Myat Nandar Oo¹, Sazia Parvin², Thandar Thein³

Computer Systems Science and Engineering, Vol.33, No.3, pp. 203-217, 2018, DOI:10.32604/csse.2018.33.203

Abstract Forensic examiners are in an uninterrupted battle with criminals in the use of Big Data technology. The underlying storage system is the main scene to trace the criminal activities. Big Data Storage System is identified as an emerging challenge to digital forensics. Thus, it requires the development of a sound methodology to investigate Big Data Storage System. Since the use of Hadoop as Big Data Storage System continues to grow rapidly, investigation process model for forensic analysis on Hadoop Storage and attached client devices is compulsory. Moreover, forensic analysis on Hadoop Big Data Storage System More >

Wint Nyein Chan¹, Thandar Thein²

Computer Systems Science and Engineering, Vol.33, No.3, pp. 187-202, 2018, DOI:10.32604/csse.2018.33.187

Abstract Nowadays, Big Data, a large volume of both structured and unstructured data, is generated from Social Media. Social Media are powerful marketing tools and social big data can offer the business insights. The major challenge facing social big data is attaining efficient techniques to collect a large volume of social data and extract insights from the huge amount of collected data. Sentiment Analysis of social big data can provide business insights by extracting the public opinions. The traditional analytic platforms need to be scaled up for analyzing a large volume of social big data. Social… More >

Lufeng Yuan^∗, Erlin Yao, Guangming Tan

Computer Systems Science and Engineering, Vol.33, No.2, pp. 105-113, 2018, DOI:10.32604/csse.2018.33.105

Abstract This paper proposes a machine learning based method which can detect certain events automatically and precisely in biomedical imaging. We detect one important and not well-defined event, which is called flash, in fluorescence images of Escherichia coli. Given a time series of images, first we propose a scheme to transform the event detection on region of interest (ROI) in images to a classification problem. Then with supervised human labeling data, we develop a feature selection technique to utilize support vector machine (SVM) to solve this classification problem. To reduce the time in training SVM model,… More >

Amin Mohajer^a, Morteza Barari^a, Houman Zarrabi^b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 413-420, 2018, DOI:10.1080/10798587.2017.1312893

Abstract It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation wireless networks. A self-optimization technique is introduced as the only viable solution for controlling and managing this type of huge data networks. This technique allows control of resources and key performance indicators without human intervention, based solely on the network intelligence. The present study proposes a big data based self optimization networking (BD-SON) model for wireless networks in which the KPI parameters affecting the QoS are assumed to be controlled through a multidimensional decision-making process. Also, Resource Management Center (RMC)… More >

Qingyuan Zhou^a, Jianjian Luo^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 133-138, 2018, DOI:10.1080/10798587.2016.1267444

Abstract Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. In a Smarter City, available resources are harnessed safely, sustainably and efficiently to achieve positive, measurable economic and societal outcomes. Most of the challenges of Big Data in Smart Cities are multi-dimensional and can be addressed from different multidisciplinary perspectives. Based on the above considerations, this paper combined the PSR method, the fuzzy logic model and the entropy weight method in an empirical More >

Zhiguo Yan, Zheng Xu, Jie Dai

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 123-132, 2018, DOI:10.1080/10798587.2016.1267251

Abstract In the Big-Data era, currently how to automatically realize acquisition, refining and fast retrieval of the target information in a surveillance video has become an urgent demand in the public security video surveillance field. This paper proposes a new gun-dome camera cooperative system, which solves the above problem partly. The system adopts a master-slave static panorama-variable view dualcamera cooperative video-monitoring system. In this dual-camera system the gun camera static camera） with a wide viewing -angle lenses is in charge of the pedestrian detection and the dome camera can maneuver its focus and cradle orientation to More >

Yefeng Ma^a, Hui Zhang^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 107-114, 2018, DOI:10.1080/10798587.2016.1267249

Abstract Emerging communication and computing technologies such as social media, Internet of Things and big data provide great opportunities to improve information management systems for emergency operations. This paper studies the issues of information management at China’s Emergency Operations Center (EOC), and proposes a data-driven knowledge management system (KMS) to support decisionmaking, coordination, and collaboration within EOCs and with the public. In the proposed KMS, big data analytics is employed to gather and analyze information from different knowledge domains and track how a crisis evolves in physical world and in cyber space. The proposed system aims More >

Yunlan Xue^a, Lingyu Xu^b, Jie Yu^b, Gaowei Zhang^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 97-106, 2018, DOI:10.1080/10798587.2016.1267247

Abstract The increase of scale and complexity of Internet big data presents unprecedented opportunities on Cyber-Physical Systems (CPS). The incompleteness and incredibility of Internet big data are challenging issues for confirming the event influence scope. To solve the above problem, we propose CyberPhysical Space Event Model (CPSEM) to analyze event influence in multi-viewer, which maps real data into Cyber Space (CS) and Physical Space (PS). In addition, we propose Event Influence Scope Detection Algorithm (EISDA) to detect the scope of a hot event in Cyber Space and Physical Space. More >

Xiaoqing Zuo^a, Hongchu Yu^a, Chenbo Zi^b, Xiaokun Xu^b, Liqi Wang^b, Haibo Liu^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 47-54, 2018, DOI:10.1080/10798587.2016.1267240

Abstract Micro deformation monitoring system (IBIS-L) using high frequency microwave as signal for transmission, is easily affected by meteorology. How to eliminate the meteorological influence effectively, and extract useful information from the big data becomes a key to monitor the slope deformation with high precision by the IBIS-L system. Evaluation of the optimum meteorological correction mode for Slope Deformation Monitoring to ensure the accuracy of measurement is considered. This objective was realized by model construction technology, which uses calculation  formula of Microwave Refraction rate, and the radial distance from the target point to the IBIS-L system to estimate More >

Hui Wang, Liang Li, Long-yun Gao, Wu Chen

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 35-40, 2018, DOI:10.1080/10798587.2016.1267238

Abstract With the development of big data science, handling intensive knowledge in the complex network becomes more and more important. Knowledge representation of multi-agent negotiation in the complex network plays an important role in big data science. As a modern approach to declarative programming, answer set programming is widely applied in representing the multi-agent negotiation knowledge in recent years. But almost all the relevant negotiation models are based on complete rational agents, which make the negotiation process complex and low efficient. Sorting negotiation demands is the most key step in creating an efficient negotiation model to More >