• The Journal of Korean Society for Radiation Therapy
• /
• v.20 no.2
• /
• pp.91-102
• /
• 2008

Purpose: To enlarge the efficiency of operation and establish a constituency for development of new radiotherapy treatment through database which is established by arranging and indexing radiotherapy related affairs in well organized manner to have easy access by the user. Materials and Methods: In this study, Access program provided by Microsoft (MS Office Access) was used to operate the data base. The data of radiation oncology was distinguished by a business logs and maintenance expenditure in addition to stock management of accessories with respect to affairs and machinery management. Data for education and research was distinguished by education material for department duties, user manual and related thesis depending upon its property. Registration of data was designed to have input form according to its subject and the information of data was designed to be inspected by making a report. Number of machine failure in addition to its respective repairing hours from machine maintenance expenditure in a period of January 2008 to April 2009 was analyzed with the result of initial system usage and one year after the usage. Results: Radiation oncology database system was accomplished by distinguishing work related and research related criteria. The data are arranged and collected according to its subjects and classes, and can be accessed by searching the required data through referring the descriptions from each criteria. 32.3% of total average time was reduced on analyzing repairing hours by acquiring number of machine failure in addition to its type in a period of January 2008 to April 2009 through machine maintenance expenditure. Conclusion: On distinguishing and indexing present and past data upon its subjective criteria through the database system for radiation oncology, the use of information can be easily accessed to enlarge the efficiency of operation, and in further, can be a constituency for improvement of work process by acquiring various information required for new radiotherapy treatment in real time.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.143-159
• /
• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Korean Journal of Remote Sensing
• /
• v.31 no.6
• /
• pp.531-548
• /
• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• Journal of International Area Studies (JIAS)
• /
• v.15 no.1
• /
• pp.61-82
• /
• 2011

Public resistance is an essential factor of the democratization process. Due to this, public resistance has been recognized as an important element in discussing the democratization of China. Recently in China, and a new era of resistance especially the agrarian resistance has been being expanded. This paper identifies trends and characteristics of that. With searching changes in the relationship between the nation and the societies in China, we will check whether democratization can be built from the whole bottom of the nation's ideology or not. It is a paradox of china's economic growth that the peasant uprising increased is a factor to the growth. The farmers' smoldering discontent exploded with rage because rural communities have been forced to sacrifice during the growth. The authoritarian party-state system in China has been faced with the limits in calming the peasant revolt down with the traditional suppression and restriction. Even though the party-state system in China has accepted farmers' dissatisfaction somewhat, and it has tried to improve its image of a benevolent government and pursued buying stability strategy, the gap between urban and rural areas has been expanded in the sustainable economic development and modernization process, therefore the authorities could not soothe the farmers' sense of alienation. Accordingly, the peasant revolt has not flickered out easily, and has been getting uncontrolled across China. Resistance characteristics of Chinese farmers have also changed. In the past, they had been sporadic and indirect ways, whereas in recent years, they have changed into organized and active ways. Of course, it is generally evaluated that the party-state system has sustained a strong social control so far. Buying stability strategy has prevented farmers' complaints from spreading to a threat to its regime, because civil societies in rural areas have still weak foundations from being formed. The party-state system, because of tensions and conflicts, will control the growing powers of civil societies in rural areas with institutionalization of interaction between the nation and the societies, and they will induce street protests to legalized struggle for a while. However, the relationship between the state and the societies has already started new rearrangement, in terms of that the conflicts between the state and rural communities have continued, and the changes of resistance ways.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.127-141
• /
• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of Intelligence and Information Systems
• /
• v.17 no.1
• /
• pp.111-125
• /
• 2011

Clustering is a process of grouping similar or relevant documents into a cluster and assigning a meaningful concept to the cluster. By this process, clustering facilitates fast and correct search for the relevant documents by narrowing down the range of searching only to the collection of documents belonging to related clusters. For effective clustering, techniques are required for identifying similar documents and grouping them into a cluster, and discovering a concept that is most relevant to the cluster. One of the problems often appearing in this context is the detection of a complex concept that overlaps with several simple concepts at the same hierarchical level. Previous clustering methods were unable to identify and represent a complex concept that belongs to several different clusters at the same level in the concept hierarchy, and also could not validate the semantic hierarchical relationship between a complex concept and each of simple concepts. In order to solve these problems, this paper proposes a new clustering method that identifies and represents complex concepts efficiently. We developed the Hierarchical Overlapping Clustering (HOC) algorithm that modified the traditional Agglomerative Hierarchical Clustering algorithm to allow overlapped clusters at the same level in the concept hierarchy. The HOC algorithm represents the clustering result not by a tree but by a lattice to detect complex concepts. We developed a system that employs the HOC algorithm to carry out the goal of complex concept detection. This system operates in three phases; 1) the preprocessing of documents, 2) the clustering using the HOC algorithm, and 3) the validation of semantic hierarchical relationships among the concepts in the lattice obtained as a result of clustering. The preprocessing phase represents the documents as x-y coordinate values in a 2-dimensional space by considering the weights of terms appearing in the documents. First, it goes through some refinement process by applying stopwords removal and stemming to extract index terms. Then, each index term is assigned a TF-IDF weight value and the x-y coordinate value for each document is determined by combining the TF-IDF values of the terms in it. The clustering phase uses the HOC algorithm in which the similarity between the documents is calculated by applying the Euclidean distance method. Initially, a cluster is generated for each document by grouping those documents that are closest to it. Then, the distance between any two clusters is measured, grouping the closest clusters as a new cluster. This process is repeated until the root cluster is generated. In the validation phase, the feature selection method is applied to validate the appropriateness of the cluster concepts built by the HOC algorithm to see if they have meaningful hierarchical relationships. Feature selection is a method of extracting key features from a document by identifying and assigning weight values to important and representative terms in the document. In order to correctly select key features, a method is needed to determine how each term contributes to the class of the document. Among several methods achieving this goal, this paper adopted the $x^2$�� statistics, which measures the dependency degree of a term t to a class c, and represents the relationship between t and c by a numerical value. To demonstrate the effectiveness of the HOC algorithm, a series of performance evaluation is carried out by using a well-known Reuter-21578 news collection. The result of performance evaluation showed that the HOC algorithm greatly contributes to detecting and producing complex concepts by generating the concept hierarchy in a lattice structure.

• The Korean Journal of Emergency Medical Services
• /
• v.6 no.1
• /
• pp.141-152
• /
• 2002

The purpose of this study is to provide the basic materials for searching the way of improvement to heighten the emergency medical welfare level by one step further. To achieve this purpose, the subjects of this study were selected 452 college students in Gwangju, using a random sampling method. The statistical analysis methods utilized for analyzing the collected data are frequency analysis, $x^2$ test. The conclusions obtained from these analyses are as following ; 1. In question about necessary optimum number of persons for rescue first aid activity, health and non-health major college students responded by 39.2%, 45.3% respectively that rescue team 15 people, first aid team 3 people is most suitable. But there was no significant difference in major department(p<0.05). 2. In question about security of the public health doctor and the emergency medical technician, all health and non-health major college students are recognizing necessity urgently, but there was no significant difference in major department(p<0.05). 3. In question about 119 rescue first aid team member applying for an examination qualification grant to the department of EMT's graduate, all health and non-health major college students were highest by 52.9%, 52.4% respectively in "necessity" item. But there was no significant difference in major department(p<0.05). 4. Because rescue first aid equipment level appears higher than 41.7% in non-health major college student's case by 54.2% in health major college student's case, health major college students are recognizing that equipment level should be supplemented more but there was no significant difference in major department(p<0.05). 5. In question about equipment supplement, all health and non-health major college students appeared highest by 64.8%, 69.3% in accident type different special equipment. But there was no significant difference in major department(p<0.05). 6. In question about rescue ambulance car size, we could know being thinking that health and non-health major college student each 61.2%, 56.5% is small and narrow that large size of the rescue ambulance amount need. But there was no significant difference in major department(p<0.05). 7. In question about patient's state is worsened, because rescue first aid equipment is inferior, health major college student responded sometimes 55.1%, many 29.5%. very many by 11.5%, while non-health major college student responded 65.8%, 23.1%, 4.0% respectively. There was significant difference in major department(p<0.05). 8. In question about emergency patient must utilize for 119 rescue ambulance car, all health and non-health major college students appeared highest by 38.8%, 41.3% in "not so" item. In question about rescue first aid team's first-aid treatment ability improves more, all health and non-health major college students appeared highest by 58.1% and 58.7% respectively in "improve" item. In question about "119 rescue ambulance car must go more rapidly than now", all health and non-health major college students are recognizing that should be quicker by 58.1%, 60.9% respectively. When called to 119 all health and non-health major college students responded highest by 55.5%, 53.3% respectively that we must receive first-aid treatment direction from a doctor. In question about "119 rescue ambulance car must be made the pay system", all health and non-health major college students responded 74%, 80% respectively in "not so" item. There was significant difference in major department(p<0.05). In conclusions, In oder to provide superior rescue first aid service to people, a public health doctor should be placed in the situation room inside the fire station so that the doctor could instruct the proper emergency treatment suitable for each situation to the rescue first aid team. Also, national education about a first-aid treatment that do to all people is necessarily necessary in emergency delivery system and this should be spread extensively through school education and broadcasting medium and education should be gone side by side, and see that will can save emergency patients' life which is more when these education consists continuously fixed period for public institution of policeman, fire officer etc. specially. And for reinforcement of patient transfer system, public organization must procure special ambulance car so that emergency patient receive first aid treatment while transfer.

• Information Systems Review
• /
• v.11 no.1
• /
• pp.161-179
• /
• 2009

Nowadays an increasing number of Internet users are running individual websites as Blog or Cyworld. As this type of personal media has a great influence on communication among people, business comes to care about Network Effect, Network Software, and Social Network. For instance, Cyworld created the web service called 'Minihompy' for individual web-logs, and acquired 2.4milion users in 2007. Although many people assumed that the popularity of Minihompy, or Blog would be a passing fad, Cyworld has improved its service, and expanded its Network with various contents. This kind of expansion reflects survival efforts from infinite competitions among ISPs (Internet Service Provider) with focus on enhancing usability to users. However, Cyworld's Network Effect is gradually diminished in these days. Both of low production cost of service vendors and the low searching/conversing costs of users combine to make ISPs hard to keep their market share sustainable. To overcome this lackluster trend, Cyworld has adopted new strategies and try to lock their users in their service. Various efforts to improve the continuance and expansion of Network effect remain unclear and uncertain. If we understand beforehand how a service would improve Network effect, and which service could bring more effect, ISPs can get substantial help in launching their new business strategy. Regardless many diverse ideas to increase their user's duration online ISPs cannot guarantee 'how the new service strategies will end up in profitability. Therefore, this research studies about Network effect of Cyworld's 'Minihompy' using System-Dynamics method which could analyze dynamic relation between users and ISPs. Furthermore, the research aims to predict changes of Network Effect based on the strategy of new service. 'Page View' and 'Duration Time' can be enhanced for the short tenn because they enhance the service functionality. However, these services cannot increase the Network in the long-run. Limitations of this research include that we predict the future merely based on the limited data. We also limit the independent variables over Network Effect only to the following two issues: Increasing the number of users and increasing the Service Functionality. Despite of some limitations, this study perhaps gives some insights to the policy makers or others facing the stiff competition in the network business.

• Korean Journal of Cognitive Science
• /
• v.27 no.4
• /
• pp.501-539
• /
• 2016

The human mind is a self-evolving system that develops along a multidimensional hierarchical pathway in response to traumatic stimulus. In absence of trauma, a mind integrated in conflict-free state is called monistic. When the monistic mind responses to a traumatic stimulus, a response polarity forms toward stimulus polarity within the mind, turning it into a bipartite structure. Dialectical interaction between the two opposites, originating from their incompatibility, creates a new third polarity in the upper dimension. Thereby, the mind turns into a trinity structure. When the interaction among the three polarities becomes optimized, the plasticity of the mind gets maximized into the "far-from-equilibrium state," and the function of three polarities is synchronized. Through this recalibration, the mind returns back to its monistic structure. If the mind with the recurred monistic structure responds to another traumatic stimulus, this cycle of hierarchical transformation repeats itself in this cyclical and fractal growth process through synchronization of basic trinity system. Applying this concept to the process of post-traumatic growth (PTG), this paper explores how the mind transforms traumatic experiences into PTG and proposes a 'PTG Clock' that shows a fundamental sequence in the development of the human mind. The PTG Clock consists of seven hierarchical phases, and each of the first six phases has two opposite sub-phases: shocked/numbed, feared/intrusive, paranoid/avoidant, obsessional/explosive, dependent/depressive, and meaningless/searching for meaning. The seventh, the synchronization phase, completes one cycle of the mind's transformation, realizing a grand trinity system, where the mind synchronizes its biological, social, and existential dimensions. At that point, the mind becomes more susceptible to not only the stimulus of its own traumatic experience but also the pain of others. Thereby, the PTG Clock sets out on a journey to another cycle of transformation in higher dimensions. The validity of this transformational process for the PTG Clock will be examined by comparing it to Horowitz's theory of stress response syndrome.

• Journal of Korean Society for Geospatial Information Science
• /
• v.8 no.1 s.15
• /
• pp.51-63
• /
• 2000

Dynamic traffic assignment(DTA) has been a topic of substantial research during the past decade. While DTA is gradually maturing, many aspects of DTA still need improvement, especially regarding its formulation and solution algerian Recently, with its promise for In(Intelligent Transportation System) and GIS(Geographic Information System) applications, DTA have received increasing attention. This potential also implies higher requirement for DTA modeling, especially regarding its solution efficiency for real-time implementation. But DTA have many mathematical difficulties in searching process due to the complexity of spatial and temporal variables. Although many solution algorithms have been studied, conventional methods cannot iud the solution in case that objective function or constraints is not convex. In this paper, the genetic algorithm to find the solution of DTA is applied and the Merchant-Nemhauser model is used as DTA model because it has a nonconvex constraint set. To handle the nonconvex constraint set the GENOCOP III system which is a kind of the genetic algorithm is used in this study. Results for the sample network have been compared with the results of conventional method.