Recently software security of the smart phone is an important issue in the field of information science and technology due to fast propagation of smart technology in our life. The smart phone as the security critical systems which are utilizing in terminal systems of the banking, ubiquitous home management, airline passengers screening, and so on are related to the risk of costs, risk of loss, risk of availability, and risk by usage. For the security issues, software hazard analysis of smart phone is the key approaching method by use of observed failures. In this paper, we propose an efficient integrative framework for software security analysis of the smart phone using Fault Tree Analysis (FTA) and Failure Mode Effect Analysis (FMEA) to gain a convergence security and reliability analysis technique on hand handle devices. And we discuss about that if a failure mode effect analysis performs simpler, not only for improving security but also reducing failure effects on this smart device, the proposed integrative framework is a key solution.

Summary. The wireless sensor network is a wireless network consisting of spatially distributed autonomous sensor devices which are called sensor nodes in remote setting to cooperatively monitor and control physical or environmental conditions. The lifetimes of sensor nodes depend on the energy availability with energy consumption. Due to the size limitation and remoteness of sensor devices after deployment, it is not able to resupply or recharge power. The system energy saving effectiveness is the probability that the wireless sensor network system can successfully meet an energy saving operational demand. To extend the system effectiveness in energy saving, the lifetimes of sensor nodes must be increased by making them energy efficient as possible. In this paper, we propose Bayesian statistical models for observed active and sleep times data of sensor nodes under the selected energy efficient CSMA contention-based MAC protocols in consideration of the system effectiveness in energy saving in a wireless sensor network. Accordingly, we propose Bayes estimators for the system energy saving effectiveness of the wireless sensor networks by use of the Bayesian method under the conjugate prior information.

The present concept of u-Healthcare is based on treatment and recuperation and in the future it will become specialized as wellness based on prevention. It is predicted that wellness care among others will develop to become the key field of u-Healthcare. For this reason in this research, ubiquitous technology was grafted to the passometer (P-meter) which is frequently used for monitoring during existing walking exercises. Emerging from the existing method of the P-meter which simply calculates the amount of exercise by counting the number of steps taken, using the GPS incoming data, the distance and speed of the location changes is calculated and the acceleration sensor will reflect the steps and intensity of movement to measure the walking activity amount to realize a smart walker system which will help the maintenance and promotion of modernists health.In this paper, we propose an integrative remote monitoring system for measuring walking activities under ubiquitous healthcare environment considering walking effects in healthcare of human life through the calculation of the distance of location changes and speed using GPS reception data and reflecting the steps and intensity of movement using the acceleration sensor.

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Recently, Industry 4.0 (next generation industrial revolution) designed by Germany to retain initiative in manufacturing business is actively studied. Goal of Industry 4.0 is 'Smart factory' which manages progress of production, supply logistics and services. To achieve the goal, we can construct value creation and new business model by integrating organically with production management systems which is existing and cyber-physical systems, Internet of Things, Services Internet and sensor, etc. However, if integration with production management systems does not work effectively by adding and developing new technologies, It does not have performance. Hence, in this research, we will analysis Industry 4.0 which is possible for small quantity batch production and one of the light and flexible manufacturing systems, and based on this, we will suggest methodology to horizontally integrate with production management systems.

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