• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.469-474
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• 2016

Abnormal sound was heard from a heat exchanger of condensate water system in a nuclear power plant, which was identified as impact sound of a loose part later. Nuclear power plants are normally equipped with loose part monitoring system for primary water system, but not for secondary water system. The abnormal sound was analyzed by using the impact signal-processing methodology based on the Hertz theory. The predicted results for impact location and size of the loose part showed good agreement with those of the actual loose part found during the overhaul period in the plant. So, this analysis methodology for the impact signal will be widely utilized for the primary and secondary side of the nuclear power plant.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1317-1320
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• 2006

This study compared the floor impact sound level of rectangular receiving room type to differed receiving room types to analyze effect of room mode. The floor impact sound level of master room were higher than the level of living room which resulted from room mode. The result showed that the level of low frequency bandwidth in the location varied with receiving room types were lower than general measuring point of rectangular receiving room.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.2
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• pp.152-159
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• 2013

A structural health monitoring(SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal(TR) and inverse filtering(IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.

• Journal of Ocean Engineering and Technology
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• v.24 no.6
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• pp.30-33
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• 2010

This study presents the effect of filling ratio on sloshing impact pressure. The experiment was done with three filling ratios of 20%, 70%, and 95% of the tank height. The input of the motion was regular excitation. The total number of sensors in use were 53. They were installed on tank top and tank wall. The maximum pressures and the average of one third highest impact pressures for the whole pressure sensors were investigated. The result shows clearly the location of sensors which are exposed to the high impact pressures for different filling ratios. The characteristics of the impact patterns for three filling ratios were also examined.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.2
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• pp.172-178
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• 2016

The location template matching (LTM) method is a technique of identifying an impact location on a structure, and is often applied to structural health monitoring and large scale human-computer interface (HCI) systems. The LTM method utilizes a certain measure of similarity between two time signals. The correlation coefficient is most widely used for this purpose, and the group delay based method is recently proposed to improve the accuracy of finding the best matching pair of signals. In practice, one of key essential consideration for implementing the LTM method is to guarantee that a sufficient number of vibration modes must be contained in the measured signal, and yet the lower sampling rate is needed for a real-time implementation. In this paper, the properties of correlation coefficient and group delay with respect to the number of vibration modes are investigated. A few important results are obtained through extensive computer simulations and experiments. If the number of vibration modes contained in the measured signal is more than four it is sufficient for the correlation based LTM method, while the group delay based LTM method requires smaller number of vibration modes.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.223-235
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• 2014

In this study, it is the study of foreign tourism content information providing utilizing mobile indoor location information services. In particular, we compared the Web App used in Osaka, Japan. Widespread use of smartphones in the world increases, it is changed to free travel of individuals from group travel. Tourists cultural complex shopping mall is able to travel in a room is increasing. By utilizing the services of the guidance location based on the room, it is possible to easily obtain the discount coupon information, tourism content. Also, it is possible to grasp the movement path and disaster relief information. Osaka Japanese tourists increased after the earthquake in Tokyo. So we compare the difference in Osaka web and applications. If improving the indoor location information service method of domestic if it would help foreign tourists attract. In addition, it will give a big impact if there is a fusion of the Internet of things.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.91-105
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• 2008

Nowadays, circulation industry is taking charge of important role in improvement of competitive power on the manufacturing industry and public welfare increase of consumer, price stabilization, employment creation and so on. A lot of research have been progressing for formation of total circulation complex, but decision making for selection of location on some facility is only calculated the optimum value when correct data values are inserted. However, a lot of decision making is accomplished in situation that have little knowledge of objective and constraints and as real world is also evaluated inclusive of analyst's subjectivity about variable, indefinite and fuzzy part, so it is decreasing a reliability on evaluation result and complicating objective evaluation on various effect and negative impact. Accordingly, from under like this situation, this study is to develop location decision model of circulation complex using fuzzy theory from the intention for the most reasonable decision making in fuzzy situation based on decision making problem on conventional location and size decision that did to be satisfactory constraints necessarily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1868-1887
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• 2024

Recommendation systems research is a subfield of information retrieval, as these systems recommend appropriate items to users during their visits. Appropriate recommendation results will help users save time searching while increasing productivity at work, travel, or shopping. The problem becomes more difficult when the items are geographical locations on the ground, as they are associated with a wealth of contextual information, such as geographical location, opening time, and sequence of related locations. Furthermore, on social networking platforms that allow users to check in or express interest when visiting a specific location, their friends receive this signal by spreading the word on that online social network. Consideration should be given to relationship data extracted from online social networking platforms, as well as their impact on the geolocation recommendation process. In this study, we compare the similarity of geographic locations based on their distance on the ground and their correlation with users who have checked in at those locations. When calculating feature embeddings for users and locations, social relationships are also considered as attention signals. The similarity value between location and correlation between users will be exploited in the overall architecture of the recommendation model, which will employ graph convolution networks to generate recommendations with high precision and recall. The proposed model is implemented and executed on popular datasets, then compared to baseline models to assess its overall effectiveness.

• Journal of Environmental Health Sciences
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• v.46 no.1
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• pp.88-95
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• 2020

Object: The purpose of this study was to select priority points for soil management using the location of groundwater and to suggest this method for soil contamination surveys. Method: Groundwater impact range was set to an area of 100 to 500 meters from the center point of agricultural groundwater wells. Data on industrial complex and factory areas, areas of stored or used ores and scrap metals, areas associated with waste and recycling, and traffic-related facilities areas were collected and checked for whether they fall within the groundwater impact range. Longitude and latitude coordinates of these data were mapped on the groundwater impact range using QGIS (Quantum Geographic Information System). Results: Considering the groundwater impact range, the points were selected as follows: 589 points were selected from 6,811 factories and 259 points were selected from 1,511 recycling business points. Traffic-related facility areas were divided between gas stations, bus depots, and auto mechanics. Thirty-four points were selected from 149 bus depots and 573 points were selected from 6,013 auto mechanic points. From the 2,409 gas station points, 323 were selected. Conclusion: Contaminated soil influences groundwater and crops, which can harm human health. However, soil pollution is not easily identified, so it is difficult to determine what has occurred. Pollution must be prevented beforehand and contaminated soil found. By selecting and investigating soil contamination survey points in consideration of the location of groundwater wells, we can safely manage water resources by preventing groundwater contamination in advance.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.1
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• pp.153-181
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• 2013

Weather is an influential factor to sales of companies. There have been growing attempts with which companies apply weather to developing their strategic marketing plans. By executing weather marketing activities, companies minimize risks (or negative impacts) of weather to their business and increase sales revenues. In spite of managerial importance of weather management, there are scarce empirical studies that comprehensively investigate its impact and present an efficient method that optimally allocates marketing budget. Our research was conducted in two parts. In the first part, we investigated influences of weather on sales based on real-world daily sales data. We specifically focused on the contextual factors that were less focused in the weather related research. In the second part, we propose an optimization model that can be utilized to efficiently allocate weather marketing budget across various regions (or branches) and show how it can be applied to real industry cases. The results of our study are as follow. Study 1 investigated the impact of weather on sales using store sales data of a family restaurant company and an outdoor fashion company. Results represented that the impacts of weather are context-dependent. The impact of weather on store sales varies across their regional and location characteristics when it rains. Based on the results derived from Study 1, Study 2 proposes a method on how optimally companies allocate their weather marketing budgets across each region.