Abstract.To realize real-time information sharing in generic platforms, it is especially important to support dynamic message structure changes. For the case of IDL, it is necessary to rewrite applications to change data sample structures. In this paper, we propose a dynamic reconfiguration scheme of data sample structures for DDS. Instead of using IDL, which is the static data sample structure model of DDS, we use a self describing model using data sample schema, as a dynamic data sample structure model to support dynamic reconfiguration of data sample structures. We also propose a data propagation model to provide data persistency in distributed environments. We guarantee persistency by transferring data samples through relay nodes to the receiving nodes, which have not participated in the data distribution network at the data sample distribution time. The proposed schemes can be utilized to support data sample structure changes during operation time and to provide data persistency in various environments, such as real-time enterprise environments and connection-less internet environments.

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Currently, we live in an era called the Fourth Industrial Revolution, and as a key technology representing this era, we use artificial intelligence instead of computers for most of the intelligence activities that can be performed using the human brain. Various systems and SW are gradually evolving due to artificial intelligence, and SW usability is increasing very rapidly. However, as SW usability increases, problems such as reproduction and misuse occur, and research institutes and companies are demanding SW similarity. Accordingly, this study aims to design a similarity detection model using artificial intelligence for SW replication emotion. The similarity detection model design of this study is based on the Few-Shot Learning in a similarity detection model proceeds with meta-learning using DataSet with sufficient data, the data with less data contained in each class, and the recognition and learning of deep learning that rationally expresses the human brain.

Abstract. Traditional search engines are usually based on keyword-based retrievals, where location information is simply treated as text data, thus resulting in incorrect search results and low degree of user satisfaction. In this paper, we propose a location-aware Web Service system, which adds location information to web contents, usually consisting of text and multimedia information. For this purpose, we describe the system architecture to enable such services, explain how to extend web browsers, and propose the web container and the web search engine. The proposed methods can be implemented on top of traditional Web Service layers. The web contents which include location information can use their location information as a parameter during search process and therefore they can increase the degree of search correctness by using actual location information instead of simple keywords.