• Title/Summary/Keyword: 공간-기반 주의

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Analyzing Self-Introduction Letter of Freshmen at Korea National College of Agricultural and Fisheries by Using Semantic Network Analysis : Based on TF-IDF Analysis (언어네트워크분석을 활용한 한국농수산대학 신입생 자기소개서 분석 - TF-IDF 분석을 기초로 -)

  • Joo, J.S.;Lee, S.Y.;Kim, J.S.;Kim, S.H.;Park, N.B.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.23 no.1
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    • pp.89-104
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    • 2021
  • Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

Calculation of Soil Moisture and Evapotranspiration for KLDAS(Korea Land Data Assimilation System) using Hydrometeorological Data Set (수문기상 데이터 세트를 이용한 KLDAS(Korea Land Data Assimilation System)의 토양수분·증발산량 산출)

  • PARK, Gwang-Ha;LEE, Kyung-Tae;KYE, Chang-Woo;YU, Wan-Sik;HWANG, Eui-Ho;KANG, Do-Hyuk
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.65-81
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    • 2021
  • In this study, soil moisture and evapotranspiration were calculated throughout South Korea using the Korea Land Data Assimilation System(KLDAS) of the Korea-Land Surface Information System(K-LIS) built on the basis of the Land Information System (LIS). The hydrometeorological data sets used to drive K-LIS and build KLDAS are MERRA-2(Modern-Era Retrospective analysis for Research and Applications, version 2) GDAS(Global Data Assimilation System) and ASOS(Automated Synoptic Observing System) data. Since ASOS is a point-based observation, it was converted into grid data with a spatial resolution of 0.125° for the application of KLDAS(ASOS-S, ASOS-Spatial). After comparing the hydrometeorological data sets applied to KLDAS against the ground-based observation, the mean of R2 ASOS-S, MERRA-2, and GDAS were analyzed as temperature(0.994, 0.967, 0.975), pressure(0.995, 0.940, 0.942), humidity (0.993, 0.895, 0.915), and rainfall(0.897, 0.682, 0.695), respectively. For the hydrologic output comparisons, the mean of R2 was ASOS-S(0.493), MERRA-2(0.56) and GDAS (0.488) in soil moisture, and the mean of R2 was analyzed as ASOS-S(0.473), MERRA-2(0.43) and GDAS(0.615) in evapotranspiration. MERRA-2 and GDAS are quality-controlled data sets using multiple satellite and ground observation data, whereas ASOS-S is grid data using observation data from 103 points. Therefore, it is concluded that the accuracy is lowered due to the error from the distance difference between the observation data. If the more ASOS observation are secured and applied in the future, the less error due to the gridding will be expected with the increased accuracy.

Report on Extended Leak-Off Test Conducted During Drilling Large Diameter Borehole (국내 대구경 시추공 굴진 중 Extended Leak-Off Test 수행 사례 보고)

  • Jo, Yeonguk;Song, Yoonho;Park, Sehyeok;Kim, Myung Sun;Park, In-Hwa;Lee, Changhyun
    • Tunnel and Underground Space
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    • v.32 no.5
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    • pp.285-297
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    • 2022
  • We report results of Extended Leak-Off Test (XLOT) conducted in a large diameter borehole, which is drilled for installation of deep borehole geophysical monitoring system to monitor micro-earthquakes and fault behavior of major fault zones in the southeastern Korean Peninsula. The borehole was planned to secure a final diameter of 200 mm (or more) at a depth of ~1 km, with 12" diameter wellbore to intermediate depths, and 7-7/8" (~200 mm) to the bottom hole depth. We drilled first the 12" borehole to approximately 504 m deep and installed American Petroleum Institute standard 8-5/8" casing, then annulus between the casing and bedrock was fully cemented. XLOT was carried out for several purposes such as confirming casing and cementing integrity, measuring rock stress states. To that end, we drilled additional 4 m long open hole interval to directly inject water and pressurize into the rock mass using the upper API casings. During the XLOT, flow rates and interval pressures were recorded in real time. Based on the logs we tried to analyze hydraulic conductivity of the test interval.

A Study on the Potential Use of ChatGPT in Public Design Policy Decision-Making (공공디자인 정책 결정에 ChatGPT의 활용 가능성에 관한연구)

  • Son, Dong Joo;Yoon, Myeong Han
    • Journal of Service Research and Studies
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    • v.13 no.3
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    • pp.172-189
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    • 2023
  • This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

Evaluation for applicability of river depth measurement method depending on vegetation effect using drone-based spatial-temporal hyperspectral image (드론기반 시공간 초분광영상을 활용한 식생유무에 따른 하천 수심산정 기법 적용성 검토)

  • Gwon, Yeonghwa;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.235-243
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    • 2023
  • Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

Study of the rise and the characteristic of 'Hyangto Gakeuk' - focusing on the Composer Ahn Ki-Young's works (근대 '향토가극'의 형성과 특질 연구 - 안기영 작곡 가극 작품을 중심으로 -)

  • Yoo, In Gyeong
    • (The) Research of the performance art and culture
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    • no.19
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    • pp.221-280
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    • 2009
  • This thesis is a study of the rise and the characteristic of 'Hyangto Gakeuk(literally Song drama of the country or local music drama)' in the Early 1940s. During the colonial period, there were attempts to incorporate traditional Korean music elements with Western operatic form. This type of music drama with librettos based on traditional tales came to be known as 'Hyangto Gakeuk'. Mostly 'Hyangto Gakeuk' has led this effort under the director Seo Hang-Suk, the composer Ahn Ki-Young and the lyricist Seol Eui-sik. In the first chapter, the study aims at arranging the performance history of 'Hyangto Gakeuk' composed by Ahn Ki-Young. Also, the study examined representative works after classifying 'Hyangto Gakeuk' performed by Lamila Music Drama Troupe, and Bando Music Drama Troupe. There is significant meaning to evaluate 'Hyangto Gakeuk' in the history of Korean music drama through this analysis of the performance history. In the second chapter, I will analyze with representative works composed by Ahn Ki-Young, a pioneer in the Korean art song. He tried to create the music that held the nationalism and tradition. His works which were called 'Kageuk' laid down the foundation of Korean original operatic style. This study demonstrated characteristics of 'Hyangto Gakeuk' as 'the beginning' in modern musical drama history and its effects on Korean musical drama developments. Namely, 'Hyangto Gakeuk' based on Korean traditions can be seen as examples of original modern musical in Korea. Practically, study on all the aspects of performance not only text generally studied, dramaturgy and criticism, but also performance concept and intention of creators in early period.

Classification of Carbon-Based Global Marine Eco-Provinces Using Remote Sensing Data and K-Means Clustering (K-Means Clustering 기법과 원격탐사 자료를 활용한 탄소기반 글로벌 해양 생태구역 분류)

  • Young Jun Kim;Dukwon Bae;Jungho Im ;Sihun Jung;Minki Choo;Daehyeon Han
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.1043-1060
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    • 2023
  • An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

Status and Improvement of Metropolitan Government Urban Agriculture Ordinances for the Enhancement of Multifunctionality in Urban Agriculture (도시농업의 다원적 기능 활성화를 위한 광역지방자치단체 도시농업 조례 현황 및 개선 방향)

  • Ji-Won Choe;Choong-Hyeon Oh
    • Korean Journal of Environment and Ecology
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    • v.38 no.1
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    • pp.90-107
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    • 2024
  • This study analyzed the status of urban agricultural regulation of metropolitan governments on supporting multi-dimensional values to suggest a direction for improving urban agriculture regulations. Moreover, a Delphi survey was conducted to derive ways to identify improvement opportunities for functions that showed relatively insufficient support for urban agricultural regulations. As a result of the study, 12 out of 17 metropolitan governments and 116 of 226 municipalities have enacted urban agricultural regulations. However, the enactment of urban agricultural regulations has generally declined since 2011. Analysis of the contents of the urban agricultural regulations showed that they focused on matters relating to the creation and expansion of the foundation of urban agriculture. Among the multi-dimensional values of urban agricultural regulations, the foundation for supporting the securing of green spaces and utilizing food production functions was most widely available. On the other hand, the foundation for support of resource recycling, healing and health, social welfare, economic imbalance mitigation, and job creation functions has been shown to be relatively insufficient. A Delphi survey conducted to determine potential measures to improve urban agricultural regulations to support these functions found that 17 of the 18 ordinance improvement measures were valid. Therefore, to revitalize the multi-dimensional values of urban agriculture, it is first necessary to enact new ordinances. Also, to revitalize the multi-dimensional values of urban agriculture evenly, it is necessary to revise the ordinances to include resource recycling, healing and health, social welfare, mitigation of economic imbalances, and job creation functions. In this process, the development of urban agriculture technology, legal review of various urban farming spaces, and fostering of industries related to urban agriculture are necessary. Above all, steady interest in the multi-dimensional values of urban agriculture and the efforts of local governments to foster urban agriculture must be supported.

End to End Model and Delay Performance for V2X in 5G (5G에서 V2X를 위한 End to End 모델 및 지연 성능 평가)

  • Bae, Kyoung Yul;Lee, Hong Woo
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.107-118
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    • 2016
  • The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

Clustering Method based on Genre Interest for Cold-Start Problem in Movie Recommendation (영화 추천 시스템의 초기 사용자 문제를 위한 장르 선호 기반의 클러스터링 기법)

  • You, Tithrottanak;Rosli, Ahmad Nurzid;Ha, Inay;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.57-77
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    • 2013
  • Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.