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The Empirical Study on University Campus Startup Space by IPA - Focused on satisfaction and importance analysis - (IPA분석을 통한 대학캠퍼스 창업공간 실증분석 - 만족도와 중요도 분석을 중심으로 -)

  • Jo, Hyeong-Jin;Lee, Yong-Hwan
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.20 no.4
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    • pp.13-20
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    • 2021
  • In the world, each country is preparing various policies to promote start-ups, and the Korean government is actively promoting policies to support start-ups and the national economy through technology-based start-ups for creating jobs. Recently, the number of start-up companies is on the rise. In particular, in accordance with the industrial structure transformation leading the 4th Industrial Revolution, technology-based start-ups are steadily growing based on knowledge-based services such as information and communication, science and technology service industry, and business support service industry. The purpose of this study is to find out whether the startup space provided by the university reflects the startup-friendly characteristics, and to investigate and analyze the satisfaction and requirements of the space required by the actual college campus startup space users to create a more efficient space configuration plan. Through this study, factors that should be considered first for universities in preparing startup spaces were derived for each space element. Therefore, it is necessary for university campuses to deeply recognize the importance of space provision among the future start-up support systems, and to improve them periodically through the consumers' satisfaction of the space in the construction and improvement of startup spaces.

Identification of 19 Species of Poisonous Plants from Jeju Island and Construction of a Database Using DNA-barcoding (DNA-barcoding을 이용한 제주도 자생 독성 식물 19종의 종 식별 및 데이터베이스 구축)

  • Kwon, Eunchae;Kim, Joo-Young;Chang, Miwha;Lee, Minji;Moon, Seohyun;Lee, Won-Hae
    • Korean Journal of Plant Resources
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    • v.35 no.2
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    • pp.346-361
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    • 2022
  • Food poisoning accidents caused by poisonous plants occur every year. As certain poisonous plants are mistaken for edible plants causing food poisoning, accurate species identification of poisonous plants is required. DNA barcodes suitable for species identification of poisonous plants and database that can be used for accurate species identification are necessary for their use in forensic cases. In this study, species identification of 19 poisonous plants native to Jeju Island using seven DNA barcodes (trnH-psbA, trnL-trnF, trnL intron, rbcL, matK, ITS1-ITS4, 18S rRNA) was performed to construct a database containing sequence information and DNA barcode universality. trnL-trnF barcode and ITS1-ITS4 barcode were the easiest markers for PCR amplification and sequence retrieval, and the combination of the two barcodes enabled single species identification in 18 out of 19 plants. Therefore, when an investigation of unknown poisonous plants is requested, combination of trnL-trnF and ITS1-ITS4 barcodes is considered as a primary marker for species identification. The database of recommended DNA barcodes for each poisonous plant presented in this study will be helpful in plants poisoning cases.

A Study on the Prediction of Rock Classification Using Shield TBM Data and Machine Learning Classification Algorithms (쉴드 TBM 데이터와 머신러닝 분류 알고리즘을 이용한 암반 분류 예측에 관한 연구)

  • Kang, Tae-Ho;Choi, Soon-Wook;Lee, Chulho;Chang, Soo-Ho
    • Tunnel and Underground Space
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    • v.31 no.6
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    • pp.494-507
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    • 2021
  • With the increasing use of TBM, research has recently been conducted in Korea to analyze TBM data with machine learning techniques to predict the ground in front of TBM, predict the exchange cycle of disk cutters, and predict the advance rate of TBM. In this study, classification prediction of rock characteristics of slurry shield TBM sites was made by combining traditional rock classification techniques and machine learning techniques widely used in various fields with machine data during TBM excavation. The items of rock characteristic classification criteria were set as RQD, uniaxial compression strength, and elastic wave speed, and the rock conditions for each item were classified into three classes: class 0 (good), 1 (normal), and 2 (poor), and machine learning was performed on six class algorithms. As a result, the ensemble model showed good performance, and the LigthtGBM model, which showed excellent results in learning speed as well as learning performance, was found to be optimal in the target site ground. Using the classification model for the three rock characteristics set in this study, it is believed that it will be possible to provide rock conditions for sections where ground information is not provided, which will help during excavation work.

Research on Trends in International Research Cooperation through Analysis of International Research Cooperation Books (국내외 단행본 분석을 통한 국제연구협력 동향 연구)

  • Noh, Younghee;Kwak, Woojung
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.35-44
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    • 2022
  • In this study, we tried to confirm the characteristics of books published on the topic of international cooperation, what kind of international cooperation-related research is being conducted through this book, and what are the main contents of international cooperation. In order to achieve this research purpose, we conducted data construction, statistical analysis, and text mining based on textom in international research cooperation at home and abroad. As a result of the study, it can be seen that there has been a particularly high interest in international research and international cooperation since the 2010s. Through this, it was found that he is interested in development, economy, technology, development, region, and relations and wants to promote development. In addition, topics such as environment, trade, education, and society appeared, and interest in international research cooperation centered on environment, trade, and education was high, was found to have a high influence on society as a whole. Through this study, we find the research significance in that it can serve as a basic research to confirm the characteristics of some national and public research institutes participating in international research cooperation, and that it confirms the trend of participating in international research cooperation in a relatively specific type of institution. can see.

Comparison of performance of automatic detection model of GPR signal considering the heterogeneous ground (지반의 불균질성을 고려한 GPR 신호의 자동탐지모델 성능 비교)

  • Lee, Sang Yun;Song, Ki-Il;Kang, Kyung Nam;Ryu, Hee Hwan
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.24 no.4
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    • pp.341-353
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    • 2022
  • Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

A study on performance improvement considering the balance between corpus in Neural Machine Translation (인공신경망 기계번역에서 말뭉치 간의 균형성을 고려한 성능 향상 연구)

  • Park, Chanjun;Park, Kinam;Moon, Hyeonseok;Eo, Sugyeong;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.12 no.5
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    • pp.23-29
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    • 2021
  • Recent deep learning-based natural language processing studies are conducting research to improve performance by training large amounts of data from various sources together. However, there is a possibility that the methodology of learning by combining data from various sources into one may prevent performance improvement. In the case of machine translation, data deviation occurs due to differences in translation(liberal, literal), style(colloquial, written, formal, etc.), domains, etc. Combining these corpora into one for learning can adversely affect performance. In this paper, we propose a new Corpus Weight Balance(CWB) method that considers the balance between parallel corpora in machine translation. As a result of the experiment, the model trained with balanced corpus showed better performance than the existing model. In addition, we propose an additional corpus construction process that enables coexistence with the human translation market, which can build high-quality parallel corpus even with a monolingual corpus.

A Study on the Technological Priorities of Manufacturing and Service Companies for Response to the 4th Industrial Revolution and Transformation into a Smart Company (4차 산업혁명 대응과 스마트 기업으로의 변화를 위한 제조 및 서비스 기업의 기술적용 우선순위에 대한 연구)

  • Park, Chan-Kwon;Seo, Yeong-Bok
    • Journal of Convergence for Information Technology
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    • v.11 no.4
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    • pp.83-101
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    • 2021
  • This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

Test Set Construction for Quality Evaluation of NAK Portal's Search Service and the Status Analysis (국가기록포털 검색서비스 품질 점검을 위한 평가셋 구축 및 현황 분석)

  • Jeong Ho, Na;Hyeon-Gi, So;Gyung Rok, Yeom;Jung-Ok, Lee;Hyo-Jung, Oh
    • Journal of Korean Society of Archives and Records Management
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    • v.22 no.4
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    • pp.25-43
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    • 2022
  • The ultimate record management's purpose is preservation and utilization. However, the National Archives of Korea (NAK)s Portal has problems such as search system aging and search tools dualization. As a result, the users' search satisfaction is not satisfied, and the improvement demand increases. This study aimed to evaluate the NAK's search quality as a preliminary study for NAK search system advancement. To this end, we analyzed the current status of CAMS and NAK's Portal. Then, we established the test sets and evaluated the NAK's Portal quality from the user's point of view. Evaluation results were analyzed using Precision, Recall, F-score, and MRR. The analysis results showed that the overall search performance was low, particularly in the "advanced subject search," which showed low performance in Precision, Recall, and MRR. Thus, improvement is urgently needed. The test sets established for this study are expected to be used as a basis for objectively measuring the improvement of the search performance after the NAK search system advancement.

Measures to improve the DEM using SAR images in the river corridor (합성개구레이더 영상을 이용한 하천내 DEM 개선 방안)

  • Kim, Joo-Hun;Noh, Hui-Seong
    • Journal of Korea Water Resources Association
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    • v.55 no.11
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    • pp.913-922
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    • 2022
  • The purpose of this research is to propose the measurement of improving DEM by using the water surface range of SAR image analysis for river corridors and to suggest the construction of satellite-based 3D river spatial information of inaccessible regions such as North Korea. For this research, it has been progressed from the accessible area, watershed of Namgang river, the branch of Nakdonggang river. The satellite image was collected from SAR satellite image data for a year in 2021 which was provided by ESA from Sentinel-1A/B data and extracted from the seasonal water surface area. Ground gauge water level was collected from hourly intervals data by WAMIS. The DEM was improved by analysis of the river altitude of water surface area change by the combination of the ground water level of minimum to maximum water surface area data extracted from SAR image analysis. After the improvement of DEM, the altitude of the river varied that it is defined to comprise more natural form of river DEM than the existing DEM. The correction validation of improvement DEM was necessary in field survey elevation data; however, the correction validation was not progressed due to the absence of the data. Although, the purpose of this research is to provide the improvement of DEM by using the analyzed water surface by existing DEM data and SAR image analysis. After the progression of additional correction validation research, we would plan to examine the application in other places and to progress the additional methodological research to apply in inaccessible and unmeasured area including the North Korea.

The Effect of Non-Face-to-Face Class on Core Competencies of College Students in Clothing Major: Focused on Application Case of Flipped Learning (언택트 시대에 비대면 수업이 의류학 분야 대학생의 핵심역량 수준에 미치는 영향: 플립러닝 기법의 적용 사례를 중심으로)

  • Kim, Tae-Youn
    • Journal of Korean Home Economics Education Association
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    • v.34 no.1
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    • pp.151-165
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    • 2022
  • The aim of this study is to examine the effectiveness of non-face-to-face classes conducted due to the COVID-19 crisis. In order to achieve this goal, a non-face-to-face class with flipped learning was applied in one subject of clothing major held at 'S' University in Cheongju, Korea. In addition, this study tried to analyze the differences between pre- and post-non-face-to-face classes in problem analysis ability, resource/information/technology literacy, convergent thinking ability as core competencies, and overall learning satisfaction. As a result, after participating in the non-face-to-face class in which the flipped learning was applied, the students recognized that their abilities improved in the three problem-solving competency sub-areas, and their overall learning satisfaction also increased. The effectiveness of non-face-to-face classes in the field of clothing and fashion has been mainly measured in fashion design and clothing construction courses. However, based on the results of this study, it can be suggested that non-face-to-face classes in a theory-oriented lecture-type class can be effective methods for improving students' core competencies such as problem-solving skills if teaching-learning methods such as flipped learning are applied. Therefore, the results of this study will be useful data for designing differentiated non-face-to-face class strategies in a theory-oriented lecture-type class to improve the core competencies of college students.