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  • Open Access


    Teensensor: Gaussian Processes for Micro-Blog Based Teen’S Acute and Chronic Stress Detection

    Yuanyuan Xue1,2, Qi Li1, LingFeng1

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 151-164, 2019, DOI:10.32604/csse.2019.34.151

    Abstract Stress is a common problem all over the world. More and more teenagers today have to cope with different stressor events coming from school, family, peer relation, self-cognition, romantic relation, etc. Over-stress without proper guidance will lead to a series of potential problems including physical and mental disorders, and even suicide due to the shortage of teen’ s psychological endurance and controllability. Therefore, it is necessary and important to timely sense adolescents’ stress and help them release the stress properly. In this paper, we present a micro-blog based system called TeenSensor, aiming to detect teens acute and chronic stress from… More >

  • Open Access


    Application of Radial Basis Function Networks with Feature Selection for GDP Per Capita Estimation Based on Academic Parameters

    Abdullah Erdal Tümer1,∗, Aytekin Akku¸s2

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 145-150, 2019, DOI:10.32604/csse.2019.34.145

    Abstract In this work, a system based on Radial Basis Function Network was developed to estimate Gross Domestic Product per capita. The data set based on 180 academic parameters of 13 Organisation for Economic Co-operation and Development countries was used to verify the effectiveness and accuracy of the proposed method. Gross Domestic Product per capita was studied to be estimated for the first time with academic parameters in this study. The system has been optimized using feature selection method to eliminate unimportant features. Radial Basis Function network results and Radial Basis Function network with feature selection method results were compared. The… More >

  • Open Access


    Non-Deterministic Outlier Detection Method Based on the Variable Precision Rough Set Model

    Alberto Fernández Oliva1, Francisco Maciá Pérez2, José Vicente Berná-Martinez2,*, Miguel Abreu Ortega3

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131

    Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with… More >

  • Open Access


    A Novel Fuzzy Rough Sets Theory Based CF Recommendation System

    C. Raja Kumar1, VE. Jayanthi2

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 123-129, 2019, DOI:10.32604/csse.2019.34.123

    Abstract Collaborative Filtering (CF) is one of the popular methodology in recommender systems. It suffers from the data sparsity problem, recommendation inaccuracy and big-error in predictions. In this paper, the efficient advisory tool is implemented for the younger generation to choose their right career based on their knowledge. It acquires the notions of indiscernible relation from Fuzzy Rough Sets Theory (FRST) and propose a novel algorithm named as Fuzzy Rough Set Theory Based Collaborative Filtering Algorithm (FRSTBCF). To evaluate the model, data is prepared using the cross validation method. Based on that, ratings are evaluated by calculating the MAE (mean average… More >

  • Open Access


    A Two-Level Morphological Description of Bashkir Turkish

    Can Eyupoglu

    Computer Systems Science and Engineering, Vol.34, No.3, pp. 113-121, 2019, DOI:10.32604/csse.2019.34.113

    Abstract In recent years, the topic of Natural Language Processing (NLP) has attracted increasing interest. Many NLP applications including machine translation, machine learning, speech recognition, sentiment analysis, semantic search and natural language generation have been developed for most of the existing languages. Besides, two-level morphological description of the language to be used is required for these applications. However, there is no comprehensive study of Bashkir Turkish in the literature. In this paper, a two-level description of Bashkir Turkish morphology is described. The description based on a root word lexicon of Bashkir Turkish is implemented using Extensible Markup Language (XML) and appended… More >

  • Open Access


    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 >

  • Open Access


    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


    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


    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


    Core – An Optimal Data Placement Strategy in Hadoop for Data Intentitive Applications Based on Cohesion Relation

    Vengadeswaran, Balasundaram

    Computer Systems Science and Engineering, Vol.34, No.1, pp. 47-60, 2019, DOI:10.32604/csse.2019.34.047

    Abstract The tremendous growth of data being generated today is making storage and computing a mammoth task. With its distributed processing capability Hadoop gives an efficient solution for such large data. Hadoop’s default data placement strategy places the data blocks randomly across the nodes without considering the execution parameters resulting in several lacunas such as increased execution time, query latency etc., Also, most of the data required for a task execution may not be locally available which creates data-locality problem. Hence we propose an innovative data placement strategy based on dependency of data blocks across the nodes. Our strategy dynamically analyses… More >

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