• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.107-133
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• 2021

This study was performed in order to provide suggestions on how to strengthen librarian competency by evaluating and analyzing the competency value of librarians as information professions. First, the study divided the common competency value of librarians as human capital of libraries into skills, knowledge, behavior and attitude, and analyzed each area of competency value for librarians of the A-library. As a result, the average of the 'librarian's behavior and attitude' area was the highest, followed by the 'librarian's skill' area and the 'librarian's knowledge' area. Second, in terms of 'librarian's skill', A-library librarians' competence values were high in the order of 'communication', 'leadership', 'technology' and in the terms of 'librarian's knowledge' ones were high in the order of 'law and policy', 'marketing', 'learning and growth' and 'finance and accounting'. In addition, in areas of 'librarian's behavior and attitude', the factors were high in the order of 'ethics and values', 'interpersonal relationships' and 'customer service'. Third, the analysis of whether the average difference exists depending on the characteristics of A-library librarians on their evaluation of the competency value shows that only the 'working period' factor in the total competency value and the two factors 'age' and 'working period' were statistically significant in the 'librarian's knowledge' area. Forth, as a result of a regression analysis to identify the characteristics of A-library librarians and their impact on competency value, only the 'final education' factor was statistically significant for the competency value of the 'librarian's skill' area. Fifth, in the survey on problems and desirable improvement measures in increasing the competency value of librarians, the proportion of presenting problems and improvement plan in systemic aspects such as the 'librarian qualification system' and 'librarian training system' was high.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.535-546
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• 2022

This study tried to explore factors for improving academic achievement in online non-face-to-face education based on the survey results of a University's online cooperative learning Q&A. Due to the Corona situation, both professors and learners can easily feel psychological isolation due to the implementation of all non-face-to-face online classes. As one of the methods, it was intended to suggest the direction of future education to various teachers and learners by sharing class cases in which the online cooperative learning methodology was applied. Previous studies on non-face-to-face online learning, online cooperative learning, and learning promotion method were reviewed, and the online Q&A method was adopted as a specific learning promotion method to conduct research. In the Q&A process, learners were given an opportunity to check their learning content, share knowledge and communicate, and performance evaluation-related factors such as guaranteeing anonymity of the questioner and answerer, improvement points system, and absolute evaluation were asked. As a result of the survey analysis, it was found that they are the success factors of online cooperative learning. It is a small change that can be applied in practice in the future where online non-face-to-face learning is likely to continue, but by sharing meaningful cases of application of teaching methodologies, both professors and learners being motivated and actively involved in. It is expected that we will be able to suggest methods and directions for improving skills together by changing and supplementing the learning field.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Management & Information Systems Review
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• v.35 no.2
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• pp.67-81
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• 2016

The purpose of this study was to investigate lots of problems that the current tax appeal system has, which are becoming serious issues as tax appeal cases are recently increasing. Those problems include the unreasonable procedure and period of deliberation on tax appeal cases, permission of a same tax appeal by more than one governmental agencies and the compulsory transposition system of tax appeal cases. All of these problems should be rectified in order to ensure that the currently tax appeal system protect taxpayers' rights and interests effectively. According to the current tax appeal system, the period from the receipt of tax appeal cases to ruling on them is up to 90 days. This is unrealistic, so that period should be allowed to be extended if those cases about more complicated taxation or if they are even harder to be treated for any reason. At present, chief of Tax Tribunal has to unconditionally accept resolution from the meeting of tax judges and make a ruling accordingly because he has no right to reject that resolution. But now, it's time to establish legal grounds based on which the chief suggests the tax judges to reconsider their resolution if it is undoubtedly wrong. Currently, there's a relatively little acceptance of tax appeals from people who can't financially afford to designate a proxy for them. To solve this problem, lots of efforts to make socially recognized the necessity to relive those people's rights and interests and make widely known the Public Proxy of Tax Appeal System. The current tax appeal system allows the Board of Audit and Inspection to be an appealer. This means taxation may be deliberated on by more than one governmental agencies. It is so inefficient. Therefore, tax appeal by the board should be only about taxation that they found unacceptable by audit and inspection. Except for this, it is not allowed that the Board of Audit and Inspection file tax appeals that are, in turn, necessarily transported to the National Taxation. Esecially, the transposition should be a procedure that is occasionally taken. In sum, this study investigated problems with the current tax appeal system, and made suggestions about solutions that are not theoretical but practical.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.129-143
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• 2012

Recently, the rapid progress of a number of standardized web technologies and the proliferation of web users in the world bring an explosive increase of producing and consuming information documents on the web. In addition, most companies have produced, shared, and managed a huge number of information documents that are needed to perform their businesses. They also have discretionally raked, stored and managed a number of web documents published on the web for their business. Along with this increase of information documents that should be managed in the companies, the need of a solution to locate information documents more accurately among a huge number of information sources have increased. In order to satisfy the need of accurate search, the market size of search engine solution market is becoming increasingly expended. The most important functionality among much functionality provided by search engine is to locate accurate information documents from a huge information sources. The major metric to evaluate the accuracy of search engine is relevance that consists of two measures, precision and recall. Precision is thought of as a measure of exactness, that is, what percentage of information considered as true answer are actually such, whereas recall is a measure of completeness, that is, what percentage of true answer are retrieved as such. These two measures can be used differently according to the applied domain. If we need to exhaustively search information such as patent documents and research papers, it is better to increase the recall. On the other hand, when the amount of information is small scale, it is better to increase precision. Most of existing web search engines typically uses a keyword search method that returns web documents including keywords which correspond to search words entered by a user. This method has a virtue of locating all web documents quickly, even though many search words are inputted. However, this method has a fundamental imitation of not considering search intention of a user, thereby retrieving irrelevant results as well as relevant ones. Thus, it takes additional time and effort to set relevant ones out from all results returned by a search engine. That is, keyword search method can increase recall, while it is difficult to locate web documents which a user actually want to find because it does not provide a means of understanding the intention of a user and reflecting it to a progress of searching information. Thus, this research suggests a new method of combining ontology-based search solution with core search functionalities provided by existing search engine solutions. The method enables a search engine to provide optimal search results by inferenceing the search intention of a user. To that end, we build an ontology which contains concepts and relationships among them in a specific domain. The ontology is used to inference synonyms of a set of search keywords inputted by a user, thereby making the search intention of the user reflected into the progress of searching information more actively compared to existing search engines. Based on the proposed method we implement a prototype search system and test the system in the patent domain where we experiment on searching relevant documents associated with a patent. The experiment shows that our system increases the both recall and precision in accuracy and augments the search productivity by using improved user interface that enables a user to interact with our search system effectively. In the future research, we will study a means of validating the better performance of our prototype system by comparing other search engine solution and will extend the applied domain into other domains for searching information such as portal.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.41-54
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• 2020

This study was conducted to provide basic data for a transparent and fair bidding system by identifying problems and suggesting improvement measures through an analysis of the bidding status for construction projects and service-related landscaping of multi-family housing. To this end, we used the data from the "Multi-Family Housing Management Information System (K-apt)" that provides the history of apartment maintenance, bidding information, and the electronic bidding system to examine the winning bid status and amount, along with the size and trends of the winning bids by year, and the results of the selection of operators by construction type. As a result, it was found that out of the total number of successful bids (36,831), 4.4% (16,631) were in the landscaping business, and the average winning bid value was found to be about 24 million won. According to the data, 73% of the landscaping cases were valued between 3 million won and 30 million won, and 58.6% of the cases were in the field of "pest prevention and maintenance". 36% of the total number of bids were awarded from February to April, with "general competitive bidding" accounting for 59.8% of the bidding methods. As for the method of selecting the winning bidder, 55% adopted the "lowest bid" and "electronic bidding method," and 45% adopted the "qualification screening system" and "direct bidding method." As an improvement to the problems derived from the bidding status data, the following are recommended: First, the exception clause to the current 'electronic bidding method' application regulations must be minimized to activate the electronic bidding method so that a fair bidding system can be operated. Second, landscaping management standards for green area environmental quality of multi-family housing must be prepared. Third, the provisions for preparing design books, such as detailed statements and drawings before the bidding announcement, and calculating the basic amount shall be prepared so that fair bidding can be made by specifying the details of the project concretely and objectively must be made. Fourth, for various bidding conditions in the 'business operator selection guidelines', detailed guidelines for each condition, not the selection, need to be prepared to maintain fairness and consistency. These measures are believed to beuseful in the fair selection of landscaping operators for multi-family housing projects and to prepare objective and reasonable standards for the maintenance of landscaping facilities and a green environment.

• Journal of the Korean Society of Radiology
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• v.10 no.1
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• pp.29-37
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• 2016

This study aims to improve the satisfaction level of the patient who undergoes CT contrast examination by developing and applying pretreatment process system, which not only can reduce the side effects caused by the test but also can help carry out the test smoothly. The subjects were 214 patients who booked CT contrast examination from January 2014 to February 2014 but could not carry out their test on schedule. We analyzed the reasons for the delay and conducted follow-up survey on them. We analyzed the usefulness of pretreatment process system by contemplating and developing pretreatment process system and applying it to the patients for whom follow-up survey was conducted from January 2015 to February 2015. The number of outpatients who came to the hospital form January to February 2014 was 2,846 and the number of patients who could not undergo the test was 214, accounting for 7.52% of the total. The specific reason for the delay includes 214 cases of unknown creatinine 98 with 120 minutes of average delay time, 40 cases of creatinine over 1.3(19%) with 30minutes of average delay time, 34 cases of past contrast media side effect 6% with 40 minutes of average delay time and 25 cases of lack of pretreatment such as fasting, etc. 11% with 120minutes of average delay time. The number of CT scan has been increasing ever since the development of CT and the frequency of using the contrast media is expected to increase. If we can employ pretreatment process system in order to effectively control the side effect of contrast media and help the CT contrast examination to be smoothly conducted on schedule, I'm sure we could improve the quality of our medical service and increase our patients' satisfaction who come to our CT scan room.