function model (RFM) is commonly used in photogrammetric and remote sensing applications because it does not need sensor parameters. Therefore, the RFM terms or also rational polynomial coefficients (RPCs) have no physical significance but depends on many ground control points (GCPs) that make the model prone to the over parameterization problem. This paper proposes a new binary particle swarm optimization algorithm to surmount the issue of over parameterization and find the optimum combination of RPCs for the RFM by adding a new transfer function in binary PSO in order to increase the convergence speed and avoid the local minimum phenomenon. The results showed that the proposed method is compatible with different types of RFM, more stable, and gives higher accuracy than the traditional binary PSO.
Behavioural verification of limited resources systems under true concurrency semantics
(University of Oum El Bouaghi, 2021-05-25) Bouneb; Messaouda; Saidouni; Djamel Eddine
In this paper we propose a true concurrency semantics for limited resources systems using K-bounded Petri net as modeling formalism and maximality labeled transition system (MLTS) as semantics model. Indeed the model of MLTS expresses clearly the semantics of true parallelism of concurrent systems. The proposed operational maximality semantics for Kbounded Petri nets makes it possible to interpret any K-bounded Petri net in terms of MLTS. Through an example we show the interest of the proposed semantics in comparison with the interleaving semantics and the ST semantics. The comparison concerns the preservation of true concurrency and the reduction of the size of the semantics model. Furthermore, we will show that expected CTL properties may be verified on the corresponding maximality labeled transition system of a modeled system using our developed tool.
Evaluation of ANN, ICA-ANN and PSO-ANN predicting ability in the prediction of CO2 emissions during the calcination of cement raw material
(University of Oum El Bouaghi, 2021-05-25) Boukhari, Yakoub
Cement industry releases large amounts of carbon dioxide CO2 as by-product to the atmosphere during the calcination of cement raw material. In fact, the calcination is a complex process and not completely understood. The amount of CO2 emitted varies with the grain size, chemical composition, burning temperature and time to pass through the kiln during calcination process. However, due to interaction of several parameters, it is not easy to establish accurate mathematic model to calculate the real amount of CO2 emission. Moreover, using the laboratory experiments to determine the amount of CO2 emissions are not usually easy, time-consuming, expensive and require good quality of reagents and equipments. To overcome the above problems, artificial neural network (ANN), ANN optimised by imperialist competitive algorithm (ICAANN), ANN optimised by particle swarm optimization (PSOANN) are applied to predict amount of CO2 emissions. A comparative accuracy of these tools is evaluated based on the coefficient of determination R2, R2 adjusted, mean absolute percentage error (MAPE) and scatter index (SI). The results obtained are promising and demonstrate that all proposed tools represent a good alternative for the prediction of CO2 emission with adequate accuracy. PSO and ICA are capable to improve the predicting accuracy of ANN. In addition, PSO-ANN can predict slightly better than ICA-ANN. Based on testing data, the results obtained show that 98.61%, 98.18% and 97.5% of experimental data are explained by PSO-ANN, ICAANN and ANN, respectively with average relative error less than 1.41%and SI less than 0.1.
Lips Recognition for Biometric Identification Systems
(University of Oum El Bouaghi, 2021-05-25) Boucetta, Aldjia; Boussaad, Leila
In recent years, researches in biometric methods have gained much attention and they have advanced to a wide scope in security concepts. Therefore, many biometric technologies have been developed and enhanced with many of the most successful security applications. Lately, lip-based biometric identification becomes one of the most relevant emerging tools, which comes from criminal and forensic real-life applications. The main purpose of this paper is to prove the benefit of lips as a biometric modality, by using both handcraft and deeplearning based feature extraction methods. So, we consider three different techniques, Histogram of Oriented Gradients(HOG), Local Binary Pattern(LBP) and pretrained Deep-CNN. All results are confirmed by a ten-fold cross-validation method using two datasets, NITRLipV1 and database1. The mean accuracy is found to be very high in all the experiments carried out. Also the feature extraction using the Inceptionv3 model always achieve highest mean accuracy.
Compressed VGG16 Auto-Encoder for Road Segmentation from Aerial Images with Few Data Training
(University of Oum El Bouaghi, 2021-05-25) Abdeldjalil, Kebir; Taibi, Mahmoud; Serradilla, Francisco; Spain, Madrid
Deep Learning methods have found many applications such as segmentation, recognition and classification. However, almost all of these methods require large data-set for the training step and a long training time. Indeed, in surveillance video domain, as for many real-world applications, samples are only accessible in limited amounts owing to acquisition and experiments complexity. In this work, we introduce compressed VGG Auto-Encoder system for road image segmentation in highresolution aerial imagery. The objective of our experiments is to improve the methodology of distinguishing the road network when only few Data is available. We propose an approach based on compressed Auto-encoder; focus on avoiding the over-fitting effect by generating new data augmentation, based on basic filter transformation to increase and enhance the quality of data training, in the aim of learn an appropriate and simplified representation of data from the original data set in order to obtain a deeper insight from large data-set, and to achieve a quick segmentation training time. Our model achieve a good result and is considered as the best network for fast and accurate segmentation of road images, compared to other models. Furthermore, we provide an explanation of these techniques and some recommendation for their use in the field of deep learning.
Distributed Secure Services Based on IoT and Blockchain for e-Health remote care
(University of Oum El Bouaghi, 2021-05-25) Reffad, Hamza; Djenaoui, Abdelatif; Alti, Adel
Nowadays, the Internet of Thing (IoT) is a potentially powerful solution for health applications. It is a smart technology that provides remote care in real time and requires low latency health data processing and transmission. The large number of connected objects to Cloud can be a problem for low-latency workloads, which is the case of several health mobile applications. To this end, Fog Computing, has emerged, where Cloud computing is extended to the edge of the network to reduce latency and network congestion. It provides a highly virtualized platform that provides health data storage on remote public Cloud servers to which users cannot be fully trusted, especially when we are dealing with sensitive data like health data. In fact, it becomes necessary to rethink a new more robust secure technique. To provide such technique, we proposed a new secure solution called IoToDChain for e-Health mobile application, based on cryptographic techniques especially Elliptic Curve Diffie Hellman-RSA and the Blockchain paradigm. They exchange of a secret key in confidential and robust manner and protect patients’ privacy in a mobile-Fog-Cloud environment. The experiments achieved promising results for good data protection against the most known attacks in healthcare systems.
Image denoising algorithms using norm minimization techniques
(University of Oum El Bouaghi, 2021-05-25) Diffellah, Nacira; Bekkouche, Tewfik; Hamdini, Rabah
Image denoising is one of the fundamental image processing problems. Noise removal is an important step in the image restoration process. In this paper, firstly we develop and implement two different image denoising algorithms based on norm minimization, namely `1 and `2-regularization applied to images contaminated by gaussian noise. Then, after their discretization and implementation, we perform a comparison between the two methods using several test images. Through this study, the algorithm which minimizes `2-norm of gradient of image has a unique solution and it’s easy to implement, but it doesn’t accept contour discontinuities, causing the obtained solution to be smooth. The `2-norm will blur the edges of the image. In order to preserve sharp edges, `1-norm is introduced. There are different methods to solve the problem of energy minimization. In this work, we have chosen the discretization finite difference method before applying the gradient descent algorithm to optimize the signal (2D grayscale images) denoising functionality. Experiments results, show that `1 regularization encourages image smoothness while allowing for presence of jumps and discontinuities, a key feature for image processing because of the importance of edges in human vision.

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