Earticle

In this paper, we propose an energy efficient machineto- machine (M2M) communication scheme for bidirectional automated metering (AMR) systems. In particular, to maximize the benefits of bidirectional AMR systems, we propose a scheme that enables near real-time M2M communication coupled with energy efficient operation. The energy efficient bidirectional M2M communication (EEBMC) basically divides each interval into three time sections: a regular report processing section, an AMR gathering section, and an irregular command processing section. The regular report processing section deals with regularly aggregated meter data and the irregular command processing section can cope well with server (user) commands requested in real time. The experimental results demonstrate that EEBMC is capable of energy efficient operation while maintaining near real-time server command processing ability.

Near Field Communication (NFC) is a key enabling technology of the mobile industry. However, its diffusion was negligible until 2010, because NFC-equipped smartphones comprised only 3% of all smartphones. Smartphone manufacturers have begun to mount basic NFC specifications, because Google has supported those specifications since Android 2.3. A wide range of NFC-based commerce business models would be expected to have been established for these reasons, but they still do not attract a large number of users. In this study, the authors discuss the implications of that fact. The findings in this article are useful for identifying the factors that must be managed for NFC-based mobile payment services to spread successfully.

This paper presents three texture feature extraction techniques: gray level co-occurrence matrix (GLCM), Gabor filter, and global neighborhood structure (GNS) map, for the fault diagnosis of induction motors. The texture of twodimensional (2D) gray level images is converted from acoustic emission (AE) fault signals and used for feature extraction of the fault signals. The extracted texture features are used as inputs to a multi-class support vector machine (MCSVM) to classify each fault. The Gaussian radial basis function kernel is used with MCSVM to handle non-linear fault features of acoustic emission (AE) signals. Experimental results with one-second AE signals sampled at 1 MHz showed that the GLCM-based feature extraction method outperformed the Gabor filter and the GNS map in terms of classification accuracy because of its ability to capture the spatial dependence of gray-level texture values.

Owing to the emergence of smart media and the evolution of digital technology, the global electronic publishing industry is taking another leap forward. Since the release of Amazon's Kindle and Apple's iPad, the e-Book market has become active again, resulting in the emergence of e-Books as the core of the content industry. The domestic e-Book market is showing signs of rapid movement and growth. However, despite these obvious changes, there is still a serious shortage of content in terms of quality and quantity. The wide variety in content development and collection may be the most urgent challenge to overcome in developing a domestic e-Book market and satisfying customers. The goal of this paper is to take advantage of an immersive sensory interface. In addition, a non-linear structure belt unbundling called “episode-type content” is proposed, and a user experience model of episode-type content is presented.

In this paper, we propose a flight conformance monitoring method based on 4D trajectory modeling using aircraft performance data for an efficient and safe control of air traffic flow. According to a recent increase in air traffic, several methods have been researched to support aircraft maneuvering in a restricted airspace. ICAO has recommended the use of PBN and RNAV navigation for controlling air traffic flow based on an aircraft’s performance as a standard. 4D trajectory modeling using flight plans, aircraft performance data, and weather data can be used to predict the current/future flight path (coordinate, flight level, speed, etc.) of an aircraft by matching with the actual flight situation. The predicted information can be utilized to control the aircraft maneuvering effectively and safety flight alarm (RAM, CALM, ETO and etc) which is not conformance to PBN, RNAV and MTCD. In this paper, we calculate an exact 4D trajectory modeling using aircraft performance data, propose a flight conformance monitoring method, and analyze their results. From now on, it is able to support efficient and safe air traffic flow management for controller.