• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.815-824
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• 2013

Traditional Pearson chi-squared test is not appropriate for the data collected by the complex sample design. When one uses the traditional Pearson chi-squared test to the complex sample categorical data, it may give wrong test results, and the error may occur not only due to the biased variance estimators but also due to the biased point estimators of cell proportions. In this study, the design based consistent Wald test statistics was derived for k-population homogeneity test, and the traditional Pearson chi-squared test statistics was partitioned into three parts according to the causes of error; the error due to the bias of variance estimator, the error due to the bias of cell proportion estimator, and the unseparated error due to the both bias of variance estimator and bias of cell proportion estimator. An analysis was conducted for empirical results of the relative size of each error component to the Pearson chi-squared test statistics. The second year data from the fourth Korean national health and nutrition examination survey (KNHANES, IV-2) was used for the analysis. The empirical results show that the relative size of error from the bias of variance estimator was relatively larger than the size of error from the bias of cell proportion estimator, but its degrees were different variable by variable.

• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.229-236
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• 2010

With an increasing number of documents in the Internet or enterprises, it becomes crucial to efficiently support users' queries on those documents. In that situation, the full-text search technique is accepted in general, because it can answer uncontrolled ad-hoc queries by automatically indexing all the keywords found in the documents. The size of index files made for full-text searches grows with the increasing number of indexed documents, and thus the disk cost may be too large to process multi-keyword queries against those enlarged index files. To solve the problem, we propose both of the index file structure and its management scheme suitable to the processing of multi-keyword queries against a large volume of index files. For this, we adopt the structure of inverted-files, which are widely used in the multi-keyword searches, as a basic index structure and modify it to a hierarchical structure for join operations and ranking operations performed during the query processing. In order to save disk costs based on that index structure, we dynamically store in the main memory the results of join operations between two keywords, if they are highly expected to be entered in users' queries. We also do performance comparisons using a cost model of the disk to show the performance advantage of the proposed scheme.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.309-319
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• 2016

There is a need to develop a data quality management algorithm in order to improve the quality of health care data. In this study, we developed a data quality control algorithms associated diseases related to diabetes in patients with hypertension. To make a data quality algorithm, we extracted hypertension patients from 2011 and 2012 discharge damage survey data. As the result of developing Data quality management algorithm, significant factors in hypertension patients with diabetes are gender, age, Glomerular disorders in diabetes mellitus, Diabetic retinopathy, Diabetic polyneuropathy, Closed [percutaneous] [needle] biopsy of kidney. Depending on the decision tree results, we defined Outlier which was probability values associated with a patient having diabetes corporal with hypertension or more than 80%, or not more than 20%, and found six groups with extreme values for diabetes accompanying hypertension patients. Thus there is a need to check the actual data contained in the Outlier(extreme value) groups to improve the quality of the data.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.113-119
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• 2017

The purpose of this study is to examine whether the enhancement of convergent job competence of social worker working in a social welfare facility affects the quality of life. In order to achieve the purpose of the study, we surveyed 20 social welfare workers working in 20 social welfare facilities in Gyeonggi area and used 188 pieces collected. The random sampling method was used for the sampling method. As a result, there was a positive correlation between personal competence and satisfaction, environmental competence and dissatisfaction, relationship competence and satisfaction in social workers' competence enhancement and quality of life. And social competence's individual competence and environmental competence play a positive role in dissatisfaction. Also, it can be seen that the relationship competency plays a negative role in dissatisfaction. The degree of individual competence, the ability to control the mind to turnover, and the relationship capacity play a positive role in satisfaction. Therefore, in order to improve the quality of life of the social welfare workers, it is expected that there will be a positive effect in implementing the job capacity enhancement education program for the social welfare workers.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1290-1298
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• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics, and uses the information to the next decoding step Turbo Code shows excellent performance, approaching Shannon Limit at the view of BER, when the size of Interleaver is big and iterate decoding is run enough. But it has the problems which are increased complexity and delay and difficulty of real-time processing due to Interleaver and iterate decoding. In this paper, it is analyzed that MAP(maximum a posteriori) algorithm which is used as one of Turbo Code decoding, and the factor which determines its performance. MAP algorithm proceeds iterate decoding by determining soft decision value through the environment and transition probability between all adjacent bits and received symbols. Therefore, to improve the performance of MAP algorithm, the trust between adjacent received symbols must be ensured. However, MAP algorithm itself, can not do any action for ensuring so the conclusion is that it is needed more algorithm, so to decrease iterate decoding. Consequently, MAP algorithm and Turbo Code performance are analyzed in the nongaussian channel applying Robust equalization technique in order to input more trusted information into MAP algorithm for the received symbols.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.725-734
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• 2017

The main purpose of this study is to analyze runoff aggregation structure and energy expenditure pattern of Choyang creek basin within the framework of power law distribution. To this end geomorphologic factors of every point in the basin of interest, which define tractive force and stream power as well as drainage area, are extracted based on GIS, and their complementary cumulative distributions are graphically analyzed through fitting them to power law distribution. The results indicate that three distinct behavioral regimes are observed from the complementary cumulative distributions of three geomorphogic factors. Based on the parameter estimation of power law distribution by maximum likelihood drainage area and stream power can be judged as scale invariance factor without finite scale while tractive force as scale dependence factor with finite scale. Furthermore, it is judged that tractive force would not follow power law distribution because it shows limited complex system behaviors only within the small extent of scale. The exponent of power law distribution for drainage area obtained in this study by maximum likelihood is larger than the previous researches due to the difference of parameter estimation methodologies. And the exponent for stream power is smaller than the previous researches due to the scaling property of channel slope for the basin of interest.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.105-114
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• 2013

Recently, Due to Climate change, extreme rainfall occurs frequently. In many preceding studies, Because of extreme hydrological events changes, it is expected that peak flood Magnitude and frequency of drainage infrastructures changes. However, at present, probability rainfall in the drainage facilities design is assumed to Stationary which are not effected from climate change and long-term fluctuation. In the future, flood control safety standard should be reconsidered about the valid viewpoint. In this paper, in order to assess impact of climate change on drainage system, Future climate change information has been extracted from RCP 8.5 Climate Change Scenario for IPCC AR5, then estimated the design rainfall for various durations at return periods. Finally, the design flood estimated through the HEC-HMS Model which is being widely used in the practices, estimated the effect of climate change on the Design Flood of Mihochen basin. The results suggested that the Design Flood increase by climate change. Due to this, the Flood risk of Mihochen basin can be identified to increase comparing the present status.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.585-595
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• 2017

This study investigates how the emotion-based learning motivation enhancement program influences learning motivation and social support of college students. The developed final program consists of Learning Motivation I, Learning Coaching, and Learning Motivation II, which has 12 sessions. In each session, every student was guided to have reflection time by writing self-evaluation and reflection paper. The participants were 38 students majoring in engineering at K-college located in G city who took one liberal arts subject based on psychology during the 1st semester in 2016 and who were divided into an experimental group (19 students) and a control group (19 students) by non-probability sampling method. In the experimental group, emotion-based learning motivation enhancement program was totally processed 12 times, one class in a week, by one main lecturer and one assistant lecturer. For data analysis, independent sample t-tests, paired samples t-tests, and review analysis were conducted. The study results are as follows. First, the experimental group participating in emotion-based learning motivation enhancement program had more significant differences in learning motivation, and both self-confidence and self-contentment among sub-components than the control group. Second, the experimental group had no significant differences in social support, compared with the control group. The impression writing analysis of the experimental group showed that this program affected learning motivation and social support. Lastly, the study discussions and implications are described.