• Title/Summary/Keyword: 소프트웨어 개발론

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Case Analysis and Applicability Review of Parametric Design in Landscape Architectural Design (조경 설계 분야에서 파라메트릭 디자인의 사례 분석과 활용 가능성)

  • Na, Sungjin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.2
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    • pp.1-16
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    • 2021
  • The act of design in landscape architecture consists of a concept within a designer's mind, technical representations, and finally, a process of construction. In the 4th Industrial Revolution, the design process is facing many changes due to the rapid development of computer technology and the IT ecosystem. Computer technology was initially developed for simple functions, such as mathematical calculation and graphic representation. However, after the spread of Personal Computers, starting with IBM and Macintosh, programming languages and hardware rapidly developed, algorithms and applications became specialized, and the purpose of using computers became very diverse. This study diagnoses issues concerning the functions and roles that new design methods, such as computational design, parametric design, and algorithmic design, can play in landscape architecture based on changes in the digital society. The study focused on the design methodology using parametric technology, which has recently received the most attention. First, the basis for discussion was developed by examining the main concepts and characteristics of parametric design in modern landscape architecture. Prior research on the use of parametric design in landscape architecture was analyzed, as were the case studies conducted by landscape design firms. As a result, it was confirmed that parametric design has not been sufficiently discussed in terms of the number and diversity of studies compared to other techniques investigated by landscape design firms. Finally, based on the discussion, the study examined specific cases and future possibilities of the parametric design in landscape architecture.

Review for Assessment Methodology of Disaster Prevention Performance using Scientometric Analysis (계량정보 분석을 활용한 방재성능평가 방법에 대한 고찰)

  • Dong Hyun Kim;Hyung Ju Yoo;Seung Oh Lee
    • Journal of Korean Society of Disaster and Security
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    • v.15 no.4
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    • pp.39-46
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    • 2022
  • The rainfall characteristics such as heavy rains are changing differently from the past, and uncertainties are also greatly increasing due to climate change. In addition, urban development and population concentration are aggravating flood damage. Since the causes of urban inundation are generally complex, it is very important to establish an appropriate flood prevention plan. Thus, the government in Korea is establishing standards for disaster prevention performance for each local government. Since the concept of the disaster prevention performance target was first presented in 2010, the setting standards have changed several times, but the overall technology, methodology, and procedures have been maintained. Therefore, in this study, studies and technologies related to urban disaster prevention performance were reviewed using the scientometric analysis method to review them. This analysis is a method of identifying trends in the field and deriving new knowledge and information based on data such as papers and literature. In this study, papers related to the disaster prevention performance of the Web of Science for the last 30 years from 1990 to 2021 were collected. Citespace, scientometric software, was used to identify authors, research institutes, countries, and research trends, including citation analysis. As a result of the analysis, consideration factors such as the the concept of asset evaluation were identified when making decisions related to urban disaster prevention performance. In the future, it is expected that prevention performance standards and procedures can be upgraded if the keywords are specified and the review of each technology is conducted.

Development of Urban Wildlife Detection and Analysis Methodology Based on Camera Trapping Technique and YOLO-X Algorithm (카메라 트래핑 기법과 YOLO-X 알고리즘 기반의 도시 야생동물 탐지 및 분석방법론 개발)

  • Kim, Kyeong-Tae;Lee, Hyun-Jung;Jeon, Seung-Wook;Song, Won-Kyong;Kim, Whee-Moon
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.26 no.4
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    • pp.17-34
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    • 2023
  • Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.

The Development of the Sustainability Appraisal Indicators for Clean Development Mechanism(CDM) Projects by Multi-Criteria Analysis(MCA) (청정개발체제(CDM)사업의 지속가능성평가 지표 개발 -다 기준분석법(MCA)을 활용하여-)

  • Yang, Chun-Seung;Park, Sung-Hwan;Park, Jung-Gu
    • Journal of Environmental Policy
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    • v.8 no.2
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    • pp.83-118
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    • 2009
  • Clean Development Mechanism(CDM) projects under the Kyoto Protocol have two objectives. One is to assist the Parties included in Annex I in achieving compliance with their quantified emission limitation and reduction commitments in cost-effective ways by allowing them to implement emission reduction projects in Non-Annex I countries and receive CERs, which will offset their reduction commitments. The other is to assist Parties not included in Annex I in achieving sustainable development and technology transfers through investments by Annex I countries. However, in reality, it is said that the former objective is achievable but the latter is not. In this light, this article suggests sustainability appraisal criteria applicable for Korea. Among various methodologies, we used the 'multi-attributes utility theory(MAUT)'; one of the 'multi-criteria analysis (MCA)' methodologies judged to be the most practical and relevant. Based on the guidelines of the MAUT methodology, we identified sustainability criteria that meet the guidelines. We took two tracks, the first to find the preferences of Korean experts, and the other to check foreign cases. In all, 37 preliminary criteria were suggested to Korean experts and each criterion was scored, from between 1 and 3, in terms of relevance, possibility of real improvement, easiness of data collection, and preferences. We combined foreign cases and the results of a survey conducted in Korea and selected 12 core criteria and 10 additional criteria. After that, all the criteria were converted into indicators. The indicators were applied to a CDM project for case study. We chose the "Sihwa Tidal Power Project", which is currently the biggest tidal power plant in the world. Twelve core indicators and 3 additional indicators were applied. In order to weight each indicator, the 'analytical hierarchy process (AHP)' was used. A total of 30 experts were asked to suggest weights and 21 answered. Among them, only 14 respondents were proven to meet the consistency ratio. We analyzed the 14 responses through Expert Choice and the CDM project was scored (+)53.082. In addition, sensitivity analysis was undertaken with the result of (+)44.667 to (+)65.522. As a result of this study, it was proven that this project would contribute to the sustainable development of Korea.

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Target Word Selection Disambiguation using Untagged Text Data in English-Korean Machine Translation (영한 기계 번역에서 미가공 텍스트 데이터를 이용한 대역어 선택 중의성 해소)

  • Kim Yu-Seop;Chang Jeong-Ho
    • The KIPS Transactions:PartB
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    • v.11B no.6
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    • pp.749-758
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    • 2004
  • In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

Analysis on the Positional Accuracy of the Non-orthogonal Two-pair kV Imaging Systems for Real-time Tumor Tracking Using XCAT (XCAT를 이용한 실시간 종양 위치 추적을 위한 비직교 스테레오 엑스선 영상시스템에서의 위치 추정 정확도 분석에 관한 연구)

  • Jeong, Hanseong;Kim, Youngju;Oh, Ohsung;Lee, Seho;Jeon, Hosang;Lee, Seung Wook
    • Progress in Medical Physics
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    • v.26 no.3
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    • pp.143-152
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    • 2015
  • In this study, we aim to design the architecture of the kV imaging system for tumor tracking in the dual-head gantry system and analyze its accuracy by simulations. We established mathematical formulas and algorithms to track the tumor position with the two-pair kV imaging systems when they are in the non-orthogonal positions. The algorithms have been designed in the homogeneous coordinate framework and the position of the source and the detector coordinates are used to estimate the tumor position. 4D XCAT (4D extended cardiac-torso) software was used in the simulation to identify the influence of the angle between the two-pair kV imaging systems and the resolution of the detectors to the accuracy in the position estimation. A metal marker fiducial has been inserted in a numerical human phantom of XCAT and the kV projections were acquired at various angles and resolutions using CT projection software of the XCAT. As a result, a positional accuracy of less than about 1mm was achieved when the resolution of the detector is higher than 1.5 mm/pixel and the angle between the kV imaging systems is approximately between $90^{\circ}$ and $50^{\circ}$. When the resolution is lower than 1.5 mm/pixel, the positional errors were higher than 1mm and the error fluctuation by the angles was greater. The resolution of the detector was critical in the positional accuracy for the tumor tracking and determines the range for the acceptable angle range between the kV imaging systems. Also, we found that the positional accuracy analysis method using XCAT developed in this study is highly useful and will be a invaluable tool for further refined design of the kV imaging systems for tumor tracking systems.