Earticle

Impervious surfaces are important indicators for urban development monitoring. Accurate mapping of urban impervious surfaces with observational satellites, such as VNREDSat-1, remains challenging due to the spectral diversity not captured by an individual PAN image. In this article, five multi-resolution image fusion techniques were compared for the task of classifting urban impervious surfaces. The result shows that for VNREDSat-1 dataset, UNB and Wavelet tranformation methods are the best techniques in reserving spatial and spectral information of original MS image, respectively. However, the UNB technique gives the best results when it comes to impervious surface classification, especially in the case of shadow areas included in non-impervious surface group.

The first D2C-era web-real variety show in Korea was broadcast via tvN of CJ E&M. The web-real variety program ‘SinSeoYuGi’ accumulated 54 million views, along with 50 million views at the Chinese portal site QQ. This study carries out an analysis using text mining that extracts portal site blogs, twitter page views and associative terms. In addition, this study derives viewers' response by extracting key words with opinion mining techniques that divide positive words, neutral words and negative words through customer sentiment analysis. It is found that the success factors of the web- real variety were reduced in appearance fees and production cost, harmony between actual cast members and scenario characters, mobile TV programing, and pre-roll advertising. It is expected that web-real variety broadcasting will increase in value as web contents in the future, and be established as a new genre with the job of ‘technical marketer’ growing as well.

The most important factor in the wireless sensor network is the use of effective energy and increase in lifetime of the individual nodes in order to operate the wireless network more efficiently. For this purpose, various routing protocols have been developed. The LEACH such a protocol, well known among typical cluster routing protocols. However, when a cluster head is selected, the energy consumption may not be equal because it does not take into account the energy of the nodes. In this paper, we seek to improve the cluster head selection method according to residual energy of each sensor node. This method then adaptively applies the LEACH algorithm and the cluster head section algorithm with consideration of node energy in accordance with the energy of the whole sensor field. Through the simulation, it was found that this proposed algorithm was effective.

This paper proposes to increase the node energy efficiency, which rapidly drops during the transmission of L-TEEN (Layered Threshold sensitive Energy Efficient sensor Network protocol), using the method of DL-TEEN (Dual-hop Layered TEEN). By introducing dual-hop method in the data transmission, the proposed single-hop method for short-range transmission and multi-hop transmission method between the cluster heads for remote transmission was introduce. By introducing a partial multi-hop method in the data transmission, a single-hop method for short range transmission method between the cluster heads for remote transmission was introduces. In the proposed DL-TEEN, the energy consumption of cluster head for remote transmission reduces and increases the energy efficiency of sensor node by reducing the transmission distance and simplifying the transmission routine for short-range transmission. As compared the general L-TEEN, it was adapted to a wider sensor field.

Internet was once used to link ideas, then people and now it is starting to connect all things. IoT constitutes a good paradigm to enable people to design and modify things, and then share their designs and modifications. Through the internet, things nowadays are able to exchange raw data and information, thus enabling the development of a new class of interconnected smart objects. Smart building block toy systema are a newly proposed concept that combines internet technology into educational blocks. It is composed of the IoT environment that has attracted attention recently. In this paper, we design a system using starUML, one of the program development tools in the system design process. Educational content can be shared to learners via the proposed service of the IoT, while also being interesting for young child learners.

In the growing data saturated world, the question of “whether data can be used” has shifted to “can it be utilized effectively?” More data is being generated and utilized than ever before. As the collection of data increases, data mining techniques also must become more and more accurate. Thus, to ensure this data is effectively utilized, the analysis of the data must be efficient. Interpretation of results from the analysis of the data set presented, have their own on the basis it is possible to obtain the desired data. In the data mining method a decision tree, clustering, there is such a relationship has not yet been fully developed algorithm actually still impact of various factors. In this experiment, the classification method of data mining techniques is used with easy decision tree. Also, it is used special technology of one R and J48 classification technique in the decision tree. After selecting a rule that a small error in the "one rule" in one R classification, to create one of the rules of the prediction data, it is simple and accurate classification algorithm. To create a rule for the prediction, we make up a frequency table of each prediction of the goal. This is then displayed by creating rules with one R, state-of-the-art, classification algorithm while creating a simple rule to be interpreted by the researcher. While the following can be correctly classified the pattern specified in the classification J48, using the concept of a simple decision tree information theory for configuring information theory. To compare the one R algorithm, it can be analyzed error rate and accuracy. One R and J48 are generally frequently used two classifications…

In transformer cooling systems, oil temperature is controlled through the use of a blower and oil pump. For this paper, set-point algorithms, a reset algorithm and control algorithms of the cooling system were developed by neural networks and fuzzy logics. The oil inlet temperature was set by a 2× 2× 1 neural network, and the oil temperature difference was set by a 2× 3× 1 neural network. Inputs used for these neural networks were the transformer operating ratio and the air inlet temperature. The inlet set temperature was reset by a fuzzy logic based on the transformer operating ratio and the oil outlet temperature. A blower was used to control the inlet oil temperature while the oil pump was used to control the oil temperature difference by fuzzy logics. In order to analysis the performance of these algorithms, the initial start-up test and the step change test were performed by using the dynamic model of a transformer cooling system. Test results showed that algorithms developed for this study were effective in controlling the oil temperature of a transformer cooling system.