• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.265-276
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• 2017

Korean petroglyphs have been found over a lot of ruins through nation-wide regions including Daegok-ri Bangudae and Cheonjeon-ri in Ulsan. In this paper, we present an information system for Korean petroglyph ruins named KPetro which supports the dedicated camera application and the timeline service. The system provides the services for searching and updating information in various ways over the primary database constructed with the data on petroglyph ruins, which are collected by the Bangudae Petroglyph Institute. In addition, through the camera application developed for the system, users can easily add photos to the appropriate petroglyph ruin according to the GPS information of the location where those photos are taken. Also, the system provides the timeline service showing the photos for a specific petroglyph ruins in order of shooting time. To support both mobile and desktop environments, KPetro provides its functions in a web browser using the HTML5 standard technology and the JavaScript language, enabling the system to be adaptable to various user devices and extendable for its functionalities.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Progress in Medical Physics
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• v.14 no.1
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• pp.34-42
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• 2003

In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.281-299
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• 2007

IS/IT 분야 실무자가 지니고 있어야 한다고 생각되는 지식과 전문 기술들을 '지식/능력 영역'과 '소프트웨어 전문 기술 영역'으로 구분하여 각각 세부 항목을 명세하였다. 그리고 분류된 두 영역에 대하여 IS/IT 분야 실무자가 생각하는 필요한 지식 및 전문 기술들의 중요도와 IS/IT 전공 교수가 생각하는 IS/IT 실무자에게 필요한 지식 및 전문 기술들의 중요도를 조사하여 두 그룹간의 인식차 비교를 시도하였다. 조사지역은 실무자는 충청지역 및 수도권 지역에 분포하는 SI 업체를 대상으로 이루어 졌다. IS/IT 실무자를 대상으로 한 조사는 실무자 본인의 일장에서 IS/IT 실무자가 갖추어야 된다고 판단되는 지식 및 전문 기술들의 중요도를 측정하였다. 그와 더불어 그들이 수행하는 IS 활동에 대하여 투자한 시간을 기준으로 군집분석을 실시하여 세가지 그룹으로 구분하여 실무자 전체와 세 그룹간의 비교가 가능하도록 조차되었다. 비교 결과, 지식/능력 영역에서는 IS 실무자들이 상대적으로 '하드웨어에 대한 지식', '특정 조직', '운영체제에 대한 지식'에 대해 더 높은 중요도를 부여하고 있는 것으로 나타났다. 소프트웨어 전문 기술 영역에서는 실무자보다 전공교수가 생각하는 중요도가 보편적으로 더 높게 나타났다. 전공 교수는 '프리젠테이션 도구', '객체지향 언어(C++, Java 등)'에 4점 대의 높은 점수를 주어 중요한 것이 무엇인가 하는 인지가 있는 것으로 보이나 실무자 그룹에서는 특별히 중요시 여기는 항목이 명확히 드러나지 않고 보편적인 값이 median 값 주변에 위치하고 있다. 이는 현재 실무자들이 빠르게 변화하고 있는 IS/IT 환경에서 본인의 경력경로 (career path)을 위해 무엇이 중요한 갓인지 아직 명확히 하고 있지 못하는 것으로도 해석이 가능하다. 자세한 비교/분석 및 해석은 현재 진행 중이며, 여러 흥미로운 해석이 가능할 것으로 기대 된다.합형 파괴가 증가하는 경향을 나타내었다. 이상의 결과로, 상아질 접착제의 접착단계/과정이 결합내구성에 영향을 미침을 알 수 있었다. 따라서 접착과정의 단순화가 반드시 접착에 효과적이라고 할 수 없다.는 저작 운동 잔에는 2군에서 Heliomolar가 Pyramid보다 변연적합도가 우수하였고 (p < 0.05) 그 외의 군에서는 유의차가 없었으며, 저작 운동 후에는 모든 군에서 재료간 유의차가 없었다. 각 부위별 변연적합도를 비교하면, 저작 운동 전 Pyramid에서는 교합면 변연에서는 4군이 2군에 비해 높은 변연적합도를 보였고 (p < 0.05), 인접면과 치은면에서는 군 간 유의차를 보이지 않았다. Heliomolar에서는 교합면 변연에서 2, 4군이 1군에 비해 높은 변연적합도를 보였고 (p < 0.05), 인접면과 치은면에서는 군간 유의차를 보이지 않았다. 저작 운동 후 Pyramid에서는 교합면 변연에서는 3군이 1, 2군에 비해 높은 변연적합도를 보였고 (p < 0.05), 인접면과 치은면에서는 군간 유의차를 보이지 않았다. Heliomolar에서는 교합면에서 2, 3, 4군이 1군에 비해 변연적합도가 높았으며 (p < 0.05), 인접면과 치은면에서는 군간 유의차를 보이지 않았다 이번 연구를 통하여 복합레진을 간헐적 광중합시킴으로써 변연적합도가 향상될 수 있음을 알 수 있었다.시장에 비해 주가가 비교적 안정적인 수준을 유지해 왔다고 볼 수 있다.36.4%)와 외식을 선호(29.1%)${\lrcorner}$ 하기 때문에 패스트푸드를 이용하게 된 것으로 응답 하였으며, 남 여 대학생간에는 유의한 차이(p<0.05)가 인정되었다. 응답자의 체형은 ${\ulcorner}$적당하다${\lrcorner}$고 응답한 경우가 가장 많이 이러한 음식을 즐겨 먹었으며(49.5%), 그 다음은 뚱뚱한 경우도 비교적 많이 먹고

• Communications of Mathematical Education
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• v.29 no.4
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• pp.573-588
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• 2015

In this paper, we introduce development process and application of a simple and effective model of a statistics laboratory using open source software R, one of leading language and environment for statistical computing and graphics. This model consists of HTML files, including Sage cells, video lectures and enough internet resources. Users do not have to install statistical softwares to run their code. Clicking 'evaluate' button in the web page displays the result that is calculated through cloud-computing environment. Hence, with any type of mobile equipment and internet, learners can freely practice statistical concepts and theorems via various examples with sample R (or Sage) codes which were given, while instructors can easily design and modify it for his/her lectures, only gathering many existing resources and editing HTML file. This will be a resonable model of laboratory for studying statistics. This model with bunch of provided materials will reduce the time and effort needed for R-beginners to be acquainted with and understand R language and also stimulate beginners' interest in statistics. We introduce this interactive statistical laboratory as an useful model for beginners to learn basic statistical concepts and R.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.253-263
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• 2016

Chrysanthemum production would benefit from crop growth simulations, which would support decision-making in crop management. Chrysanthemum is a typical short day plant of which floral initiation and development is sensitive to photoperiod. We developed a model to predict phenological development and leaf appearance of chrysanthemum (cv. Baekseon) using daylength (including civil twilight period), air temperature, and management options like light interruption and ethylene treatment as predictor variables. Chrysanthemum development stage (DVS) was divided into juvenile (DVS=1.0), juvenile to budding (DVS=1.33), and budding to flowering (DVS=2.0) phases for which different strategies and variables were used to predict the development toward the end of each phenophase. The juvenile phase was assumed to be completed at a certain leaf number which was estimated as 15.5 and increased by ethylene application to the mother plant before cutting and the transplanted plant after cutting. After juvenile phase, development rate (DVR) before budding and flowering were calculated from temperature and day length response functions, and budding and flowering were completed when the integrated DVR reached 1.33 and 2.0, respectively. In addition the model assumed that leaf appearance terminates just before budding. This model predicted budding date, flowering date, and leaf appearance with acceptable accuracy and precision not only for the calibration data set but also for the validation data set which are independent of the calibration data set.

• Archives of design research
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• v.19 no.2 s.64
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• pp.163-172
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• 2006

Sign is one of the important factors in city and national image formation, thus requires high level of quality. However, domestic sign emphasize only the sense of attention that leads to big sized signs, thus often results in a poor coordination with the surrounding space. This situation requires employees in sign business want to learn specialized knowledge about design field. Based on these circumstances, we propose sign design software to employees in sign business field as an aid tool that can help to develop good signs in terms of functionality as well as harmony of design. Thus, in this investigation, sign simulation software application case that can design sign and apply this sign to the actual application site is presented. In order to develop this software, literature survey and preliminary studies were performed to analyze the preparation process and environment, and designed sign design element and software elements, user interrace, and finally Java software were utilized. This developed software can be used as a textbook in sign design related departments in schools, and hopefully to enhance the social recognition of sign as well as academic interest.

• Korean Journal of Cognitive Science
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• v.12 no.3
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• pp.29-46
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• 2001

This study attempted to demonstrate that the integration of the two premises in linear syllogism is mediated by the middle term the term that is repeated in the two premises. In Experiment 1. we examined whether representing the middle term is more important than representing the end terms. We asked a question to each premise. Depending on the order of the questions either the two end terms or the middle term became the answer in both premises. Participants solved the problems better when the middle term became the answer suggesting that it is more important to represent the middle term than the end terms. In Experiment 2 we examined whether additional processing is needed for the integration beyond establishing co-referential link through the middle term. We pronominalized the middle term in the second premise and provided two kinds of information to disambiguate the pronoun. In the direct information condition we provided information about who the pronoun is whereas in the indirect information condition we provided information about the relative location of the pronoun. Participants solved the problems more quickly in the indirect information condition than in the direct information condition indicating that mere co-referential link was not enough and that the relative location of the middle term needs to be computed for the integration of the two premises.

• Journal of Food Hygiene and Safety
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• v.32 no.1
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• pp.8-13
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• 2017

This study was conducted to develop an agent-based computing platform enabling simulation of on-farm produce contamination by enteric foodborne pathogens, which is herein called PPMCS (Preharvest Produce Microbial Contamination Simulator). Also, fecal contamination of preharvest produce was simulated using PPMCS. Although Agent-based Modeling and Simulation, the tool applied in this study, is rather popular in where socio-economical human behaviors or ecological fate of animals in their niche are to be predicted, the incidence of on-farm produce contamination which are thought to be sporadic has never been simulated using this tool. The agents in PPMCS including crop, animal as a source of fecal contamination, and fly as a vector spreading the fecal contamination are given their intrinsic behaviors that are set to be executed at certain probability. Once all these agents are on-set following the intrinsic behavioral rules, consequences as the sum of all the behaviors in the system can be monitored real-time. When fecal contamination of preharvest produce was simulated in PPMCS as numbers of animals, flies, and initially contaminated plants change, the number of animals intruding cropping area affected most on the number of contaminated plants at harvest. For further application, the behaviors and variables of the agents are adjustable depending on user's own scenario of interest. This feature allows PPMCS to be utilized in where different simulating conditions are tested.