Subjects -> PHOTOGRAPHY (Total: 20 journals)
Showing 1 - 10 of 10 Journals sorted alphabetically
British Journal of Photography     Full-text available via subscription   (Followers: 28)
Ciel variable : Art, photo, médias, culture     Full-text available via subscription   (Followers: 1)
Color Research & Application     Hybrid Journal   (Followers: 4)
Études photographiques     Open Access   (Followers: 8)
Fotocinema : Revista Científica de Cine y Fotografía     Open Access   (Followers: 10)
Getty Research Journal     Full-text available via subscription   (Followers: 5)
History of Photography     Hybrid Journal   (Followers: 39)
Imaging Science Journal     Hybrid Journal   (Followers: 4)
International Journal of Multimedia Intelligence and Security     Hybrid Journal   (Followers: 9)
ISPRS Journal of Photogrammetry and Remote Sensing     Hybrid Journal   (Followers: 80)
Journal of Imaging Science and Technology     Full-text available via subscription   (Followers: 8)
Peritia     Full-text available via subscription   (Followers: 9)
Philosophical Papers and Review     Open Access   (Followers: 3)
Photographies     Hybrid Journal   (Followers: 13)
Photography and Culture     Hybrid Journal   (Followers: 31)
Rivista di studi di fotografia. Journal of Studies in Photography     Open Access   (Followers: 1)
The Photogrammetric Record     Hybrid Journal   (Followers: 11)
Trans-Asia Photography Review     Free   (Followers: 6)
Similar Journals
Journal Cover
International Journal of Multimedia Intelligence and Security
Number of Followers: 9  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2042-3462 - ISSN (Online) 2042-3470
Published by Inderscience Publishers Homepage  [450 journals]
  • Implementation of liquefied natural gas as an alternative fuel technology
           using stochastic traffic: a case study for Morocco

    • Free pre-print version: Loading...

      Authors: Ali Gounni, Noureddine Rais, Mostafa Azzouzi Idrissi
      Pages: 321 - 336
      Abstract: This paper examines the possibility of reducing greenhouse gas emissions by using liquefied natural gas (LNG) as an alternative fuel technology for light-duty vehicles. The survey uses a scenario-based traffic simulation approach by applying a simulation of microscopic traffic emissions. We have considered three scenarios: the first scenario, current and pessimistic, presents the case of absence of the intervention of the state and supposes 0% of liquefied natural gas and 100% of diesel; second scenario, optimistic, in case of partial intervention of the state and supposes 50% of liquefied natural gas and 50% of diesel; third scenario, optimistic, in the case of a total intervention of the state, which supposes 100% of LNG and 0% of diesel. SUMO includes two emission assessment models. Both models implement different classes of vehicle emissions. The first model is based on HBEFA v2.1 (a continuous reformulation of the HBEFA v2.1 emissions database). The second is PHEMLIGHT, a derivation of the original PHEM emission model. The results presented in this article are generated by using PHEMLIGHT.
      Keywords: liquefied natural gas; LNG; greenhouse gas emissions; stochastic traffic; alternative fuels; compressed natural gas; CNG; Morocco
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 321 - 336
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114774
      Issue No: Vol. 3, No. 4 (2021)
       
  • Unsupervised graph clustering for community detection in complex networks
           using spectral analysis

    • Free pre-print version: Loading...

      Authors: Zakariyaa Ait El Mouden, Abdeslam Jakimi, Moha Hajar
      Pages: 337 - 347
      Abstract: Clustering is a recent technique for a smart classification of data, where the output is a set of clusters and each cluster regroups data points having similar behaviours. Traditional clustering algorithms are those where we predefine the number of clusters as an input parameter, and we control the size of the neighbourhood, also called supervised clustering. Recently, with data evolution in term of volume and variety, supervised clustering techniques were overwhelmed and unsupervised algorithms started to appear. Spectral clustering (SC) is a graph clustering technique based on spectral analysis, and it is one of the most powerful unsupervised clustering techniques. This paper presents an application of a spectral clustering algorithm to data modelled by graphs and a comparison between the two families of SC; unnormalised SC and normalised SC. We also introduce a modification of normalised SC algorithm to make the number of clusters estimated and not given as an input parameter. Further works are needed to apply the approach to larger datasets in order to evaluate its performance against big data challenges.
      Keywords: big data; graph clustering; spectral clustering; community detection; complex networks; spectral analysis
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 337 - 347
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114775
      Issue No: Vol. 3, No. 4 (2021)
       
  • XEW 2.0: big data analytics tool based on swarm intelligence

    • Free pre-print version: Loading...

      Authors: Fadwa Bouhafer, Anass El Haddadi, Mohammed Heyouni, Ouafaa Ben Ali
      Pages: 348 - 370
      Abstract: Nowadays, data is a golden capital for any business organisation that wants to improve their business. The big organisations and the most reputed ones do not only think to collect data, but they make continuous efforts to use this data for efficient decision-making. Data visualisation plays a crucial importance in big data analysis. The existence of various data visualisation methods can be confusing for users to choose the most appropriate. In this paper, we present the big data analytics tool XEW 2.0 based on swarm intelligence, especially the ant colony optimisation. XEW 2.0 design is based on a detailed study of data visualisation. This study presents a guide for choosing data visualisation methods, and how the traditional methods are improved to meet the big data visualisations need.
      Keywords: big data visualisation; big data analytics; incremental clustering; ant colony optimisation; swarm intelligence; XEW 2.0
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 348 - 370
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114776
      Issue No: Vol. 3, No. 4 (2021)
       
  • An anonymous electronic voting scheme for multiple elections using a
           variant of the ElGamal digital signature

    • Free pre-print version: Loading...

      Authors: Leila Zahhafi, Omar Khadir
      Pages: 371 - 382
      Abstract: In this paper we present an electronic voting protocol valid for multiple elections. The work is based on a variant of the ElGamal digital signature. Our proposed method allows to run <i>t</i> elections using the same parameters. We use the RSA blind signature for all transactions in the voting process. Security and complexity of the presented scheme are analysed.
      Keywords: public key cryptography; e-voting; digital signature; blind signature; discrete logarithm problem
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 371 - 382
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114777
      Issue No: Vol. 3, No. 4 (2021)
       
  • New generic approach based on cross compilation for securing IoT
           communications

    • Free pre-print version: Loading...

      Authors: Anouar Abdelhakim Boudhir, Ikram Ben Abdel Ouahab, Mohamed Ben Ahmed, Lotfi Elaachak, Mohammed Bouhorma
      Pages: 383 - 392
      Abstract: More and more devices are connected to the internet today. However security solutions are insufficient to well secure all these things. IoT devices are limited in terms of processing, storage and energy. So using classical cryptography solutions to secure IoT communications is not the best choice. In a previous work we proposed a new security approach for IoT communications system. Our proposed architecture used multi-agent systems to secure smart home environment. As generalisation, in this paper we present a generic approach touching on securing different IoT applications using multi-agent systems and KQML language. We get inspiration from the cross compilation concept to secure IoT communications. So the main goal of this paper is to clear up the proposed idea. In addition we perform a detailed explanation of the security process to secure the communication between groups of IoT devices in different environment.
      Keywords: security; internet of things; IoT; multi-agent system; MAS
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 383 - 392
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114781
      Issue No: Vol. 3, No. 4 (2021)
       
  • A supervised learning approach to estimating the urban traffic state based
           on floating car data

    • Free pre-print version: Loading...

      Authors: Marouane Mzibri, Abdelilah Maach, Driss Elghanami
      Pages: 393 - 406
      Abstract: Intelligent transportation systems aim to increase the efficiency of mobility through the use of new information and communication technologies. This paper presents a supervised learning approach to estimate the traffic state in the urban road networks. The data used in this work were collected from the GPS sensors installed on the connected vehicles. We validate the proposed model using the k-fold cross-validation method and we evaluate the prediction accuracy with the root mean square error and the mean absolute error metrics. The proposed model was evaluated by numerical simulation. The results obtained by estimating the mean travel time in the road network using the proposed method showed good accuracy with a ratio of the connected vehicles not exceeding 15%.
      Keywords: travel time prediction; supervised learning; intelligent transportation system; data-driven; floating car data; probe data; GPS
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 393 - 406
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114795
      Issue No: Vol. 3, No. 4 (2021)
       
  • Study and review of OSN and SIoT trust models: towards a dynamic MOOC
           trust model

    • Free pre-print version: Loading...

      Authors: Khadija Elghomary, Driss Bouzidi, Najima Daoudi
      Pages: 407 - 431
      Abstract: The lack of collaboration among learners has proven to be an influential factor for their demotivation and disengagement. In MOOCs which are overpopulated by a huge number of learners, with heterogeneous communications and ever-changing behaviours, trust concerns can easily discourage learners to interact among their co-learners. Hence, supporting learners to find trusted peers to collaborate with is a promising solution to overcome this problem. In this paper, we offer a study of certain representative trust models pertaining to online social networks (OSNs) and social internet of things (SIoT). This analysis allows us to reach the following objectives: 1) clearer comprehension of these algorithms and understanding how to assess trust between entities; 2) determine the central elements requested for an efficient trust model; 3) be in a position to elaborate an adapted MOOC trust model.
      Keywords: trust models; online social networks; OSNs; social internet of things; SIoT; MOOC platform; social tutoring
      Citation: International Journal of Multimedia Intelligence and Security, Vol. 3, No. 4 (2020) pp. 407 - 431
      PubDate: 2021-05-06T23:20:50-05:00
      DOI: 10.1504/IJMIS.2020.114796
      Issue No: Vol. 3, No. 4 (2021)
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 35.172.217.174
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-