• Journal of Positioning, Navigation, and Timing
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• v.7 no.4
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• pp.205-215
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• 2018

The recent emergence of new Global Navigation Satellite Systems (GNSS) has resulted in a gradual improvement in the performance of positioning services. This paper verifies the degree of improvement in positioning performance of Assisted-GNSS (A-GNSS) receivers using assistance information compared to standalone-GNSS receivers that do not use assistance information in various urban environments in Korea. For this purpose, field tests are performed in various urban and indoor environments in Korea. The assistance information is provided by u-blox's AssistNow Online and low-cost commercial receivers are used for mobile station receivers. Through experiments, the Time to First Fix (TTFF), acquisition sensitivity, and position accuracy performance improvement are analyzed. The results of the experiments show that using assistance data improved the performance in all experiment locations, and, in particular, a significant performance improvement in terms of TTFF.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.107-112
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• 2022

The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.1069-1076
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• 2017

C-ITS(Cooperative-Intelligent Transportation System) provides services that require strict real-time such as forward collision warning, road safety service and emergency stop. WAVE(Wireless Access in Vehicular Environments), a core technology of C-ITS, is a technology designed for high-speed driving. However, in order to provide stable communication service by applying to real road environment, various performance tests of real vehicular environment are required. In the real road environment, WAVE communication performance is influenced by the surrounding environment such as moving vehicle, road shape and topography. Especially, when the vehicle is moving at high speed, the traveling position according to the speed of the vehicle, The surrounding environment changes rapidly. Such changes are factors affecting the communication performance, therefore a system and methods for analyzing them are needed. In this paper, we propose the configuration and test method of an effective performance evaluation system under high-speed driving and describe the results of analyzing the communication performance based on the data measured through the actual vehicle test.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.53-59
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• 2022

After the 3rd level autonomous driving vehicle, the 4th and 5th level of autonomous driving technology is trying to maintain the optimal condition of the passengers as well as the perfect driving of the vehicle. However current autonomous driving technology is too dependent on visual information such as LiDAR and front camera, so it is difficult to fully autonomously drive on roads other than designated roads. Therefore this paper proposes a Braking Strength Calculation System (BSCS), in which a vehicle classifies road conditions using data other than visual information and calculates optimal braking strength according to road conditions and driving conditions. The BSCS consists of RCDM (Road Condition Definition Module), which classifies road conditions based on KNN algorithm, and BSCM (Braking Strength Calculation Module), which calculates optimal braking strength while driving based on current driving conditions and road conditions. As a result of the experiment in this paper, it was possible to find the most suitable number of Ks for the KNN algorithm, and it was proved that the RCDM proposed in this paper is more accurate than the unsupervised K-means algorithm. By using not only visual information but also vibration data applied to the suspension, the BSCS of the paper can make the braking of autonomous vehicles smoother in various environments where visual information is limited.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.91-105
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• 2023

This paper identified the difference in perception of the consignment system between the freight company and the consigned vehicle owners, derived factors that urgently need to improve the difference in perception, and presented the basis for establishing a management model based on this. A management model based on the difference in perception of consigned borrowers was established, and research hypotheses were established to conduct reliability, validity, and confirmatory factor analysis, path analysis, and mediation effect verification. As a result of the analysis, out of 58 questions, 56 of the total 65 questions showed a difference in perception of the consignment system between trucking companies and consigned vehicle owners, and the questions were input as management model factors. As a result of conducting confirmatory factor analysis, path analysis, and mediating effect verification using only recognition data, 5 hypotheses were adopted, and it was analyzed that the factor had no mediating effect. It can be analyzed that the appropriateness of the compensation system affects the improvement of each other's relationship, and the improvement of each other's relationship leads to the improvement of transportation services. However, since the mediating effect was rejected because it was not significant, this effect should not be exaggerated.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.19-30
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• 2023

An electric scooter(e-scooter), one popularized micro-mobility vehicle has shown rapidly increasing use in many cities. In South Korea, the use of e-scooters has greatly increased, as some companies have launched e-scooter sharing services in a few large cities, starting with Seoul in 2018. However, the use of e-scooters is still controversial because of issues such as parking and safety. Since the perception toward the means of transportation affects the mode choice, it is necessary to track the trends for electric scooters to make the use of e-scooters more active. Hence, this study aimed to analyze the trends related to e-scooters. For this purpose, we analyzed news articles related to e-scooters published from 2014 to 2020 using dynamic topic modeling to extract issues and sentiment analysis to investigate how the degree of positive and negative opinions in news articles had changed. As a result of topic modeling, it was possible to extract three different topics related to micro-mobility technologies, shared e-scooter services, and regulations for micro-mobility, and the proportion of the topic for regulations for micro-mobility increased as shared e-scooter services increased in recent years. In addition, the top positive words included quick, enjoyable, and easy, whereas the top negative words included threat, complaint, and ilegal, which implies that people satisfied with the convenience of e-scooter or e-scooter sharing services, but safety and parking issues should be addressed for micro-mobility services to become more active. In conclusion, this study was able to understand how issues and social trends related to e-scooters have changed, and to determine the issues that need to be addressed. Moreover, it is expected that the research framework using dynamic topic modeling and sentiment analysis will be helpful in determining social trends on various areas.

• The Korean Journal of Emergency Medical Services
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• v.3 no.1
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• pp.20-32
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• 1999

The purpose of this retrospective research of 603 patients who were transferred to the emergency medical center of university hospital from 1 Jan, 1998 to 31 Jan, 1998 was making of basic data for emergency medical transfer system improvement countermeasure and the point at issue of overlapping reexamination ststus of patients transfered to emergency medical center of university hospital from 1,2 level hospital. The data analysis was done by SPSS, t-test, ANOVA, Pearson correlation. The results were as follows: 1. Male to female ratio was 1.7:1 and peak age group was patients over forties and under nine years of age(70.5%) 2. Traumatic patients were 17.8%, motor vehicle accident patients were 16.7% and Non-traumatic patients were 65.3%. Transferring hospital was divided into 2groups: primary hospital, secondary hospital. The majority was secondary hospital(73.3%). The result of symptom severity classification of patients transferred to 3rd emergency medical center was urgent patients 32.5%, emergency patients 33.58%, non-emergency patients 34.0% 3. Most highest score items amoung overlapping reexamination of patients transfered to emergency medical center of university hospital from 1,2 level hospital were CBC test, simple X-ray (0.93점), CBC test(0.97점), urin test(0.88점), chemistry test(0.94점), simple X-ray(0.98점), CT(0.42점), EKG(0.89점) amoung overlapping reexamination of motor vehicle accident patients were more higher reexamination score than traumatic patients and non-traumatic patients 4. CBC test(P<0.001), urin test(P<0.001), chemistry test(P<0.001), simple X-ray(P<0.001), CT(P<0.01), EKG(P<0.001) amoung overlapping reexamination of patients in 2 level hospital were more higher reexamination score than 1 level hospital patients 5. About symptom severity classification of patients transferred to 3rd emergency medical center, CBC test(P<0.001), urin test(P<0.001), chemistry test(P<0.001), simple X-ray(P<0.01), CT(P<0.001), EKG(P<0.001) amoung overlapping reexamination items in urgent patients were more higher reexamination score than other patients 6. Influencing variation for overlapping reexamination in hospital was CBC test(P<0.001), CT (P<0.001), MRI (P<0.05).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2960-2965
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• 2013

Customized services for individuals in analysis of recently collected GPS information have been investigated in various aspects. As the size of collected GPS data gets larger, a variety of services is being released accordingly. Existing studies, however, are limited to presenting service models for users while there is little study on developing intelligent computing technologies in the introduction of GPS information into the system. This study suggests an algorithm to analyze traffic information by introducing GPS information into the system in order to take the lead among intelligent computing technologies. The suggested algorithm analyzes a map by means of the collected vehicle GPS information and sectional traffic information interpretation method; thus, the computer judges the traffic information collected by humans. The experiment result shows that the traffic information was properly analyzed upon the utilization of the given data. Although a small quantity of analyzed data was less reliable, the system maintained high reliability as the data was sufficient.

• The Korean Journal of Emergency Medical Services
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• v.1 no.1
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• pp.100-111
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• 1997

This is the first Korea study to evaluate the effects od the safety of ambulance driving and the occurrence of ambulance traffic accidents and to provide basic informaion for the description of various factors to reduce the ambulance traffic accidents. The major insturment of this study were Krean Self-Analysis Driver Opinionnaire. Questionnaire contains 8 items which measure driver's opinions or attitudes : driving courtesy, emotion, traffic law, speed, vehicle conditions, the use of drugs, high-risk behaviors, and human factors. To take the analysis of data, the total of 350 divers were investigated ambulance divers and others in Taejon City and others (6 City) from 1996. 1. July to 1996. 31. July. The data were analyzed by the descriptive statistics and the logistic regression - path analysis - with SPSS and SAS package program. The result are as follows : 1. There was desirable attitude group(16.2%) and undesirable attitude group(17.6%) on safety ambulance driving. 2. It have suggested that risk factors of ambulance traffic accidents much affected with emotion and speed control on safety ambulance driving < Y(Accdient) = -2.64 + 0.57 $X_1$ (Emotion Control) + 0.30 $X_2$(Seed control) + E > and motor traffic acident much affected with emotion control and high-risk behavior on safety driving < Y(Accident) = -1.11 + 0.33 $X_1$(Emotion Control) + 0.29 $X_2$(High-risk Behvior) + E > 4. The primary emphassis of ambulance drivers was make us realized that improthatnt factors on safety ambulance driving were 1)making way for emergent ambulance, 2)driver's career, 3)The ability of emergency medical technics, and the knowledge or under standing of ambulance way difficut(or easy) of accdess. 5. Almost 96.6% of respondents have agreed to necessity of emergency medical technics for ambulance drivers. 6. Almost 94.6% of respondents have consented to necessity of emergtency medical technicians for ambulance driving. 7. It have suggested that the proportion of traffic accident proportion by desitable attitude group(16.7%) was much less than that of undesirable attitude group(30.8%) on safety ambulance driving(P < 0.05)/Ps) Accidents are unplanned, unforesen incidents which can lead to harmful or unfortunate outcomes, Collisons are not accidents, since the basic cause of the majority of collisons invovles high-risk human behavior. Although there are many factors which contribute to accident causation, four basic factors seem to predominate in most traffic related situations. These four factors include: the human factor, the vehicle factor, the environmental factors and destination factor(Peto G. et al. 1995).