• Title/Summary/Keyword: information link

Search Result 3,902, Processing Time 0.029 seconds

A Study on Content Analysis and Types of Forest Education According to the 2015 Revised Curriculum (2015 개정 초등교육과정 내 산림교육 내용분석 및 유형화 연구)

  • Choi, Seon Hye;Ha, Si Yeon
    • Journal of Korean Society of Forest Science
    • /
    • v.110 no.4
    • /
    • pp.689-710
    • /
    • 2021
  • The purpose of this study was to analyze contents of the elementary school textbooks on 'Forest Education' based on the 2015 revised curriculum. This study is designed to determine the status of forest educationrelated content in the curriculum. Thetypesofforesteducationintextbooksweredividedintoanalysis. In addition, the standards of achievement of the curriculum were analyzed into the areas of forest education curriculum to determine the similarities between the curriculum and the achievement of forest education. This study shows that, first, the field of knowledge in forest education was included in all subjects and grades except mathematics. It noted that the curriculum includes areas of knowledge that directly convey knowledge related to forest education. This showed that the forest education knowledge area is linked to various courses. Second, the types of forest education included in the curriculum appeared differently depending on age. In the lower grades, there was the most information on the tools and sensibilities of forest education, and in the higher grades, the more knowledge and value-related areas were addressed. As the school year increases, so do forest education levels. Third, when analyzing the achievement criteria in the curriculum, the curriculum achievement criteria included key points in forest education. Thus, this study confirmed the link between the curriculum and forest education.

Association between Relative Preference for Vegetables and Meat and Cancer Incidence in Korean Adults: A Nationwide Population-based Retrospective Cohort Study (채소 및 육류 섭취의 상대적인 선호도와 암 발생의 연관성: 국민건강보험공단 국민건강정보자료 활용)

  • Yie, Ga-Eun;Kim, An Na;Cho, Hyun Jeong;Kang, Minji;Moon, Sungji;Kim, Inah;Ko, Kwang-Pil;Lee, Jung Eun;Park, Sue K.
    • Korean Journal of Community Nutrition
    • /
    • v.26 no.3
    • /
    • pp.211-227
    • /
    • 2021
  • Objectives: We aimed to examine the association between the relative preference for vegetables and meat and cancer incidence, in a population-based retrospective cohort in Korea. Methods: We included 10,148,131 participants (5,794,124 men; 4,354,007 women) who underwent national health screening between 2004 and 2005 from the National Health Information Database of the National Health Insurance Service (NHIS-NHID). Participants were asked whether they preferred consuming 1) vegetables more often, 2) both vegetables and meat or 3) meat more often. Participants were followed up to Dec. 31, 2017. All cancer and eighteen common cancer cases were identified through the code from the International Classification of Diseases, 10th revision. We estimated sex-specific relative risks and 95% confidence intervals, adjusting for age, body mass index, alcohol consumption, smoking, physical activity, and income level. Results: During an average follow-up of 12.4 years, 714,170 cancer cases were documented. In men, consuming meat more often was associated with lower risk of esophageal, liver, and stomach cancers, but higher risk of lung and kidney cancers. Consuming both vegetables and meat was associated with higher risk of prostate cancer, but with lower risk of esophageal, liver, and stomach cancers in men. In women, consuming meat more often was associated with a higher risk of colorectal cancer and breast, endometrial, and cervical cancers diagnosed before the age of 50. Consuming both vegetables and meat was associated with lower risk of liver cancer in women. Conclusions: Our study suggests a potential link between vegetable and meat intake and cancer incidence in the Korean population. Further investigation on the association between the intake of specific types of vegetables and meat and cancer risk in Korean prospective cohort studies is needed.

Archival Appraisal and Classification of the Official Documents of the Government-General of Choson Related to Urban District Planning (조선총독부 시가지계획 관련 공문서의 분류와 평가)

  • Lee, Song-Soon
    • The Korean Journal of Archival Studies
    • /
    • no.14
    • /
    • pp.53-89
    • /
    • 2006
  • The historical value of the official documents of the Government General of Choson preserved as permanent archived documents has long been recognized. However, the fact that only parts of the overall documents were preserved and that the contents of the existing documents is not uniform, results in many problems regarding the evaluation and usage of such documents as archives. This study attempts to appraise a series of archival documents related to urban district planning compiled during the colonial era. Although limited in terms of its applicability to the development of an evaluation method for the official documents of the Government General of Choson as a whole, by evaluating the value of these documents based on the background of the documents produced during the Government General of Choson's implementation of its colonial policy, this study provides an important indicator of how such documents should be used in the future. On the other hand, the assessment of historical records such as the official documents of the Government General of Choson which have already been designated and preserved as permanent archived documents should not be perceived as an attempt to dispose of the relevant documents. With regard to the appraisal of historical archives, it is necessary to consider measures to link such documents with existing databases or information contents in order to heighten access to and usage of the relevant documents in the future.

Analysis of Spatial Trip Regularity using Trajectory Data in Urban Areas (도시부 경로자료를 이용한 통행의 공간적 규칙성 분석)

  • Lee, Su jin;Jang, Ki tae
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.17 no.6
    • /
    • pp.96-110
    • /
    • 2018
  • As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

Development of Indoor Navigation System based on the Augmented Reality in Subway Station (증강현실 기반 지하철 역사의 보행안내 시스템)

  • KIM, Wongil;LIM, Guk hyun;KIM, Hyun
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.18 no.1
    • /
    • pp.43-55
    • /
    • 2019
  • Smart phone based navigation applications are very useful in everyday life. Cost-effective and user friendly navigation can be provided to the user by many applications available in market. Using the Smart phone these navigation applications provide accurate navigation for outdoor locations. But providing an accurate navigation underground space such as subway station is still a challenge. It is hence more convenient and appropriate for mobility services if the visitors could simply view the guidance of the subway station on their mobile phone, wherever and whenever it is needed. This study develops a algorithm for indoor navigation with the help of Augmented Reality(AR) and QR marker code from the entrance to the train platform for users. This indoor navigation uses AR and QR maker codes for two purposes: to provide the user link to the subway station location and to provide the current guidance details to the user. This Smart phone algorithm that uses a smart phone optical tool to decode the QR marker to determine the location information and provide guidance to the AR without indoor Maps. This algorithm also provides a module to guide mobility vulnerable to the Barrier Free route to destination.

Establishment and Application of Subway Line Chain OD Using SSA (SSA를 이용한 지하철 노선 Chain OD 구축 및 활용)

  • Lee, Mee Young;Nam, Doohee
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.18 no.5
    • /
    • pp.100-111
    • /
    • 2019
  • The existing selected station analysis (SSA) method analyzes the link transfer mode data between origin and destination of individuals passing through stations from a microscopic standpoint. As such, existing SSA is insufficient as it uses integrated analysis using macroscopic data such as subway lines. This research builds a line chain OD based on path search of individual passenger's movement through the subway, and explores means to utilize the findings. First, a method is proposed that searches the traversed subway path from the linked passage modes that the passenger uses and applies the results to SSA line analysis. Compared to the existing SSA, this method provides for analysis of commonly conflicting features such as the line on which the station is passed, and the stations included on the line thanks to the presence of complete information of the individual passenger's traversed path. It also allows for integrated observation of the line chain OD that approaches a certain station. For enhanced understanding, Seoul Metro Line 9 is used as a case study to demonstrate the integrated formulation concept of line chain OD centered around a certain station as well as the macroscopic features of the traversed path that approaches stations included on the line.

Analysis of E2E Latency for Data Setup in 5G Network (5G 망에서 Data Call Setup E2E Latency 분석)

  • Lee, Hong-Woo;Lee, Seok-Pil
    • Journal of Internet Computing and Services
    • /
    • v.20 no.5
    • /
    • pp.113-119
    • /
    • 2019
  • The key features of 5G mobile communications recently commercialized can be represented by High Data Rate, Connection Density and Low Latency, of which the features most distinct from the existing 4G will be low Latency, which will be the foundation for various new service offerings. AR and self-driving technologies are being considered as services that utilize these features, and 5G Network Latency is also being discussed in related standards. However, it is true that the discussion of E2E Latency from a service perspective is much lacking. The final goal to achieve low Latency at 5G is to achieve 1ms of air interface based on RTD, which can be done through Ultra-reliable Low Latency Communications (URLLC) through Rel-16 in early 20 years, and further network parity through Mobile Edge Computing (MEC) is also being studied. In addition to 5G network-related factors, the overall 5G E2E Latency also includes link/equipment Latency on the path between the 5G network and the IDC server for service delivery, and the Processing Latency for service processing within the mobile app and server. Meanwhile, it is also necessary to study detailed service requirements by separating Latency for initial setup of service and Latency for continuous service. In this paper, the following three factors were reviewed for initial setup of service. First, the experiment and analysis presented the impact on Latency on the Latency in the case of 1 Data Lake Setup, 2 CRDX On/Off for efficient power, and finally 3H/O on Latency. Through this, we expect Low Latency to contribute to the service requirements and planning associated with Latency in the initial setup of the required services.

IoT data processing techniques based on machine learning optimized for AIoT environments (AIoT 환경에 최적화된 머신러닝 기반의 IoT 데이터 처리 기법)

  • Jeong, Yoon-Su;Kim, Yong-Tae
    • Journal of Industrial Convergence
    • /
    • v.20 no.3
    • /
    • pp.33-40
    • /
    • 2022
  • Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

A Study on the Method for Managing Hazard Factors to Support Operation of Automated Driving Vehicles on Road Infrastructure (자율주행시스템 운행지원을 위한 도로 인프라 측면의 위험 요소 관리 방안)

  • Kim, Kyuok;Choi, Jung Min;Cho, Sun A
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.21 no.2
    • /
    • pp.62-73
    • /
    • 2022
  • As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

Deep Learning-Based Prediction of the Quality of Multiple Concurrent Beams in mmWave Band (밀리미터파 대역 딥러닝 기반 다중빔 전송링크 성능 예측기법)

  • Choi, Jun-Hyeok;Kim, Mun-Suk
    • Journal of Internet Computing and Services
    • /
    • v.23 no.3
    • /
    • pp.13-20
    • /
    • 2022
  • IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.