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As people use smart devices while watching TV increase, recently, researches on a wide range of services linked with second-screen devices around the smart TV in the home network have been actively conducted. The study proposes a second screen personalized services in next-generation broadcasting service environment. Also, the service applies web technologies to realize additional information representation, wide connection of devices, and real-time content transmission.

In this paper, the extended kalman filter based direct kinematic method was proposed to calculate the real-time end-effector position in a Stewart platform. A noise analysis based on the data transmission is proposed firstly, in which the size order of time domain noises is concerned. Then non-linear kinematic model and numerical method for Stewart platform are presented respectively. Later, an extended kalman filter based direct kinematic method is proposed, where transmission delays and synchronous errors are considered as a drift in the platform trajectory. Finally, various simulation results demonstrated the validity of the algorithm proposed in this article.

Recently, the computing environment is changing rapidly by a wide spread and the development of a wireless terminal. In particular, computing environment of enterprise is changing largely due to cloud computing and big data. Utilization value of big data is expanded across all sectors of society of administration, welfare transportation, health care, finance, manufacturing, etc. and the importance of big data as a driving force of the national economy is increased. In Korea, it is estimated that there is lack of professional staff, and a technology gap with developed countries although it is expected that demand of technology and professional staff will increase rapidly because big data is a source of future competitive advantage. In this paper, we identify concept and organization of big data business ecosystem and analyze the development step of the ecosystem. In particular, we investigated features by step of the big data business and analyzed systematically the development direction accordingly. The analyzed result in this paper is utilized to many companies and related policies of big data and will provide a number of advantages.

This paper investigated the problem of improved delay-dependent stability criteria for neural networks with two additive time-varying delay components. By constructing a more general type of Lyapunov functional and using effective mathematical technique to estimate the upper bound on the time derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived in terms of linear matrix inequalities. The resulting stability criteria are of fewer matrix variables and less conservative than some existing ones. Numerical examples are given to illustrate the effectiveness and less conservativeness of the proposed method.

In this paper, we propose a new method to design an observer and control the linear singular systems described by Chebyshev wavelets. The idea of the proposed approach is based on solving the generalized Sylvester equations. An example is also given to illustrate the procedure.

In this paper, we propose the integrated management system for the safe transport of dangerous goods vehicles. It provides a safe path to reduce secondary accident damage and manages in real time the running state of the vehicle(over speeding , rapid speed-up or down, whether the vehicle is moving the given path) to prevent accident and automatically detect the vehicle accident and transfer the information concerning the accident to relevant governments to support the quick and accurate accident response. The system consists of the control center and a device attached on vehicle. They are connected with LTE(Long Term Evolution) network in real time. Therefore, we could gather all information about the status of the vehicle and the goods and then manage in real time the running vehicle no matter what a driver does. So, the transport of dangerous goods vehicles is more safety.

Current grey clustering analysis methods have some defects. So, this paper proposes a prediction model based on improved grey clustering analysis. Firstly, it constructs the grey classical domain and the grey sector domain based on prediction subjects and data and according to relevant theory about grey clustering analysis. Secondly, it categorizes samples according to features of prediction subjects and confirms the analysis categories corresponding to the classical domain. Thirdly, based on the grey system theory, it constructs the grey correlation coefficient model and grey correlation degree model so as to obtain the weighed grey correlation degree. Thus, prediction subjects can be divided into proper category. Finally, power load forecasting in the power industry is taken as a case to prove that the model is reliable and has efficacy.

The problem of the grim employment of university graduate is the hot topic of today's college students and even the whole society in China. For now, the situation of university graduate's employment is becoming increasingly serious, the competition of employment is unprecedentedly intense. With the problem of the grim employment of university graduate continuous outstanding, the influence factor of the employment of university graduate has become a research hotspot to solve the problem of employment. This article used multivariate Logistic regression analysis method to analysis with the data obtained from the colleges and universities. It analyzed the factors that affect the employment of university graduate from the angle of quantitative and qualitative through the estimation and test to the model, put forward suggestions on how to promote graduates employment.