Home / Journals / CSSE / Vol.34, No.2, 2019
  • Open Access

    ARTICLE

    Incorporating Stress Status in Suicide Detection through Microblog

    Yuanyuan Xue1,2, Qi Li1, TongWu1, LingFeng1, Liang Zhao3, FengYu3
    Computer Systems Science and Engineering, Vol.34, No.2, pp. 65-78, 2019, DOI:10.32604/csse.2019.34.065
    Abstract Suicide has been a perplexing social problem around the world for a long time. Timely sensing hidden suicide risk and offering effective intervention are highly desirable and valuable for individuals and their families. Psychological studies prove that stress status, suicide-related expressions, and social engagement are reliable predictors of suicide risk. However, existing clinical diagnosis can only provide effective treatments to a restricted number of people because of its limited capacity. With the popular usage of social media like microblogs, a new channel to touch the inner world of many potential suicides arises. In this paper, we explore to automatically detect… More >

  • Open Access

    ARTICLE

    A Load Balanced Task Scheduling Heuristic for Large-Scale Computing Systems

    Sardar Khaliq uz Zaman1, Tahir Maqsood1, Mazhar Ali1, Kashif Bilal1, Sajjad A. Madani1, Atta ur Rehman Khan2,*
    Computer Systems Science and Engineering, Vol.34, No.2, pp. 79-90, 2019, DOI:10.32604/csse.2019.34.079
    Abstract Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute a predefined number of tasks… More >

  • Open Access

    ARTICLE

    A New Enhanced Learning Approach to Automatic Image Classification Based on Salp Swarm Algorithm

    Mohammad Behrouzian Nejad1, Mohammad Ebrahim Shiri1,2,*
    Computer Systems Science and Engineering, Vol.34, No.2, pp. 91-100, 2019, DOI:10.32604/csse.2019.34.091
    Abstract In this paper we propose a new image classification technique. According to this note that most research focuses on extraction of features in the frequency domain, location, and reduction of feature dimensions, in this research we focused on learning step in image classification. The main aim is to use the heuristic methods to increase the function of the estimator of the learning algorithm and continue to achieve the desired state, as well as categorization without user interference and automatically performed by the model produced from the above steps. So, in this paper, a new learning approach based on the Salp… More >

  • Open Access

    ARTICLE

    The Implementation of Optimization Methods for Contrast Enhancement

    Ahmet Elbir1,∗, Hamza Osman Ilhan1, Nizamettin Aydin1
    Computer Systems Science and Engineering, Vol.34, No.2, pp. 101-107, 2019, DOI:10.32604/csse.2019.34.101
    Abstract The performances of the multivariate techniques are directly related to the variable selection process, which is time consuming and requires resources for testing each possible parameter to achieve the best results. Therefore, optimization methods for variable selection process have been proposed in the literature to find the optimal solution in short time by using less system resources. Contrast enhancement is the one of the most important and the parameter dependent image enhancement technique. In this study, two optimization methods are employed for the variable selection for the contrast enhancement technique. Particle swarm optimization (PSO) and artificial bee colony (ABC) optimization… More >

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