• Journal of Korean Medicine Rehabilitation
• /
• v.31 no.4
• /
• pp.129-143
• /
• 2021

Objectives This study was aimed to evaluate clinical practice guidelines (CPGs) of traffic injuries, which has already been developed at domestic or outside of country, and to explore the Korean medical treatments included in the CPGs. Methods Twelve electronic databases (PubMed, Cochrane library, China National Knowledge Infrastructure [CNKI {Chinese Academic Journals, CAJ}], Research Information Sharing Service [RISS], Oriental Medicine Advanced Searching Integrated System [OASIS], KoreaMed, Korean Medical Guideline Information [KoMGI), National Guideline Clearinghouse [AHRQ], Core Outcome Measures in Effectiveness Trials Initiative Website [COMET], Turning Research into Practice [TRIP], The National Institute for Health and Care Excellence [NICE], and Medical Research Information Center [MedRIC]) up to July 2021 were searched. Only systematically developed CPGs for traffic injuries were selected and appraised. The appraisal was conducted by using Appraisal of Guidelines for Research & Evaluation (AGREE) II tool. Results Six CPGs were included and evaluated. All CPGs were appraised as highly recommended because they exceeded 60% in more than 4 among 6 domains of AGREE II, including domain of 'rigor of development', and 30% in the rest. Recommendations related to Korean medicine treatments such as on manual therapy related to Chuna were given in 6 CPGs, 4 for acupuncture, 1 for Qigong and 1 for Taping. Conclusions The 6 CPGs were developed up to now through a systematic development methodology and there were many recommendations for Korean medical treatments related to manual (Chuna) treatment, acupuncture and Qigong. However, the evidence for the side effects and risk factors of Korean medical treatments was scantly reflected in CPGs. Therefore, it is considered that balanced CPG with benefits and risks should be developed, covering Korean medical diagnosis, treatment and prognosis.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.4
• /
• pp.785-794
• /
• 2019

Recently Deep Learning technology, one of the fourth industrial revolution technologies, is used to identify the hidden meaning of network data that is difficult to detect in the security arena and to predict attacks. Property and quality analysis of data sources are required before selecting the deep learning algorithm to be used for intrusion detection. This is because it affects the detection method depending on the contamination of the data used for learning. Therefore, the characteristics of the data should be identified and the characteristics selected. In this paper, the characteristics of malware were analyzed using network data set and the effect of each feature on performance was analyzed when the deep learning model was applied. The traffic classification experiment was conducted on the comparison of characteristics according to network characteristics and 96.52% accuracy was classified based on the selected characteristics.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.6
• /
• pp.648-656
• /
• 2001

In this paper, we propose a new feature-based vehicle tracking system using trajectory matching for intelligent traffic surveillance. The proposed system consists of three parts: feature extraction, feature tracking, and feature grouping using trajectory matching. For feature extraction and feature tracking, features of vehicles are selected based on the measure of cornerness and are tracked using linear Kalman filtering. We then group features from the same vehicle in the grouping step. We suggest a new grouping algorithm using the spatial information of features and trajectory matching to solve the over-grouping Problems of the feature-based tracking method. Finally, our proposed tracking system demonstrates good performance for typical traffic scenes with partial occlusion and neighboring conditions.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1290-1293
• /
• 2021

Currently, blind people are experiencing a lot of inconvenience in their daily lives. In order to provide helpful service for the visually impaired, this study was carried out to make a new smart glasses that transmit information monitoring walking environment in real-time object recognition. In terms of object recognition, YOLOv4 was used as the artificial intelligence model. The objects, that should be identified during walking of the visually impaired, were selected, and the learning data was populated from them and re-learning of YOLOv4 was performed. As a result, the accuracy was average of 68% for all objects, but for essential objects (Person, Bus, Car, Traffic_light, Bicycle, Motorcycle) was measured to be 84%. In the future, it is necessary to secure the learning data in more various ways and conduct CNN learning with various parameters using darkflow rather than YOLOv4 to perform comparisons in the various ways.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.5
• /
• pp.72-84
• /
• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• The Journal of Asian Finance, Economics and Business
• /
• v.5 no.3
• /
• pp.95-102
• /
• 2018

The objective of this research is to explore the diverse challenges faced by the customer as well transport providers through the selected modes of transportation of the second most populous country in the world - India. Two separate well-structured questionnaires administered to garner the opinions on different challenges. A random sample of 100 equally selected from the customers of 3 modes of transportation along with 30 transport providers. The collected data was analyzed in Microsoft Excel and R Studio platforms using Percentile Rank Tool and R Programming Language for Chi-square test respectively. Traffic congestion coupled with parking is the major problem in case of roadways while Safety and cleanliness in railways are the first amongst the problems to reckon with. High fares and lack of trained employees are the biggest challenges faced by aviation industry. The research is concentrated only in the states of Andhra Pradesh and Telangana in India with most widely used three modes of transportation viz., Road, Rail and Airways. This research paper is first of its kind which has collected the opinions of both customers as well transport providers on the problems faced. This research proffers information about the challenges faced by the customers which there will be an enormous possibility to review their strategies and plans.

• Journal of KIISE:Information Networking
• /
• v.27 no.1
• /
• pp.58-67
• /
• 2000

The paper presents a representative-based feedback mechanism and rate adaptation policy for congestion control in multicast traffic for multimedia applications. In multicast congestion control, feedback implosion occurs as many receivers send feedback to a sender. We propose to use representatives to avoid the feedback implosion. In our scheme, receivers feedback packet loss information periodically and a sender adapts the sending rate based on the information collected through a hierarchy of representatives. A representative is selected in each region and roles as a filter to decrease the number of feedbacks. The simulation results show that the proposed scheme solves the feedback implosion problem and well adapts in a congested situation.

• Journal of Intelligence and Information Systems
• /
• v.23 no.3
• /
• pp.155-175
• /
• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.2
• /
• pp.231-238
• /
• 2023

Since there is a limit to the physically visible horizon that sensors for autonomous driving can perceive, complementary utilization of digital map data such as a Local Dynamic Map (LDM) along the probable route of an Autonomous Vehicle (AV) is proposed for safe and efficient driving. Although the amount of digital map data may be insignificant compared to the amount of information collected from the sensors of an AV, efficient management of map data is inevitable for the efficient information processing of AVs. The objective of this study is to analyze the efficiency of information use and information processing time of AV according to the expansion of the active section of LDM-based static road and traffic information. To carry out this objective, a microscopic simulator model, VISSIM and VISSIM COM, was employed, and an area of about 9 km × 13 km was selected in the Busan Metropolitan Area, which includes heterogeneous traffic flows (i.e., uninterrupted and interrupted flows) as well as various road geometries. In addition, the LDM information used in AVs refers to the real high-definition map (HDM) built on the basis of ISO 22726-1. As a result of the analysis, as the electronic horizon area increases, while short links are intensively recognized on interrupted urban roads and the sum of link lengths increases as well, the number of recognized links is relatively small on uninterrupted traffic road but the sum of link lengths is large due to a small number of long links. Therefore, this study showed that an efficient range of electronic horizon for HDM data collection, processing, and management are set as 600 m on interrupted urban roads considering the 12 links corresponding to three downstream intersections and 700 m on uninterrupted traffic road associated with the 10 km sum of link lengths, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.27 no.11C
• /
• pp.1055-1063
• /
• 2002

In this paper, we have studied path selection problem using multiple metric. Current Internet selects a path using only one metric. The path selected by one metric is a best-effort service that can satisfy one requirements. In order to satisfy a call with various Qualify-of-Service(QoS) requirements, the path must satisfy multiple constraints. In many cases, path selection is NP-complete. The proposed algorithm is widest-least cost routing algorithm that selects a path based on cost metric which is basically a delay metric influenced by the network status. The proposed algorithm is a multiple metric path selection algorithm that has traffic distribution ability to select shortest path when network load is light and move traffic to other alternate path when the link load is high. We have compared the results with other routing algorithms.