• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.611-618
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• 2020

In this paper, we propose a design and implementation method of speed quiz content that can be driven by a social robot capable of interacting with humans, and a method of developing an intelligent module necessary for implementation. In addition, we propose a method of implementing speed quiz content through the process of constructing a map by arranging and connecting intelligent module blocks. Recently, software education has become mandatory and interest in programming is increasing. However, programming is difficult for students without basic knowledge of programming languages to directly access, and interest in block-type programming platforms suitable for beginners is growing. The block-type programming platform used in this paper is a platform that supports immediate and intuitive programming by supporting interactions between humans and robots. In this paper, the intelligent module implemented for the speed quiz content was used by blocking it within a block-type programming platform. In order to implement the scenario of the speed quiz content proposed in this paper, we implement a total of three image-based artificial intelligence modules. In addition to the intelligent module, various functional blocks were placed to implement the speed quiz content. In this paper, we propose a method of designing a speed quiz content scenario and a method of implementing an intelligent module for speed quiz content.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.2
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• pp.73-80
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• 2011

The study reviewed the content and the meaning of the present Yeoju Palkyung(eight scenery) through analyzing and interpreting the Palkyung poems, old maps and paintings, and classic materials transmitted in Yeoju area, and investigated the landscape structure of the area around the Cheongshimru(淸心樓: pavilion). On the other hand, many Palkyung poems and Noojeongjeyong(樓亭) poems illustrating the Cheongshimru as the view point or the objective have clarified the scenic excellence when the Cheongshimru is the view point. The Yeoju Palkyung viewed from the Cheongshimru was described as constructing all around allocation structure, and six scenes are categorized as a distant view of the visual influence while the 7th scene Ireungdogyeon and the 8th scene Pasagwau are a psychologically influencing landscapes. The panoramic composition of the Yeoju Palkyung at the Cheongshimru is interpreted as the Seunggyeong distribution considering Palchaejigyeongsaek(八采之景色), where main viewpoint is the Cheongshimru and the distant landscape is Paldaejangrim. The reputation of the Cheongshimru, the central place of the Yeoju Palkyung, is confirmed by the technique of scene processing describing a various way of illustrating landscapes such as near view, distant view, pulling view and collecting view. The restoration of Cheongshimru and Paldaesup(八大藪) currently undertaken is the essential business for the full recovery of the Yeoju Palkyung, which will be not only for physical restoration but also for the shortcut to revitalize the history and the spirit of Yeoju. Furthermore, the business direction should be reconsidered to truly understand the meaning, the value, and the structure of the Yeoju Palkyung to ensure the pursuit of the sustainability aiming at the project "Local attractions", one of the Namhangnag Four rivers project of the ministry of Land, Transport and Maritime Affairs.

• Analytical Science and Technology
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• v.34 no.6
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• pp.251-258
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• 2021

Knives are most frequently used as weapons in violent crimes. Criminals leave behind knife sheaths made of paper and tape at crime scenes. It is difficult to develop fingerprints using tape attached to a porous surface, resulting in the need to explore effective techniques for identifying fingerprints as well as the distribution of fingerprints on each surface, when evidence such as paper knife sheaths are found. In this study, 50 knife sheaths were prepared. The cyanoacrylate fuming (CA fuming) method was applied to develop fingerprints on the non-adhesive side of the tape, and a dual-purpose 1,2-indanedione/Zn (1,2-IND/Zn) reagent was used to separate tape from paper while simultaneously developing fingerprints on the paper. The fingerprints on the adhesive side of the tape were developed using Wet Powder Black^®. Using the R statistical analysis program (The R Foundation for Statistical Computing), we used a heat map to indicate the location of fingerprints developed from each surface. More fingerprints were detected at the ends than in the center of the adhesive side of the tape, and although the non-adhesive sides of tape and paper did not present clear distribution patterns, many fingerprints were developed that had sufficient clarity for personal identification. The results of this study may be applicable for processing evidence when paper sheaths are found at crime scenes.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.267-274
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• 2023

In this paper, a method for estimating the illuminant chromaticity of a scene for an input image is proposed. The illuminant chromaticity is estimated using the illuminant reference region. The conventional method uses a certain number of reference lighting information. By comparing the chromaticity distribution of pixels from the input image with the chromaticity set prepared in advance for the reference illuminant, the reference illuminant with the largest overlapping area is regarded as the scene illuminant for the corresponding input image. In the process of calculating the overlapping area, the weights for each reference light were applied in the form of a Gaussian distribution, but a clear standard for the variance value could not be presented. The proposed method extracts an independent reference chromaticity region from a given reference illuminant, calculates the characteristic values in the r-g chromaticity plane of the RGB color coordinate system for all pixels of the input image, and then calculates the independent chromaticity region and features from the input image. The similarity is evaluated and the illuminant with the highest similarity was estimated as the illuminant chromaticity component of the image. The performance of the proposed method was evaluated using the database image and showed an average of about 60% improvement compared to the conventional basic method and showed an improvement performance of around 53% compared to the conventional Gaussian weight of 0.1.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.35-52
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• 2019

As public services are provided in various forms, including e-government, the level of public demand for public service quality is increasing. Although continuous measurement and improvement of the quality of public services is needed to improve the quality of public services, traditional surveys are costly and time-consuming and have limitations. Therefore, there is a need for an analytical technique that can measure the quality of public services quickly and accurately at any time based on the data generated from public services. In this study, we analyzed the quality of public services based on data using process mining techniques for civil licensing services in N city. It is because the N city's building license complaint service can secure data necessary for analysis and can be spread to other institutions through public service quality management. This study conducted process mining on a total of 3678 building license complaint services in N city for two years from January 2014, and identified process maps and departments with high frequency and long processing time. According to the analysis results, there was a case where a department was crowded or relatively few at a certain point in time. In addition, there was a reasonable doubt that the increase in the number of complaints would increase the time required to complete the complaints. According to the analysis results, the time required to complete the complaint was varied from the same day to a year and 146 days. The cumulative frequency of the top four departments of the Sewage Treatment Division, the Waterworks Division, the Urban Design Division, and the Green Growth Division exceeded 50% and the cumulative frequency of the top nine departments exceeded 70%. Higher departments were limited and there was a great deal of unbalanced load among departments. Most complaint services have a variety of different patterns of processes. Research shows that the number of 'complementary' decisions has the greatest impact on the length of a complaint. This is interpreted as a lengthy period until the completion of the entire complaint is required because the 'complement' decision requires a physical period in which the complainant supplements and submits the documents again. In order to solve these problems, it is possible to drastically reduce the overall processing time of the complaints by preparing thoroughly before the filing of the complaints or in the preparation of the complaints, or the 'complementary' decision of other complaints. By clarifying and disclosing the cause and solution of one of the important data in the system, it helps the complainant to prepare in advance and convinces that the documents prepared by the public information will be passed. The transparency of complaints can be sufficiently predictable. Documents prepared by pre-disclosed information are likely to be processed without problems, which not only shortens the processing period but also improves work efficiency by eliminating the need for renegotiation or multiple tasks from the point of view of the processor. The results of this study can be used to find departments with high burdens of civil complaints at certain points of time and to flexibly manage the workforce allocation between departments. In addition, as a result of analyzing the pattern of the departments participating in the consultation by the characteristics of the complaints, it is possible to use it for automation or recommendation when requesting the consultation department. In addition, by using various data generated during the complaint process and using machine learning techniques, the pattern of the complaint process can be found. It can be used for automation / intelligence of civil complaint processing by making this algorithm and applying it to the system. This study is expected to be used to suggest future public service quality improvement through process mining analysis on civil service.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.125-136
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• 2024

This study presents an automated Python algorithm for analyzing rainfall characteristics to establish critical rainfall thresholds as part of a landslide early warning system. Rainfall data were sourced from the Korea Meteorological Administration's Automatic Weather System (AWS) and the Korea Forest Service's Automatic Mountain Observation System (AMOS), while landslide data from 2020 to 2023 were gathered via the Life Safety Map. The algorithm involves three main steps: 1) processing rainfall data to correct inconsistencies and fill data gaps, 2) identifying the nearest observation station to each landslide location, and 3) conducting statistical analysis of rainfall characteristics. The analysis utilized power law and nonlinear regression, yielding an average R² of 0.45 for the relationships between rainfall intensity-duration, effective rainfall-duration, antecedent rainfall-duration, and maximum hourly rainfall-duration. The critical thresholds identified were 0.9-1.4 mm/hr for rainfall intensity, 68.5-132.5 mm for effective rainfall, 81.6-151.1 mm for antecedent rainfall, and 17.5-26.5 mm for maximum hourly rainfall. Validation using AUC-ROC analysis showed a low AUC value of 0.5, highlighting the limitations of using rainfall data alone to predict landslides. Additionally, the algorithm's speed performance evaluation revealed a total processing time of 30 minutes, further emphasizing the limitations of relying solely on rainfall data for disaster prediction. However, to mitigate loss of life and property damage due to disasters, it is crucial to establish criteria using quantitative and easily interpretable methods. Thus, the algorithm developed in this study is expected to contribute to reducing damage by providing a quantitative evaluation of critical rainfall thresholds that trigger landslides.

• The Korean Journal of Air & Space Law and Policy
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• v.20 no.1
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• pp.87-107
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• 2005

Land Remote Sensing' is defined as the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. Narrowly speaking, this is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information. Remote sensing technology was initially developed with certain purposes in mind ie. military and environmental observation. However, after 1970s, as these high-technologies were taught to private industries, remote sensing began to be more commercialized. Recently, we are witnessing a 0.61-meter high-resolution satellite image on a free market. While privatization of land remote sensing has enabled one to use this information for disaster prevention, map creation, resource exploration and more, it can also create serious threat to a sensed nation's national security, if such high resolution images fall into a hostile group ie. terrorists. The United States, a leading nation for land remote sensing technology, has been preparing and developing legislative control measures against the remote sensing industry, and has successfully created various policies to do so. Through the National Oceanic and Atmospheric Administration's authority under the Land Remote Sensing Policy Act, the US can restrict sensing and recording of resolution of 0.5 meter or better, and prohibit distributing/circulating any images for the first 24 hours. In 1994, Presidential Decision Directive 23 ordered a 'Shutter Control' policy that details heightened level of restriction from sensing to commercializing such sensitive data. The Directive 23 was even more strengthened in 2003 when the Congress passed US Commercial Remote Sensing Policy. These policies allow Secretary of Defense and Secretary of State to set up guidelines in authorizing land remote sensing, and to limit sensing and distributing satellite images in the name of the national security - US government can use the civilian remote sensing systems when needed for the national security purpose. The fact that the world's leading aerospace technology country acknowledged the magnitude of land remote sensing in the context of national security, and it has made and is making much effort to create necessary legislative measures to control the powerful technology gives much suggestions to our divided Korean peninsula. We, too, must continue working on the Korea National Space Development Act and laws to develop the necessary policies to ensure not only the development of space industry, but also to ensure the national security.