Publisher: Inderscience Publishers   (Total: 447 journals)

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Showing 1 - 200 of 447 Journals sorted alphabetically
African J. of Accounting, Auditing and Finance     Hybrid Journal   (Followers: 15)
African J. of Economic and Sustainable Development     Hybrid Journal   (Followers: 18)
Afro-Asian J. of Finance and Accounting     Hybrid Journal   (Followers: 8, SJR: 0.195, CiteScore: 0)
American J. of Finance and Accounting     Hybrid Journal   (Followers: 24)
Asian J. of Management Science and Applications     Hybrid Journal   (Followers: 4)
Atoms for Peace: an Intl. J.     Hybrid Journal   (Followers: 3)
Electronic Government, an Intl. J.     Hybrid Journal   (Followers: 16, SJR: 0.424, CiteScore: 1)
EuroMed J. of Management     Hybrid Journal  
European J. of Cross-Cultural Competence and Management     Hybrid Journal   (Followers: 7)
European J. of Industrial Engineering     Hybrid Journal   (Followers: 10, SJR: 0.595, CiteScore: 1)
European J. of Intl. Management     Hybrid Journal   (Followers: 3, SJR: 0.3, CiteScore: 1)
Global Business and Economics Review     Hybrid Journal   (Followers: 3, SJR: 0.154, CiteScore: 0)
Interdisciplinary Environmental Review     Hybrid Journal   (Followers: 3)
Intl. J. of Abrasive Technology     Hybrid Journal   (Followers: 2, SJR: 0.279, CiteScore: 0)
Intl. J. of Accounting and Finance     Hybrid Journal   (Followers: 18)
Intl. J. of Accounting, Auditing and Performance Evaluation     Hybrid Journal   (Followers: 16, SJR: 0.14, CiteScore: 0)
Intl. J. of Ad Hoc and Ubiquitous Computing     Hybrid Journal   (Followers: 8, SJR: 0.21, CiteScore: 1)
Intl. J. of Adaptive and Innovative Systems     Hybrid Journal   (Followers: 1)
Intl. J. of Additive and Subtractive Materials Manufacturing     Hybrid Journal   (Followers: 7)
Intl. J. of Advanced Intelligence Paradigms     Hybrid Journal   (Followers: 5, SJR: 0.144, CiteScore: 1)
Intl. J. of Advanced Mechatronic Systems     Hybrid Journal   (Followers: 3, SJR: 0.132, CiteScore: 0)
Intl. J. of Advanced Media and Communication     Hybrid Journal   (Followers: 27, SJR: 0.124, CiteScore: 0)
Intl. J. of Advanced Operations Management     Hybrid Journal   (Followers: 10, SJR: 0.163, CiteScore: 0)
Intl. J. of Aerodynamics     Hybrid Journal   (Followers: 33)
Intl. J. of Agent-Oriented Software Engineering     Hybrid Journal   (Followers: 3)
Intl. J. of Agile and Extreme Software Development     Hybrid Journal   (Followers: 5)
Intl. J. of Agile Systems and Management     Hybrid Journal   (Followers: 5, SJR: 0.878, CiteScore: 3)
Intl. J. of Agricultural Resources, Governance and Ecology     Hybrid Journal   (Followers: 2, SJR: 0.152, CiteScore: 0)
Intl. J. of Agriculture Innovation, Technology and Globalisation     Hybrid Journal  
Intl. J. of Alternative Propulsion     Hybrid Journal   (Followers: 14)
Intl. J. of Applied Cryptography     Hybrid Journal   (Followers: 9, SJR: 0.455, CiteScore: 3)
Intl. J. of Applied Decision Sciences     Hybrid Journal   (Followers: 1, SJR: 0.275, CiteScore: 1)
Intl. J. of Applied Management Science     Hybrid Journal   (Followers: 4, SJR: 0.229, CiteScore: 0)
Intl. J. of Applied Nonlinear Science     Hybrid Journal   (Followers: 1)
Intl. J. of Applied Pattern Recognition     Hybrid Journal   (Followers: 8)
Intl. J. of Applied Systemic Studies     Hybrid Journal   (SJR: 0.129, CiteScore: 0)
Intl. J. of Arab Culture, Management and Sustainable Development     Hybrid Journal   (Followers: 7)
Intl. J. of Artificial Intelligence and Soft Computing     Hybrid Journal   (Followers: 11)
Intl. J. of Arts and Technology     Hybrid Journal   (Followers: 6, SJR: 0.225, CiteScore: 1)
Intl. J. of Auditing Technology     Hybrid Journal   (Followers: 5)
Intl. J. of Automation and Control     Hybrid Journal   (Followers: 11, SJR: 0.189, CiteScore: 1)
Intl. J. of Automation and Logistics     Hybrid Journal   (Followers: 5)
Intl. J. of Automotive Composites     Hybrid Journal   (Followers: 4)
Intl. J. of Automotive Technology and Management     Hybrid Journal   (Followers: 7, SJR: 0.374, CiteScore: 1)
Intl. J. of Autonomic Computing     Hybrid Journal   (Followers: 2)
Intl. J. of Autonomous and Adaptive Communications Systems     Hybrid Journal   (Followers: 3, SJR: 0.128, CiteScore: 0)
Intl. J. of Aviation Management     Hybrid Journal   (Followers: 7)
Intl. J. of Banking, Accounting and Finance     Hybrid Journal   (Followers: 16, SJR: 0.137, CiteScore: 0)
Intl. J. of Behavioural Accounting and Finance     Hybrid Journal   (Followers: 11)
Intl. J. of Behavioural and Healthcare Research     Hybrid Journal   (Followers: 8)
Intl. J. of Bibliometrics in Business and Management     Hybrid Journal   (Followers: 2)
Intl. J. of Big Data Intelligence     Hybrid Journal   (Followers: 24)
Intl. J. of Bio-Inspired Computation     Hybrid Journal   (Followers: 1, SJR: 0.721, CiteScore: 4)
Intl. J. of Bioinformatics Research and Applications     Hybrid Journal   (Followers: 16, SJR: 0.157, CiteScore: 0)
Intl. J. of Biomechatronics and Biomedical Robotics     Hybrid Journal   (Followers: 4)
Intl. J. of Biomedical Engineering and Technology     Hybrid Journal   (Followers: 5, SJR: 0.205, CiteScore: 1)
Intl. J. of Biomedical Nanoscience and Nanotechnology     Hybrid Journal   (Followers: 8)
Intl. J. of Biometrics     Hybrid Journal   (Followers: 5, SJR: 0.155, CiteScore: 0)
Intl. J. of Biotechnology     Hybrid Journal   (Followers: 6, SJR: 0.269, CiteScore: 1)
Intl. J. of Blockchains and Cryptocurrencies     Hybrid Journal   (Followers: 1)
Intl. J. of Bonds and Derivatives     Hybrid Journal   (Followers: 1)
Intl. J. of Business and Data Analytics     Hybrid Journal  
Intl. J. of Business and Emerging Markets     Hybrid Journal   (Followers: 2)
Intl. J. of Business and Globalisation     Hybrid Journal   (Followers: 3, SJR: 0.263, CiteScore: 1)
Intl. J. of Business and Systems Research     Hybrid Journal   (Followers: 1, SJR: 0.104, CiteScore: 0)
Intl. J. of Business Competition and Growth     Hybrid Journal   (Followers: 5)
Intl. J. of Business Continuity and Risk Management     Hybrid Journal   (Followers: 16)
Intl. J. of Business Environment     Hybrid Journal   (Followers: 3)
Intl. J. of Business Excellence     Hybrid Journal   (Followers: 4, SJR: 0.274, CiteScore: 1)
Intl. J. of Business Forecasting and Marketing Intelligence     Hybrid Journal   (Followers: 6)
Intl. J. of Business Governance and Ethics     Hybrid Journal   (Followers: 7, SJR: 0.171, CiteScore: 0)
Intl. J. of Business Information Systems     Hybrid Journal   (Followers: 17, SJR: 0.266, CiteScore: 1)
Intl. J. of Business Innovation and Research     Hybrid Journal   (Followers: 11, SJR: 0.28, CiteScore: 1)
Intl. J. of Business Intelligence and Data Mining     Hybrid Journal   (Followers: 30, SJR: 0.249, CiteScore: 2)
Intl. J. of Business Intelligence and Systems Engineering     Hybrid Journal  
Intl. J. of Business Performance and Supply Chain Modelling     Hybrid Journal   (Followers: 19, SJR: 0.18, CiteScore: 0)
Intl. J. of Business Performance Management     Hybrid Journal   (Followers: 9, SJR: 0.197, CiteScore: 1)
Intl. J. of Business Process Integration and Management     Hybrid Journal   (Followers: 12, SJR: 0.149, CiteScore: 1)
Intl. J. of Chinese Culture and Management     Hybrid Journal   (Followers: 4)
Intl. J. of Circuits and Architecture Design     Hybrid Journal   (Followers: 6)
Intl. J. of Cloud Computing     Hybrid Journal   (Followers: 25)
Intl. J. of Cognitive Biometrics     Hybrid Journal   (Followers: 3)
Intl. J. of Cognitive Performance Support     Hybrid Journal   (Followers: 4)
Intl. J. of Collaborative Engineering     Hybrid Journal   (Followers: 1)
Intl. J. of Collaborative Enterprise     Hybrid Journal   (Followers: 1)
Intl. J. of Collaborative Intelligence     Hybrid Journal   (Followers: 3)
Intl. J. of Communication Networks and Distributed Systems     Hybrid Journal   (Followers: 7, SJR: 0.177, CiteScore: 1)
Intl. J. of Comparative Management     Hybrid Journal  
Intl. J. of Competitiveness     Hybrid Journal   (Followers: 3)
Intl. J. of Complexity in Applied Science and Technology     Hybrid Journal  
Intl. J. of Complexity in Leadership and Management     Hybrid Journal   (Followers: 28)
Intl. J. of Computational Biology and Drug Design     Hybrid Journal   (Followers: 1, SJR: 0.231, CiteScore: 1)
Intl. J. of Computational Complexity and Intelligent Algorithms     Hybrid Journal   (Followers: 2)
Intl. J. of Computational Economics and Econometrics     Hybrid Journal   (Followers: 6)
Intl. J. of Computational Intelligence in Bioinformatics and Systems Biology     Hybrid Journal   (Followers: 13)
Intl. J. of Computational Intelligence Studies     Hybrid Journal   (Followers: 3)
Intl. J. of Computational Materials Science and Surface Engineering     Hybrid Journal   (Followers: 6, SJR: 0.135, CiteScore: 0)
Intl. J. of Computational Medicine and Healthcare     Hybrid Journal   (Followers: 1)
Intl. J. of Computational Science and Engineering     Hybrid Journal   (Followers: 2, SJR: 0.373, CiteScore: 1)
Intl. J. of Computational Systems Engineering     Hybrid Journal   (Followers: 1)
Intl. J. of Computational Vision and Robotics     Hybrid Journal   (Followers: 5, SJR: 0.129, CiteScore: 0)
Intl. J. of Computer Aided Engineering and Technology     Hybrid Journal   (Followers: 3, SJR: 0.131, CiteScore: 0)
Intl. J. of Computer Applications in Technology     Hybrid Journal   (Followers: 1, SJR: 0.225, CiteScore: 1)
Intl. J. of Computers in Healthcare     Hybrid Journal   (Followers: 3)
Intl. J. of Computing Science and Mathematics     Hybrid Journal   (Followers: 2, SJR: 0.299, CiteScore: 1)
Intl. J. of Continuing Engineering Education and Life-Long Learning     Hybrid Journal   (Followers: 5, SJR: 0.196, CiteScore: 0)
Intl. J. of Convergence Computing     Hybrid Journal   (Followers: 2)
Intl. J. of Corporate Governance     Hybrid Journal   (Followers: 5)
Intl. J. of Corporate Strategy and Social Responsibility     Hybrid Journal   (Followers: 6)
Intl. J. of Creative Computing     Hybrid Journal   (Followers: 1)
Intl. J. of Critical Accounting     Hybrid Journal   (Followers: 3)
Intl. J. of Critical Computer-Based Systems     Hybrid Journal   (Followers: 1, SJR: 0.127, CiteScore: 0)
Intl. J. of Critical Infrastructures     Hybrid Journal   (Followers: 2, SJR: 0.173, CiteScore: 1)
Intl. J. of Data Analysis Techniques and Strategies     Hybrid Journal   (Followers: 17, SJR: 0.23, CiteScore: 0)
Intl. J. of Data Mining and Bioinformatics     Hybrid Journal   (Followers: 19, SJR: 0.217, CiteScore: 1)
Intl. J. of Data Mining, Modelling and Management     Hybrid Journal   (Followers: 14, SJR: 0.209, CiteScore: 0)
Intl. J. of Data Science     Hybrid Journal   (Followers: 10)
Intl. J. of Decision Sciences, Risk and Management     Hybrid Journal   (Followers: 10)
Intl. J. of Decision Support Systems     Hybrid Journal   (Followers: 2)
Intl. J. of Design Engineering     Hybrid Journal   (Followers: 12)
Intl. J. of Digital Culture and Electronic Tourism     Hybrid Journal   (Followers: 6)
Intl. J. of Digital Enterprise Technology     Hybrid Journal   (Followers: 1)
Intl. J. of Digital Signals and Smart Systems     Hybrid Journal   (Followers: 2)
Intl. J. of Diplomacy and Economy     Hybrid Journal   (Followers: 6)
Intl. J. of Dynamical Systems and Differential Equations     Hybrid Journal   (Followers: 1, SJR: 0.184, CiteScore: 0)
Intl. J. of Earthquake and Impact Engineering     Hybrid Journal   (Followers: 4)
Intl. J. of Economic Policy in Emerging Economies     Hybrid Journal   (Followers: 4, SJR: 0.134, CiteScore: 1)
Intl. J. of Economics and Accounting     Hybrid Journal   (Followers: 1)
Intl. J. of Economics and Business Research     Hybrid Journal   (Followers: 5, SJR: 0.129, CiteScore: 0)
Intl. J. of Education Economics and Development     Hybrid Journal   (Followers: 5, SJR: 0.156, CiteScore: 0)
Intl. J. of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 10, SJR: 0.225, CiteScore: 1)
Intl. J. of Electronic Banking     Hybrid Journal   (Followers: 6)
Intl. J. of Electronic Business     Hybrid Journal   (Followers: 2, SJR: 0.24, CiteScore: 0)
Intl. J. of Electronic Customer Relationship Management     Hybrid Journal   (Followers: 3, SJR: 0.148, CiteScore: 0)
Intl. J. of Electronic Democracy     Hybrid Journal   (Followers: 2)
Intl. J. of Electronic Finance     Hybrid Journal   (Followers: 5, SJR: 0.155, CiteScore: 0)
Intl. J. of Electronic Governance     Hybrid Journal   (SJR: 0.142, CiteScore: 1)
Intl. J. of Electronic Healthcare     Hybrid Journal   (Followers: 2, SJR: 0.254, CiteScore: 1)
Intl. J. of Electronic Marketing and Retailing     Hybrid Journal   (Followers: 7, SJR: 0.249, CiteScore: 1)
Intl. J. of Electronic Security and Digital Forensics     Hybrid Journal   (Followers: 8, SJR: 0.137, CiteScore: 0)
Intl. J. of Electronic Transport     Hybrid Journal   (Followers: 9)
Intl. J. of Embedded Systems     Hybrid Journal   (Followers: 5, SJR: 0.48, CiteScore: 1)
Intl. J. of Emergency Management     Hybrid Journal   (Followers: 12, SJR: 0.185, CiteScore: 0)
Intl. J. of Energy Technology and Policy     Hybrid Journal   (Followers: 7, SJR: 0.224, CiteScore: 0)
Intl. J. of Engineering Management and Economics     Hybrid Journal   (Followers: 4)
Intl. J. of Engineering Systems Modelling and Simulation     Hybrid Journal   (Followers: 8, SJR: 0.175, CiteScore: 0)
Intl. J. of Enterprise Network Management     Hybrid Journal   (SJR: 0.118, CiteScore: 0)
Intl. J. of Entrepreneurial Venturing     Hybrid Journal   (Followers: 1, SJR: 0.308, CiteScore: 1)
Intl. J. of Entrepreneurship and Innovation Management     Hybrid Journal   (Followers: 29, SJR: 0.255, CiteScore: 1)
Intl. J. of Entrepreneurship and Small Business     Hybrid Journal   (Followers: 32, SJR: 0.401, CiteScore: 1)
Intl. J. of Environment and Health     Hybrid Journal   (Followers: 5, SJR: 0.181, CiteScore: 0)
Intl. J. of Environment and Pollution     Hybrid Journal   (Followers: 2, SJR: 0.215, CiteScore: 1)
Intl. J. of Environment and Sustainable Development     Hybrid Journal   (Followers: 17, SJR: 0.132, CiteScore: 0)
Intl. J. of Environment and Waste Management     Hybrid Journal   (Followers: 4, SJR: 0.175, CiteScore: 0)
Intl. J. of Environment, Workplace and Employment     Hybrid Journal   (Followers: 6, SJR: 0.117, CiteScore: 0)
Intl. J. of Environmental Engineering     Hybrid Journal   (Followers: 6)
Intl. J. of Environmental Policy and Decision Making     Hybrid Journal   (Followers: 2)
Intl. J. of Environmental Technology and Management     Hybrid Journal   (Followers: 1, SJR: 0.141, CiteScore: 0)
Intl. J. of Exergy     Hybrid Journal   (Followers: 3, SJR: 0.396, CiteScore: 1)
Intl. J. of Experimental and Computational Biomechanics     Hybrid Journal   (Followers: 8)
Intl. J. of Experimental Design and Process Optimisation     Hybrid Journal   (Followers: 7)
Intl. J. of Export Marketing     Hybrid Journal   (Followers: 3)
Intl. J. of Financial Engineering and Risk Management     Hybrid Journal   (Followers: 5)
Intl. J. of Financial Innovation in Banking     Hybrid Journal   (Followers: 4)
Intl. J. of Financial Markets and Derivatives     Hybrid Journal   (Followers: 5)
Intl. J. of Financial Services Management     Hybrid Journal   (Followers: 1)
Intl. J. of Food Safety, Nutrition and Public Health     Hybrid Journal   (Followers: 22)
Intl. J. of Forensic Engineering     Hybrid Journal   (Followers: 3)
Intl. J. of Forensic Engineering and Management     Hybrid Journal   (Followers: 3)
Intl. J. of Forensic Software Engineering     Hybrid Journal   (Followers: 2)
Intl. J. of Foresight and Innovation Policy     Hybrid Journal   (Followers: 7, SJR: 0.115, CiteScore: 0)
Intl. J. of Functional Informatics and Personalised Medicine     Hybrid Journal   (Followers: 4)
Intl. J. of Fuzzy Computation and Modelling     Hybrid Journal   (Followers: 2)
Intl. J. of Gender Studies in Developing Societies     Hybrid Journal   (Followers: 5)
Intl. J. of Global Energy Issues     Hybrid Journal   (Followers: 8, SJR: 0.199, CiteScore: 0)
Intl. J. of Global Environmental Issues     Hybrid Journal   (Followers: 3, SJR: 0.153, CiteScore: 0)
Intl. J. of Global Warming     Hybrid Journal   (Followers: 2, SJR: 0.259, CiteScore: 1)
Intl. J. of Globalisation and Small Business     Hybrid Journal   (Followers: 14, SJR: 0.233, CiteScore: 1)
Intl. J. of Governance and Financial Intermediation     Hybrid Journal  
Intl. J. of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
Intl. J. of Green Economics     Hybrid Journal   (Followers: 6, SJR: 0.209, CiteScore: 0)
Intl. J. of Grid and Utility Computing     Hybrid Journal   (SJR: 0.341, CiteScore: 2)
Intl. J. of Happiness and Development     Hybrid Journal   (Followers: 8)
Intl. J. of Healthcare Policy     Hybrid Journal   (Followers: 1)
Intl. J. of Healthcare Technology and Management     Hybrid Journal   (Followers: 7, SJR: 0.139, CiteScore: 0)
Intl. J. of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7, SJR: 0.23, CiteScore: 0)
Intl. J. of High Performance Computing and Networking     Hybrid Journal   (Followers: 4, SJR: 0.428, CiteScore: 1)
Intl. J. of High Performance Systems Architecture     Hybrid Journal   (Followers: 6, SJR: 0.116, CiteScore: 0)
Intl. J. of Higher Education and Sustainability     Hybrid Journal   (Followers: 6)
Intl. J. of Hospitality and Event Management     Hybrid Journal   (Followers: 4)
Intl. J. of Human Factors and Ergonomics     Hybrid Journal   (Followers: 20, SJR: 0.117, CiteScore: 0)
Intl. J. of Human Factors Modelling and Simulation     Hybrid Journal   (Followers: 18)
Intl. J. of Human Resources Development and Management     Hybrid Journal   (Followers: 29, SJR: 0.162, CiteScore: 0)
Intl. J. of Human Rights and Constitutional Studies     Hybrid Journal   (Followers: 14)
Intl. J. of Humanitarian Technology     Hybrid Journal   (Followers: 1)
Intl. J. of Hybrid Intelligence     Hybrid Journal  
Intl. J. of Hydrology Science and Technology     Hybrid Journal   (Followers: 8, SJR: 0.43, CiteScore: 2)
Intl. J. of Hydromechatronics     Hybrid Journal  
Intl. J. of Image Mining     Hybrid Journal   (Followers: 1)
Intl. J. of Immunological Studies     Hybrid Journal   (Followers: 1)

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Similar Journals
Journal Cover
International Journal of Computational Science and Engineering
Journal Prestige (SJR): 0.373
Citation Impact (citeScore): 1
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1742-7185 - ISSN (Online) 1742-7193
Published by Inderscience Publishers Homepage  [447 journals]
  • A holistic IT infrastructure management framework
    • Authors: Sergio Varga, Gilmar Barreto, Paulo David Battaglin
      Pages: 1 - 9
      Abstract: Information systems (IS) are becoming increasingly complex and they have issues to be solved. New technologies, products and deployment models make the management of an IS difficult to maintain. Organisations need to deploy tools, processes, and governance in their information technology (IT) environment to support their IS. This increases even more the complexity of an IT environment and it drives organisations to manage the environment by silos or components. This type of management inhibits organisations to ensure the entire environment has been properly managed according to what was agreed in the outsourcing contract despite the usage of IT frameworks available. This paper intends to analyse and identify these issues, and also to propose an IT management framework that will help organisations to provide an efficient service. This service is based on agreed scope and will ensure that all contracted services will be deployed with accuracy, completeness, management, and awareness.
      Keywords: information systems; information technology; IT management; information technology infrastructure library; ITIL; information technology service management; ITSM; cloud
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 1 - 9
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105222
      Issue No: Vol. 21, No. 1 (2020)
       
  • An anchor node selection mechanism-based node localisation for mines using
           wireless sensor networks
    • Authors: Kangshun Li, Hui Wang, Ying Huang
      Pages: 10 - 18
      Abstract: To improve the low localisation accuracy problem facing wireless sensor network (WSN) nodes in mines, a localisation algorithm is proposed to improve the localisation accuracy of received signal strength indication (RSSI) using an anchor node selection mechanism. This localisation mainly includes three phases: first, the anchor node RSSI values received from an unknown node are sorted from high to low; second, the four anchor nodes with the highest RSSI values are selected by a Gaussian elimination method. These nodes are not in the same plane and form a prismatic shape, and the distance from any one node to a plane consisting of another three points is not less than a certain threshold value; finally, the square method is used to estimate the coordinates of the unknown nodes to realise the precise localisation of the unknown nodes. The simulation results show that the proposed algorithm has greatly improved the localisation accuracy compared with other traditional localisation algorithms.
      Keywords: underground tunnels; received signal strength indication; RSSI; anchor node selection; least square method; Gaussian elimination method
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 10 - 18
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105208
      Issue No: Vol. 21, No. 1 (2020)
       
  • A malware variants detection methodology with an opcode-based feature
           learning method and a fast density-based clustering algorithm
    • Authors: Hui Yin, Jixin Zhang, Zheng Qin
      Pages: 19 - 29
      Abstract: Malware is one of the most terrible and major security threats facing the internet today, which can be defined as any type of malicious code to harm a computer or network. As malware variants can be equipped with sophisticated mechanisms to bypass traditional detection systems, in this paper, we propose a malware variant detection approach that can automatically, rapidly and accurately detect malware variants. In our approach, we present an asynchronous architecture for automated training and detection. Under this architecture, to improve the detection speed while retaining the accuracy, we propose an information entropy-based feature extraction method to extract a few but very useful features and a distance-based weight learning method to weight these features. To further improve the detection speed, we propose our fast density-based clustering algorithm. We evaluate our approach with a number of Windows-based malware instances which belong to six large families, and our experiments demonstrate that our automated malware variant detection method is able to achieve high accuracy with a significant speedup compared with the other state-of-art approaches.
      Keywords: distance-based weight learning; fast density-based clustering; FDBC; information entropy; malware variants
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 19 - 29
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105209
      Issue No: Vol. 21, No. 1 (2020)
       
  • Optimised tags with time attenuation recommendation algorithm based on
           tripartite graphs network
    • Authors: Ming Zhang, Wei Chen
      Pages: 30 - 37
      Abstract: Social recommendation has attracted increasing attention in recent years due to the potential value of social relations in recommender systems. Social tags play an important role in improving recommendation accuracy. However, garbage tags may lead to data matrix sparseness and affect the accuracy and performance of recommendation system. To optimise social tags in the recommendation system, tags are sorted by popularity ranking method with the time attention model in order to remove the garbage tags. The time attenuation model is used to consider the variation of tags with time change. Then a novel recommendation algorithm with optimised social tags is proposed based on complete tripartite graph network. This method considers the preference information of users and items and generates recommendation items for users based on collaborative filtering. Experimental results show that the proposed algorithm predicts recommendation items more accurately than other existing approaches.
      Keywords: tags optimisation; tripartite graphs network; time attenuation model; social recommendation
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 30 - 37
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105210
      Issue No: Vol. 21, No. 1 (2020)
       
  • Probabilistic rough set-based band selection method for hyperspectral
           data classification
    • Authors: Min Li, Shaobo Deng, Lei Wang, Jun Ye
      Pages: 38 - 48
      Abstract: This paper proposes an innovative band selection algorithm called probabilistic rough set-based band selection (PRSBS) algorithm. The proposed PRSBS is a supervised band selection algorithm with efficiency for it only needs to calculate the first-order significance measure. The main novelty of the proposed PRSBS algorithm lies in the criterion function which measures the effectiveness of considered band. The PRSBS algorithm uses a probabilistic distribution dependency as the relevance measure between the bands and class labels, which can effectively measure the uncertainty in both the positive and the boundary samples in a dataset. We compared the proposed PRSBS with the most relevant band selection algorithm RSBS on three different hyperspectral datasets, the experimental results show that the PRSBS has better results than the RSBS. Moreover, the PRSBS algorithm runs significantly faster than the RSBS algorithm, which makes it a proper choice for band selection in hyperspectral image dataset.
      Keywords: band selection; probabilistic rough set; hyperspectral image; classification
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 38 - 48
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105211
      Issue No: Vol. 21, No. 1 (2020)
       
  • A universal designated multi verifiers content extraction signature scheme
    • Authors: Min Wang, Yuexin Zhang, Jinhua Ma, Wei Wu
      Pages: 49 - 59
      Abstract: A notion combined the content extraction signature and the universal designated verifier signature was put forth by Lin in 2012. Specifically, it allows an extracted signature holder to designate the signature to a prospective verifier. However, existing designs become inefficient when multi verifiers are involved. To improve the efficiency, in this paper, we extend the notion to the universal designated multi verifiers content extraction signature (UDMVCES). Implementing our new scheme, the extracted signature holder can efficiently designate the signature to multi verifiers. Additionally, we provide the security notions and prove the security of the proposed scheme in the random oracle model. To illustrate the efficiency of our UDMVCES scheme, we analyse the performance of it. The analysis shows that the computation costs and signature lengths of the new scheme are independent of the number of verifiers.
      Keywords: content extraction signature; CES; universal designated multi verifiers signature; extracted signature; random oracle model
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 49 - 59
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105212
      Issue No: Vol. 21, No. 1 (2020)
       
  • Dynamic input domain reduction for test data generation with iterative
           partitioning
    • Authors: Esmaeel Nikravan, Saeed Parsa
      Pages: 60 - 68
      Abstract: A major difficulty concerning test data generation for white box testing is to detect the domain of input variables covering a certain path. With this aim, a new concept, domain coverage, is introduced in this article. In search of appropriate input variable subdomains, covering a desired path, the domains are randomly partitioned as far as subdomains whose boundaries satisfy the path constraints are found. When partitioning, the priority is given to those subdomains whose boundary variables do not satisfy the path constraints. Representing the relation between the subdomains and their parents as a directed acyclic graph, an Euler/Venn reasoning system could be applied to select the most appropriate subdomains. To evaluate our proposed path oriented test data generation method, the results of applying the method to six known benchmark programs, triangle, GCD, calday, shellsort, quicksort and heapsort, is presented.
      Keywords: random testing; test data generation; Euler/Venn diagram; directed acyclic graph; DAG
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 60 - 68
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105213
      Issue No: Vol. 21, No. 1 (2020)
       
  • Multi-class instance-incremental framework for classification in
           fully dynamic graphs
    • Authors: Hardeo Kumar Thakur, Anand Gupta, Sreyashi Nag, Ritvik Shrivastava
      Pages: 69 - 83
      Abstract: Existing work in the area of graph classification is mostly restricted to static graphs. These static classification models prove ineffective in several real life scenarios that require an approach capable of handling data of a dynamic nature. Further, the limited work in the domain of dynamic graphs mainly focuses on solely incremental graphs which fail to accommodate fully dynamic graphs (FDG). Hence, in this paper, we propose a comprehensive framework targeting multi-class classification in fully dynamic graphs by utilising the efficient Weisfeiler-Lehman graph kernel (W-L) with a multi-class support vector machine (SVM). The framework iterates through each update using the instance-incremental method while retaining all historical data in order to ensure higher accuracy. Reliable validation metrics are utilised for the model parameter selection and output verification. Experimental results over four case studies on real-world data demonstrate the efficacy of our approach.
      Keywords: fully dynamic graph; FDG; dynamic graph; graph classification; multi-class classification
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 69 - 83
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105214
      Issue No: Vol. 21, No. 1 (2020)
       
  • Recognition of the landslide disasters with extreme learning machine
    • Authors: Guanyu Chen, Xiang Li, Wenyin Gong, Hui Xu
      Pages: 84 - 94
      Abstract: The geological disasters of landslides induced by the Wenchuan earthquake are great in number so landslide disaster recognition and investigation must be conducted in the early stage of large construction planning in the disaster area. In recent years, the studies on image recognition focus on the extreme learning machine algorithm. Based on the preprocessing of remote sensing images, this paper conducts landslide recognition with remote sensing images through the extreme learning machine classification combined with colour and texture features of ground objects. The comparison experiments of landslide recognition with the support vector machine algorithm shows that the recognition accuracy of the extreme learning machine algorithm is not much different from that of the SVM algorithm, but the extreme learning machine takes short time in training with absolute advantage.
      Keywords: geological disaster; remote sensing image; extreme learning machine; landslide recognition; landslide disasters; image recognition; image classification; neural networks; computational science engineering
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 84 - 94
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105215
      Issue No: Vol. 21, No. 1 (2020)
       
  • A new neural architecture for feature extraction of remote sensing data
    • Authors: Mustapha Si Tayeb, Hadria Fizazi
      Pages: 95 - 104
      Abstract: The paper presents a novel method for the classification of remote sensing data. The proposed approach comprises two main steps: 1) extractor multi-layer perceptron (EMLP) is used for feature extraction of the remote sensing data; 2) the data resulted from the EMLP are classified using support vector machine (SVM) algorithm. The contribution of this work is mainly in the creation of the EMLP method based on the multi-layer perceptron (MLP) method, which has the role of creating a dataset more representative of the classes from the original dataset. To better situate and evaluate our proposed approach, we applied our proposed technique to three datasets, namely, Statlog Landsat satellite, urban land cover and Landsat TM Oran. Several measures were used, for example, classification rate, classification error, precision, recall and F-measure. The experimental results show that the proposed approach (EMLP-SVM) is more efficient and powerful than the basic methods (MLP and SVM) and the existing state-of-the-art classification methods.
      Keywords: classification methods; feature extraction; remote sensing data; extractor multi-layer perceptron; EMLP; support vector machine; SVM; supervised learning
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 95 - 104
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105216
      Issue No: Vol. 21, No. 1 (2020)
       
  • Parallelisation of practical shared sampling alpha matting with OpenMP
    • Authors: Tien-Hsiung Weng, Chi-Ching Chiu, Meng-Yen Hsieh, Huimin Lu, Kuan-Ching Li
      Pages: 105 - 115
      Abstract: In modern filmmaking industry, image matting has been one of the common tasks in video side effects and the necessary intermediate steps in computer vision. It pulls the foreground object from the background of an image by estimating the alpha values. However, the computational speed for matting high resolution images can be significantly slow due to its complexity and computation that is proportional to the size of unknown region. In order to improve the performance, we implement a parallel alpha matting code with OpenMP from existing sequential code for running on the multicore servers. We present and discuss the algorithm and experimentation results from the perspective of the parallel application developer. The development takes less effort, and the results show significant performance improvement of the entire program.
      Keywords: image matting; OpenMP; multicore processing; parallel programming
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 105 - 115
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105217
      Issue No: Vol. 21, No. 1 (2020)
       
  • A novel coverless text information hiding method based on double-tags
           and twice-send
    • Authors: Xiang Zhou, Xianyi Chen, Fasheng Zhang, Ningning Zheng
      Pages: 116 - 124
      Abstract: Recently, coverless text information hiding (CTIH) attracts the attention of an increasing number of researchers because of the high security. However, there are still many problems to be solved, for example the efficiency of retrieving and the hiding capacity. In the existing CTIH methods, the secret information is embedded to be one carrier with one label to ensure the success rate of information hiding. In this paper, we propose a novel CTIH method based on the double-tags and twice-send, in which the double tags in a text are achieved by designing the odd-even adjudgement, and a reverse index is created firstly to promote the efficiency of retrieving, then transform characters into binary numbers, which will be employed as the location tags to determine the secret information in the received texts. Finally, we improve the success rate of information hiding by sending the document twice. The experimental results show that the proposed method makes an improvement in the hiding capacity and efficiency compared with existing text CIH algorithms.
      Keywords: coverless information hiding; double tags; twice-send; text big data
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 116 - 124
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105218
      Issue No: Vol. 21, No. 1 (2020)
       
  • Aligning molecular sequences using hybrid bioinspired algorithm in GPU
    • Authors: J. Jayapriya, Michael Arock
      Pages: 125 - 136
      Abstract: To explicate the functionality of the basic cell, there is a need for the study of bioinformatics. To better understand the structural and functional information of molecules, sequence analysis is considered as the root domain. In this, aligning the sequence is the first step, an NP-complete problem like all biological problems. Owing to the increased molecular data in biology, there is a demand for the development of efficient approaches to this sequence alignment problem. From the study it is concluded that there is trade-off between accuracy and computational time. Focusing on the latter in this paper, a new parallel hybridised bio-inspired approach (PGWOGO) is proposed without sacrificing the accuracy. A grey wolf optimiser technique is hybridised with the genetic operators and the parallel phases are implemented in Quadro 4,000 graphics processing unit. A new crossover and mutation operator's namely horizontal crossover and local gaps shuffle mutation operator between aligned blocks are employed. The performance of proposed algorithm is evaluated using the cells update per second (CUPS) and compared with the state-of-the-art techniques. The results show that the proposed algorithm yields better alignment than other techniques.
      Keywords: graphical processing unit; GPU; alignment; hybrid bioinspired; grey wolf optimiser; GWO; genetic operators; crossover; mutation
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 125 - 136
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105219
      Issue No: Vol. 21, No. 1 (2020)
       
  • Deep learning for collective anomaly detection
    • Authors: Mohiuddin Ahmed, Al-Sakib Khan Pathan
      Pages: 137 - 145
      Abstract: Deep learning has been performing well in a number of application domains. Inspired by its popularity in domains such as image processing, speech recognition, etc., in this paper we explore the effectiveness of deep learning and other supervised learning algorithms for collective anomaly detection. Recently, collective anomaly has become popular for denial of service (DoS) attack detection, however, all these approaches are unsupervised in nature and often have high false alarm rate due to being unsupervised. Therefore, to reduce the false alarm rates, we have experimented using the deep learning method which is supervised in nature. Our experimental results on UNSW-NB15 and KDD Cup 1999 datasets show that the deep learning implemented using H<SUB align="right">2O achieves ≈97% recall for collective anomaly detection. Deep learning outperforms a wide range of unsupervised techniques for collective anomaly detection. The key insight of this paper is to report the efficiency of deep learning for collective anomaly detection. To the best of our knowledge, this paper is the first one to address the collective anomaly detection problem using deep learning.
      Keywords: deep learning; collective anomaly; DoS attack; network; traffic analysis
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 137 - 145
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105220
      Issue No: Vol. 21, No. 1 (2020)
       
  • Evaluating the trustworthiness of BPEL processes based on data dependency
           and XBFG
    • Authors: Chunling Hu, Cuicui Liu, Bixin Li
      Pages: 146 - 161
      Abstract: Composite services implement value-added functionality by composing service components of various granularities. Trust is an important criterion to judge whether a composite service can behave as expected. There is a great need for a flexible trust evaluation method for composite services. In this paper, a data dependency-based trust evaluation approach for composite services is proposed. Firstly, we derive define-use pairs of variables to identify data dependency between service components in BPEL processes modelled by an extensible BPEL flow graph (XBFG); then, dependency links including both direct and indirect data dependencies are used to evaluate the trust of these service components; furthermore, on the basis of BPEL structure and XBFG, reduction rules are proposed to evaluate the global trust of BPEL processes. Experimental results demonstrate that the proposed approach is effective for the trust evaluation of BPEL composite services and stable with the growing number of service components in BPEL.
      Keywords: composite service; trust evaluation; data dependency; dependency link; reduction rules; business process execution language; BPEL; extensible BPEL flow graph; XBFG; service component; value-added functionality; global trust
      Citation: International Journal of Computational Science and Engineering, Vol. 21, No. 1 (2020) pp. 146 - 161
      PubDate: 2020-02-22T23:20:50-05:00
      DOI: 10.1504/IJCSE.2020.105221
      Issue No: Vol. 21, No. 1 (2020)
       
 
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