• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.89-97
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• 2017

Recent Internet of Things(IoT), and in addition to wearable PC, such as software development methodologies based on a variety of object-oriented design and design patterns of GoF(Gang of Four) with OOP(Object-Oriented Programming) intended for portable devices. However, incorrect application design specification is that the higher the importance of the optimization of the program on the device because it can cause problems such as decreased operating speed, increase the memory occupancy and battery usage. In this paper, we propose an optimized design pattern based on the method of application, such as Android (Android) OS Strategy Pattern, State Pattern, Observer pattern. Test results show that the proposed scheme selection patterns can be selected to optimize the design pattern in the device that specification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1275-1281
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• 2019

The automatic modulation recognition of a radio signal is a major task of an intelligent receiver, with various civilian and military applications. In this paper, we propose a method to recognize the modulation of radio signals in wireless communication based on the deep neural network. We classify the modulation pattern of radio signal by using the LSTM model, which can catch the long-term pattern for the sequential data as the input data of the deep neural network. The amplitude and phase of the modulated signal, the in-phase carrier, and the quadrature-phase carrier are used as input data in the LSTM model. In order to verify the performance of the proposed learning method, we use a large dataset for training and test, including the ten types of modulation signal under various signal-to-noise ratios.

• Journal of Korea Game Society
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• v.13 no.3
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• pp.5-18
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• 2013

This study analyzed the effect by comparing it with 2D game using playtest experimental treatment methodology to verify the video effect, materiality and fatigue effect of 3D video game. First, for the hypothesis to verify the difference of video experience of users for 3D and 2D games, visual clarity was rejected, but materiality, tangibility and presence hypotheses were all accepted. Second, it was shown that there was no difference in eye fatigue and physical fatigue in 3D and 2D games. It was different from results of existing research which claimed that fatigue occurred due to video distortion occurring in 3D video and fatigue inducing factors. Third, the results of measurement of changes in brain wave occurring in the course of playing 3D and 2D games showed that there was no difference in average amplitude of EEG alpha wave, but EEG beta wave occurred in higher amplitude. This study proved the cerebral physiological change and difference in the process of experience to use 3D video game by complementing the methodology in measurement in EEG brain wave in the traditional experimental method.

• KDI Journal of Economic Policy
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• v.36 no.1
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• pp.107-126
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• 2014

The core of the neoclassical growth theory is the capital investment. Solow proposed that the diminishing return is key to such growth process in establishing the stability of the equilibrium growth path. This key postulation has critical implications on the sustainable and effective development policies, emphasizing the importance of productivity growth not only for the steady-state growth but also for the transitional growth from capital accumulation. This paper suggests a novel way to test the diminishing return, the backbone assumption of Solow model, and confirms its strong presence using the Penn World Tables version 8.0 data, hence validates Solow's implications on effective development policies.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.62.2-62.2
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• 2019

한국의 고천문 자료는 삼국시대 이후 근대 조선까지 다수가 존재하여 세계적으로 드문 기록 문화를 보유하고 있으나, 한문 번역이 많이 이루어지지 않아 학술적 활용이 활발하지 못한 상태이다. 고문헌의 한문 문장 번역은 전문인력의 수작업에 의존하는 만큼 소요 시간이 길기에 투자대비 효율성이 떨어지는 편이다. 이에 최근 여러 분야에서 응용되는 인공지능의 적용을 대안으로 삼을 수 있으며, 초벌 번역 수준일지라도 자동번역기의 개발은 유용한 학술도구가 될 수 있다. 한국천문연구원은 한국정보화진흥원이 주관하는 2019년도 Information and Communication Technology 기반 공공서비스 촉진사업에 한국고전번역원과 공동 참여하여 인공신경망 기계학습이 적용된 고문헌 자동번역모델을 개발하고자 한다. 이 연구는 고천문 도메인에 특화된 인공지능 기계학습 기법으로 자동번역모델을 개발하여 이를 서비스하는 것을 목적으로 한다. 연구 방법은 크게 4가지 개발을 진행하는 것으로 나누어 볼 수 있다. 첫째, 인공지능의 학습 데이터에 해당되는 '코퍼스'를 구축하는 것이다. 이는 고문헌의 한자 원문과 한글 번역문이 쌍을 이루도록 만들어 줌으로써 학습에 최적화한 데이터를 최소 6만 개 이상 추출하는 것이다. 둘째, 추출된 학습 데이터 코퍼스를 다양한 인공지능 기계학습 기법에 적용하여 천문 분야 특수고전 도메인에 특화된 자동번역 모델을 생성하는 것이다. 셋째, 클라우드 기반에서 참여 기관별로 소장한 고문헌을 자동 번역 모델에 기반하여 도메인 특화된 모델로 도출 및 활용할 수 있는 대기관 서비스 플랫폼 구축이다. 넷째, 개발된 자동 번역기의 대국민 개방을 위해 웹과 모바일 메신저를 통해 자동 번역 서비스를 클라우드 기반으로 구축하는 것이다. 이 연구는 시스템 요구사항 분석과 정의를 바탕으로 설계가 진행 또는 일부 완료되어 구현 중에 있다. 추후 이 연구의 성능 평가는 자동번역모델 평가와 응용시스템 시험으로 나누어 진행된다. 자동번역모델은 평가용 테스트셋에 의한 자동 평가와 전문가에 의한 휴먼 평가에 따라 모델의 품질을 수치로 측정할 수 있다. 또한 응용시스템 시험은 소프트웨어 방법론의 개발 단계별 테스트를 적용한다. 이 연구를 통해 고천문 분야가 인공지능 자동번역 확산 플랫폼 시범의 첫 케이스라는 점에서 의의가 있다. 즉, 클라우드 기반으로 시스템을 구축함으로써 상대적으로 적은 초기 비용을 투자하여 활용성이 높은 한문 문장 자동 번역기라는 연구 인프라를 확보하는 첫 적용 학문 분야이다. 향후 이를 활용한 고천문 분야 학술 활동이 더욱 활발해질 것을 기대해 볼 수 있다.

• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.49-55
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• 2013

Recently the CGF/SAF (Computer Generated Force / Semi-Automated Force) technology has been getting attention to deal with the increasing complexity in a DM&S(Defence Modeling and Simulation) environment. OneSAF is one of well-known CGF/SAF systems, however, it is not able to support the DEVS framework which is an advanced discrete event based modeling and simulation environment. Especially, most DM&S systems in Korea has been developed on the basis of the DEVS framework. In this paper, we have proposed the agent-based SAF design methodology and tool for supporting DEVS M&S environment. The proposed SAF modeling tool is divided into two parts; the agent modeling part and SAF modeling part. In the agent modeling environment, the modeler can simply create the agent model by writing down the necessary rules. It also provides the agent testing environment so that the modeler maybe conveniently verify the prescribed agent model. The SAF model is finally created by combing the individual agents based on the pre-defined structure. DM&S engineers will be able to employ our tools and modeling methodology to design the DEVS-based DM&S system to be developed.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.87-99
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• 2013

As Internet advances, websites with simpel HTML pages are changing to complex web application systems with enormous contents and various services. With this trend, it is noted that situations where Web accessibility of the old and the handicapped is inhibited are growing. To solve this problem, The Disability Discrimination Act has been enacted since April 2013. This act triggers massive website reorganization efforts. However, in order for the huge and sophisticated web applications and web sites to ensure a web accessibility, a framework is required to throughout the web site development. Based on thorough review of website development methodologies, web accessibility compliance standards, and various web accessibility issues related to website characteristics, this study proposes a practice oriented "Web Accessibility Compliance Framework". The current study also examines the usefulness and value of this framework by applying it to the internet banking development project of W bank and receiving a certificate for high quality website complying web accessibility standards.

• CRM연구
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• v.2 no.2
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• pp.53-70
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• 2009

Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.31-42
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• 2021

We propose a deep learning-based method that can estimate an appropriate lighting of both indoor and outdoor images. The method consists of two networks: Crop-to-PanoLDR network and LDR-to-HDR network. The Crop-to-PanoLDR network predicts a low dynamic range (LDR) environment map from a single partially observed normal field of view image, and the LDR-to-HDR network transforms the predicted LDR image into a high dynamic range (HDR) environment map which includes the high intensity light information. The HDR environment map generated through this process is applied when rendering virtual objects in the given image. The direction of the estimated light along with ambient light illuminating the virtual object is examined to verify the effectiveness of the proposed method. For this, the results from our method are compared with those from the methods that consider either indoor images or outdoor images only. In addition, the effect of the loss function, which plays the role of classifying images into indoor or outdoor was tested and verified. Finally, a user test was conducted to compare the quality of the environment map created in this study with those created by existing research.