• The KIPS Transactions:PartB
• /
• v.10B no.7
• /
• pp.735-742
• /
• 2003

In the information retrieval system, document clustering technique is to provide user convenience and visual effects by rearranging documents according to the specific topics from the retrieved ones. In this paper, we clustered documents using K-Means algorithm and present the effect of index terms weighting scheme on the document clustering. To verify the experiment, we applied Latent Semantic Indexing approach to illustrate the clustering results and analyzed the clustering results in 2-dimensional space. Experimental results showed that in case of applying local weighting, global weighting and normalization factor, the density of clustering is higher than those of similar or same weighting schemes in 2-dimensional space. Especially, the logarithm of local and global weighting is noticeable.

• Korean Journal of Remote Sensing
• /
• v.17 no.3
• /
• pp.243-251
• /
• 2001

GPS is one of today's most widely used surveying techniques. But, users can't acquire an enough accuracy in applications of the navigation or geodesy by the GPS positioning technique because of the effects of the ionosphere and troposphere. The solution of these restrictions in the DGPS technique that is to eliminate the common errors and can achieve a high accuracy. Although of sufficient density for good DGPS, accuracy of positioning is just not dense enough to provide complete coverage for real-time positioning, because distances between base and rover is short. In this paper, we suggest Realtime Long-Distance Transmission Method of DGPS Error Correction Signal, which consist of TCP, UDP and IP, which allows a user to increase the distance at which the rover receiver is located from the base, due to radio modem.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.5
• /
• pp.927-934
• /
• 2019

Recently, mobile devices have evolved into small computers with various functions according to user requirements. Careful attention must be paid to the design of the power supply network for the stable operation of the application processor (AP), the wireless communication modem, the high performance camera, and the various interfaces of the mobile device to implement various functions of the mobile device. In this paper, we analyzed and verified the method of optimizing the design parameters such as the position, capacity, and number of decoupling capacitors to meet the target impedance required by the driver IC chip to ensure the stability of the power supply network of mobile devices that should be designed as wiring type due to mounting density limitation. The proposed wired power supply network design method can be applied to various applications including high-speed signal transmission line in addition to mobile applications.

• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.36 no.1
• /
• pp.49-60
• /
• 2020

Although the number of child loss in commercial facilities has been growing recently, the prevention method for child loss are still lacking in the environmental aspect. This research examines the causes of lost child in behavioral aspects in order to develop a guideline to prevent child loss in U.E.C. The observational study on the behaviors of guardians and children was conducted in the U.E.C that is visited by many customers accompanied with children. Then the results of the observational study were marked on the behavioral maps. After analyzing the behavioral maps, the causes of child loss were determined by classifying into behaviors by age and behaviors by functional space. As a result, when guardian is unable to pay attention to child by doing something else such as making a purchase, or an inquiry, child may lose guardian by going towards the interesting factors or playing around. Moreover, if the spaces related to children are located at the node with high pedestrian density and open structure or the environment that is hard for the guardians to watch over their children, it will be easy for guardians to be inattentive to their children, and get separated from each other.

• Journal of IKEEE
• /
• v.26 no.4
• /
• pp.596-601
• /
• 2022

The application of the EGR system is increasing according to the recent trend of conversion to green-ships. EGR blower, one of the core parts of the EGR, consists of aerodynamic system and e-motor and inverter and etc. For the e-motor, a permanent magnet type synchronous motor with high energy density and excellent efficiency is applied recently. Small and medium-sized enterprises trying to develop the e-motors, however, for marine inverters mostly developed by global advanced companies due to the rigid classification certification and technical difficulties. One of disadvantage of universal inverters is that when optimal control fails, it is difficult to find the cause from user's point of view. Therefore, in this study, optimal controllers(Current vector contol and Tracking observer) for SPMSM for EGR blower was designed and verified to analyze the causes of failure of optimal control of universal inverter.

• Geomechanics and Engineering
• /
• v.36 no.3
• /
• pp.231-245
• /
• 2024

In recent decades, the protection and vulnerability of civil structures under explosion loads became a critical issue in terms of security, which may cause loss of lives and structural damage. Concrete retaining walls also restrict soils and slopes from displacements; meanwhile, intensive temporary loading may cause massive damage. In the current study, the modified Johnson-Holmquist (also known as J-H2) material model is implemented for concrete materials to model damages into the ABAQUS through user-subroutines to predict the blasting-induced concrete damages and volume strains. For this purpose, a 3D finite-element model of the concrete retaining wall was conducted in coupled Eulerian-Lagrangian simulation. Subsequently, a blast load equal to 500 kg of TNT was considered in three different positions due to UFC 3-340-02. Influences of the critical parameters in smooth blastings, such as distance from a free face, position, and effective blasting time, on concrete damage rate and destroy patterns, are explored. According to the simulation results, the concrete penetration pattern at the same distance is significantly influenced by the density of the progress environment. The result reveals that the progress of waves and the intensity of damages in free-air blasting is entirely different from those that progress in a dense surrounding atmosphere such as soil. Half-damaged elements in air blasts are more than those of embedded explosions, but dense environments such as soil impose much more pressure in a limited zone and cause more destruction in retaining walls.

• Journal of Korean Society of Forest Science
• /
• v.90 no.4
• /
• pp.420-430
• /
• 2001

The object of this study is to develop a computer program for the arrangement of the forest-road network maximizing the investment effect in forest-road construction with factors such as terrains, forest physiognomy, management plan, logging system, cost of forest-road construction, capacity of inputted labour, capacity of timber production and so on. The operating system developed by this study is Korean Windows 95/98 and Microsoft Visual Basic ver. 5.0. User interface was designed as systematic structure, it is presented as a kind of GUI(graphic user interface). The developed program has result of the most suitable forest-road arrangement, has suitable forest-road density calculated with cost of logging, cost of forest-road construction, diversion ratio of forest-road, cost of walking in forest. And the most suitable forest-road arrangement was designed for forest-road arrangement network which maximized investment effect through minimizing the sum of cost of logging and cost of forest-road construction. Input data were divided into map data and control data. Digital terrain model, division of forest-road layout plan, division of forest function and the existing road network are obtained from map data. on the other hand, cost of logging related terrain division, diversion ratio of forest-road and working road, cost of forest-road construction, cost of walking, cost of labor, walking speed, capacity of inputted labor, capacity of timber production and total distance of forest-road are inputted from control data. And map data was designed to be inputted by mesh method for common matrix. This program can be used to construct a new forest-road or vice forest-road which compensate already existing forest-road for the functional forestry.

• Asia pacific journal of information systems
• /
• v.18 no.3
• /
• pp.123-145
• /
• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Journal of Korea Water Resources Association
• /
• v.46 no.8
• /
• pp.821-831
• /
• 2013

Recently image velocimetries, including particle image velocimetry (PIV) and surface image velocimetry (SIV), are often used to measure flow velocities in laboratories and rivers. The most difficult point in using image velocimetries may be how to determine the sizes of the interrogation areas and the measurement uncertainties. Especially, it is a little hard for unskilled users to use these instruments, since any standardized measuring techniques or measurement uncertainties are not well evaluated. Sometimes the user's skill and understanding on the instruments may make a wide gap between velocity measurement results. The present study aims to evaluate image velocimetry's uncertainties due to the changes in the sizes of interrogation areas and searching areas with the error analyses. For the purpose, we generated 12 series of artificial images with known velocity fields and various numbers and sizes of particles. The analysis results showed that the accuracy of velocity measurements of the image velocimetry was significantly affected by the change of the size of interrogation area. Generally speaking, the error was reduced as the size of interrogation areas became small. For the same sizes of interrogation areas, the larger particle sizes and the larger number of particles resulted smaller errors. Especially, the errors of the image velocimetries were more affected by the number of particles rather than the sizes of them. As the sizes of interrogation areas were increased, the differences between the maximum and the minimum errors seemed to be reduced. For the size of the interrogation area whose average errors were less than 5%, the differences between the maximum and the minimum errors seemed a little large. For the case, in other words, the uncertainty of the velocity measurements of the image velocimetry was large. In the viewpoint of the particle density, the size of the interrogation area was small for large particle density cases. For the cases of large number of particle and small particle density, however, the minimum size of interrogation area became smaller.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.