• Journal of Service Research and Studies
• /
• v.3 no.2
• /
• pp.53-60
• /
• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• Journal of KIISE:Software and Applications
• /
• v.29 no.1_2
• /
• pp.80-90
• /
• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• Korean Journal of Radiology
• /
• v.22 no.7
• /
• pp.1172-1184
• /
• 2021

Objective: The purposes of this study were to analyze the radiation doses for pediatric abdominopelvic and chest CT examinations from university hospitals in Korea and to establish the local diagnostic reference levels (DRLs) based on the body weight and size. Materials and Methods: At seven university hospitals in Korea, 2494 CT examinations of patients aged 15 years or younger (1625 abdominopelvic and 869 chest CT examinations) between January and December 2017 were analyzed in this study. CT scans were transferred to commercial automated dose management software for the analysis after being de-identified. DRLs were calculated after grouping the patients according to the body weight and effective diameter. DRLs were set at the 75th percentile of the distribution of each institution's typical values. Results: For body weights of 5, 15, 30, 50, and 80 kg, DRLs (volume CT dose index [CTDI_vol]) were 1.4, 2.2, 2.7, 4.0, and 4.7 mGy, respectively, for abdominopelvic CT and 1.2, 1.5, 2.3, 3.7, and 5.8 mGy, respectively, for chest CT. For effective diameters of < 13 cm, 14-16 cm, 17-20 cm, 21-24 cm, and > 24 cm, DRLs (size-specific dose estimates [SSDE]) were 4.1, 5.0, 5.7, 7.1, and 7.2 mGy, respectively, for abdominopelvic CT and 2.8, 4.6, 4.3, 5.3, and 7.5 mGy, respectively, for chest CT. SSDE was greater than CTDI_vol in all age groups. Overall, the local DRL was lower than DRLs in previously conducted dose surveys and other countries. Conclusion: Our study set local DRLs in pediatric abdominopelvic and chest CT examinations for the body weight and size. Further research involving more facilities and CT examinations is required to develop national DRLs and update the current DRLs.

• Journal of Korean Neurosurgical Society
• /
• v.63 no.1
• /
• pp.119-135
• /
• 2020

Objective : To investigate the epidemiology of newly-diagnosed, histologically-confirmed (NDHC) central nervous system (CNS) tumours and its changes over a 21-year period in a regional hospital in Hong Kong. Methods : This is a single-institute retrospective descriptive study of patients undergoing surgery for CNS tumours in a regional hospital of Hong Kong in the period from January 1996 to December 2016. The histological definition of CNS tumours was according to the World Health Organization classification, while the site definition for case ascertainment of CNS tumours was as set out by the Central Brain Tumour Registry of the United States. Patients of any age, who had NDHC CNS tumours, either primary or secondary, were included. The following parameters of the patients were retrieved : age at diagnosis, gender, tumour location, and histological diagnosis. Population data were obtained from sources provided by the Government of Hong Kong. The incident rate, estimated by the annual number of cases per 100000 population, for each histology grouping was calculated. Statistical analyses, both including and excluding brain metastases, were performed. Statistical analysis was performed with Microsoft Excel, 2016 (Microsoft, Redmond, WA, USA). Results : Among the 2134 cases of NDHC CNS tumours, there were 1936 cases of intracranial tumours and 198 cases of spinal tumours. The annual number of cases per 100000 population of combined primary intracranial and spinal CNS tumours was 3.6 in 1996, and 11.1 in 2016. Comparing the 5-year average annual number of cases per 100000 population of primary CNS tumours from the period 1996-2000 to 2011-2015, there was an 88% increase, which represent an increase in the absolute number of cases by 4.52 cases/100000 population. This increase was mainly contributed by benign histologies. In the aforementioned periods, meningiomas increased by 1.45 cases/100000 population; schwannomas by 1.05 cases/100000 population, and pituitary adenomas by 0.91 cases/100000 population. While gliomas had a fluctuating 5-year average annual number of cases per 100000 population, it only had an absolute increase of 0.51 cases/100000 population between the 2 periods, which was mainly accounted for by the change in glioblastomas. Conclusion : This retrospective study of CNS tumour epidemiology revealed increasing trends in the incidences of several common CNS tumour histologies in Hong Kong, which agrees with the findings in large-scale studies in Korea and the United States. It is important for different geographic locations to establish their own CNS tumour registry with well-defined and structured data collection and analysis system to meet the international standards.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.2
• /
• pp.713-720
• /
• 2013

The objectives of this study are to identify whether the small area variation also exists in the oriental medicine and, if it exists, what causes, to expand our boundary of research interests on the small area variation observed at the western medicine toward the oriental medicine as one of the fundamental research foundations and to provide any fundamental findings from this study results to the healthcare politicians to promote consumer's rational behaviors for the use of healthcare. This study analyzed the health insurance claim data (2010, 2011) which were the patients of western medicine and the outpatients of the oriental medicine with the top 10 most frequent diseases and looked into the variation of healthcare utilization among the areas after grouping resident area into an 86-area category. The study result shows that the small area variation was also observed at the part of the oriental medicine in which the characteristics of patients critically affect the healthcare expenditure per visit day rather than those of providers and the characteristics of both patients and providers equally affect the healthcare expenditure per patient. Therefore, this study suggests that government set up healthcare policies on the standardization of oriental medicine to prevent its over-utilization and unmet need, enforcing the roles of oriental medicine in the markets, enhancing the appropriate health care utilization, and expanding provision and sharing the health care information to reduce unnecessary health care utilization.

• The Journal of the Korea Contents Association
• /
• v.8 no.1
• /
• pp.68-74
• /
• 2008

Application areas of Knowledge Discovery in Database(KDD) have been expanded to many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not moderate, korean language processing is impossible, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information(KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. KnowledgeMatrix's main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. Matrix generation unit help extract information items which will be analyzed, and calculate occurrence, co-occurrence, proximity of the items. Cluster analysis unit enable matrix data to be clustered by hierarchical or non-hierarchical clustering methods and present tree-type structure of clustered data. Visualization unit offer various methods such as chart, FDP, strategic diagram and PFNet. Data pre-processing unit consists of data import editor, string editor, thesaurus editor, grouping method, field-refining methods and sub-dataset generation methods. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Journal of Home Health Care Nursing
• /
• v.3
• /
• pp.75-85
• /
• 1996

Nursing Intervention Classification(NIC) includes the 433 intervention lists to standardize the nursing language. Efforts to standardize and classify nursing care are important because they make explicit what has previously been implicit, assumed and unknown. NIC is a standardized language of both nurse-initiated and physician-initiated nursing treatments. Each of the 433 interventions has a label, definition and set of activities that a nurse does to carry it out. It defines the interventions performed by all nurses no matter what their setting or specialty. Principles of label, definition and activity construction were established so there is consistency across the classification. NIC was developed for following reasons; 1. Standandization of the nomen clature of nursing treatments. 2. Expansion of nursing knowledge about the links between diagnoses, treatments and outcomes. 3. Devlopment of nursing and health care information systems. 4. Teaching decision making to nursing students. 5. Determination of the costs of service provided by nurses. 6. Planning for resources needed in nursing practice settings. 7. Language to communicate the unigue function of nursing. 8. Articulation with the classification systems of other health care providers. The process of NIC development ; 1. Develop implement and evaluate an expert review process to evaluate feedback on specific interventions in NIC and to refine the interventions and classification as feedback indicates. 2. Define and validate indirect care interventions. 3. Refine, validate and publish the taxonomic grouping for the interventions. 4. Translate the classification into a coding system that can be used for computerization for articulation with other classifications and for reimbursement. 5. Construct an electronic version of NIC to help agencies in corporate the classifiaction into nursing information systems. 6. Implement and evaluate the use of the classification in a nursing information system in five different agencies. 7. Establish mechanisms to build nursing knowledge through the analysis of electronically retrievable clinical data. 8. Publish a second edition of the nursing interventions classification with taxonomic groupings and results of field testing. It is suggested that the following researches are needed to develp NIC in Korea. 1. To idenilfy the intervention lists in Korea. 2. Nursing resources to perform the nursing interventions. 3. Comparative study between Korea and U.S.A. on NIC. 4. Linkage among nursing diagnosis, nursing interventions and nursing outcomes. 5. Linkage between NIC and other health care information systems. 6. determine nursing costs on NIC.

• Knowledge Management Research
• /
• v.18 no.1
• /
• pp.83-116
• /
• 2017

The purpose of this study is to analyze empirically analyze how the characteristics of participants in educational and social learning forums and the quality of events influence expectations and satisfaction of forums. The study also aims to provide strategic implications for forum organizers and give them suggestions on how to set up target audience, manage forum contents, speakers, and services, improve attendee satisfaction, and ultimately maximize overall outcomes. As exchanges among individuals, enterprises, and organizations, as well as countries are growing rapidly, the convention industry has become a key player in the market. Conventions have also become a venue for people to discuss a specific agenda or topic, exchange information and learn knowledge and insights. Especially, the forum - as part of the convention industry - plays a vital role providing educational and social learning opportunities as scholars and expertise come together to share their knowledge and experience through a variety of discussions. With its role, many of forums are taking place in recent years; however, there have been few empirical studies upon the forum itself. Also, there have been few attempts to research how the quality of forums affect participants' satisfaction along with their characteristics and how much of practical knowledge is provided throughout the events. This study is meaningful in that it is the first practical study that takes a deep understanding of the forum and sees how the quality of the forums influences participants' satisfaction and whether the characteristics of participants have a moderating effect in increasing the level of satisfaction. Forum organizers could also take a strategic approach as their major concerns are to increase the number of participants and raise degree of satisfaction by providing significant information. There are four key elements that determine success or failure of a social learning forum. The four elements are contents, speakers, services, and participants. Content plays an important role in providing rich information and knowledge for participants. Speakers are the main knowledge providers who contribute to the forum's social learning role. Also, the services provided by forum organizers such as simultaneous interpretation services, program brochures, lunch and refreshments, and the overall design of event hall can also influence the level of participants' satisfaction. Lastly, the participants and their characteristics are important since they are the ones who receive knowledge from the providers. The results of this study show that the quality of forum (content, speaker, and services) has a decisive effect on the participants' satisfaction and there are some differences in expectation among the participants in the forum. Also, some groups of participants were more likely to be stimulated by the quality of forum when determining their satisfaction. The study is modeled after MBN Y Forum 2016 and its participants' characteristics. The forum is one of the most representative social learning forums of South Korea and its audiences are mostly young people. It has analyzed how the participants' characteristics influence their satisfaction by grouping them into ${\Delta}participants$ who have invited for free and those who paid for the entrance fee, ${\Delta}first-time$ participants and returning participants, ${\Delta}voluntary$ and involuntary participants, ${\Delta}participants$ who registered through web and those who did through mobile, and ${\Delta}participants$ who registered during pre-sale opens and those who registered during general opens.

• The Korean Journal of Financial Management
• /
• v.2 no.1
• /
• pp.55-75
• /
• 1986

This article is to analyse the economic efficiency of capital market, which plays a role of resource allocation in terms of financial claims such as stock and bond. It provides various contributions to the welfare theoretical aspects of modern capital market theory. The key feature that distinguishes the theory described here from traditional welfare theory is the presence of uncertainty. Securities has time dimensions and the state and outcome of the future are really uncertain. This problem resulting from this uncertainty can be solved by complete market, but it has a weak power to explain real stock market. Capital Market is faced with the uncertainity because it is a kind of incomplete market. Individuals and firms in capital market made their consumption-investment decision by their own criteria, i. e. the maximization of expected utility form intertemporal consumption and the maximization of the market value of firm. We noted that allocative decisions that had to be made in the economy could be naturally subdivided into two groups. One set of decisions concerned the allocation of first-period resources among consumption $C_i$, investment in risky firms $I_j$, and riskless investment M. The other decisions concern the distribution among individuals of income available in the second period $Y_i(\theta)$. Corresponing to this grouping, the theoretical analysis of efficiency has also been dichotomized. The optimality of the distribution of output in the second period is distributive efficiency" and the optimality of the allocation of first-period resources is 'the efficiency of investment'. We have found in the distributive efficiency that the conditions for attainability is the same as the conditions for market optimality. The necessary and sufficient conditions for attainability or market optimality is that (1) all utility functions are such that -$\frac{{U_i}^'(Y_i)}{{U_i}^"(Y_i)}={\mu}_i+{\lambda}Y_i$-linear risk tolerance function where the coefficients ${\mu}_i$ and $\lambda$ are independent of $Y_i$, and (2) there are homogeneous expectations, i. e. ${\Large f}_i(\theta)={\Large f}(\theta)$ for every i. On the other hand, the efficiency of investment has disagreement about optimal investment level. The investment level for market rule will not generally lead to Pareto-optimal allocation of investment. This suboptimality is caused by (1)the difference of Diamond's decomposable production function and mean-variance valuation model and (2) the selection of exelusive investment or competitive investment. In conclusion, this article has made an analysis of conditions and processes of Pareto-optimal allocation of resources in capital marker and tried to connect with significant issues in modern finance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.5
• /
• pp.370-376
• /
• 2020

In this study, we consider a group-based random access method for group connection and delivery by grouping devices when H2H devices and large-scale M2M devices coexist in a cell in NB-IoT environment. H2H devices perform individual random access, but M2M devices are grouped according to a NPRACH transmission period, and a leader of each group performs random access. The preamble is allocated using the variable preamble allocation algorithm of the Disjoint Allocation(DA) method. The proposed preamble allocation algorithm is an algorithm that preferentially allocates preambles that maximizes throughput of H2H to H2H devices and allocates the rest to M2M devices. The access distribution of H2H and M2M devices was set as Poisson distribution and Beta distribution, respectively, and throughput, collision probability and resource utilization were analyzed. As the random access transmission slot is repeated, the proposed preamble allocation algorithm decreases the collision probability from 0.93 to 0.83 and 0.79 when the number M2M device groups are 150. In addition, it was found that the amount of increase decreased to 33.7[%], 44.9[%], and 48.6[%] of resource used.