• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.64-76
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• 2014

This study identified the causes of errors that could take place in the estimation process of vehicle miles traveled and quantified the effects of each of those causes on the estimation accuracy of vehicle miles traveled via error rate to propose an efficient way to estimate vehicle miles traveled. The study proceeded as follows: first, the study established survey data of vehicle miles traveled in the pilot test areas to test the accuracy of a method to estimate vehicle miles traveled. Second, the causes of errors with the estimation of vehicle miles traveled were categorized into errors with the sample size, sampling methods, and homogeneous link setting methods. In addition, many different methodologies were set to minimize errors with the estimation of vehicle miles traveled according to each of the causes. Third, error rates of estimation of vehicle miles traveled were compared and analyzed according to each of the methodologies. Finally, a toy network was established to propose a way of estimating vehicle miles traveled by taking the local characteristics into consideration. The study finds its significance in that it proposed an efficient way to estimate vehicle miles traveled through an experiment and planning approach and made use of survey data of vehicle miles traveled to test estimation accuracy. The proposed way of estimating vehicle miles traveled by taking into account the local characteristics will make a contribution to the estimation of vehicle miles traveled by the areas in future along with the level of data offered in the study.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.723-732
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• 2001

In this paper, the neurofuzzy controller of optically guided AGV is proposed to improve the path-tracking performance A differential steered AGV has front-side and rear-side optical sensors, which can identify the guiding path. Due to the discontinuity of measured data in optical sensors, optically guided AGVs break away easily from the guiding path and path-tracking performance is being degraded. Whenever the On/Off signals in the optical sensors are generated discontinuously, the motion errors can be measured and updated. After sensing, the variation of motion errors can be estimated continuously by the dead reckoning method according to left/right wheel angular velocity. We define the estimated contour error as the sum of the measured contour in the sensing error and the estimated variation of contour error after sensing. The neurofuzzy system consists of incorporating fuzzy controller and neural network. The center and width of fuzzy membership functions are adaptively adjusted by back-propagation learning to minimize th estimated contour error. The proposed control system can be compared with the traditional fuzzy control and decision system in their network structure and learning ability. The proposed control strategy is experience through simulated model to check the performance.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1226-1232
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• 2004

Biometric authentication is rising technology for the security market of the next generation. But most of biometric systems are developed using only one of various biological features. Recently, there is a vigorous research for the standardization of various biometric systems. In this paper, we propose a web-based authentication system using three other verifiers based on functional, parametric, and structural approaches for one biometrics of handwritten signature, which is conformable to a specification of BioAPI introduced by BioAPI Consortium for a standardization of biometric technology. This system is developed with a client-server structure, and clients and servers consist of three layers according to the BioAPI structure. The proposed neb-based multiple authentication system of one biometrics can be used to highly increase confidence degree of authentication without additional several biological measurements, although rejection rate is a little increased. That is, the false accept rate(FAR) decreases on the scale of about 1:40,000, although false reject rate(FRR) increases about 2.7 times in the case of combining above three signature verifiers. So the proposed approach can be used as an effective identification method on the internet of an open network. Also, it can be easily extended to a security system using multimodal biometrics.

• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.83-91
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• 2012

The objective of this study is to build a methodology for evaluating intelligent transportation systems (ITS) projects, by selecting measures of effectiveness (MOEs) and developing an approach to collect and process traffic data. While reviewing the existing MOEs and evaluation methodologies for ITS projects, several problems were found, such as the complication in delineating study areas, the absence of standardized evaluation methodologies, and the duplication in selecting MOEs. To tackle these problems, two MOEs capable of directly evaluating traffic conditions were chosen: i.e., average vehicle speed and traffic volume. Both MOEs can not only include all the functions of the existing MOEs, but also be simpler and more objective in evaluating real traffic conditions. The traffic volume can be measured by using either "cordon line" or "all point average" methods. On the other hand, measuring the average vehicle speed depends on site-specific characteristics such as traffic flow states (interrupted or uninterrupted) and traffic conditions (congested or uncongested). The present methodology is easily understandable for anyone and applicable for any ITS project, and is also expected to contribute to building a standardized evaluation system.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.101-109
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• 2014

This paper aims to design and implement a collaborative learning system based on the augmented reality. The existing augment reality-based learning systems have just focused on interactivity between a system and learners without consideration of cooperability, thereby leading to an ineffective approach to encouraging an learning system to be more supportive and conducive of and to cooperation among learners. The collaborative learning system is a learning method, with which learners achieve a common objective through critical thinking and cooperative teamwork so as to seek solutions to such fulfillment. This requires positive interdependence, proactive interactions, a sense of responsibility shared by individuals as well as the group, and development of teamwork among learners. Educators and systems assume a critical role in helping the collaborative education be effective. An educator is responsible for defining a project at the outset of learning activities, organizing groups for learners, and providing evaluation criteria applied to a group's project activities. Meanwhile, a system shall support interactions to take place while facilitating learning activities. Furthermore, an educator shall provide a system for managing and evaluating activities involving interactions among learners. This paper suggests and embodies a collaborative learning system based on the augmented reality with consideration of the aforementioned collaborative education.

• Therapeutic Science for Rehabilitation
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• v.9 no.3
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• pp.103-120
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• 2020

Objective : This study aims to understand the phenomenon of social admission in Korea's rehabilitation system by analyzing the perspectives of occupational therapists. Methods : We developed a written questionnaire based on RSAT and, in August 2019, distributed it to occupational therapists with more than three years of experience at the time. Data were analyzed using the van Kaam's method. Further, high frequency words were analyzed by word cloud in order to extract significant statements. Results : Forty-six written interviews were collected from various areas of Korea. We analyzed the data into 2 categories, 4 themes, 13 sub-themes. The two categories were 'hospital system' and 'external factors of occupational therapy practice'. The themes according to 'hospital system' were 'difficulties in implementing multidisciplinary approach' and 'inadequate discharge planning system'. The themes according to 'internal and external factors of occupational therapy' were analyzed as 'difficulties of occupational therapists' and 'difficulties in occupational therapy practice'. Conclusion : Occupational therapists in rehabilitation hospitals recognize that the reason for social admission is insufficient insurance systems related to occupational therapy services in rehab hospitals. This leads to difficulties in occupational therapy practice. We need to develop the insurance systems that can meet patient needs for social recovery.

• Korean Journal of Environmental Biology
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• v.34 no.2
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• pp.107-115
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• 2016

Currently, there are 442 operating nuclear power plants in the world, and 62 more are under construction. According to this reasoning, the treatment of radioactive waste is important to prevent the environmental ecosystem including humans, animals, and plants. Especially, a leakage of radioactive waste causes not only regional problem but also serious global one. In this study, we demonstrate the effect of radioisotopes (e.g., cesium, strontium, and cobalt) on a 3D culture cell. To develop the 3D cell culture system, we used a 96-well-culture plate with biocompatible agarose hydrogel. Using this method, we can perform the 3D cell culture system with three different cell lines such as HeLa, HepG2, and COS-7. In addition, we conducted a cell viability test in the presence of radioisotopes. Interestingly, the 3D morphological cells showed 42% higher cell viability than those on the 2D against cesium. This result indicates that the 3D platform provides cells morphological and physiological characteristic similar to in vivo grown tissues. Moreover, it overcomes the limitation of conventional cell culture system that can't reflect in vivo systems. Finally, we believe that the proposed approach can be applied a new strategy for simple high-throughput screening and accurate evaluation of metal toxicity assay.

• Information Systems Review
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• v.12 no.2
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• pp.189-203
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• 2010

Is presenting guidance of information performance measurement as government PRM version 2.0 these common reference models in public sector. Government PRM is consisted of assessment classification system and standard line of sight and performance management standard form. Through this, is sorting performance element and define cause-and effect. Government PRM is supplying measurement categories at assessment classification system, but relative importance for application standard by measurement categories is not presenting. In this study, importance for government PRM's measurement categories been applying by commonness Test of information performance measurement of public sector wishes to deduce estimation and priority. Research model used Fuzzy QFD, and designed so that can reflect well PRM's development purpose. I applied Fuzzy AHP and FPP method that graft together fuzzy theory to minimize uncertainty and ambiguity in that expert opinion. Is drawn to element that "Standard model offer for information department and management" is the most important in government PRM's development purpose. "Quality of service" is showing the highest priority in customer results in measurement category. Importance for government PRM's measurement categories can offer common valuation basis in government and public institution. Hereafter if examine closely quantitative cause-and effect for structure model of measurement classification system when study government PRM more objective and efficient reference model become.

• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.