• Journal of Korean Ophthalmic Optics Society
• /
• v.14 no.4
• /
• pp.65-69
• /
• 2009

Purpose: Recently incidence of VDT syndrome has gradually increased as extensive use of computers. VDT syndrome reported by VDT workers include musculoskeletal disorder, neuropsychiatric disoders and eye symptoms such as eye strain, tired eyes, irritation and blurred vision. The environmental factors of VDT syndrome include electromagnetic waves, size, brightness and lighting of computer screen, height of a monitor and a worktable, working hours, kind of task, distance between screen and workers, indoor humidity and temperature, indoor air contamination and ventilation. In this study, we investigated the environmental factors related to body symptoms and health effects included in VDT syndrome. Methods: Study subjects were total 120 persons (54 male, 66 female) with age from 19 to 28. We surveyed the body symptoms and physical discomfort when doing an activity in a short distance such as reading book or paper, computer work. The questionnaire included main body symptoms, self-consciousness symptoms of eye, satisfaction of working environment, pain of the wrist when using keyboard and mouse. Results: Most of people (70%) felt physical pain from long time work of computer, paper, electrical apparatus. They mainly complained pain of neck and low back (57.1%), eye (45.2%) and head (31%). With the environmental factors, 78.3% of the subjects complaint pain of eye from inappropriate illumination. Most of the symptoms included 'eye fatigue'(38.3%), 'dryness of eye'(31.9%) and 'blurred vision'(23.7%). Subjects in this study complained discomfort of their chairs and most of them experienced pain in the wrist when using keyboard or mouse. Conclusions: When people use electrical apparatus or work with paper, people would get their eye fatigue and feeling of physical fatigue because of not harmonizing various environmental factors such as light, space, posture, worktable with theirselves. Therefore, workers should develop preventive method such as self-control of adequate break time to avoid fatigue while VDT work. Work environment should be changed to ergonomic design for optimal visual environment to prevent musculoskeletal disorder through constant research.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.31 no.1
• /
• pp.28-37
• /
• 2013

As a symbolic landscape of Seoul, Namsan has undergone not only physical changes but also changes in its human use and characteristics. At this point, research on Namsan, which holds diverse stories that have accumulated over a long period, as a cultural landscape is necessary. In particular, a concrete understanding of the characteristics of the mountain's use in the period of its initiation as a modern park is an important task in research on the history of urban parks. Consequently, the purpose of the present study lies in grasping the use of Namsan at the time of the establishment of Kyongsungbu Namsan Park Design Proposal in 1917 and examining the characteristics per space. The research process was based on the status of the park design plan. The primary source of information came from the analysis of historical newspaper articles. Additional materials including documents, old maps, photographs, postcard materials were also used. The period of the study was 1883 to 1917. This time was the initial period of Namsan Park soon after the opening up of Korea's ports to the world. The major spaces in which Namsan was used as a park encompassed Hanyang Park, Waeseongdae Park, Noin-jeong, Jangchung-dan, and remaining parts of Namsan in a natural state. When the main ways in which each space is used are examined based on the data analyzed, Namsan has been used for purposes including public events, accidents, religious worship, track and field days, field trips, and strolls. When the nature of each of the spaces is determined in terms of the characteristics of their use, these spaces were characterized as community parks, outdoor community spaces, indoor community spaces, sports arenas, and natural parks, among other things. The present study is significant in terms of research on the history of parks for confirming that Namsan in the initial period already served as a modern park for urban activities and grasping the specific urban activities that were engaged in on Namsan.

• Current Research on Agriculture and Life Sciences
• /
• v.8
• /
• pp.129-138
• /
• 1990

This study investigated the relationship between the cutflow of rural population and agricultural policy by using time series method. For the analytical tools, decomposition time series methods and regression technique were employed in computing seasonal fluctuation and cyclical fluctuation of population migration. Also, this study predicted farmhouse, rural population till the 2000's by means of the mathematical methods. The analytical forms employed in forecasting farmhouse, rural population were Exponential curve, Gompertz curve and Transcendental form. The major findings of this study were identified as follows: 1) Rural population and farmhouse population began to decrease from 1965 and hastily went down since 1975. Rural population which accounted for 36.4 percent, 35.6 percent of national population respectively in 1960 diminished about two times: 17.5 percent, 17.1 percent respectively. 2) The rapid decreasing of the rural population was caused because of the outflow of rural people to the urban regions. Of course, that was also caused from the natural decreases but the main reason was heavily affected more the former than the latter. In the outflowing course shaped from rural to the urban regions, rural people concentrated on such metropolis as Seoul, Pusan, Keanggi. But these trends were diminishing slowly. On the other hand, compared with that of the 1970's the migration to Keanggi was still increasing in the 1980's. That is, people altered the way of migration from the migration to Seoul, Pusan to the migration to the out-skirts of Seoul. 3) The seasonal fluctuation index of population migration has gone down since the June which the request of agricultural labor force increases and has turned to be greatly wanted in the March as result of decomposition time series method. As result of cyclical analysis, the cyclical patterns of migration have greatly 7 cycle. 4) As result of forecasting the rural and farmhouse population, rural and farmhouse population in the 2000 will be about 9,655(thousand/people) and 4,429(thousand/people) respectively. Thus, it is important to analyze the probloms that rural and farmhouse population will decrease or increase by the degree. But fairly defining the agricultural into a industry that supply the food, this problem - how much our nation need the rural and farmhouse population - is greatly significant too. Therefore, the basic problems of the agricultural including the outflows of rural people are the earning differentials between rural and urban regions. And we should regard the problems of the gap of relative incomes between rural and urban regions as the main task of the agricultural policy and treat the agricultural policy in the viewpoint of developing economic equilibrium than efficiency by using actively the natural resources of the rural regions.

• Journal of Distribution Science
• /
• v.9 no.4
• /
• pp.63-73
• /
• 2011

The relationship between buyers and sellers is changing into a long-term relationship. A number of distribution channel researchers have determined that the behavior of distribution channel members can be characterized by relational exchanges. The members of relational distribution channels may be perceived as strategic partners; however, even within these arrangements, member asymmetries may exist, which can create unequal distributions of power and dependence. Thus, as all distribution channel members may not be equal in power, it is possible that a less-dependent channel leader may emerge. Therefore, leadership in distribution channels is a very important variable. Distribution channel leadership can be defined as the activities undertaken by the distribution channel leader to influence the marketing programs and strategies of channel members. A distribution channel's performance is influenced by the leadership style of the channel leader. Although research on channel leadership styles can be broadly categorized, many researchers have dealt with analyzing distribution channel leadership by using the power-influence approach, which includes looking at variables, such as power, power base, and influence strategies. Moreover, they have examined the direct relationship between leadership styles and performance. Many distribution channel scholars have attempted to justify the application of leadership styles identified in alternative leadership theories to the inter-organizational context of distribution channels. They have made suggestions regarding how great the usefulness of leadership style as a strategy is to secure the compliance of distribution channel members and have conceptually and empirically linked it to channel-related phenomena, such as manifest conflict, cooperation, channel efficiency, and effectiveness. However, as few empirical studies have examined the antecedents and consequences of leadership styles, research on leadership style can be considered nascent. Thus, it is required to investigate the antecedents and consequences of the leadership style of a distribution channel leader. This study aims to empirically identify whether there are influences of the antecedents of leadership on two different leadership styles, and to reveal whether these leadership styles induce any consequences. The research subjects were 220 franchisees. Research findings are as follows: First, the results show a positive effect of technological capability on transformational relationships. However, it does not have a significant effect on transactional leadership. Second, innovation-oriented organizational culture has negatively influenced both leaderships. However, task-oriented organizational culture positively and significantly influenced both forms of leadership. Third, the ethics of leaders has influenced both leadership styles positively and significantly. Fourth, regarding consequences, transformational leadership strengthens financial performances, whereas it weakens relational citizenship behaviors. However, transactional leadership positively influences relational citizenship behavior whilst negatively affecting financial performance.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.131-146
• /
• 2011

It is becoming more essential than ever for office professionals to become competent in information collection/gathering and problem solving in today's global business society. In particular, office professionals do not only assist simple chores but are also forced to make decisions as quickly and efficiently as possible in problematic situations that can end in either profit or loss to their company. Since office professionals rely heavily on their tacit knowledge to solve problems that arise in everyday business situations, it is truly helpful and efficient to refer to similar business cases from the past and share or reuse such previous business knowledge for better performance results. Case-based reasoning(CBR) is a problem-solving method which utilizes previous similar cases to solve problems. Through CBR, the closest case to the current business situation can be searched and retrieved from the case or knowledge base and can be referred to for a new solution. This reduces the time and resources needed and increase success probability. The main purpose of this study is to design a system called COKRS(Case-based reasoning Office Knowledge Recommender System) and develop a prototype for it. COKRS manages cases and their meta data, accepts key words from the user and searches the casebase for the most similar past case to the input keyword, and communicates with users to collect information about the quality of the case provided and continuously apply the information to update values on the similarity table. Core concepts like system architecture, definition of a case, meta database, similarity table have been introduced, and also an algorithm to retrieve all similar cases from past work history has also been proposed. In this research, a case is best defined as a work experience in office administration. However, defining a case in office administration was not an easy task in reality. We surveyed 10 office professionals in order to get an idea of how to define a case in office administration and found out that in most cases any type of office work is to be recorded digitally and/or non-digitally. Therefore, we have defined a record or document case as for COKRS. Similarity table was composed of items of the result of job analysis for office professionals conducted in a previous research. Values between items of the similarity table were initially set to those from researchers' experiences and literature review. The results of this study could also be utilized in other areas of business for knowledge sharing wherever it is necessary and beneficial to share and learn from past experiences. We expect this research to be a reference for researchers and developers who are in this area or interested in office knowledge recommendation system based on CBR. Focus group interview(FGI) was conducted with ten administrative assistants carefully selected from various areas of business. They were given a chance to try out COKRS in an actual work setting and make some suggestions for future improvement. FGI has identified the user-interface for saving and searching cases for keywords as the most positive aspect of COKRS, and has identified the most urgently needed improvement as transforming tacit knowledge and knowhow into recorded documents more efficiently. Also, the focus group has mentioned that it is essential to secure enough support, encouragement, and reward from the company and promote positive attitude and atmosphere for knowledge sharing for everybody's benefit in the company.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.21-44
• /
• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.23-45
• /
• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• The Journal of Korean Society for Radiation Therapy
• /
• v.31 no.2
• /
• pp.13-24
• /
• 2019

Purpose: CT scan range is insufficient for various reasons in head and neck Tomotherapy^®. To solve that problem, Re-CT simulation is good because CT scan range affects accurate dose calculations, but there are problems such as increased exposure dose, inconvenience, and a change in treatment schedule. We would like to evaluate the minimum CT scan range required by changing the plan setup parameter of the existing CT scan range. Materials and methods: CT Simulator(Discovery CT590 RT, GE, USA) and In House Head & Neck Phantom are used, CT image was acquired by increasing the image range from 0.25cm to 3.0cm at the end of the target. The target and normal organs were registered in the Head & Neck Phantom and the treatment plan was designed using ACCURAY Precision^®. Prescription doses are Daily 2.2Gy, 27 Fxs, Total Dose 59.4Gy. Target is designed to 95%~107% of prescription dose and normal organ dose is designed according to SMC Protocol. Under the same treatment plan conditions, Treatment plans were designed by using five methods(Fixed-1cm, Fixed-2.5cm, Fixed-5cm, Dynamic-2.5cm Dynamic-5cm) and two pitches(0.43, 0.287). The accuracy of dose delivery for each treatment plan was analyzed by using EBT3 film and RIT(Complete Version 6.7, RIT, USA). Results: The accurate treatment plan that satisfying the prescribed dose of Target and the tolerance dose in normal organs(SMC Protocol) require scan range of at least 0.25cm for Fixed-1cm, 0.75cm for Fixed-2.5cm, 1cm for Dynamic-2.5cm, and 1.75cm for Fixed-5cm and Dynamic-5cm. As a result of AnalysisAnalysis by RIT. The accuracy of dose delivery was less than 3% error in the treatment plan that satisfied the SMC Protocol. Conclusion: In case of insufficient CT scan range in head and neck Tomotherapy^®, It was possible to make an accurate treatment plan by adjusting the FW among the setup parameter. If the parameter recommended by this author is applied according to CT scan range and is decide whether to re-CT or not, the efficiency of the task and the exposure dose of the patient are reduced.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.12
• /
• pp.292-300
• /
• 2016

The purpose of this study was to investigate the effects of case-based learning about infants and toddlers on healthcare department students, using a video in an emergency care environment. A total of 57 students from a healthcare department of D university in J city were enrolled. They were divided into two groups: The experimental group (n=29) and the control group (n=28). This study is pre-post designed with a non-equivalent control group. The experimental group received a 1-week education for a duration of 3 weeks (3 sessions in total) with 180 minutes per session. The control group received a traditional curriculum of lecture. Before and after the education, we measured the knowledge and skill confidence of emergency care toward infants and toddlers, the academic self-efficacy, and problem solving ability. Data collection and intervention were carried out from November to December of 2014. Data were analyzed with x2-test, paired t-test, unpaired t-test with SPSS version 20.0 Program. The experimental group showed a significantly higher improvement of skill confidence of emergency care toward infants and toddlers (P<001), as well as preferred task difficulty among sub-items of academic self-efficacy (p=.029), approach avoidance style (P=.001), and problem solving confidence (p=.040) among sub-items of problem solving ability on preference compared with the control group. In this study, a case-based learning was verified to be an effective teaching method to enhance professional competency of healthcare department students. The findings from this study suggest that a case-based learning using various educational contents should be developed, expanded, and carried out to promote better learning.

• Journal of radiological science and technology
• /
• v.32 no.1
• /
• pp.87-93
• /
• 2009

Background/aim : Atherosclerotic disease at the origin of the vertebral arteries is one of the risk factors for vertebrobasilar ischemic disease. Assessment and visualization of the origin of the vertebral arteries with color doppler sonography is a non-trivial task. The aim of this study is to increase the visualization rate of the origin of the vertebral arteries with color doppler sonography. Materials and Methods : Color doppler sonography for the vertebral arteries included carotid arteries was performed to 198 patients. We first examined the vertebral artery in the upper neck in the direction of the subclavian artery to distinguish its origin more easily. If the vertebral artery origin was not visualized in natural position, the examiner pushed the transducer toward a clavicle or pushed the shoulder of patient by the other hand. The technical methods for visualization of the vertebral artery origin were classified into three grades: natural position, pushing the transducer, and pushing the shoulder of patient according to the depth (3.0 cm and shallower, deeper than 3.0 cm) of the origin. Results : The origin of the vertebral arteries could be visualized in 97% on the right and in 92% on the left. The origin of the vertebral arteries could be visualized in 98.6%, 1.4%, and 0.0% in natural position, pushing the transducer, and pushing the shoulder of patient, respectively, at shallower than 3.0 cm on the right side. The origin of the vertebral arteries could be visualized in 81.2%, 14.6%, and 4.2% in natural position, pushing the transducer, and pushing the shoulder of patient, respectively, at deeper than 3.0 cm on the right side. The origin of the vertebral arteries could be visualized in 85.4%, 10.7%, and 3.9% in natural position, pushing the transducer, and pushing the shoulder of patient, respectively, at shallower than 3.0 cm on the left side. The origin of the vertebral arteries could be visualized in 55.7%, 30.4%, and 13.9% in natural position, pushing the transducer, and pushing the shoulder of patient, respectively, at deeper than 3.0 cm on the left side. Conclusion : If the examiner pushes the transducer toward a clavicle or pushes the shoulder of patient by the other hand, when the vertebral artery origin during the color doppler sonography is not visualized in natural position, visualization rate of the origin of the both vertebral arteries is increased.