Recent Submissions

  • Multiple Benefits through Smart Home Energy Management Solutions—A Simulation-Based Case Study of a Single-Family-House in Algeria and Germany 

    Ringel, Marc; Laidi, Roufaida; Djenouri, Djamel
    In : (mdpi, 2019-04-23)
    From both global and local perspectives, there are strong reasons to promote energy efficiency. These reasons have prompted leaders in the European Union (EU) and countries of the Middle East and North Africa (MENA) to adopt policies to move their citizenry toward more efficient energy consumption. Energy efficiency ...
  • UDEPLOY: User-Driven Learning for Occupancy Sensors DEPLOYment In Smart Buildings 

    Laidi, Roufaida; Djenouri, Djamel
    In : (IEEE, Athens, Greece, 2018-03)
    A solution for motion sensors deployment in smart buildings is proposed. It differentiates the monitored zones according to their occupancy, where highly-occupied zones have higher coverage requirements over low-occupied zones, and thus are assigned higher granularity in the targeted coverage (weights). The proposed ...
  • Machine Learning for Smart Building Applications: Review and Taxonomy 

    Djenouri, Djamel; Laidi, Roufaida; Djenouri, Youcef; Balasingham, Ilangko
    In : (ACM, 2019-03)
    The use of machine learning (ML) in smart building applications is reviewed in this paper. We split existing solutions into two main classes, occupant-centric vs. energy/devices centric. The first class groups solutions that use ML for aspects related to the occupants, including (1) occupancy estimation and identification, ...
  • Machine Learning for Smart Building Applications: Review and Taxonomy 

    DJENOURI, DJAMEL; LAIDI, ROUFAIDA; DJENOURI, YOUCEF; BALASINGHAM, ILANGKO
    In : (ACM, 2019-03)
    The use of machine learning (ML) in smart building applications is reviewed in this paper. We split existing solutions into two main classes, occupant-centric vs. energy/devices centric. The first class groups solutions that use ML for aspects related to the occupants, including (1) occupancy estimation and identification, ...
  • Entraide entre les apprenants dans les formations à distance : rôle du sentiment d’appartenance sociale 

    Bebbouchi, Dalila; Jézégou, Annie
    In : Rapports de recherche internes, (CERIST, Alger, 2019-03-19)
    La communication présente une recherche doctorale actuellement en cours dans un contexte d’e-formation des adultes. Elle vise à décrire les comportements d’entraide spontanée entre étudiants engagés dans une formation intégralement à distance et à examiner l’effet du sentiment d’appartenance sociale sur ces comportements. ...
  • Using ABE for Medical Data Protection in Fog Computing 

    KRINAH, Abdelghani; CHALLAL, Yacine; OMAR, Mawloud; NOUALI, Omar
    In : (Heraklion, Crete - Grèce, 2019-05-03)
    Fog is an extension of the cloud computing paradigm, developed to fix the clouds latency, especially for applications requiring a very short response time, such as e-health applications. However, these applications also require a high level of data confidentiality, hence the need to apply appropriate encryption techniques, ...
  • Secure Inverted Index Based Search over Encrypted Cloud Data with User Access Rights Management 

    Boucenna, Fateh; Nouali, Omar; Kechid, Samir; Kechadi, M. Tahar
    In : (Springer, 2019-01-18)
    Cloud computing is a technology that provides users with a large storage space and an enormous computing power. However, the outsourced data are often sensitive and confidential, and hence must be encrypted before being outsourced. Consequently, classical search approaches have become obsolete and new approaches that are ...
  • Bidirectional Variable-Order de Bruijn Graphs 

    Belazzougui, Djamal; Gagie, Travis; Mäkinen, Veli; Previtali, Marco; Puglisi, Simon J.
    In : (World Scientific Publishing, 2018-12)
    Compressed suffix trees and bidirectional FM-indexes can store a set of strings and support queries that let us explore the set of substrings they contain, adding and deleting characters on both the left and right, but they can use much more space than a de Bruijn graph for the strings. Bowe et al.’s BWT-based de Bruijn ...
  • Social Business Process Model Recommender: An MDE approach 

    Khider, Hadjer; Hammoudi, Slimane; benna, Amel; Meziane, Abdelkrim
    In : Rapports de recherche internes, (CERIST, Alger, 2018-09-26)
    with the advent of the social Web (Web 2.0) and the massive use of online social networks (OSNs) (e.g. Facebook, LinkedIn). OSNs have become new opportunity that provides huge Masses of data about users’, rich in their diversity and important in their quantity. Exploring the profiles data among these OSNs attract a ...
  • A parallel BSO Metaheuristic for Molecular Docking problem 

    Hocine, SAADI; Malika, MEHDI; Nadia, Nouali Taboudjemat
    In : Rapports de recherche internes, (CERIST, Alger, 2018-09-12)
    Dans ce rapport, nous proposons un modèle parallèle d’une métaheuristique basée sur l’essaim d'abeilles (BSO) pour résoudre le problème de Docking moléculaire. Cette solution est basée sur le modèle MapReduce, nous utilisons le framework MapCG pour implémenter ce modèle sur les cartes de traitement graphique GPUs ...
  • Leveraging Learners' Activity Logs for Course Reading Analytics Using Session-Based Indicators 

    Sadallah, Madjid; Encelle, Benoît; Maredj, Azze-Eddine; Prié, Yannick
    In : (Inderscience, 2018)
    A challenge that course authors face when reviewing their contents is to detect how to improve their courses in order to meet the expectations of their learners. In this paper, we propose an analytical approach that exploits learners' logs of reading to provide authors with insightful data about the consumption of their ...
  • Visual Data Mining by Virtual Reality for Protein-Protein Interaction Networks 

    Aouaa Noureddine;; Gherbi Rachid; Meziane Abdelkrim; Hayat Hadjar; Insaf Setitra
    In : Rapports de recherche internes, (CERIST, Alger, 2018-03-28)
    Currently, visualization techniques in the genetic field require a very important modeling phase in terms of resources. Traditional modeling techniques (in two dimensions) are rarely adapted to manage and process this mass of information. To overcome this kind of problem, we propose to use a new graph modeling technique ...
  • Random input helps searching predecessors 

    Belazzougui, Djamal; Kaporis, Alexis C.; Spirakis, Paul G.
    In : (CEUR-WS.org, Athènes, 2018-06-17)
    A data structure problem consists of the finite sets: D of data, Q of queries, A of query answers, associated with a function f : D ×Q → A. The data structure of file X is “static” (“dynamic”) if we “do not” (“do”) require quick updates as X changes. An important goal is to compactly encode a file X ∈ D, such that ...
  • Angle Minimization and Graph Analysis for text line segmentation in handwritten documents 

    Setitra, Insaf; Meziane, Abdelkrim
    In : Rapports de recherche internes, (CERIST, Alger, 2018-07-08)
    We propose in this paper a novel approach for text line segmentation in handwritten documents. The approach is based on angle minimization and graph analysis for text lines extraction. We apply our approach on images of ICDAR 2013 Handwriting Segmentation Contest, and give details about its robustness against skew ...
  • Fast matching statistics in small space 

    Belazzougui, Djamal; Cunial, Fabio; Denas, Olgert
    In : (Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik, L'Aquila, 2018-06-27)
    Computing the matching statistics of a string S with respect to a string T on an alphabet of size sigma is a fundamental primitive for a number of large-scale string analysis applications, including the comparison of entire genomes, for which space is a pressing issue. This paper takes from theory to practice an existing ...
  • Memory-Efficient and Ultra-Fast Network Lookup and Forwarding Using Othello Hashing 

    Yu, Ye; Belazzougui, Djamal; Qian, Chen; Zhang, Qin
    In : (IEEE, 2018-04-11)
    Abstract: Network algorithms always prefer low memory cost and fast packet processing speed. Forwarding information base (FIB), as a typical network processing component, requires a scalable and memory-efficient algorithm to support fast lookups. In this paper, we present a new network algorithm, Othello hashing, and ...
  • Classification automatique des images histologiques du cancer du sein par réseaux de neurones convolutifs (RNC) 

    Setitra, Insaf; Meziane, Insaf; Mayouf, Mouna Sabrine; Hamrioui, Amel
    In : Rapports de recherche internes, (CERIST, Alger, 2018-08-01)
    Après le cancer de la peau, le cancer du sein est le deuxième type de cancer le plus commun chez la femme à l’échelle mondiale. Ce dernier enregistre un taux de mortalité assez élevé comparé aux autres types de cancer. (Spanhol, Oliveira et al. 2016). Le diagnostic des tumeurs du sein pour différencier les cellules ...
  • Classification automatique des images histologiques du cancer du sein par réseaux de neurones convolutifs (RNC) 

    Setitra, Insaf; Meziane, Abdelkrim; Mayouf, Mouna Sabrine; Hamrioui, Amel
    In : (Publication en ligne, Nancy, France, 2018-08-01)
    Après le cancer de la peau, le cancer du sein est le deuxième type de cancer le plus commun chez la femme à l’échelle mondiale. Ce dernier enregistre un taux de mortalité assez élevé comparé aux autres types de cancer. (Spanhol, Oliveira et al. 2016). Le diagnostic des tumeurs du sein pour différencier les cellules ...
  • WebVR based Interactive Visualization of Open Health Data 

    HADJAR, Hayet; Meziane, Abdelkrim; GHERBI, Rachid; Setitra, Insaf; Zeghichi, Seyf eddine; Lahmil, Abdessalam
    In : Rapports de recherche internes, (CERIST, Alger, 2018-04-22)
    Visualization and manipulation of complex and multivariate data in virtual worlds is important for both holders of these data and for their users. Indeed, Virtual Reality helps to make multidimensional data more intelligible and to bring useful information and knowledge. Offering Virtual Reality to browsers, also known ...
  • A Tracking Approach for Text Line Segmentation in Handwritten Documents 

    Setitra, Insaf
    In : (Springer / LNCS Series Book, Porto Portugal, 2017-02-24)
    Tracking of objects in videos consists of giving a label to the same object moving in different frames. This labelling is performed by predicting position of the object given its set of features observed in previous frames. In this work, we apply the same rationale by considering each connected component in the manuscript ...

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