• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.1-16
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• 2007

According to the expansion of the Internet use and the utilization of e-business, there are an increasing number of studies of intelligent-based systems for the preparation of ubiquitous environment. In addition, expert systems have been developed from Stand Alone types to web-based Client-Server types, which are now used in various Internet environments. In this paper, we investigated the environment of development for web-based expert systems, we classified and analyzed them according to type, and suggested general typical models of web-based expert systems and their architectures. We classified the web-based expert systems with two perspectives. First, we classified them into the Server Oriented model and Client Oriented model based on the Load Balancing aspect between client and server. Second, based on the degree of knowledge and inference-sharing, we classified them into the No Sharing model, Server Sharing model, Client Sharing model and Client-Server Sharing model. By combining them we derived eight types of web-based expert systems. We also analyzed the location problems of Knowledge Bases, Fact Bases, and Inference Engines on the Internet, and analyzed the pros & cons, the technologies, the considerations, and the service types for each model. With the framework proposed from this study, we can develop more efficient expert systems in future environments.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.17-36
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• 2022

The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.167-180
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• 2021

The purpose of this study is to present a framework of the MyData business ecosystem that shows a different pattern from the previous one by the MyData concept and to define the characteristics of actors participating in the ecosystem. Because MyData is an individual exercising sovereignty over his or her data, there is a characteristic that the individual participates as a key actor in the business. In other words, MyData Operators participate in the MyData business ecosystem to help individuals who own MyData, MyData creating business and MyData using business, among them, manage their own data. Therefore, this study conducts a case study of domestic and foreign MyData businesses to revitalize the domestic MyData industry. In particular, the business model of 45 cases of overseas MyData operators was analyzed and classified into 7 types of 4 groups. And through this, the importance of the role of MyData Operator in the MyData industry ecosystem is confirmed and a developmental ecosystem model is proposed.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.37-55
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• 2023

With the development of electronic journals and the emergence of various interdisciplinary studies, the selection of journals for publication has become a new challenge for researchers. Even if a paper is of high quality, it may face rejection due to a mismatch between the paper's topic and the scope of the journal. While research on assisting researchers in journal selection has been actively conducted in English, the same cannot be said for Korean journals. In this study, we propose a system that recommends Korean journals for submission. Firstly, we utilize SBERT (Sentence BERT) to embed abstracts of previously published papers at the document level, compare the similarity between new documents and published papers, and recommend journals accordingly. Next, the order of recommended journals is determined by considering the similarity of abstracts, keywords, and title. Subsequently, journals that are similar to the top recommended journal from previous stage are added by using a dictionary of words constructed for each journal, thereby enhancing recommendation diversity. The recommendation system, built using this approach, achieved a Top-10 accuracy level of 76.6%, and the validity of the recommendation results was confirmed through user feedback. Furthermore, it was found that each step of the proposed framework contributes to improving recommendation accuracy. This study provides a new approach to recommending academic journals in the Korean language, which has not been actively studied before, and it has also practical implications as the proposed framework can be easily applied to services.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.3
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• pp.103-113
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• 2024

This study is based on the design project of 'Sun-Garden' within the Solaseado Solar Power Plant located in Solaseado, which is a New City being developed in Haenam, Jeollanam-do. The purpose of this study is to create an integrated and sustainable energyscape that harmonizes energy infrastructure with the natural environment, while supporting the city's carbon neutrality agenda. To achieve this, design principles were established by considering three key aspects. The first aspect is economic, which seeks to create multifunctional spaces that integrate nature and technology, pursuing long-term sustainability while generating additional economic value. The second aspect is natural, emphasizing the creation of planting environments that conserve and enhance ecosystems, introduce region-specific species, and maintain ecosystem services and sustainable resource use. The third aspect is landscape, offering sensory and educational experiences to visitors and functioning as a landmark that symbolizes the carbon-neutral garden city of Solaseado through the aesthetic harmony of nature and technology. Through the creation of the 'Sun-Garden,' the Solaseado Solar Power Plant exemplifies a sustainable energyscape development model that merges economic, environmental, and landscape aspects beyond the conventional energy production facility. This project is expected to provide guidelines and implications for future energy infrastructure design, contributing to global energy transition efforts.

• Information Systems Review
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• v.21 no.4
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• pp.125-141
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• 2019

With the advent of deep learning technology, which is represented by AlphaGo, artificial intelligence (A.I.) has quickly emerged as a key theme of digital transformation to secure competitive advantage for businesses. In order to understand the trends of A.I. based digital transformation, a clear comprehension of the A.I. business ecosystem should precede. Therefore, this study analyzed the A.I. business ecosystem from the multi-actor network perspective and identified the A.I. platform strategy type. Within internal three layers of A.I. business ecosystem (infrastructure & hardware, software & application, service & data layers), this study identified four types of A.I. platform strategy (Tech. vertical × Biz. horizontal, Tech. vertical × Biz. vertical, Tech. horizontal × Biz. horizontal, Tech. horizontal × Biz. vertical). Then, outside of A.I. platform, this study presented five actors (users, investors, policy makers, consortiums & innovators, CSOs/NGOs) and their roles to support sustainable A.I. business ecosystem in symbiosis with human. This study identified A.I. business ecosystem framework and platform strategy type. The roles of government and academia to create a sustainable A.I. business ecosystem were also suggested. These results will help to find proper strategy direction of A.I. business ecosystem and digital transformation.

• Information Systems Review
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• v.21 no.4
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• pp.47-68
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• 2019

As cloud services and deployment models become diverse, there are a growing number of cloud computing selection options. Therefore, financial companies need a methodology to select the appropriated cloud for each financial computing system. This study adopted the Balanced Scorecard (BSC) framework to classify factors for the introduction of cloud computing in financial companies. Using Analytic Hierarchy Process (AHP), the evaluation items are layered into the performance perspective and the cloud consideration factor and a comprehensive decision model is proposed. To verify the proposed research model, a system of financial company is divided into three: account, information, and channel system, and the result of decision making by both financial business experts and technology experts from two financial companies were collected. The result shows that some common factors are important in all systems, but most of the factors considered are very different from system to system. We expect that our methodology contributes to the spread of cloud computing adoption.

• Management & Information Systems Review
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• v.36 no.5
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• pp.1-26
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• 2017

In the meantime, research on corporate informatization focuses on the completeness of information technology itself and its financial effects, so there is insufficient research on whether information technology can support business strategy. It is necessary to verify whether the management strategy implementation of the company can be led through the informatization of the enterprise and the relation between the main mechanism factors and the informatization performance. In this study, what a mechanism factor is applied in the process of result creation of informatization from three mechanism perspectives such as selecting mechanism, learning mechanism and coordinating mechanism with cases of representative domestic IT company and what an importance mechanism factors have been ascertained. This study results in 8 propositions. For a main agent of companies, securement of information capability of organizations has been selected to realize informatization results and investment of informatization has been selected to solve organizational decentralization problems as the most important factor. Additionally, as competition in the industry gets fierce, investment on informatization has been changed to a utility way of implementation of strategies and decision on investment has been made through the official process and information technology. Differentiated company capability has been made based on acquisition of technical knowledge and company information has been expanded to its whole employees through the information system. Also, informatization change management and outside subcontractor management have been acknowledged as an important adjustment factor of company. The first implication of this study is that since case studies on mechanism factors that preceding studies on informatization results did not empirically cover have directly been dealt with based on experiences of executives in charge of business and in charge of informatization, this study can provide practical views about factors that should be mainly managed for informatization results of IT companies. Secondly, since ser-M framework has been applied for IT companies for the first time, this study can academically contribute to companies in other fields about main mechanism factors for result creation of informatization based on deeper understanding and empirical cases.