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

• Korea Science and Art Forum
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• v.37 no.4
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• pp.149-159
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• 2019

This research was started to identify the color status of signboards at the target site and suggest the direction of improvement for the signboard project in Dongsang-dong, Jongno-gil, a central area of the old city center of Gimhae. The area under study forms a depressed street atmosphere with old facilities, and is a typical type of old city center sign that needs to be rebuilt. The purpose of this study is to investigate prior research related to signage and similar signboard improvement cases, and then to identify the current status of colors by sorting out the casting, auxiliary and highlighted colors through the survey of the color of the signboard in the target area, and to propose a desirable direction for the future sign business based on the basis of these findings. This paper divided the target sections by industry and conducted a color analysis of signboards. The results and contents of the research are as follows. First, cast-colored signboards in general businesses showed a variety of primary color distributions with high L* values, on average, with high intensity and high chromaticity. Second, the auxiliary colors were mostly white or black in color-free, making a contrast between the casting colors. Third, the highlight was that a* value showed a high distribution in positive water plus and was mainly distributed in obsolescence, such as red or yellow, and color was used to reflect the characteristics of each store. However, the stores in the entire section lack unity because they were using colors that were higher in color than middle colors, which was causing the street's aesthetic look to be undermined. Based on the results of these studies, it is thought that the future color scheme for Gimhae's signature improvement project will limit the number of colors to a certain extent and give a sense of security and visual comfort to the use of colorlessness and obscurity around the representative colors of Gimhae.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Maritime Security
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• v.7 no.1
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• pp.31-60
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• 2023

This study proposes a new convergence weapon system that combines the covert placement and detection abilities of a self-propelled mobile mine with the rapid tracking and attack abilities of supercavitating rocket torpedoes. This innovative system has been designed to counter North Korea's new underwater weapon, 'Haeil'. The concept behind this convergence weapon system is to maximize the strengths and minimize the weaknesses of each weapon type. Self-propelled mobile mines, typically placed discreetly on the seabed or in the water, are designed to explode when a vessel or submarine passes near them. They are generally used to defend or control specific areas, like traditional sea mines, and can effectively limit enemy movement and guide them in a desired direction. The advantage that self-propelled mines have over traditional sea mines is their ability to move independently, ensuring the survivability of the platform responsible for placing the sea mines. This allows the mines to be discreetly placed even deeper into enemy lines, significantly reducing the time and cost of mine placement while ensuring the safety of the deployed platforms. However, to cause substantial damage to a target, the mine needs to detonate when the target is very close - typically within a few yards. This makes the timing of the explosion crucial. On the other hand, supercavitating rocket torpedoes are capable of traveling at groundbreaking speeds, many times faster than conventional torpedoes. This rapid movement leaves little room for the target to evade, a significant advantage. However, this comes with notable drawbacks - short range, high noise levels, and guidance issues. The high noise levels and short range is a serious disadvantage that can expose the platform that launched the torpedo. This research proposes the use of a convergence weapon system that leverages the strengths of both weapons while compensating for their weaknesses. This strategy can overcome the limitations of traditional underwater kill-chains, offering swift and precise responses. By adapting the weapon acquisition criteria from the Defense force development Service Order, the effectiveness of the proposed system was independently analyzed and proven in terms of underwater defense sustainability, survivability, and cost-efficiency. Furthermore, the utility of this system was demonstrated through simulated scenarios, revealing its potential to play a critical role in future underwater kill-chain scenarios. However, realizing this system presents significant technical challenges and requires further research.

• Journal of Korean Home Economics Education Association
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• v.19 no.3
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• pp.37-60
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• 2007

This study has been historically reviewed the clothing and textiles education through references. The clothing and textiles education had been informally offered as a part of household skill, skill of daily life and home skill before the law of school education was established. Therefore, we have reviewed the changes in the clothing and textiles education by separating the prior period between the end of the old Korea and the liberation in 1945, from the later period from the liberation up to now. And also contents of clothing and textiles education between before and after the revision of the 7th curriculum were compared and analyzed. The clothing and textiles education had put emphasis on sewing, handicraft and household during the prior period from the end of the old Korea to the liberation, but after liberation, it became involved in Home Economics Education. The number of classes and the contents of clothing and textiles education had been increased and deepened from the 1st term to the 5th term of curriculum. In particular, the 4th and 5th term of curriculum became a turning point where home life section was intensified. Even though the number of classes was reduced during the 6th term of curriculum, with increase in target school grades for this education, and Home Economics in the middle school remained an independent subject matter. However, during the 7th term of curriculum, Technology-Home Economics Education in the middle school courses led to losing independent subject name and shrinking its contents. Through the revision in the 7th curriculum, the clothing and textiles education achieved great improvement and progress by gaining balance in distribution of contents among school grades and balance between theory and practice. However it still remains as an issue to be more studied and resolved how well the contents are matched with the interests and attention of students. We need to consider and reflect request of students under learner-centered curriculum. Considering enormous changes in the environment surrounding the clothing and textiles education, it is crystal clear that the gap between existing contents of education and teaching methods and our real life will be widened. Because students' perceptions of value have been diversified, it is our task to develop better contents and learning system in order to help students have interests, attention and desire in clothing and textiles life in line with social needs for desirable clothing and textiles education.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.41-52
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• 2002

Purpose : 3D conformal radiotherapy, the optimum dose delivered to the tumor and provided the risk of normal tissue unless marginal miss, was restricted by organ motion. For tumors in the thorax and abdomen, the planning target volume (PTV) is decided including the margin for movement of tumor volumes during treatment due to patients breathing. We designed the respiratory gating radiotherapy device (RGRD) for using during CT simulation, dose planning and beam delivery at identical breathing period conditions. Using RGRD, reducing the treatment margin for organ (thorax or abdomen) motion due to breathing and improve dose distribution for 3D conformal radiotherapy. Materials and Methods : The internal organ motion data for lung cancer patients were obtained by examining the diaphragm in the supine position to find the position dependency. We made a respiratory gating radiotherapy device (RGRD) that is composed of a strip band, drug sensor, micro switch, and a connected on-off switch in a LINAC control box. During same breathing period by RGRD, spiral CT scan, virtual simulation, and 3D dose planing for lung cancer patients were peformed, without an extended PTV margin for free breathing, and then the dose was delivered at the same positions. We calculated effective volumes and normal tissue complication probabilities (NTCP) using dose volume histograms for normal lung, and analyzed changes in doses associated with selected NTCP levels and tumor control probabilities (TCP) at these new dose levels. The effects of 3D conformal radiotherapy by RGRD were evaluated with DVH (Dose Volume Histogram), TCP, NTCP and dose statistics. Results : The average movement of a diaphragm was 1.5 cm in the supine position when patients breathed freely. Depending on the location of the tumor, the magnitude of the PTV margin needs to be extended from 1 cm to 3 cm, which can greatly increase normal tissue irradiation, and hence, results in increase of the normal tissue complications probabiliy. Simple and precise RGRD is very easy to setup on patients and is sensitive to length variation (+2 mm), it also delivers on-off information to patients and the LINAC machine. We evaluated the treatment plans of patients who had received conformal partial organ lung irradiation for the treatment of thorax malignancies. Using RGRD, the PTV margin by free breathing can be reduced about 2 cm for moving organs by breathing. TCP values are almost the same values $(4\~5\%\;increased)$ for lung cancer regardless of increasing the PTV margin to 2.0 cm but NTCP values are rapidly increased $(50\~70\%\;increased)$ for upon extending PTV margins by 2.0 cm. Conclusion : Internal organ motion due to breathing can be reduced effectively using our simple RGRD. This method can be used in clinical treatments to reduce organ motion induced margin, thereby reducing normal tissue irradiation. Using treatment planning software, the dose to normal tissues was analyzed by comparing dose statistics with and without RGRD. Potential benefits of radiotherapy derived from reduction or elimination of planning target volume (PTV) margins associated with patient breathing through the evaluation of the lung cancer patients treated with 3D conformal radiotherapy.

• The Journal of Society for e-Business Studies
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• v.13 no.3
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• pp.1-20
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• 2008

Today's computing environment which is getting distributed to communicate with various systems needs dynamic inter-connectivity of the systems. MOM(Message Oriented Middleware) is popularly used for transmitting XML messages among the distributed systems for the inter-connectivity. But, they do not support event-based message routing functionalities with XML transformation for processing effective message routing, which is essential to inter-connectivity, and there is no integrated platform to cope with these requirements. Although event-based message routing and XML transformation have been studied in a wide range of computer science areas, development of message routing systems is considered as a tough job due to the technological difficulties. In order to address these requirements, we proposed a novel system, named RMRS(Rule-based Message Routing System), which supports event-based message routing as well as XML message transformation. To make the proposed system easy to use, we also redesigned ECA(Event- Condition-Action) rule to fit in our system and developed a tool to map source XML structure into target XML structure.

• The Journal of Korean Academic Society of Nursing Education
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• v.14 no.2
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• pp.294-304
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• 2008

Purpose: Cancer patients experience a range of physical and psychological sequelae. Consistent nursing support should be provided along the cancer treatment path. This study aimed to i)examine the effects of a telephone counseling program after discharge on perceived health, psychological well-being, and satisfaction with nursing services, and ii)describe symptom distress and their coping methods. Method: The study was a quasi-experimental design with a non-equivalent pre-post test. The sample included 20 women with gynecologic cancer in the experimental group and the same in the control group from a university hospital in Seoul. The telephone intervention was given once from 5 to 7 days after the chemotherapy. The General Well-Being Schedule and Symptom Distress Scale were used. Result: An effect from telephone counseling was found only in the vitality subscale of psychological well-being. Other subscores, perceived health, or satisfaction with nursing services did not differ between the two groups. Pain, skin change, decreased appetite, and constipation were the major symptoms and a relatively few coping strategies were utilized. Conclusion: Protocol of telephone counseling led by a nurse needs to be further developed in regard to best timing, amount, and target effects for follow-up care of gynecologic cancer patients.

• Journal of Korean society of Dental Hygiene
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• v.11 no.6
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• pp.951-959
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• 2011

Objectives : The author has studied the effects of behavior of preventive treatment on job satisfaction in dental hygienist. Methods : The hygienists who had worked from June 27th to August 1st in 2011 were explained about this research objectives and only the hygienists who agreed with this research participation were conducted a self-administered Questionnaire survey and the results were collected immediately. The collected questionnaire was 297, but the final 250 questionnaire were decided as a target except for the trustless ones. This analysis was extracted using SPSS(SPSS 12.0 for windows, SPSS Inc, Chicago, USA). Results : 1. Preventive treatment of dental hygienist was shown as this order - Educational needs 4.25, Importance 4.12, Usefulness 4.09, Perform 3.42. Job satisfaction was reached the moderate level. 2. Analysis of preventive treatment of hygienist was shown as this order - Basic brushing education 4.72 was ranked the highest, Taking patient history and Incremental dental health care 4.58 was held the second place. Dental caries activity tests 3.30 was shown the lowest figures. Response of preventive treatment conducting was like this order - Taking patient history 4.30, Dental prophylaxis 4.28, Basic brushing education 4.11, Incremental dental health care 4.04. Dental caries activity tests 2.05 was shown the lowest figures. 3. General characteristics in behavior of preventive treatment was resulted in this case that the respondents who have worked for less one year in current job than the ones who have worked for more than five years was shown such a low level, this was taken as a meaningful difference.(p=0.008) 4. It was shown that the higher fulfillment of preventive treatment(${\beta}$=0.340, p<0.001) and the greater earnings(${\beta}$=0.194, p=0.001) and usefulness of preventive treatment(${\beta}$=0.130, p=0.042), the higher job satisfaction. Conclusions : Considering these results, environment where the hygienists can concentrate on preventive treatment which is their proper job should be built up as soon as possible. And through this environment, the atmosphere where hygienists, as oral health professionals, can play a role to improve the oral health of the people by boosting job satisfaction should be created. Also It is thought that an institutional, actual improvement-changing the social awareness towards hygienists and dentists, the recognition of scope of the hygienists' work - should be established urgently.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.247-256
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• 2014

Purpose : To assess target motion during radiotherapy by quantifying daily setup errors and inter-fractional and intra-fractional movements of pancreatic fiducials. Materials and Methods : Eleven patients were treated via stereotactic body radiotherapy (SBRT) with volumetric modulated arc therapy. Bony setup errors were calculated using cone beam computed tomography (CBCT). Inter-fractional and intrafractional fiducial (seed) motion was determined via cone beam computed tomography (CBCT) projections and orthogonal fluoroscopy. Results : Using an off-line correction protocol, setup errors were 0.0 (-1.7-4.0), 0.3 (-0.5-3.0), and 0.0 (-4.1-6.6) mm for the left-right, anterior-posterior, and superior-inferior directions respectively. Random inter-fractional setup errors in the mean fiducial positions were -0.1, -1.1, and -2.3 mm respectively. Intra-fractional fiducial margins were 9.9, 7.8, and 12.5 mm, respectively. Conclusion : Online inter-fractional and intra-fractional corrections based on daily kV images and CBCT expedites SBRT of pancreatic cancer. Importantly, inter-fractional and intra-fractional motion needs to be measured regularly during treatment of pancreatic cancer to account for variations in patient respiration.