• Title/Summary/Keyword: Map making

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Design of Emergency Notification Smart Farm Service Model based on Data Service for Facility Cultivation Farms Management (시설 재배 농가 관리를 위한 데이터 서비스 기반의 비상 알림 스마트팜 서비스 모델 설계)

  • Bang, Chan-woo;Lee, Byong-kwon
    • Journal of Advanced Technology Convergence
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    • v.1 no.1
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    • pp.1-6
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    • 2022
  • Since 2015, the government has been making efforts to distribute Korean smart farms. However, the supply is limited to large-scale facility vegetable farms due to the limitations of technology and current cultivation research data. In addition, the efficiency and reliability compared to the introduction cost are low due to the simple application of IT technology that does not consider the crop growth and cultivation environment. Therefore, in this paper, data analysis services was performed based on public and external data. To this end, a data-based target smart farm system was designed that is suitable for the situation of farms growing in facilities. To this end, a farm risk information notification service was developed. In addition, light environment maps were provided for proper fertilization. Finally, a disease prediction model for each cultivation crop was designed using temperature and humidity information of facility farms. Through this, it was possible to implement a smart farm data service by linking and utilizing existing smart farm sensor data. In addition, economic efficiency and data reliability can be secured for data utilization.

Performance Comparison of Autoencoder based OFDM Communication System with Wi-Fi

  • Shiho Oshiro;Takao Toma;Tomohisa Wada
    • International Journal of Computer Science & Network Security
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    • v.23 no.5
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    • pp.172-178
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    • 2023
  • In this paper, performance of autoencoder based OFDM communication systems is compared with IEEE 802.11a Wireless Lan System (Wi-Fi). The proposed autoencoder based OFDM system is composed of the following steps. First, one sub-carrier's transmitter - channel - receiver system is created by autoencoder. Then learning process of the one sub-carrier autoencoder generates constellation map. Secondly, using the plural sub-carrier autoencoder systems, parallel bundle is configured with inserting IFFT and FFT before and after the channel to configure OFDM system. Finally, the receiver part of the OFDM communication system was updated by re-learning process for adapting channel condition such as multipath channel. For performance comparison, IEEE802.11a and the proposed autoencoder based OFDM system are compared. For channel estimation, Wi-Fi uses initial long preamble to measure channel condition. but Autoencoder needs re-learning process to create an equalizer which compensate a distortion caused by the transmission channel. Therefore, this autoencoder based system has basic advantage to the Wi-Fi system. For the comparison of the system, additive random noise and 2-wave and 4-wave multipaths are assumed in the transmission path with no inter-symbol interference. A simulation was performed to compare the conventional type and the autoencoder. As a result of the simulation, the autoencoder properly generated automatic constellations with QPSK, 16QAM, and 64QAM. In the previous simulation, the received data was relearned, thus the performance was poor, but the performance improved by making the initial value of reception a random number. A function equivalent to an equalizer for multipath channels has been realized in OFDM systems. As a future task, there is not include error correction at this time, we plan to make further improvements by incorporating error correction in the future.

The development of the seismic fragility curves of existing bridges in Indonesia (Case study: DKI Jakarta)

  • Veby Citra Simanjuntak;Iswandi Imran;Muslinang Moestopo;Herlien D. Setio
    • Structural Monitoring and Maintenance
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    • v.10 no.1
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    • pp.87-105
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    • 2023
  • Seismic regulations have been updated from time to time to accommodate an increase in seismic hazards. Comparison of seismic fragility of the existing bridges in Indonesia from different historical periods since the era before 1990 will be the basis for seismic assessment of the bridge stock in Indonesia, most of which are located in earthquake-prone areas, especially those built many years ago with outdated regulations. In this study, seismic fragility curves were developed using incremental non-linear time history analysis and more holistically according to the actual strength of concrete and steel material in Indonesia to determine the uncertainty factor of structural capacity, βc. From the research that has been carried out, based on the current seismic load in SNI 2833:2016/Seismic Map 2017 (7% probability of exceedance in 75 years), the performance level of the bridge in the era before SNI 2833:2016 was Operational-Life Safety whereas the performance level of the bridge designed with SNI 2833:2016 was Elastic - Operational. The potential for more severe damage occurs in greater earthquake intensity. Collapse condition occurs at As = FPGA x PGA value of bridge Era I = 0.93 g; Era II = 1.03 g; Era III = 1.22 g; Era IV = 1.54 g. Furthermore, the fragility analysis was also developed with geometric variations in the same bridge class to see the effect of these variations on the fragility, which is the basis for making bridge risk maps in Indonesia.

An Attention-based Temporal Network for Parkinson's Disease Severity Rating using Gait Signals

  • Huimin Wu;Yongcan Liu;Haozhe Yang;Zhongxiang Xie;Xianchao Chen;Mingzhi Wen;Aite Zhao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2627-2642
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    • 2023
  • Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.

Development of underground facility information collection technology based on 3D precision exploration (3차원 정밀탐사 지하시설물 정보 수집 기술 개발)

  • Jisong RYU;Yonggu JANG
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.56-66
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    • 2023
  • Safety accidents are increasing, such as changes in groundwater levels due to construction work or natural influences, or ground cave-ins caused by soil runoff from old water supply and sewage pipes. In addition, underground facility management agencies must make efforts to improve the accuracy of underground information through continuous investigation and exploration in accordance with the Special Act on Enhanced Underground Safety Management. Accordingly, in this study, we defined the configuration of equipment and data processing method to collect 3D precise exploration underground facility information and developed 3D underground facility information collection technology to ensure accuracy of underground facilities. As a result of verifying the developed technology, the horizontal accuracy improved by an average of 6cm compared to the existing method, making it possible to acquire 3D underground facility information within the error range of the public survey work regulations.

Network analysis for assessing urban resilience from the perspective of urban flooding: case study of Seoul, Korea (도시침수 관점에서의 도시회복력 평가를 위한 네트워크 분석: 서울특별시 중심으로)

  • Park, HyungJun;Song, Sumin;Kim, DongHyun;Lee, Seung Oh
    • Journal of Korea Water Resources Association
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    • v.57 no.6
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    • pp.371-383
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    • 2024
  • The quantification methods and definitions of resilience vary and are studied across many fields. However, this diversity can lead to gaps in interpretation regarding the meaning and indicators of resilience, potentially having a negative impact on resilience assessments. Therefore, uniform standards for defining and quantifying resilience are essential. This study presented a definition of resilience and socio-structural evaluation methods of resilience through network analysis. Furthermore, through analyzing various definitions of resilience, the definition of resilience in the context of urban flooding was presented. Distinguishing between static and dynamic resilience, an evaluation method based on common attributes was proposed. Lastly, the economic effects of introducing resilience were analyzed using an inundation trace map. Future research on the secondary effects through standardized resilience assessments is expected to be widely utilized in decision-making stages within urban flood policies.

A Big Data Analysis to Prevent Elderly Solitary Deaths by High-risk Area Clusterization (노인 고독사 방지를 위한 빅데이터 기반 고독사 고위험 지역 탐지 연구)

  • Soyon Kim;Soo Hyung Kim;Bong Gyou Lee
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.5
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    • pp.177-182
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    • 2024
  • This study proposes a big data-based analytical method to detect high-risk areas for solitary deaths among the elderly in Seoul. The study categorizes and analyzes the risk factors of solitary deaths into demographic, health, economic, and socio-environmental factors. Using data collected from the Seoul Open Data Plaza and Public Data Portal, variables were generated and scatter plots were created using K-means clustering, followed by visual implementation through map creation. The analysis identified Jungnang-gu, Gangbuk-gu, Nowon-gu, Eunpyeong-gu, Gangseo-gu, and Gwanak-gu as the highest-risk areas. This study addresses the limitations of previous survey-based research through big data analysis. The findings are expected to enhance the efficiency of solitary death prevention programs and serve as a basis for informed decision-making in budget allocation across districts.

Establishment of the Suitability Class in Ginseng Cultivated Lands (인삼 재배 적지 기준 설정 연구)

  • Hyeon, Geun-Soo;Kim, Seong-Min;Song, Kwan-Cheol;Yeon, Byeong-Yeol;Hyun, Dong-Yun
    • Korean Journal of Soil Science and Fertilizer
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    • v.42 no.6
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    • pp.430-438
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    • 2009
  • An attempt was made to establish the suitability classes of lands for the cultivation of ginseng(Panax ginseng C. A. Meyer). For this study, the relationships between various soil characteristics and ginseng yields were investigated on altogether 450 ginseng fields (150 sites in paddy and 300 sites in upland), across Kangwon, Kyunggi, Chungbug, Chungnam, Jonbug and Kyungbug Provinces, where ginseng is widely cultivated. In the paddy fields, most influential properties of soil on the ginseng yields was found to be the drainage class. Texture of surface soil and available soil depths affected the ginseng yields to some extents. However, the topography, slope, and the gravel content were found not to affect the ginseng yields. In the uplands, the texture of surface soil was most influential and the topography, slope, and occurrence depth of hard-pan were least influential on the performance of the crop. Making use of multiple regression, by SAS, the contribution of soil morphological and physical properties such as, topography, surface soil texture, drainage class, slope, available soil depth, gravel content, and appearance depth of hard-pan, for the suitability of land for ginseng cultivation was analyzed. Based on the results of above analysis, adding up all of the suitability indices, land suitability classes for ginseng cultivation were proposed. On top of this, taking the weather conditions into consideration, suitability of land for ginseng cultivation was established in paddy field and in uplands. As an example, maps showing the distribution of suitable land for ginseng cultivation were drawn, adopting the land suitability classes obtained through current study, soil map, climate map, and GIS information, for Eumsung County, Chungbug Province. Making use of the information on the land suitability for ginseng cultivation obtained from current study, the suitability of lands currently under cultivation of ginseng was investigated. The results indicate that 74.0% of them in paddy field and 88.3% in upland are "highly suitable" and "suitable".

A Study for Planning Optimal Location of Solar Photovoltaic Facilities using GIS (GIS를 이용한 태양광시설 설치를 위한 적정지역 선정에 관한 연구)

  • Yun, Sung-Wook;Paek, Yee;Jang, Jae-Kyung;Choi, Duk-Kyu;Kang, Donghyeon;Son, Jinkwan;Park, Min-Jung;Kang, Suk-Won;Gwon, Jin-Kyung
    • Journal of Bio-Environment Control
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    • v.28 no.3
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    • pp.243-254
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    • 2019
  • With the recent accelerated policy-making and interests in new renewable energy, plans to develop and supply the new renewable energy have been devised across multiple regions in Korea. Solar energy, in particular, is being applied to small-scale power supply in provincial areas, as solar cells are used to convert solar energy into electric energy to produce electric power. Nonetheless, in the case of solar power plants, the need for a large stretch of land and considerable sum of financial support implies that the planning step should take into consideration the most suitable meteorological and geographical factors. In this study, the proxy variables of meteorological and geographical factors associated with solar energy were considered in analyzing the vulnerable areas regarding the photovoltaic power generation facility across the nation. GIS was used in the spatial analysis to develop a map for assessing the optimal location for photovoltaic power generation facility. The final vulnerability map developed in this study did not reveal any areas that exhibit vulnerability level 5 (very high) or 1 (very low). Jeollanam-do showed the largest value of vulnerability level 4 (high), while a large value of vulnerability level 3 (moderate) was shown by several administrative districts including Gwangju metropolitan city, Jeollabuk-do, Chungcheongbuk-do, and Gangwon-do. A value of vulnerability level 2 (low) was shown by the metropolitan cities including Daegu, Ulsan, and Incheon. When the 30 currently operating solar power plants were compared and reviewed, most were found to be in an area of vulnerability level 2 or 3, indicating that the locations were relatively suitable for solar energy. However, the limited data quantity for solar power plants, which is the limitation of this study, prevents the accuracy of the findings to be clearly established. Nevertheless, the significance of this study lies in that an attempt has been made to assess the vulnerability map for photovoltaic power generation facility targeting various regions across the nation, through the use of the GIS-based spatial analysis technique that takes into account the diverse meteorological and geographical factors. Furthermore, by presenting the data obtained for all regions across the nation, the findings of this study are likely to prove useful as the basic data in fields related to the photovoltaic power generation.

Visualizing the Results of Opinion Mining from Social Media Contents: Case Study of a Noodle Company (소셜미디어 콘텐츠의 오피니언 마이닝결과 시각화: N라면 사례 분석 연구)

  • Kim, Yoosin;Kwon, Do Young;Jeong, Seung Ryul
    • Journal of Intelligence and Information Systems
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    • v.20 no.4
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    • pp.89-105
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    • 2014
  • After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.