• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.13-21
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• 2020

The Android author identification study can be interpreted as a method for revealing the source in a narrow range, but if viewed in a wide range, it can be interpreted as a study to gain insight to identify similar works through known works. The problem found in the Android author identification study is that it is an important code on the Android system, but it is difficult to find the important feature of the author due to the meaningless codes. Due to this, legitimate codes or behaviors were also incorrectly defined as malicious codes. To solve this, we introduced the concept of survival network to solve the problem by removing the features found in various Android apps and surviving unique features defined by authors. We conducted an experiment comparing the proposed framework with a previous study. From the results of experiments on 440 authors' identified apps, we obtained a classification accuracy of up to 92.10%, and showed a difference of up to 3.47% from the previous study. It used a small amount of learning data, but because it used unique features without duplicate features for each author, it was considered that there was a difference from previous studies. In addition, even in comparative experiments with previous studies according to the feature definition method, the same accuracy can be shown with a small number of features, and this can be seen that continuously overlapping meaningless features can be managed through the concept of a survival network.

• Journal of Technology Innovation
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• v.29 no.1
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• pp.1-38
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• 2021

In this paper, an exploratory analysis study was conducted on establishing a strategy to utilize living labs to enhance the innovation of the energy sector. Through the previous research literature, it was possible to confirm the concept, essential components, innovation characteristics of living labs, and types of innovation issues in the energy sector as the theoretical background. Based on this, the case studies of energy living lab (8 overseas, 1 domestic) were analyzed focusing on the possibility of utilizing living lab as an approach to innovation issues in the energy sector, establishing a customized strategy for essential components of living lab and enhancing innovation. It was confirmed that the establishment of a customized strategy for the essential components of the living lab could be a driving force in enhancing innovation, and the Living Lab is effectively used as an approach method for innovation issues(demand management, supply technology, enhance R&D acceptance and promote commercialization, technology policies) in the energy sector. As a result of the case studies, the driving force of each living lab was derived from the viewpoint of contributing to innovation, and strategies for using the living labs for each energy innovation problem were established. This study is an exploratory and descriptive analytical study of the utilization strategy and value of the living lab model as an approach to innovation issues in the energy field, which can provide a living lab strategy framework that has not been tried in the past and enables living lab activation and network formation. It can also be considered to have academic, practical, and policy implications in that it can also contribute.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.183-200
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• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.49-57
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• 2022

Currently, the problem of food shortage is emerging in our society due to climate problems and an increase population in the world. As a solution to this problem, we propose a multi-remote control smart farm that combines artificial intelligence (AI) and information and communication technology (ICT) technologies. The proposed smart farm integrates ICT technology to remotely control and manage crops without restrictions in space and time, and to multi-control the growing environment of crops. In addition, using Arduino and deep-learning technology, a smart farm capable of multiple control through a smart-phone application (APP) was proposed, and Ai technology with various data securing and diagnosis functions while observing crop growth in real-time was included. Various sensors in the smart farm are controlled by using the Arduino, and the data values of the sensors are stored in the built database, so that the user can check the stored data with the APP. For multiple control for multiple crops, each LED, COOLING FAN, and WATER PUMP for two or more growing environments were applied so that the user could control it conveniently. And by implementing an APP that diagnoses the growth stage through the Tensor-Flow framework using deep-learning technology, we developed an application that helps users to easily diagnose the growth status of the current crop.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.725-735
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• 2022

Currently, disasters occurring in Korea are characterized by unpredictability and complexity. Due to these features, property damage and human casualties are increasing. Since the initial response process of these disasters is directly related to the scale and the spread of damage, optimal decision-making is essential, and information of the site must be obtained through timely applicable sensors. However, it is difficult to make appropriate decisions because indiscriminate information is collected rather than necessary information in the currently operated Disaster and Safety Situation Office. In order to improve the current situation, this study proposed a framework that quickly collects various disaster image information, extracts information required to support decision-making, and utilizes it. To this end, a web-based display system and a smartphone application were proposed. Data were collected close to real time, and various analysis results were shared. Moreover, the capability of supporting decision-making was reviewed based on images of actual disaster sites acquired through CCTV, smartphones, and UAVs. In addition to the reviewed capability, it is expected that effective disaster management can be contributed if institutional mitigation of the acquisition and sharing of disaster-related data can be achieved together.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1115-1124
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• 2022

The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.1-25
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• 2021

In order to respond and prevent underground safety accidents, the Korean government has been preparing a submitting completion drawing web system project for converting the current manual-based 3D Underground Geospatial Map construction and its update system to an automation-based 3D underground information construction. However, research on standard drawings required for the automatic update of 3D underground structures is insufficient, so detailed research is needed. In this research paper, a standard map-based 3D underground structure construction plan was presented for the six types of underground structures constituting the 3D Underground Geospatial Map, enabling rapid and accurate drawing data creation and systematically 3D underground structure drawing data could be managed. In addition, we developed a 3D construction drawing tool that can be used in underground information practice so that ordinary CAD program users can easily produce processing drawings. The results derived from this paper are expected to be major reference materials for the establishment of standard frameworks and practical application guidelines for the construction of 3D underground structures in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.17-28
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• 2022

This study is to develop the direction of the development of the next-generation mapping of marine information required to develop a base of the utilization localization of maritime production tools. The GIS data-processing products and technologies currently used in the Korea's marine sector depend on external applications which is renewal costs, technical updates, and unreflected characteristics. Meanwhile, the S-100 standard, the next generation hydrographic data model that complements S-57's problems in marine GIS data processing, was adopted as a new marine data standard. This study aims to present the current status and problems of marine GIS technology in Korea and to suggest the development direction of GIS software based on the next generation hydrogrphic data model S-100 standard of IHO(International Hydrographic Organization). S-100-based marine GIS localization technology development and industrial ecosystem development research is expected to scientific decision-making on policy issues that occur with other countries such as marine territory management and development and use of marine resources.

• 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.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.