Earticle

The frequency and scale of natural disasters such as typhoons, floods, earthquakes, and tidal waves from earthquakes have increased recently. Several nations have recognized that earth observation is essential for protecting the Earth’s environment. Therefore, 50 nations around the world have agreed upon the construction of GEO (Group on Earth Observation), which is to be in charge of the earth observation in an effort to gain understanding of earth system changes as well as to monitor and predict these changes. However, the data format from earth observation varies depending on the areas, institutions, and countries. This presents a challenge when attempting to share and exchange data among different organizations. Thus, a metadata scheme and system of ontology suitable for domestic situations is developed in this study to facilitate exchanges of data regarding areas that benefit society with reference to the principles of data sharing and exchange regarding GEO. Also established is the KGEO metadata and ontology required to identify the metadata situation of earth observation data that is used for nine societal benefit areas of GEOSS (Global Earth Observation System of Systems).

The most commonly adopted approach to find valuable information from trees data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) the computationally high cost of the candidate maintenance, (2) the repetitious input dataset scans, and (3) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. We would present some new theorems derived from and evaluate the effectiveness of the proposed algorithm in comparison to the previous works.

Quality data is necessary for different data mining techniques and reversely, data mining techniques can be utilized to measure quality of data. Data mining and data quality issues got much attention for relational data in past. But, as a massive amount of data is being stored and represented over the web in XML, the issue of data quality for mining purposes and also using data mining techniques for quality measures get research interest. We propose two important interrelated issues: how quality XML data is useful for data mining in XML and how data mining in XML is used to measure the quality data for XML. When we address both issues, we consider XML constraints because constraints in XML can be used for quality measurement in XML data and also for finding some important patterns and association rules in XML data mining. We mainly address the theoretical framework for data quality and data mining for XML. Our research is towards the broader task of data mining and data quality for XML data integrations.

The selection of a path in the exponentially growing internet is a difficult task. The upcoming high-speed networks are expected to support a wide variety of communication-intensive real-time multimedia applications. There are many significant factors which affect the performance of a computer network such as choice of routing algorithm, heavy traffic, etc. There must be a mechanism to effectively use the network. Using shortest paths conserves network resources, but it causes some resources of the network to be over utilized while other resources remain under utilized. As the path selection directly affects the throughput, an efficient path selection algorithm is needed which periodically finds the optimum path. In this paper, we would like propose an algorithm that can be used in both datagram and virtual circuit environment. This is a small step in building throughput-aware and traffic-sensitive path selection. Ultimately, our idea contributes to find a route in an integrated network environment.

We have seen an increase use of technology in contactless payment card as well as access cards that make the same Mifare technology. However, it has been shown that such a technology is carrying serious security flows that allow card cloning by suing a simple personal laptop. The use of mobile handheld devices is expanding rapidly within both the business and individual contexts. These devices are now essential tools that offer competitive business advantages in today’s growing world of ubiquitous computing environments. The technology advancement has made it possible to embed more facilities in mobile phones. While they provide benefits, they also pose new risks on security by either the information they contain or information that they can access remotely. Secure cash transaction is of serious concerns in growing use of cash cards and internet transactions. Cash withdrawal card, chip and pin facilities have increasingly been used for business and social activities. This paper will propose the concept of physical browsing and development of a system that will allow users to use their mobile phones to securely withdraw cash from ATM machines. The paper presents the architecture for the M-Cash withdrawal application, discusses relevant technologies and security issues, and provides an analysis of relevant procedures and steps for fully implementing the application.