• Korean Security Journal
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• no.47
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• pp.7-36
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• 2016

The security providers industry, often referred to as an industry with unconfined growth ceiling, has entered a remarkable mass-growth phase since the 1980. In the modern era, private-sector security increasingly cover functions relating to general security awareness (including counter-terrorism) in partnership with State bodies, and the scale of operations continue to accelerate, relative to the expanding roles. In the era of pluralisation of policing, there has been widening efforts pursued to develop a range of regulatory strategies internationally in order to manage such growth and development. To date, in South Korea, a diverse set of industry review studies have been conducted. However, the analyses have been conventionally confined to North America, Britain, Germany and Japan, while developments in other world regions remain unassessed. This article is intended to inform the drivers and determinants of regulatory reforms in Australia, and examine the effectiveness of the main pillars of licensing innovations. Over the past decades, the Australian regime has undergone a wave of reforms in response to emerging issues, and in recognition of the industry as a 'public good' due to underpopulation density and the resulting security challenges. The focus of review in this study was on providing a detailed review of the regulatory approach taken by Australia that has expanded police-private security co-operation since the 1980s. The emphasis was on examining the core pillars of risk management strategies and oversight practices progressed to date and evaluating areas of possible improvement in regulation relative to South Korea. Overall, this study has identified three key features of Australian regime: (1) close checks on questionable close associates (including fingerprinting), (2) power of inspection and seizure without search warrant, (3) the 'three strikes' scheme. The rise of the private security presence in day-to-day policing operations means that industry warrant some intervening government-sponsored initiative. The overall lessons learnt from the Australian case was taken into account in determining the following checks and balances that would provide the ideal setting for the best-practice arrangement: (1) regulatory measure should be evaluated against a set of well-defined indicators, such as the merits of different enforcement tools for each given risk, (2) information about regulatory impacts should be analysed by a specialist research institute, (3) regulators should be innovative in applying a range of strategies available to them by employing a mixture of compliance promotional strategies, and adjust the mix as required.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.54-75
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• 2011

PoC(Push-to-talk Over Cellular) is an integrated technology of group voice calls, video calls and internet based multimedia services. If a PoC user can not participate in the PoC session for various reasons such as an emergency situation, lack of battery capacity, then the user can use the PoC Box which has a similar functionality to the MM Box in the MMS(Multimedia Messaging Service). The RTSP(Real-Time Streaming Protocol) method is recommended to be used when there is a transmission session between the PoC box and a terminal. Since the existing VOD service uses a wired network, the packet size of RTSP-based VOD service is huge, however, the PoC service has wireless communication environments which have general characteristics to be used in RTSP method. Packet loss in a wired communication environments is relatively less than that in wireless communication environment, therefore, a buffering latency occurs in PoC service due to a play-out delay which means an asynchronous play of audio & video contents. Those problems make a user to be difficult to find the information they want when the media contents are played-out. In this paper, the following techniques and methods were proposed and their performance and superiority were verified through testing: cross-over dual reception buffering technique, advance partition multi-reception buffering technique, and on-demand multi-reception buffering technique, which are designed for effective picking up of information in media content being transmitted in short amount of time using RTSP when a user searches for media, as well as for reduction in playback delay; and same-priority packetization transmission method and priority-based packetization transmission method, which are media data packetization methods for transmission. From the simulation of functional evaluation, we could find that the proposed multiple receiving buffering and packetizing methods are superior, with respect to the media retrieval inclination, to the existing single receiving buffering method by 6-9 points from the viewpoint of effectiveness and excellence. Among them, especially, on-demand multiple receiving buffering technology with same-priority packetization transmission method is able to manage the media search inclination promptly to the requests of users by showing superiority of 3-24 points above compared to other combination methods. In addition, users could find the information they want much quickly since large amount of informations are received in a focused media retrieval period within a short time.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.111-125
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• 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 Nuclear Medicine
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• v.18 no.2
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• pp.17-23
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• 1984

For nearly a century it has been known that chemical activity accompanies mental activity, but only recently has it been possible to begin to examine its exact nature. Positron-emitting radioactive tracers have made it possible to study the chemistry of the human mind in health and disease, using chiefly cyclotron-produced radionuclides, carbon-11, fluorine-18 and oxygen-15. It is now well established that measurable increases in regional cerebral blood flow, glucose and oxygen metabolism accompany the mental functions of perception, cognition, emotion and motion. On May 25, 1983 the first imaging of a neuroreceptor in the human brain was accomplished with carbon-11 methyl spiperone, a ligand that binds preferentially to dopamine-2 receptors, 80% of which are located in the caudate nucleus and putamen. Quantitative imaging of serotonin-2, opiate, benzodiazapine and muscarinic cholinergic receptors has subsequently been accomplished. In studies of normal men and women, it has been found that dopamine and serotonin receptor activity decreases dramatically with age, such a decrease being more pronounced in men than in women and greater in the case of dopamine receptors than serotonin-2 receptors. Preliminary studies in patients with neuropsychiatric disorders suggests that dopamine-2 receptor activity is diminished in the caudate nucleus of patients with Huntington's disease. Positron tomography permits quantitative assay of picomolar quantities of neuro-receptors within the living human brain. Studies of patients with Parkinson's disease, Alzheimer's disease, depression, anxiety, schizophrenia, acute and chronic pain states and drug addiction are now in progress. The growth of any scientific field is based on a paradigm or set of ideas that the community of scientists accepts. The unifying principle of nuclear medicine is the tracer principle applied to the study of human disease. Nineteen hundred and sixty-three was a landmark year in which technetium-99m and the Anger camera combined to move the field from its latent stage into a second stage characterized by exponential growth within the framework of the paradigm. The third stage, characterized by gradually declining growth, began in 1973. Faced with competing advances, such as computed tomography and ultrasonography, proponents and participants in the field of nuclear medicine began to search for greener pastures or to pursue narrow sub-specialties. Research became characterized by refinements of existing techniques. In 1983 nuclear medicine experienced what could be a profound change. A new paradigm was born when it was demonstrated that, despite their extremely low chemical concentrations, in the picomolar range, it was possible to image and quantify the distribution of receptors in the human body. Thus, nuclear medicine was able to move beyond physiology into biochemistry and pharmacology. Fundamental to the science of pharmacology is the concept that many drugs and endogenous substances, such as neurotransmitters, react with specific macromolecules that mediate their pharmacologic actions. Such receptors are usually identified in the study of excised tissues, cells or cell membranes, or in autoradiographic studies in animals. The first imaging and quantification of a neuroreceptor in a living human being was performed on May 25, 1983 and reported in the September 23, 1983 issue of SCIENCE. The study involved the development and use of carbon-11 N-methyl spiperone (NMSP), a drug with a high affinity for dopamine receptors. Since then, studies of dopamine and serotonin receptors have been carried out in over 100 normal persons or patients with various neuropsychiatric disorders. Exactly one year later, the first imaging of opitate receptors in a living human being was performed [1].

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Spatial Information Research
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• v.22 no.1
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• pp.55-63
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• 2014

Near surface air temperature data which are one of the essential factors in hydrology, meteorology and climatology, have drawn a substantial amount of attention from various academic domains and societies. Meteorological observations, however, have high spatio-temporal constraints with the limits in the number and distribution over the earth surface. To overcome such limits, many studies have sought to estimate the near surface air temperature from satellite image data at a regional or continental scale with simple regression methods. Alternatively, we applied various Kriging methods such as ordinary Kriging, universal Kriging, Cokriging, Regression Kriging in search of an optimal estimation method based on near surface air temperature data observed from automatic weather stations (AWS) in South Korea throughout 2010 (365 days) and MODIS land surface temperature (LST) data (MOD11A1, 365 images). Due to high spatial heterogeneity, auxiliary data have been also analyzed such as land cover, DEM (digital elevation model) to consider factors that can affect near surface air temperature. Prior to the main estimation, we calculated root mean square error (RMSE) of temperature differences from the 365-days LST and AWS data by season and landcover. The results show that the coefficient of variation (CV) of RMSE by season is 0.86, but the equivalent value of CV by landcover is 0.00746. Seasonal differences between LST and AWS data were greater than that those by landcover. Seasonal RMSE was the lowest in winter (3.72). The results from a linear regression analysis for examining the relationship among AWS, LST, and auxiliary data show that the coefficient of determination was the highest in winter (0.818) but the lowest in summer (0.078), thereby indicating a significant level of seasonal variation. Based on these results, we utilized a variety of Kriging techniques to estimate the surface temperature. The results of cross-validation in each Kriging model show that the measure of model accuracy was 1.71, 1.71, 1.848, and 1.630 for universal Kriging, ordinary Kriging, cokriging, and regression Kriging, respectively. The estimates from regression Kriging thus proved to be the most accurate among the Kriging methods compared.

• Korean Security Journal
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• no.31
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• pp.73-100
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• 2012

Republic of Korea for the last 2012 nuclear security summit in Seoul in three days from March 26, has held great success. This industry watchers at home and abroad through professional meetings and private organizations to promote global nuclear security was intended to draw, for the preparation of this event the most important one of the things that should be addressed at the meeting was over the top guard. The national guard of heads of state and nationally significant as the important issues should be dealt with. So who is responsible for national security summit national guard for a successful guard against participants should have a higher understanding, these stories ever to be dealt with important security subjects is the psychological state of cognition. This study is currently a source of honor to escort the psychological state of subjects, and whether the search as I looked at cognition. Qualitative research methods to conduct research in-depth interview technique was used for one of the transcribed data analysis program, a non-quantitative data were analyzed using NVivo 8. As a result of this study, analysis of the problem compared with the usual methods 39 (72.2%), fine-grained observation and 15 (27.7%), through the media how cognition 41 (73.2%), marginal help of 15 (26.7%) were. The usual comparison with how honored Issue sources to detect security of those words and actions and facial expressions, etc. Security of subjects over the state of mind cognition that he, detailed observation of the national guard to security subjects the psychological state of cognition which are pre-Thorough Information subjects that can have all the information about security and the state can be obtained by saying that. Media coverage through a cognitive approach national guard of the media coverage to understand the security subjects of the political situation to understand the prerequisite that were marginal for help through the cognitive approach of security subjects surrounding the execution of security workers, Secretary in charge of protocol and security, and be propagated through the selection techniques to be utilized was that.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.12 no.2
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• pp.163-170
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• 2009

Purpose: Intussusception is the most common cause of intestinal obstruction in young children. Although intussusceptions are easily treated, some intussusceptions with or without a pathologic lead point (PLP) often recur. In this study, we analyzed the clinical characteristics and prognosis of recurrent intussusceptions (RI), the frequency of the PLP, and correlation between RI with PLP. Methods: The medical records of 144 patients, among 590 patients with intussusceptions who had been admitted to the Department of Pediatrics and Pediatric Surgery of Dankook University Hospital between May 1994 and June 2009 were reviewed retrospectively. Results: The overall recurrence rate of intussusceptions in this study was 9.2%. The mean interval between the initial occurrence and the first recurrent attack was 130${\pm}$175 days (range, 12 hours to 3 years). There was no statistically significant difference in the recurrence rate among patients who underwent air, barium, and manual reduction (p=0.131). Eighty-seven cases (92.6%) of RI had a successful reduction by the use of non-operative techniques. A PLP was present in 18 patients (3.0%). The most common PLP was intestinal lymphoid hyperplasia, followed by Meckel's diverticulum, duplication cyst, intestinal polyp, and adenomyoma. The mean number of intussusceptions was 4.7${\pm}$1.9 in 7 patients with PLP, which was significantly higher than (2.4${\pm}$0.9) patients without a PLP (p=0.023). The mean duration of recurrences was 17.4${\pm}$19.8 months (range, 2 days to 72 months). Conclusion: A careful search for a PLP should be performed to prevent recurrence of intussusception, especially when intussusception has recurred more than three times.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Korean Security Journal
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• no.29
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• pp.139-162
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• 2011

The purpose of this study is to compare with the general and behavioral characteristics between simple and serial arsonists using the data derived from Scientific Crime Analysis System, Criminal Filing Search System, and Crime Information Management System. The analysis and findings reported here are derived from data extracted from 160 arsonists arrested by police officer. The independent variables included such socio-economic characteristic as arsonists' gender, age, occupation, education level, and previous criminal records of arsonists, and finally the general characteristics of the scene of fire settings. The dependent variable is whether or not serial fire setter. To achieve the purpose, the analysis of frequencies and cross-tab were conducted. According to frequence and cross-tab analysis, there are great differences of the general and behavior characteristics between two groups. In the comparison of simple and serial arsonists, serial arsonists are more likely to have previous criminal records, low socio-economic status, unmarried and no cohabitants than simple arsonists. furthermore, serial arsonists are more likely to use garbage papers for fire setting in the scene of the crime, to have mental or psychological problems, and to get involved in fire setting for the psychological pleasure than simple arsonists do. The present research has some obvious limitations. First, the analysis is based only on arsonists arrested by police officers. These may be considerable differences in arsonists arrested by police officers and fire setters not arrested by them. Additional research is needed to assess the extent to which these findings would apply to fire setters not arrested by police officer in Korea. Secondly, the data in this study are cross-sectional and simple cross-tab analysis are used. Potential limitation of cross-sectional data concerns the inability to specify the changes in measures as arsonists behavioral characteristics. Therefore, further studies need to use longitudinal data and more complicate statistical techniques such as correlation analysis, multiple regression analysis, or LISREL models to specify the casual relationships between dependent and independent variables for fire settings. Even if this study has some limitations, it is meaningful in which it first investigated the comparison of simple and serial arsonists focusing on the general and behavioral characteristics between two groups in Korea.