Tianqing Zhu¹, Mengmeng Yang¹, Ping Xiong², Yang Xiang¹, Wanlei Zhou¹

Computer Systems Science and Engineering, Vol.33, No.2, pp. 61-69, 2018, DOI:10.32604/csse.2018.33.061

Abstract Online social networks provide an unprecedented opportunity for researchers to analysis various social phenomena. These network data is normally represented as graphs, which contain many sensitive individual information. Publish these graph data will violate users’ privacy. Differential privacy is one of the most influential privacy models that provides a rigorous privacy guarantee for data release. However, existing works on graph data publishing cannot provide accurate results when releasing a large number of queries. In this paper, we propose a graph update method transferring the query release problem to an iteration process, in which a large set of queries are used… More >

Heng Qi^1,2, Keqiu Li¹

Computer Systems Science and Engineering, Vol.33, No.2, pp. 57-59, 2018, DOI:10.32604/csse.2018.33.057

Abstract This article has no abstract. More >

Jen-Yuan Yeh^∗

Computer Systems Science and Engineering, Vol.33, No.1, pp. 41-52, 2018, DOI:10.32604/csse.2018.33.041

Abstract As a crucial task in information retrieval, ranking defines the preferential order among the retrieved documents for a given query. Supervised learning has recently been dedicated to automatically learning ranking models by incorporating various models into one effective model. This paper proposes a novel supervised learning method, in which instances are represented as bags of contexts of features, instead of bags of features. The method applies rank-order correlations to measure the correlation relationships between features. The feature vectors of instances, i.e., the 1st-order raw feature vectors, are then mapped into the feature correlation space via projection to derive the context-level… More >

Vidblain Amaro-Ortega^1,∗, Arnoldo Díaz-Ramírez², Brenda Leticia Flores-Ríos¹, Félix Fernando González-Navarro¹, Frank Werner³, Larysa Burtseva¹

Computer Systems Science and Engineering, Vol.33, No.1, pp. 31-40, 2018, DOI:10.32604/csse.2018.33.031

Abstract The Linux operating system has been employed to execute numerous real-time applications. However, it is limited to support soft real-time systems by two scheduling policies: First-In-First-Out and Round Robin. For real-time systems with critical constraints, the soft real-time support and these scheduling policies are still insufficient. In this work, the Earliest Deadline First scheduling policy, which has been shown in theory to be an optimal one in uniprocessor systems, is introduced as an extension of the Linux kernel. This policy is implemented into the real-time class, without the necessity of defining an additional class. The Linux kernel affords capabilities of… More >

Amjad Gawanmeh^1,3,∗, Usman Pervez², Osman Hasan^2,3

Computer Systems Science and Engineering, Vol.33, No.1, pp. 21-29, 2018, DOI:10.32604/csse.2018.33.021

Abstract Electrocardiography (ECG) is a heart signal wave that is recorded using medical sensors, which are normally attached to the human body by the heart. ECG waves have repetitive patterns that can be efficiently used in the diagnosis of heart problems as they carry several characteristics of heart operation. Traditionally, the analysis of ECG waves is done using informal techniques, like simulation, which is in-exhaustive and thus the analysis results may lead to ambiguities and life threatening scenarios in extreme cases. In order to overcome such problems, we propose to analyze ECG heart signals using probabilistic model checking, which is a… More >

M. Teimoortashloo¹, A. Khaki Sedigh^2,*

Computer Systems Science and Engineering, Vol.33, No.1, pp. 5-20, 2018, DOI:10.32604/csse.2018.33.005

Abstract This paper presents a fault detection method based on Dynamic Independent Component Analysis (DICA) with new statistics. These new statistics are statistical moments and first characteristic function that surrogate the norm operator to calculate the fault detection statistics to determine the control limit of the independent components (ICs). The estimation of first characteristic function by its series is modified such that the effect of series remainder on estimation is reduced. The advantage of using first characteristic function and moments, over second characteristic function and cumulants, as fault detection statistics is also presented. It is shown that the proposed method can… More >

Yao-Liang Chung^1,*, Hung-Yuan Chung², Yu-Shan Chen²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 367-383, 2020, DOI:10.31209/2020.100000206

Abstract In this study, we introduce an algorithm which is based on a series of wellknown algorithms and mainly uses an improved dark channel prior algorithm and the White-Patch Retinex algorithm (both are heterogeneous algorithms) in order to effectively remove the haze from a single image. When used in conjunction with a heterogeneous architecture, the value of the algorithm becomes even greater. With an effective design and a novel procedure, the proposed algorithm can not only restore a clear image, but also solve the halo effect, color distortion, and long operating time issues resulting from the dark channel prior. Rich experimental… More >

Vijayalakshmi. K^1,*, Anandan. P²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 303-311, 2020, DOI:10.31209/2020.100000165

Abstract The advent of sensors that are light in weight, small-sized, low power and are enabled by wireless network has led to growth of Wireless Sensor Networks (WSNs) in multiple areas of applications. The key problems faced in WSNs are decreased network lifetime and time delay in transmission of data. Several key issues in the WSN design can be addressed using the Multi-Objective Optimization (MOO) Algorithms. The selection of the Cluster Head is a NP Hard optimization problem in nature. The CH selection is also challenging as the sensor nodes are organized in clusters. Through partitioning of network, the consumption of… More >

Li-Hong Juang^1,*, Yi-Hua Zhao²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164

Abstract Speech recognition is one of the most convenient forms of human beings engaging in the exchanging of information. In this research, we want to make robots understand human language and communicate with each other through the human language, and to realize man–machine interactive and humanoid– robot interactive. Therefore, this research mainly studies NAO robots’ speech recognition and humanoid communication between double -humanoid robots. This paper introduces the future direction and application prospect of speech recognition as well as its basic method and knowledge of speech recognition fields. This research also proposes the application of the most advanced method—establishment of the… More >

Abid Nisar¹, Waheed Iqbal^1,*, Fawaz Bokhari¹, Faisal Bukhari¹, Khaled Almustafa²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 353-365, 2020, DOI:10.31209/2019.100000159

Abstract The adaptive resource provisioning of cloud-hosted applications is enabled to provide a better quality of services to the users of applications. Most of the cloud-hosted applications follow the multi-tier architecture model. However, it is challenging to adaptively provision the resources of multi-tier applications. In this paper, we propose an auto-scaling method to dynamically scale resources for multi-tier web applications. The proposed method exploits the horizontal scaling at the web server tier and vertical scaling at the database tier dynamically to maintain response time guarantees. We evaluated our proposed method on Amazon Web Services using a real web application. The extensive… More >