This study proposes a context-aware auction solution suitable for the intelligent user. The solution informs the most reasonable prices for brokers after considering the size of each species of the catch along with ot...
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This study proposes a context-aware auction solution suitable for the intelligent user. The solution informs the most reasonable prices for brokers after considering the size of each species of the catch along with other information and their effects on the fish price. This solution is expected to improve the safety of the catch and increase the competitiveness of auction sites by introducing a digitalized auction system to replace the traditional analog system which could be unsanitary sometimes. The solution's Unified Modeling Language has been developed with java android and the data obtained from the proposed solution is useful in simplifying the bidding process, avoiding over-heated bidding, or stabilizing the fish prices for consumers in the distribution process starting from a broker, distributor and then to consumers. Such a simplified procedure will be able to maintain the freshness of the catch and strengthen the food safety as well as the competitiveness of auction sites, assisting brokers who often experience some difficulties in making a decision on the bidding price due to many variables. This study has focused on the new paradigms, software, middleware and systems for intelligent user. Thus, cost reduction was considered mainly in terms of software engineering. The proposed system is to be supplied with a price 30% less than the existing systems.
Recently, there have been some concerns for the network control systems which have been built for the major closed national communication infrastructures in the Republic of Korea. In particular, the control systems us...
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Recently, there have been some concerns for the network control systems which have been built for the major closed national communication infrastructures in the Republic of Korea. In particular, the control systems used by the small- and medium-sized enterprises (SMEs) often did not consider much on the sophisticated internal or external threats such as hacking or identity theft when they were first developed. For this reason, SMEs have been constantly exposed to internal/external security threats posed by both internal and external attackers, while they are using their own internal business networks constantly stay linked to the external networks operated by their cooperating companies or institutions for the convenience of conducting business. Hence, the security of SMEs' business networks is still vulnerable, but it is not easy to obtain the information from security officials about what are the actual problems they are facing. In this study, a method of strengthening the SMEs' security capability is proposed, especially focusing on a framework to be used when applying big data. For the simulations, necessary data was provided by the SMEs who have experienced security threats in the past. An empirical analysis was conducted with such data, and a framework was designed accordingly. The framework was simulated in a test bed for adjustment. The demographic characteristics of the data providers were studied to ensure a more accurate analysis of the data. The frequency and reliability analysis methods were used together with the machine learning technique to measure the reliability of the data, whereas a factor analysis was applied the validity. Partial least squares (PLS) was used for the empirical analysis as well. An application to which these methodologies were applied was implemented with java android and will be provided to the security managers of SMEs upon completion. It is expected that the framework proposed in this study will be a useful solution for SMEs f
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