• Title/Summary/Keyword: navigation analysis

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A Study on Predictive Traffic Information Using Cloud Route Search (클라우드 경로탐색을 이용한 미래 교통정보 예측 방법)

  • Jun Hyun, Kim;Kee Wook, Kwon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.33 no.4
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    • pp.287-296
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    • 2015
  • Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

Design and Implementation of OASIS Considering Web Accessibility (웹 접근성을 고려한 전통의학정보포털 설계 및 구현)

  • Han, Jeong-Min;Jang, Hyun-Chul;Kim, Jin-Hyun;Yea, Sang-Jun;Kim, Sang-Kyun;Kim, Chul;Song, Mi-Young
    • Journal of Information Management
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    • v.41 no.4
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    • pp.187-204
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    • 2010
  • This study shows evaluation of how much OASIS meets "the korean web content accessibility guidelines" and analysis of some of the accessibility problems and their solutions in OASIS(Oriental Medicine Advanced Searching Integrated System) which is the only web site that offers papers and project information related to Traditional Medicine in Korea. The evaluation criteria to determine if OASIS is accessible is classified into four sub items; Perceivable - if information and user interface components is presentable to users in ways they can perceive, Operable - if user interface components and navigation are operable, Understandable - if information and the operation of user interface are understandable, Robust - if content is robust enough that it can be interpreted reliably by a wide variety of user agents, including assistive technologies. Based on the measured results, OASIS has just been redesigned and implemented in more accessible and effective way. OASIS that improves web accessibility for the disabled is expected to help them study oriental medicine more easily and conveniently by providing equal access and equal opportunity to use the web.

Analysis for Accuracies of Position Fix by GPS in Kusan Area (군산지역에서의 GPS측위정도 해석)

  • LEE Won-Woo;SHIN Hyeong-Il;LEE Dae-Jae
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.26 no.3
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    • pp.250-257
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    • 1993
  • The Global Positioning System(GPS) is a worldwide radio navigation system based on satellite technology. Signal availability and accuracy of GPS are subject to change due to an incomplete constellation and operational test activities. In order to analyze the signal availability and accuracy of GPS, we made an experiment on this system in Kunsan during April 6, 7, 9, 10, 1992. The results obtained are summarized as follows: 1. It was possible to avail the GPS system almost 24 hours per day, but sometimes it was impossible to obtain the GPS signal 2 or 3 times per day and its total time was at the most an hour. 2. By using satellite almanac, we also could calculate PDOP(HDOP) and forecast signal availability. And the mean positional error was $37.9{\sim}73.6m$ and standard deviation was $37.4{\sim}133.1m$. The positional error almost coincided with PDOP(HDOP). 3. The mean positional error of 3D was less than that of 2D. And the altitude error in 3D was about $56{\sim}74m$ and its standard deviation was about $65{\sim}93m$.

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Estimation Model for Freight of Container Ships using Deep Learning Method (딥러닝 기법을 활용한 컨테이너선 운임 예측 모델)

  • Kim, Donggyun;Choi, Jung-Suk
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.5
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    • pp.574-583
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    • 2021
  • Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.

A Study on Motion Response of Small Fishing Vessels According to Various Tonnage in Regular Waves (소형어선의 크기에 따른 규칙파 중 운동응답 특성에 관한 연구)

  • Im, Nam-Kyun;Lee, Sang-Min
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.27 no.6
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    • pp.832-838
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    • 2021
  • Recently, reports of marine accidents of small fishing vessels less than 10 tons have been increasing. In this study, the characteristics of the motion response in regular waves were analyzed using computations for these ships. Small vessels less than 10 tons are classified by size and used for marine accident investigations. Therefore, the motion response analysis was performed on three small fishing vessels of different sizes. In the case of the head sea, it was confirmed that as the speed of the vessel increased in the long wavelength region, the motion responses of heave and pitch became large. The motion response of the smallest 3-ton fishing vessel was greater than that of the other sizes of fishing vessels. The maximum value of the roll motion shifted to the long wavelength region as the speed gradually increased in the bow sea, regardless of the size of the ship. In all the three small fishing vessels, it was found that the roll motion was the greatest at 15 knots, the highest speed in both bow and beam seas. When sailing in the head sea and bow sea conditions, lowering the speed is one of the effective approaches to reduce the effects of the vertical and lateral plane motions. The roll motion caused by the beam wave showed a tendency to increase rapidly only at a specific wavelength regardless of the speed and the size of the vessel. It was confirmed that the roll motion was significantly reduced with forward speed in the stern wave compared to the bow wave. As there is a specific region where the maximum value of the hull motion response appears depending on the size and speed of the ship, an operation method that can minimize the effect of this motion should be considered and implemented.

Comparative Analysis of CNN Deep Learning Model Performance Based on Quantification Application for High-Speed Marine Object Classification (고속 해상 객체 분류를 위한 양자화 적용 기반 CNN 딥러닝 모델 성능 비교 분석)

  • Lee, Seong-Ju;Lee, Hyo-Chan;Song, Hyun-Hak;Jeon, Ho-Seok;Im, Tae-ho
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.59-68
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    • 2021
  • As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

Integration Application of Node-Link Data Using Open LR Method (Open LR 기법을 이용한 노드-링크 데이터의 통합활용 방안에 관한 연구)

  • Kwon, Tae Ho;Choi, Yun-Soo
    • Journal of the Korean Institute of Gas
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    • v.25 no.5
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    • pp.78-87
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    • 2021
  • This paper analyzes the range and attributes of the traffic information service between domestic public institutions and private companies, and suggests the possibility of joint application of node-link information for each company and the possibility of joint use of private traffic information. For this purpose, the present condition and attributes of domestic and foreign traffic information node-links (link length, node ID number, U-turn information, lane information, left turn information, right turn information, etc.) were analyzed. The analysis targets, the node-link of the national standard node and the two companies were analyzed. The area of the experiment was selected in Jongno-gu, Seoul, where standard-link information is complex, traffic volume is high, and various standard-links exist. The experiment was conducted by comparing and analyzing the traffic information attributes of three types of node-links and performing node-links overlapping matching (utilizing encoding_decoding method), and the possibility of matching node-links and attributes of different specifications was analyzed using Open LR technique.

Retrieval Biases Analysis on Estimation of GNSS Precipitable Water Vapor by Tropospheric Zenith Hydrostatic Models (GNSS 가강수량 추정시 건조 지연 모델에 의한 복원 정밀도 해석)

  • Nam, JinYong;Song, DongSeob
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.4
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    • pp.233-242
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    • 2019
  • ZHD (Zenith Hydrostatic Delay) model is important parameter in estimating of GNSS (Global Navigation Satellite System) PWV (Precipitable Water Vapor) along with weighted mean temperature. The ZWD (Zenith Wet Delay) is tend to accumulate the ZHD error, so that biases from ZHD will be affected on the precision of GNSS PWV. In this paper, we compared the accuracy of GNSS PWV with radiosonde PWV using three ZHD models, such as Saastamoinen, Hopfield, and Black. Also, we adopted the KWMT (Korean Weighted Mean Temperature) model and the mean temperature which was observed by radiosonde on the retrieval processing of GNSS PWV. To this end, GNSS observation data during one year were processed to produce PWVs from a total of 5 GNSS permanent stations in Korea, and the GNSS PWVs were compared with radiosonde PWVs for the evaluating of biases. The PWV biases using mean temperature estimated by the KWMT model are smaller than radiosonde mean temperature. Also, we could confirm the result that the Saastamoinen ZHD which is most used in the GNSS meteorology is not valid in South Korea, because it cannot be exclude the possibility of biases by latitude or height of GNSS station.

Development of a Web-based User Experience Certification System based on User-centered System Design Approach (사용자 중심의 웹 기반 제품 사용경험 인증·평가 시스템 개발)

  • Na, Ju Yeoun;Kim, Jihee;Jung, Sungwook;Lee, Dong Hyun;Lee, Cheol;Bahn, Sangwoo
    • The Journal of Society for e-Business Studies
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    • v.24 no.1
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    • pp.29-48
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    • 2019
  • Recently, product design innovation to improve user experience has been perceived as a core element of enterprise competitiveness due to the fierce market competition and decrease of the technological gap between companies, but there is insufficient services to support the product experience evaluation of small and medium-sized companies (SMCs). The aim of this study is to develop a web-based product user experience evaluation and certification system supporting product design practices for SMCs. For system interface design, we conducted systematic functional requirement elicitation methods such as user survey, workflow analysis, user task definition, and function definition. Then main functions, information structure, navigation method, and detailed graphic user interfaces were developed with consideration of user interactions and requirements. In particular, it provides the databases for evaluation efficiency to support the evaluation process above a certain level of performance and efficiency, and knowledge databases to utilize in the evaluation and product design improvement. With help of the developed service platform, It is expected that the service platform would enhance SMCs' product development capability with regard to the user experience evaluation by connecting the consulting firms with SMCs.

Development Plan of R.O.K. Naval forces to prepare Tasks in the Arctic Ocean: Based on Operational Environment(SWOT) Analysis (한국 해군의 북극해 진출과 발전방안에 대한 고찰: 작전환경(SWOT) 분석을 중심으로)

  • Ji, Young
    • Maritime Security
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    • v.1 no.1
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    • pp.311-343
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    • 2020
  • Because of the global warming, the Arctic Ocean is expected to be ice-free by the year 2035. When the Arctic Ocean will be opened, a number of national interests will become more salient as experiencing a shortened sailing distance and decreasing navigation expense, possibility of natural resources transport by sea from Arctic Circle, and indirect-profit making by building a herb port in Asia. To secure the national interests and support the free activities of people in this region, R.O.K government is trying to make advanced policies. In order to carry out the naval tasks in the Arctic Ocean, using the operational characteristics(mobility, flexibility, sustainability, presence of capabilities, projection) is necessary. To this end, ROK Navy should analyze the operational environment (O.E.) by its capability(weakness and strength), opportunity, and threat. R.O.K. Navy should make an effort over the following issues to implement the tasks in the Arctic Ocean: first, Navy needs to map out her own plan (Roadmap) under the direction of government policies and makes crews participate in the education·training programs in home and abroad for future polar experts. Third, to develop the forces and materials for the tasks in cold, far operations area, Navy should use domestic well-experienced shipbuilding skills and techniques of the fourth industrial revolution. Next, improving the combined operations capabilities and military trust with other countries in the Arctic region to cover the large area with lack of forces' number and to resolve the ports of call issues. Lastly, preparation in advance to execute a variety of missions against military and non-traditional threats such as epidemics, HA/DR, SOLAS, in the future operation area is required.

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