• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.1
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• pp.20-27
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• 2010

This paper describes a design of 5-stage pipelined de-blocking filter with power reduction scheme and proposes a efficient memory architecture and filter order for high performance H.264/AVC Decoder. Generally the de-blocking filter removes block boundary artifacts and enhances image quality. Nevertheless filter has a few disadvantage that it requires a number of memory access and iterated operations because of filter operation for 4 time to one edge. So this paper proposes a optimized filter ordering and efficient hardware architecture for the reduction of memory access and total filter cycles. In proposed filter parallel processing is available because of structured 5-stage pipeline consisted of memory read, threshold decider, pre-calculation, filter operation and write back. Also it can reduce power consumption because it uses a clock gating scheme which disable unnecessary clock switching. Besides total number of filtering cycle is decreased by new filter order. The proposed filter is designed with Verilog-HDL and functionally verified with the whole H.264/AVC decoder using the Modelsim 6.2g simulator. Input vectors are QCIF images generated by JM9.4 standard encoder software. As a result of experiment, it shows that the filter can make about 20% total filter cycles reduction and it requires small transposition buffer size.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.676-693
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• 2016

Although the methodology and models to assess the economic value of technology assets such as patents are being presented in various ways, there does not exist a structured assessment model which enables to objectively assess a database property's value, and thus there is a need to enhance the application feasibility of practical purposes such as licensing of DB assets, commercialization transfer, security, etc., through the establishment of the valuation model and the life-cycle decision logic. In this study, during the valuation process of DB assets, the size of customer demand group expected and the amount of demand, the size and importance of data sets, the approximate degree of database' contribution to the sales performance of a company, the life-cycle of database assets, etc. will be analyzed whether they are appropriate as input variables or not. As for most of DB assets, due to irregular updates there are hardly cases their life-cycle expires, and thus software package's persisting period, ie. 5 years, is often considered the standard. We herein propose the life-cycle estimation logic and valuation models of DB assets based on the concept of half life for DB usage frequency under the condition that DB assets' value decays and there occurs no data update over time.

• Korean Journal of Health Education and Promotion
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• v.21 no.4
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• pp.35-49
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• 2004

The purpose of this study was to analyze variables associated with smoking and selected health behaviors. This study targeted adult men and women over 20 of age. The sample population was drawn from the national sample, and the samples were chosen from the telephone book. A total of 1,500 cases were collected through a telephone based interview survey. As a tool for this study, a structured questionnaire was developed. the variables included self-perceived health status, and selected 7 health behaviors; smoking behavior, physical activities, eating habit, weight control, alcohol consumption, stress management, and cancer exam. The healthy life practice actions of Trans-theoretical model have been classified into five stages. Smokers were more likely than non-smokers to positive attitudes toward smoking and the impact of smoking in this study. This means that smokers's awareness toward the impact of smoking is very week. Smoking behavior was significantly related to other health related behaviors based on the correlation analysis. However, gender, engaging in regular physical activities, moderate consumption of alcoholic beverages, and receiving a cancer examination were the variables that can explain and predict a person's stages of adopting a non-smoking behavior. Self perceived health status was closely related to other health behaviors. Gender, age, and monthly household income were important demographic variables that have significant relationship with the self-perceived health status. Among the health behaviors, regular physical activities and weight control were significant predictable variables. Similar results have been found in the National health and Nutrition examination survey in Korea. As a result of this study, it was found that among the selected health behaviors, engaging in physical activity was an important variable to increase positive sense of health and non-smoking behaviors. Educational and policy level input is needed to increase awareness and provide chances to participate in fitness activities. To those who maintain exercise, the environmental support and diffusion of knowledge information and education data should be strengthened. To change attitudes toward smoking, more in-dept awareness campaign and education should be provided according to people's different behavioral status. In addition, not only diffusing health education data and delivering knowledge information through related programs, but also environmental support system that helps an individual maintain his/her action is required. Such a support system means settlement of the health enhancement base of school, workplace and community should be carried out, and the policy level support and regular programs should be provided and spread to the unit of community.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.600-611
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• 1996

Recently, neural network-based speech recognition has been studied to utilize the adaptivity and learnability of neural network models. However, conventional neural network models have difficulty in the co-articulation processing and the boundary detection of similar phonmes of the Korean speech. Also, in case of using one phonotopic map, learning speed may dramatically increase and inaccuracies may be caused because homogeneous learning and recognition method should be applied for heterogenous data. Hence, in this paper, a neural net typewriter has been designed using a hierarchical self-organizing classifier(HSOC), and related algorithms are presented. This HSOC, during its learing stage, distributed phoneme data on hierarchically structured multiple phonotopic maps, using Kohonen's self-organizing feature maps(SOFM). Presented and experimented in this paper were the algorithms for deciding the number of maps, map sizes, the selection of phonemes and their placement per map, an approapriate learning and preprocessing method per map. If maps are divided according to a priorlinguistic knowledge, we would have difficulty in acquiring linguistic knowledge and how to alpply it(e.g., processing extended phonemes). Contrarily, our HSOC has an advantage that multiple phonotopic maps suitable for given input data are self-organizable. The resulting three korean phonotopic maps are optimally labelled and have their own optimal preprocessing schemes, and also confirm to the conventional linguistic knowledge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.127-136
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• 2020

This study investigated the correlation between the participation in health-related decisions and self-care competency and the factors influencing self-care competence of patients with chronic disease. The participants were 518 patients with chronic illnesses who were admitted to a public health center. Using a structured-questionnaire, the data was collected from January 1, 2019 to 31, 2019. The data was analyzed using descriptive statistics, t-tests, ANOVA, Scheffé tests, Pearson correlation coefficients and multiple linear regression with the IBM SPSS/WIN 22.0 program. The mean scores on the participation in health-related decisions and self-care competency were 3.62±0.20 and 4.57±0.34, respectively. The main variables that distinguish significant differences between participation in healthcare decisions and self-care capabilities are gender, age, education level, diagnosis, and subjective health status. Self-care competency was positively correlated with the participation in health-related decisions (r=.66, p=.043). Factors influencing self-care competence were education (β=-2.23, p<.001), health concerns (β=0.14, p=.003), subjective health statues (β=2.57, p=.011), and age (β=-0.36, p=.048). The input variables explained .56 of self-care competence. The results of the study indicate that approaches focusing on enhancing the participation in health-related decisions could potentially improve self-care competency of patients with chronic disease.

• Therapeutic Science for Rehabilitation
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• v.8 no.1
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• pp.51-62
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• 2019

Objective: To develop and verify the usability of a cognitive rehabilitation system with diverse cognitive functional levels based on tangible objects for the elderly population. Methods: A study was conducted to investigate the system's strengths and weaknesses by upgrading it with responses from two groups of 15 patients and 4 occupational therapists. After undergoing three forms of training - regarding executive function, memory, and concentration for a total of 20-30 min, the participants were asked to answer a structured questionnaire about contents of the three forms of training, hardware including the tablet PC functioning as a CPU and display media and tangible objects, and satisfaction of experiential usage of the system. Results: Both groups responded that the most interesting training area was executive function while the least interesting was concentration. Six participants reported that the size of the screen of the tablet PC was inappropriate, and five responded that the size of the tool was inappropriate. All therapists and 40% of the patients responded that they were satisfied with this system. Conclusion: This system's features include easy manipulation of tangible tools for performing training tasks, easy selection of and training in cognitive areas based on users' needs, and automatic adjustment of difficulty level based on users' performance. The training environment was designed to be similar to the natural environment by using tangible objects in both hands as input devices for the system, and the system was considered as an alternative to the lack of community cognitive rehabilitation specialists.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.104-112
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• 2021

In this study, emotional analysis was conducted based on the basic attribute data of music and the emotional model in psychology, and the result was applied to the visualization rules in the formative arts. In the existing studies using musical parameter, there were many cases with more practical purposes to classify, search, and recommend music for people. In this study, the focus was on enabling sound data to be used as a material for creating artworks and used for aesthetic expression. In order to study the music visualization as an art form, a method that can include human emotions should be designed, which is the characteristics of the arts itself. Therefore, a well-structured basic classification of musical attributes and a classification system on emotions were provided. Also, through the shape, color, and animation of the visual elements, the visualization of the musical elements was performed by reflecting the subdivided input parameters based on emotions. This study can be used as basic data for artists who explore a field of music visualization, and the analysis method and work results for matching emotion-based music components and visualizations will be the basis for automated visualization by artificial intelligence in the future.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.4
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• pp.333-341
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• 2008

Three embankments are located in the Chunggye Bay, each named as Changpo, Bokkil and Kuil and environmental changes are expected due to freshwater input. To investigate this phenomenon, three sample sites in front of each embankment gate were selected in Nov. 2006(autumn), Feb. 2007(winter), May. 2007(spring) and Aug. 2007(summer). At every point of embankment spot, large cells(micro-size, >$20\;{\mu}m$) of phytoplankton were turned out to be a major cause of algal bloom in Feb. 2007 and nano-size($2-20\;{\mu}m$) phytoplankton became dominant during rainy season. In rainy season, each point of embankment showed low salinity and transparency with higher ammonium and phosphorus concentrations than dry season. However, the number of phytoplankton has decreased and it is expected that freshwater influx has more influence on high turbidity and radical decrease of salinity than nutrient. According to the results of this study, therefore, nutrient could have more influence on growth of phytoplankton in dry season, but high turbidity and radical changes of salinity have more influence in rainy season.

• Agribusiness and Information Management
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• v.8 no.1
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• pp.17-26
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• 2016

India is largest producer of banana in the world producing 29.72 million tonnes from an area of 0.803 million ha with a productivity of 35.7 MT ha-1 and accounted for 15.48 and 27.01 per cent of the world's area and production respectively (www.nhb.gov.in). In India, Tamil Nadu leads other states both in terms of area and production followed by Maharashtra, Gujarat and Andhra Pradesh. In Rayalaseema region of Andhra Pradesh, Kurnool district had special reputation in the cultivation of banana in an area of 5765 hectares with an annual production of 2.01 lakh tonnes in the year 2012-13 and hence, it was purposively chosen for the study. On $23^{rd}$ November 2003, the Government of Andhra Pradesh has commenced a comprehensive project called 'Andhra Pradesh Micro Irrigation Project (APMIP)', first of its kind in the world so as to promote water use efficiency. APMIP is offering 100 per cent of subsidy in case of SC, ST and 90 per cent in case of other categories of farmers up to 5.0 acres of land. In case of acreage between 5-10 acres, 70 per cent subsidy and acreage above 10, 50 per cent of subsidy is given to the farmer beneficiaries. The sampling frame consists of Kurnool district, two mandals, four villages and 180 sample farmers comprising of 60 farmers each from Marginal (<1ha), Small (1-2ha) and Other (>2ha) categories. A well structured pre-tested schedule was employed to collect the requisite information pertaining to the performance of drip irrigation among the sample farmers and Data Envelopment Analysis (DEA) model was employed to analyze the performance of drip irrigation in banana farms. The performance of drip irrigation was assessed based on the parameters like: Land Development Works (LDW), Fertigation costs (FC), Volume of water supplied (VWS), Annual maintenance costs of drip irrigation (AMC), Economic Status of the farmer (ES), Crop Productivity (CP) etc. The first four parameters are considered as inputs and last two as outputs for DEA modelling purposes. The findings revealed that, the number of farms operating at CRS are more in number in other farms (46.66%) followed by marginal (45%) and small farms (28.33%). Similarly, regarding the number of farmers operating at VRS, the other farms are again more in number with 61.66 per cent followed by marginal (53.33%) and small farms (35%). With reference to scale efficiency, marginal farms dominate the scenario with 57 per cent followed by others (55%) and small farms (50%). At pooled level, 26.11 per cent of the farms are being operated at CRS with an average technical efficiency score of 0.6138 i.e., 47 out of 180 farms. Nearly 40 per cent of the farmers at pooled level are being operated at VRS with an average technical efficiency score of 0.7241. As regards to scale efficiency, nearly 52 per cent of the farmers (94 out of 180 farmers) at pooled level, either performed at the optimum scale or were close to the optimum scale (farms having scale efficiency values equal to or more than 0.90). Majority of the farms (39.44%) are operating at IRS and only 29 per cent of the farmers are operating at DRS. This signifies that, more resources should be provided to these farms operating at IRS and the same should be decreased towards the farms operating at DRS. Nearly 32 per cent of the farms are operating at CRS indicating efficient utilization of resources. Log linear regression model was used to analyze the major determinants of input use efficiency in banana farms. The input variables considered under DEA model were again considered as influential factors for the CRS obtained for the three categories of farmers. Volume of water supplied ($X_1$) and fertigation cost ($X_2$) are the major determinants of banana farms across all the farmer categories and even at pooled level. In view of their positive influence on the CRS, it is essential to strengthen modern irrigation infrastructure like drip irrigation and offer more fertilizer subsidies to the farmer to enhance the crop production on cost-effective basis in Kurnool district of Andhra Pradesh, India. This study further suggests that, the present era of Information Technology will help the irrigation management in the context of generating new techniques, extension, adoption and information. It will also guide the farmers in irrigation scheduling and quantifying the irrigation water requirements in accordance with the water availability in a particular season. So, it is high time for the Government of India to pay adequate attention towards the applications of 'Information and Communication Technology (ICT) and its applications in irrigation water management' for facilitating the deployment of Decision Supports Systems (DSSs) at various levels of planning and management of water resources in the country.