• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.15-25
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• 2017

As the value and importance of softwares are growing up, software theft and piracy become a much larger problem. To tackle this problem, it is highly required to provide an accurate method for detecting software theft and piracy. Especially, while software theft is relatively easy in the case of Android applications (apps), screening illegal apps has not been properly performed in Android markets. In this paper, we propose a method to effectively measure the similarity between Android apps for detecting software theft at the executable file level. Our proposed method extracts method reference frequency and manifest information through static analysis of executable Android apps as the main features for similarity measurement. Each app is represented as an n-dimensional vectors with the features, and then cosine similarity is utilized as the similarity measure. We demonstrate the effectiveness of our proposed method by evaluating its accuracy in comparison with typical source code-based similarity measurement methods. As a result of the experiments for the Android apps whose source file and executable file are available side by side, we found that our similarity degree measured at the executable file level is almost equivalent to the existing well-known similarity degree measured at the source file level.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.219-219
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• 2021

서해안 중부 아산만 안쪽에 위치하는 평택·당진항에서 장래 개발 예정인 면적 6.9km²의 내항2공구 수역은 내항2공구 외곽호안 - 내항가호안 - 내항2공구 중앙 분리호안으로 둘러싸여 있으며, 투수성 제체인 내항가호안 사석 공극을 통하여 해수가 유통되어 조석 현상이 나타나고 있다. 2020년 8~9월의 2개월간 내항2공구 외곽호안 내·외측에서 조석 관측 결과, 2공구 수역의 최대 조차는 1.97m로서 외측 해역 최대 조차 9.79m의 20.1%이고 내·외측의 순간 수위차는 최대 5.82m에 달한다. 내항가호안은 내항2공구 개발이 거의 완료되는 시기까지 유지될 예정이므로 2공구 개발에 따른 내측 조차와 내·외측 수위차의 변화를 정확하게 예측하는 것은 내항가호안 제체 안전에 매우 중요하다. 이 연구의 목적은 장래 개발단계별 변화 예측에 앞서, 관측이 이루어진 2개월간의 실시간 내측 조석과 내·외측 수위차 시계열을 Delft3D-Flow를 이용하여 기 구축된 아산만 수치모델에서 재현하는 것이다. 내항가호안 제체 통과 유량은 내·외측 수위차에 비례하는 것으로 가정하고, 수위차 - 유량 관계식을 도출하였다. 수위차는 평택 조위관측소와 내항2공구 수역의 1분 간격 관측 조위로부터 산출하였고, 제체 통과 유량은 내측 조위(z, 평택항 DL 기준, m) - 수용적(V, 10⁶m³) 관계식으로 계산하였다. 내측 조위 - 수용적 관계식은 수심측량 성과로부터 V = 0.28z² + 3.73z + 2.96 (r²=1.00)으로 얻어졌다. 다양한 함수식의 적합성을 검토한 결과, 다음과 같은 수위차(𝚫z, m) - 제체 통과 유량(Q, m³/s) 관계식을 도출하였다. [내항가호안 내측으로 유입시] $Q_{IN}=\{\begin{array}{lll}{\exp}\{0.54\;{\ln}({\Delta}z)+6.00\}&&\text{; }{\Delta}z{\leq}1.8\\219.82{\Delta}z+158.56&&\text{; }{\Delta}z>1.8\end{array}\;\;(r^2=0.86)$ [내항가호안 외측으로 유출시] Q_OUT = -exp{0.44 ln(-𝚫z) + 5.70} (r²=0.59) 매 𝚫t 마다 제체 통과 유량을 계산하는 알고리즘을 Delft3D 소스 코드에 추가하고, 8개 분조 합성조석(M₂, S₂, K₁, O₁, N₂, K₂, P₁, Q₁)을 외력조건으로 설정하여 2개월간 조석 수치모델링을 수행하였다. 내항2공구 수역의 매 시별 조위 관측치와 모델치를 비교한 결과, 오차는 -0.37~0.37m의 범위이고, 오차 평균은 0.02m, 절대오차 평균은 0.08m로 상당히 정확하게 실시간 조위 변동을 모의하였다. 보정·검정된 이 모델을 이용하여 향후 내항2공구 개발에 따른 내측 조석과 내·외측 수위차 변화에 대한 예측모의를 진행할 예정이다.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.259-271
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• 2023

Since the short-wave infrared spectrum has a significant range of variation depending on the production environment, countries with advanced resource exploration are collecting the spectrum and building a database. Representative organizations include the USGS and CSIRO, and they are currently carrying out a project in China that can synthesize and use a large number of existing data. The USGS library provides a total of 2,457 spectra targeting not only minerals but also various materials that respond to infrared radiation. Among these, there are 1,276 mineral spectra, which are about half of the total. The spectrum title includes information, such as analysis devices (NIC4, BECK, ASDNG, etc.), purity codes (a, b, c, d, u), and measurement methods (AREF, RREF, RTGC, TRAN). Analyzed raw data are provided in ASCII and GIF format. The CSIRO library has a total of 502 spectra, of which the majority, 493, correspond to mineral spectra. The USGS library is a free, publically available resource, while the CSIRO library is bundled with TSG8 or must be purchased separately. Among these, when comparing the eight spectra whose spectral shapes can be analyzed with the spectra of domestic illite, the positions of the absorption peaks are significantly different from those of domestic illite, except for one Japanese illite. Additional research will be needed to determine the causes of such differences, and the domestically relevant databases should be established as well.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.273-285
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• 2024

With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

• Knowledge Management Research
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• v.25 no.2
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• pp.19-47
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• 2024

Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.48-71
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• 2024

Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.

• Journal of the Korean Institute of Gas
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• v.28 no.2
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• pp.93-104
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• 2024

Facility diagnosis is essential for the smooth operation and life extension of rotating equipment used in industrial sites. Compared to other diagnostic methods, vibration diagnosis can find most of the initial defects, such as unbalance, alignment failure, bearing defects and resonance, compared to other diagnostic methods. Therefore, vibration analysis is the most commonly used facility diagnosis method in industrial sites, and is usefully used as a predictive preservation (PdM) technology to manage the condition of the facility. However, since the vibration diagnosis method is performed based on experience based on the standard, it is carried out by experts. Therefore, it is intended to contribute to the reliability of the facility by establishing a system that anyone can easily judge defects by establishing a vibration diagnosis method performed based on experience as a knowledgeable code system. An algorithm was developed based on the ISO-20816 standard for vibration measurement, and the reliability was verified by comparing the results of vibration measurement at various demonstration sites such as petrochemical plant compressors, hydrogen charging stations, and industrial machinery with the results of analysis using a development system. The developed algorithm can contribute to predictive maintenance (PdM) technology that anyone can diagnose the condition of the rotating machine at industrial sites and identify defects early to replace parts at the exact time of replacement. Furthermore, it is expected that it will contribute to reducing maintenance costs and downtime due to the failure of rotating machines when applied to various industrial sites such as oil refining facilities, transportation, production facilities, and aviation facilities.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.3
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• pp.8-17
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• 2023

The current weapon system is operated as a complex weapon system with various standards and protocols applied, so there is a risk of failure in smooth information exchange during combined and joint operations on the battlefield. The interoperability of weapon systems to carry out precise strikes on key targets through rapid situational judgment between weapon systems is a key element in the conduct of war. Since the Korean military went into service, there has been a need to change the configuration and improve performance of a large number of software and hardware, but there is no verification system for the impact on interoperability, and there are no related test tools and facilities. In addition, during combined and joint training, errors frequently occur during use after arbitrarily changing the detailed operation method and software of the weapon/power support system. Therefore, periodic verification of interoperability between weapon systems is necessary. To solve this problem, rather than having people schedule an evaluation period and conduct the evaluation once, AI should continuously evaluate the interoperability between weapons and power support systems 24 hours a day to advance warfighting capabilities. To solve these problems, To this end, preliminary research was conducted to improve defense interoperability capabilities by applying natural language processing techniques (①Word2Vec model, ②FastText model, ③Swivel model) (using published algorithms and source code). Based on the results of this experiment, we would like to present a methodology (automated evaluation of interoperability requirements evaluation / level measurement through natural language processing model) to implement an automated defense interoperability evaluation tool without relying on humans.

• Journal of the Korean Society for information Management
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• v.41 no.3
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• pp.431-459
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• 2024

In contemporary South Korea, ultra-low birth rates have become a critical social issue. Equally important is the social responsibility to support the healthy physical and mental development of children. This study aimed to assess the children and adolescents related to online health information available on the websites of 17 metropolitan representative libraries in South Korea. Using literature review and content analysis methodologies, the study found that only two libraries (11.8%) offered 32 health-related resources for children and adolescents through their library websites. Of these resources, 25 (78.1%) were provided by public health centers, while hospitals contributed six resources (18.8%), and public institutions provided two resources (6.3%). Additionally, an evaluation of these 32 health information resources using the HON code, a recognized tool for assessing online health information, revealed relatively low satisfaction in areas such as "complementarity," "attribution," "transparency of authorship," and "honesty in advertising and editorial policy." Furthermore, the researcher conducted a comparative evaluation of children and adolescent health information resources available through the search engines Naver and Google in Korea. Based on these findings, the study outlines recommendations for improving online health information services related to children and adolescents.