• Information Systems Review
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• v.25 no.4
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• pp.113-130
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• 2023

Due to economic development and increasing gross national income, the number of automobiles continues to rise, leading to a serious issue of illegal parking due to limited road conditions and insufficient parking facilities. Illegal parking causes significant inconvenience and displeasure to people and can even result in accidents and loss of lives. The severity of accidents and their consequences, related to the growing number of vehicles and illegal parking, is escalating, particularly in the metropolitan areas. Consequently, efforts are being made to address this problem as a cause of social issues and come up with measures to reduce illegal parking. In particular, half of the public complaints in the metropolitan area are related to illegal parking, and the highest physical and human damage occurs in Gyeonggi. Thus, this study aims to use machine learning techniques based on data related to illegal parking in Suwon city, Gyeonggi, to categorize regional characteristics and propose effective measures to crack down on illegal parking. Additionally, practical, social, policy, and legal measures to decrease illegal parking in the metropolitan area are suggested. This study has academic significance in that it solved the problem of illegal parking, which is mentioned as one of the social problems that cause traffic congestion, by classifying regional characteristics using K-prototype, a machine learning algorithm. Furthermore, the results of this study contribute to practical and social aspects by providing measures to decrease illegal parking in the metropolitan area.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.13-19
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• 2023

Following the signing of the Paris Agreement on Climate Change (UNFCCC, 2015), the world is expanding greenhouse gas reduction activities through comprehensive participation that includes not only developed countries but also developing countries. Major countries around the world are placing high expectations on the effectiveness of total carbon emissions regulation through the carbon emissions market. However, in order to obtain carbon credits, third-party verification is required based on quantitative carbon reduction data. Accordingly, in this paper, we developed an AIoT high-efficiency street light for carbon emissions and conducted a performance analysis study to measure the luminous efficiency of the lighting fixture. To obtain carbon emissions rights, we used high-efficiency LED PKG, developed our own high-voltage PFC, and developed high-efficiency lighting fixtures capable of communication. For communication, the 2.4GHz LoRa method was adopted between the lighting fixture and the gateway. Lens design was conducted through simulation of Korea Expressway Corporation's standard streetlight types A, B, and C. The performance of the streetlight was verified as being more efficient than other existing products through the measurement of luminous efficiency by an accredited rating agency, and it is expected that carbon emissions rights will be obtained by reducing electrical energy through this.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.15-31
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• 2024

The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.250-258
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• 2007

Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.101-117
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• 2004

Standards are essential to facilitate the efficient use of GIS data. International Standards such as ISO TC211's 19100 series and various technical specifications from OpenGIS Consortium are some of the examples of efforts to maintain the interoperability among GIS applications. Marine GIS is no exception to this rule and in this context. developing standards for marine GIS is also in urgent needs. Using the same meaning and definition for the features commonly found in marine GIS applications is one of the ways to increase the interoperability among systems. One of the key requirements for maintaining the standard meanings for features is to build a common feature catalogue. This paper examines the concept of feature catalogue and describe the ways in which the feature catalogue can be organized. To identify the common features found in various marine GIS applications, a comprehensive search has been made to collect and analyze the features used in various applications. To maintain the interoperability with the National GIS (NGIS) system, the features used in various NGIS applications have been analyzed as well. The result of these analyses are used to create a comprehensive list of common features for marine GIS. This paper then explains the common feature catalogue for marine GIS and the provides the appropriate classification and coding systems for the common features. In addition, a registration tool for registering the common features into the standard registry has been developed in this study. This Web-based tool can be used to input features into the feature catalogue by various applications and also to maintain a standard-compliant feature catalogue by standard agencies.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.322-331
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• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.367-377
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• 2018

A cultural ecosystem service(CES), which is non-material benefit that human gains from ecosystem, has been recently further recognized as gross national income increases. Previous researches proposed to quantify the value of CES, which still remains as a challenging issue today due to its social and cultural subjectivity. This study proposes new way of assessing CES which is called Cultural Service Opportunity Spectrum(CSOS). CSOS is accessibility based CES assessment methodology for regional scale and it is designed to be applicable for any regions in Korea for supporting decision making process. CSOS employed public spatial data which are road network and population density map. In addition, the results of 'Rapid Assessment of Natural Assets' implemented by National Institute of Ecology, Korea were used as a complementary data. CSOS was applied to Namyangju-si and the methodology resulted in revealing specific areas with great accessibility to 'Natural Assets' in the region. Based on the results, the advantages and limitations of the methodology were discussed with regard to weighting three main factors and in contrast to Scenic Quality model and Recreation model of InVEST which have been commonly used for assessing CES today due to its convenience today.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.233-254
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• 2017

The purpose of this study is to analyze the main factors influencing the severity of traffic accidents and to visualize spatiotemporal characteristics of traffic accidents in Seoul. To do this, we collected the traffic accident data that occurred in Seoul for four years from 2012 to 2015, and classified as slight, serious, and death traffic accidents according to the severity of traffic accidents. The analysis of spatiotemporal characteristics of traffic accidents was performed by kernel density analysis, hotspot analysis, space time cube analysis, and Emerging HotSpot Analysis. The factors affecting the severity of traffic accidents were analyzed using decision tree model. The results show that traffic accidents in Seoul are more frequent in suburbs than in central areas. Especially, traffic accidents concentrated in some commercial and entertainment areas in Seocho and Gangnam, and the traffic accidents were more and more intense over time. In the case of death traffic accidents, there were statistically significant hotspot areas in Yeongdeungpo-gu, Guro-gu, Jongno-gu, Jung-gu and Seongbuk. However, hotspots of death traffic accidents by time zone resulted in different patterns. In terms of traffic accident severity, the type of accident is the most important factor. The type of the road, the type of the vehicle, the time of the traffic accident, and the type of the violation of the regulations were ranked in order of importance. Regarding decision rules that cause serious traffic accidents, in case of van or truck, there is a high probability that a serious traffic accident will occur at a place where the width of the road is wide and the vehicle speed is high. In case of bicycle, car, motorcycle or the others there is a high probability that a serious traffic accident will occur under the same circumstances in the dawn time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.6
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• pp.74-83
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• 2011

The high-pass transportation information system directly collects section information by using probe cars and therefore can offer more reliable information to drivers. However, because the running condition and features of probe cars and statistical processing methods affect the reliability of the information and particularly because the section travel time is greatly influenced by whether there has been delay by signals on urban roads or not, there can be much deviation among the collected individual probe data. Accordingly, researches in multilateral directions are necessary in order to enhance the credibility of the section information. Yet, the precedent studies related to high-pass information provision have been conducted on the highway sections with the feature of continuous flow, which has a limit to be applied to the urban roads with the transportational feature of an interrupted flow. Therefore, this research aims at analyzing the features of high-pass transportation data on urban roads and finding a proper processing method. When the characteristics of the high-pass data on urban roads collected from RSE were analyzed by using a time-space diagram, the collected data was proved to have a certain pattern according to the arriving cars' waiting for signals with the period of the signaling cycle of the finish node. Moreover, the number of waiting for signals and the time of waiting caused the deviation in the collected data, and it was bigger in traffic jam. The analysis result showed that it was because the increased number of waiting for signals in traffic jam caused the deviation to be offset partially. The analysis result shows that it is appropriate to use the mean of this collected data of high-pass on urban roads as its representative value to reflect the transportational features by waiting for signals, and the standard of judgment of delay and congestion needs to be changed depending on the features of signals and roads. The results of this research are expected to be the foundation stone to improve the reliability of high-pass information on urban roads.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.