• International Journal of Highway Engineering
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• v.14 no.1
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• pp.1-8
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• 2012

The horizontal alignment of road is deeply related with the stability of the road and traffic capacity. It is necessary to analyze horizontal alignment of road accurately for efficient maintenance of the road and relevance judgment about the standard. Recently the study on horizontal alignment of road using Lidar data and GPS was concluded, but they were many problem analyzing horizontal alignment radius of curvature in wide area. In this study, the tool which the radius of curvature can evaluate the suitability about "Rules about the Road Structure & Facilities Standards" by using center lines of the road of the digital map tries to implement on GIS. The interface was designed and implemented which can automatically estimate the Road Centerline Horizontal Alignment by using $ESRI^{(R)}$ $ArcObject^{TM}$.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Korean Journal of Social Welfare
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• v.66 no.2
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• pp.31-49
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• 2014

The purpose of this study is to analyze precedents related with child abuse for protection of the rights of the child. There should be the law related with 'punishment for child abuse,' which is the grounds of punishment, to make a precedent in the law punishing for 'child abuse,' but there is the concept only for 'child abuse' in the Child Welfare Law, the fundamental law; therefore, for a direct judgment for punishment, only precedents of 'child abuse' related with loss of parental rights and judgements for criminal cases, civil cases and laws covering special cases have been made. For that reason, 'the special law related with punishment for child abuse cases' is desperately required (On last December 23, 2013, the special law related with punishment for child abuse cases passed the National Assembly). Hence, precedent analysis had performed by grouping precedent from 2000 to 2013 which were not judged as child abuse in trial but can be regarded as child abuse. When analyzing each precedent according to the contents of analysis and judgment by fact relevance in this study, problems which the current legislative system has were deducted through an implication of each case by diagnosing using diagraming after classifying lower instance terminated cases, which precedents of the Supreme Court and judgments sent to the Supreme Court were excluded, while excluding cases settled in the civil level and classifying analysis of civil case precedents which did not become a criminal case and completed as a civil case, analysis of criminal case precedents, classification of precedents of loss of the parental rights (regarding child abuse) and precedents of any other special laws. And compensatory tasks for special laws regarding punishment of child abuse were presented while suggesting compensatory tasks for the legislation regarding deducted problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.224-231
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• 2019

The current paper was conducted to unravel the influence of affect induction as a background emotion in the process of cognitive task to judge the degree of sequence in groups with or without anxiety symptoms. Four types of affect induction and two sequential task types were used as within-subject variables, and two types of college students groups classified under the Beck Anxiety Inventory (BAI) as a between-subject variable were selected to determine reaction times involving sequential judgment among the lexical relevance information. DmDx5 was used to present a series of stimuli and elicit a response from subjects. Repeated measured ANOVA analyses revealed that reaction times and error rates were significantly larger with anxiety participants compared to the normal group regardless of affect and task types. Within-subject variable effects found that specific affect type (sorrow condition) and number-related task type showed a more rapid response compared to other affect types and magnitude-related task type, respectively. In sum, these findings confirmed the difference in tendency with reaction time and error rates that varied as a function of accompanying affect types as well as anxiety level and task types suggesting the that underlying background affect plays a major role in processing affect-cognitive association tasks.

• Journal of the Korean Society for information Management
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• v.25 no.2
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• pp.49-68
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• 2008

In many information retrieval experiments, the data fusion techniques have been used to achieve higher effectiveness in comparison to the single evidence-based retrieval. However, there had not been many image retrieval studies using the data fusion techniques especially in combining retrieval results based on multiple retrieval methods. In this paper, we describe how the image retrieval effectiveness can be improved by combining two sets of the retrieval results using the Sobel operator-based edge detection and the Self Organizing Map(SOM) algorithms. We used the clip art images from a commercial collection to develop a test data set. The main advantage of using this type of the data set was the clear cut relevance judgment, which did not require any human intervention.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.75-94
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• 2010

This study designed a pilot system in which queries can be expanded through a tag ontology where equivalent, synonymous, or related tags are bound together, in order to improve the retrieval effectiveness of videos. We evaluated the proposed pilot system by comparing it to a tag-based system without tag control, in terms of recall and precision rates. Our study results showed that the mean recall rate in the structured folksonomy-based system was statistically higher than that in the tag-based system. On the other hand, the mean precision rate in the structured folksonomy-based system was not statistically higher than that in the tag-based system. The result of this study can be utilized as a guide on how to effectively use tags as social metadata of digital video libraries.

• Journal of Arbitration Studies
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• v.18 no.1
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• pp.31-47
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• 2008

An arbitrator's duty shall be independence and impartiality such as a judge who has procedurally absolute position. Independence is the freedom from others, impartiality is the status of having no-partial condition. Although these show relevance between independence and impartiality, in actuality, it is not easy to prove them. Therefore, arbitrator has to prove his or her position by opening the public of reality and by having an obligation of notification. Each country which applies Arbitration rules or Arbitration act stays the same as Korean Commercial Arbitration Board does. Hence, each country has the moral principles in order to establish a standard of judgement for essential factors and requests preferentially the impartiality and the publicity. In reality, court of justice in England excludes arbitrator who has the close relation to a person concerned. Justice in France cancelled an authorization of arbitrator because of having the economic interest to the person concerned. And also, In United States, Federal Court reverses an arbitration judgment without giving any partiality to a person concerned because of not opening a public about the relationship between arbitrator and a person concerned. Therefore, decision basis of the independence and the impartiality is standardized by the economic interest of a person concerned, professional relation, society connection, relationship between arbitrator and arbitration representative in the same case while in process of arbitration, arbitrator's nationality If arbitrator does not keep the independence and the impartiality by a position of judge, he or she has to make responsible. this duty is divided by two things: civil case and crime case. and if arbitrator does break this responsibility, he or she will get the cancellation of judge and compensation of damage. However, Korea is placed in the real circumstance without judge precedent and moral principles including the independence and impartiality. In order to getting the good reputation of international arbitration institution, this country will have to enact principles of the independence and impartiality for arbitrator.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.269-276
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• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• Asia Marketing Journal
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• v.14 no.2
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• pp.23-37
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• 2012

Individuals often make their judgments on the basis of the ease or difficulty with which information comes to mind (for reviews, see Greifeneder, Bless, and Pham 2010; Schwarz 1998, 2004). Recent research, however, has documented that variables known to determine the degree of cognitive resources invested in information processing such as personal relevance (Grayson and Schwarz 1999; Rothman and Schwarz 1998), accuracy motivation (Aarts and Dijksterhuis 1999), and processing capacity (Menon and Raghubir 2003) can affect the extent to which individuals draw on metacognitive difficulty in making their judgments. The primary aim of this research is thus to investigate whether individuals with substantial cognitive resources or those with lack of cognitive resources are more likely to draw on metacognitive difficulty when making their product evaluations. The findings from two laboratory experiments indicate that individuals who perceive a greater level of fit between their self-regulatory orientation and temporal construal (Experiment 1), and between their self-construal and the type of product benefit appeal (Experiment 2) are more likely than those who perceive the lack of such fit to evaluate a target product less positively after thinking of many rather than a few positive reasons. The findings provide supporting evidence for the two-stage backward inference process involved with the effect of metacognitive difficulty on consumer judgments in that consumer judgments based on metacognitive difficulty may require greater cognitive resources than those based on the content of information generated. Also, the current research documents further empirical evidence for the relationship between self-regulatory orientation-construal level fit and cognitive resources such that perceived regulatory-construal level fit can increase consumer willingness to invest cognitive resources into their judgment tasks. Last, the findings can help marketers differentiate purchase situations where asking consumers to think of many positive benefits from purchase situations where asking consumers to think of a few key benefits is relatively more beneficial.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1197-1206
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• 2023

To assess the risk level of a public restroom implemented in virtual reality, we sought to evaluate the spatial elements present in the restroom. To provide the theoretical foundation for the evaluation subjects and criteria, we introduced prior research that proposed a checklist to entance the safety of public restroom. To set up evaluation criteria, we analyzed and established based on the theories of Paul J. Brantingham and Patricia L. Brantingham, focusing on the interaction between space and criminals. Ronald V. Clarke's "Routine Activity Theory" was also introduced and incorporated into the evaluation approach. We analyzed based on the correlation between the criminal, user, and spatial elements of the public restroom in terms of the criminal's actions, the spatial relevance to crime, and user exposure during use. Using these criteria, we developed an algorithm to evaluate th spatial elements of public restroom. Based on this, we created an application, demonstrating the feasibility of developing on evaluation tool.