• Journal of Distribution Science
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• v.13 no.12
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• pp.41-52
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• 2015

Purpose - Given globalization, the new niche market of medical tourism is likely to experience sustainable growth for various reasons, such as aging populations and a shift in the medical consumerism paradigm toward prevention. Importantly, understanding medical customers' behavior is necessary to benefit from a competitive advantage in this industry. The existing research primarily accessed the key factors of medical quality and costs to explain health customers' behavior but is limited in terms of enabling an understanding of the decision process. This limitation exists because, given the intangibility and greater associated risks in the highly professional industry of international medical tourism, most customers lack the knowledge and experience needed to evaluate the central factors-such as the medical competence of health care countries-before purchases. Therefore, they actively search for useful information through various distributions to reduce uncertainty and to make better choices. Interestingly, most of these information channels are associated with word-of-mouth (WOM). However, no evidence is found in the literature to estimate the effect of WOM in the medical tourism field. Thus, this study focuses on WOM to explore its interaction with key medical characteristic factors and the attractiveness of destinations referred to by sources. This study also affects customers' evaluations and, in turn, influences their intention to seek health care services abroad. Research design, data, and methodology - The literature review addressed an interesting research model for estimating the relations among WOM, medical characteristics, attractiveness, and customers' choice intention regarding international health care. In the key economic regions in China, such as Beijing, Shanghai, Jiangsu, Shandong, and Guangdong, 2,500 survey questionnaires were distributed to potential customers of different ages, education, and income levels. A resulting 1,717 (68.68 percent of the original 2,500) usable surveys were obtained for analysis. Moderated regression analysis was used to determine the effects of WOM in the decision process regarding international health care destinations. Results - The results indicate that WOM is a good moderator of the relationships between the factors evaluated by sources and customers. More importantly, the WOM effects reflect the factors of tie strength, credibility, and vividness. The results also reveal that, given the moderating role of WOM, the intention of potential Chinese customers to seek the referred health care country varies according to the medical characteristics of medical competency and reputation as evaluated by customers. In contrast, the travel attractiveness of the attractions, facilities, accessibility, and social environment are critical determinants of destination choice intention. Conclusions - The moderating role of WOM has been confirmed through the international healthcare destination selection process. Medical tourism managers should user WOM as an effective marketing tool for industry development. Specially, marketers should consider the effects of WOM determinants, such as tie strength, credibility, and vividness, to develop an effective strategy. Furthermore, this study estimates the factors that affect customers' selection of medical tourism destinations. Health care managers or policy makers should consider a broad variety of variables that may attract more Chinese customers to international health care.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2844-2858
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• 2014

The society experiencing the industrialization and urbanization has got over the socio-demographic change. these changes make the number of the population around the world, and this phenomenon is flowing into the whole country. Korea has became a Aging Society since 2000 and will be turned into the aged society by the 2018. therefore, the importance of preparing elderly living life such as silver town is getting emphasized. the purpose of this study is aimed at analyzing the decision elements of the preliminary demanders' intention who selecting Elderly Housing. Based on this study, it was broken down by the type much more. Binary Logistic Regression Analysis of Factors affecting the Elderly housing choices were subdivided. Through this process, improvement and the implications of this study was derived. this study deducts 3 kinds of implications. First, the preference for the development of elderly housing are different with each type of characteristics. Second, the indicators along with the individual characteristics account for the most part of the surface. so the specific investigation for the demand must be required to check the indicators. Third, when it comes to development of urban elderly housing, it requires to have a part of a local government plans securing the land. Fourth, when it comes to development of suburb elderly housing, it is required to arrange the living environment around the suburbs to let user classes living in Gyeonggi-do flow into elderly housing and live their new-life in the suburbs. Finally, when it comes to development of rural elderly housing, a variety of production, leisure and other programs should be made and put into there.

• The KIPS Transactions:PartC
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• v.18C no.4
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• pp.265-278
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• 2011

The objective of this paper is to analyze and characterize end-to-end packet statistics after modeling and simulation of WiFi (IEEE 802.11g) and WiMAX (IEEE 802.16e) of a virtual wireless network using OPNET Modeler Wireless Suite. Wireless internal and external network simulators such as Remcom's Wireless InSite Real Time (RT) module, WinProp: W-LAN/Fixed WiMAX/Mobile WiMAX, and SMI system, are designed to consider data transfer rate based on wireless propagation signal strength. However, we approached our research in a different perspective without support for characteristic of these wireless network simulators. That is, we will discuss the purpose of a visual analysis for these packets, how to receive each point packets (e.g., wireless user, base station or access point, and http server) through end-to-end virtual network modeling based on integrated wired and wireless network without wireless propagation signal strength. Measuring packet statistics is important in QoS metric analysis among wireless network performance metrics. Clear packet statistics is an especially essential metric in guaranteeing QoS for WiMAX users. We have found some interesting results through modeling and simulation for virtual wireless network using OPNET Modeler Wireless Suite. We are also able to analyze multi-view efficiency through experiment/observation result.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.181-199
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• 2021

Recently, financial companies are promoting chatbot services in line with the reduction of branches and the expansion of non-face-to-face services. However, it is difficult to expand the chatbot services at once in the presence of technical limitations and constraints of internal and external environment. Therefore, it is necessary to analyze the various situations of chatbot service to preemptively identify problems that can occur in stages and seek solutions. This study conducted interviews with 12 field practitioners and researchers to examine the intentions and behaviors of financial chatbot service users and interpreted them using TPB. The study revealed the characteristics of 'feelings and attitudes' such as convenience or inconvenience from the chatbot experience, 'subjective norms' such as herd behavior or the yearning for empathy of others, and 'behavioral control' according to the recognition of difficulty or convenience of chatbot use process. This study shows that this characteristic can affect the intention and actual behavior of users to use chatbot service continuously. In the future research, it is necessary to empirically study specific intentions and influence factors for actual users.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.45-54
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• 2023

Under combat simulation environment when inputting the detection performance data of the real system into the simulated object the given data affects the simulation analysis result. ACQUIRE-Target Task Performance Metric (TTPM)-Target Angular Size (TAS) model is used as a target acquisition model to simulate the detection ability of entities in the main combat simulation tool. This model estimates the decomposition curve of the object sensor and output the detection distance according to the target type. However, it is not easy to apply the performance of the new detection object that the user wants to input to the target acquisition model. Users want to input the detection distance into the target acquisition model, but the target acquisition model requires sensor decomposition curve data according to encounter conditions. In this paper, we propose a method of inversely deriving the sensor decomposition curve data of the target acquisition model by taking the detection distance to the target as an input. Here, the sensor decomposition curve data simultaneously satisfies each detection distance for three types of targets: personnel, ground vehicles, and aircraft. Finally, the detection distance of various reconnaissance equipment is applied to the detection object, and the detection effect according to the reconnaissance equipment is analyzed.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.355-363
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• 2023

In safety assessment of a aged bridge, dynamic characteristics and displacement are directly related to the rigidity of the structural system, especially displacement is the most important factor as the physical quantity that the bridge user can directly detect. However, in order to measure the displacement of the bridge, it is difficult to install displacement sensors at the bottom of the bridge and conduct traffic blocking and loading tests, resulting in increased costs or impossible measurements depending on the bridge's environment. In this study, a method of measuring the displacement of a bridge using only accelerometers without installing displacement sensors and ambient vibration without a loading test was proposed. For the analysis of bridge dynamic characteristics and displacement using ambient vibration, the mode shape and natural frequency of the bridge were extracted using a TDD technique known to enable quick analysis with simple calculations, and the unit load displacement of the bridge was analyzed through flexibility analysis to calculate static displacement. To verify this proposed technology, an on-site test was conducted on C Bridge, and the results were compared with the measured values of the loading test and the structural analysis data. As a result, it was confirmed that the mode shape and natural frequency were 0.42 to 1.13 % error ratio, and the maximum displacement at the main span was 3.58 % error ratio. Therefore, the proposed technology can be used as a basis data for indirectly determine the safety of the bridge by comparing the amount of displacement compared to the design and analysis values by estimating the displacement of the bridge that could not be measured due to the difficulty of installing displacement sensors.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.30-43
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• 2018

Many studies have been carried out to retrieve images using colors, shapes, and textures which are characteristic of images. In addition, there is also progress in research related to the disease images of the crop. In this paper, to be a help to identify the disease occurred in crops grown in the agricultural field, we propose a similarity-based crop disease search system using the diseases image of horticulture crops. The proposed system improves the similarity retrieval performance compared to existing ones through the combination descriptor without using a single descriptor and applied the weight based calculation method to provide users with highly readable similarity search results. In this paper, a total of 13 Descriptors were used in combination. We used to retrieval of disease of six crops using a combination Descriptor, and a combination Descriptor with the highest average accuracy for each crop was selected as a combination Descriptor for the crop. The retrieved result were expressed as a percentage using the calculation method based on the ratio of disease names, and calculation method based on the weight. The calculation method based on the ratio of disease name has a problem in that number of images used in the query image and similarity search was output in a first order. To solve this problem, we used a calculation method based on weight. We applied the test image of each disease name to each of the two calculation methods to measure the classification performance of the retrieval results. We compared averages of retrieval performance for two calculation method for each crop. In cases of red pepper and apple, the performance of the calculation method based on the ratio of disease names was about 11.89% on average higher than that of the calculation method based on weight, respectively. In cases of chrysanthemum, strawberry, pear, and grape, the performance of the calculation method based on the weight was about 20.34% on average higher than that of the calculation method based on the ratio of disease names, respectively. In addition, the system proposed in this paper, UI/UX was configured conveniently via the feedback of actual users. Each system screen has a title and a description of the screen at the top, and was configured to display a user to conveniently view the information on the disease. The information of the disease searched based on the calculation method proposed above displays images and disease names of similar diseases. The system's environment is implemented for use with a web browser based on a pc environment and a web browser based on a mobile device environment.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.27-36
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• 2018

This study suggests the necessity of behavior analysis as changes to a park environment to reflect user desires can be implemented only by grasping the needs of park users. Online data (blog) were defined as the basic data of the study. After collecting data by 5 - year units, data mining was used to derive the characteristics of the time series behavior while the significance of the online data was verified through social network analysis. The results of the text mining analysis are as follows. First, primary results included 'walking', 'photography', 'riding bicycles'(inline, kickboard, etc.), and 'eating'. Second, in the early days of the collected data, active physical activity such as exercise was the main factor, but recent passive behavior such as eating, using a mobile phone, games, food and drinking coffee also appeared as a new behavior characteristic in parks. Third, the factors affecting the behavior of park users are the changes of various conditions of society such as internet development and a culture of expressing unique personalities and styles. Fourth, the special behaviors appearing at Olympic Park were derived from educational activities such as cultural activities including watching performances and history lessons. In conclusion, it has been shown that people's lifestyle changes and the behavior of a park are influenced by the changes of the various times rather than the original purpose that was intended during park planning and design. Therefore, it is necessary to create an environment tailored to users by considering the main behaviors and influencing factors of Olympic Park. Text mining used as an analytical method has the merit that past data can be collected. Therefore, it is possible to form analysis from a long-term viewpoint of behavior analysis as well as to measure new behavior and value with derived keywords. In addition, the validity of online data was verified through social network analysis to increase the legitimacy of research results. Research on more comprehensive behavior analysis should be carried out by diversifying the types of data collected later, and various methods for verifying the accuracy and reliability of large-volume data will be needed.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.