• Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.16-25
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• 2015

Since construction projects are large and complex, it is especially important to provide concurrent construction process to BIM models with construction automation. In particular, the schematic Quantity Take-Off (QTO) estimation on the BIM models is a strategy, which can be used to assist decision making in just minutes, because 70-80% of construction costs are determined by designers' decisions in the early design stage. This paper suggests a QTO process and a QTO prototype system within the building frame of Open BIM to improve the low reliability of estimation in the early design stage. The research consists of the following four steps: (1) analyzing Level of Detail (LOD) at the early design stage to apply to the QTO process and system, (2) BIM modeling for Open BIM based QTO, (3) checking the quality of the BIM model based on the checklist for applying to QTO and improving constructability, and (4) developing and verifying a QTO prototype system. The proposed QTO system is useful for improving the reliability of schematic estimation through decreasing risk factors and shortening time required.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.11a
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• pp.157-160
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• 2009

The decision of the Form removal time which leads the early assuring strength of the concrete from Apartment construction is the fact which is important from Reducing the period of works and the economical efficiency side. Especially, with Complex building of recent times the same Tall building and Multiple Apartment Site which only follows in upgrade of interior construction of apartment site and shortening the frame construction period becomes very, importantly is the actual condition where the effort which is various for this is attempted. But is caused by with limit and economical efficiency problem of case concrete early strength revelation of most and is not put to practical use is the actual condition. Develops concrete mixture which is a utility from the research which sees hereupon and the effect which is economic leads construction duration shortening under maximizing boil.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.185-195
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• 2010

In this paper, we propose an efficient inter and intra prediction algorithms for fast encoding of H.264/AVC. First, inter prediction mode decision method decides early using temporal/spatial correlation information and pixel direction information. Second, intra prediction mode decision method selects block size judging smoothness degree with inner/outer pixel value variation and decides prediction mode using representative pixel and reference pixel. Lastly, adaptive motion search region restriction sets search region using mode information of neighboring block and predicted motion vector. The experimental results show that proposed method can achieve about 18~53% reduction compared with the existing JM 14.1 in the encoding time. In RD performance, the proposed method does not cause significant PSNR value losses while increasing bitrates slightly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.419-424
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• 2015

The Decision-directed (DD) algorithm is known to be not effective to initialize a blind equalizer in the channel conditions when the eye diagram of received signals is completely closed because it can not open the eye diagram enough. In this paper, we propose a new error to replace the error of the conventional DD algorithm. The new DD error is the conventional DD error scaled by the modulus of symbol decision, new DD algorithm using this error is effective to open the closed eye diagram in early stage of equalization unlike the conventional DD. The new DD algorithm appling the new error is showed excellent convergence characteristics as compared to the CMA widely used in blind initialization, particularly, is useful for equalization of signals having multimodulus. The performance of the new DD algorithm is verified through the simulation for the higher-order QAM signals.

• Journal of Engineering Education Research
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• v.12 no.3
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• pp.73-78
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• 2009

The purpose of the study was to analyze the career decision level and career preparation behavior of 2-3 and 4 year college students majoring in science and engineering. We used the raw data of KEEP(Korean Education & Employment Panel) survey. In the results, we found that the career decision level of the subjects had no relationship with gender, high school type, university level, and study fields. On the other hand, in terms of the career preparation behavior, male students had more concrete perception regarding future jobs and tasks in labor market than female counterparts. In addition, 4 year college students were more positive and directed to pursue the career search planning and activities than 2 or 3 year college students. Finally, the students who had high career decision level could identify future job-related tasks, direction, rewards, and skill matches. We suggested that early career education and counselling should be provided for freshman or sophomore level students majoring in science and engineering at colleges and universities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.69-74
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• 2021

Internet access is also increasing as online activities increase due to the influence of Corona 19. However, network attacks are also diversifying by malicious users, and DDoS among the attacks are increasing year by year. These attacks are detected by intrusion detection systems and can be prevented at an early stage. Various data sets are used to verify intrusion detection algorithms, but in this paper, CICIDS2017, the latest traffic, is used. DDoS attack traffic was analyzed using the decision tree. In this paper, we analyzed the traffic by using the decision tree. Through the analysis, a decisive feature was found, and the accuracy of the decisive feature was confirmed by proceeding the decision tree to prove the accuracy of detection. And the contents of false positive and false negative traffic were analyzed. As a result, learning the feature and the two features showed that the accuracy was 98% and 99.8% respectively.

• Progress in Medical Physics
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• v.15 no.2
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• pp.70-76
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• 2004

The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.

• Proceedings of the KSRS Conference
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• v.2
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• pp.706-709
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• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

• ETRI Journal
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• v.29 no.6
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• pp.736-744
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• 2007

We propose a fast macroblock (MB) mode prediction and decision algorithm based on temporal correlation for P-slices in the H.264/AVC video standard. There are eight block types for temporal decorrelation, including SKIP mode based on rate-distortion (RD) optimization. This scheme gives rise to exhaustive computations (search) in the coding procedure. To overcome this problem, a thresholding method for fast inter mode decision using a MB tracking scheme to find the most correlated block and RD cost of the correlated block is suggested for early stop of the inter mode determination. We propose a two-step inter mode candidate selection method using statistical analysis. In the first step, a mode is selected based on the mode information of the co-located MB from the previous frame. Then, an adaptive thresholding scheme is applied using the RD cost of the most correlated MB. Secondly, additional candidate modes are considered to determine the best mode of the initial candidate modes that does not satisfy the designed thresholding rule. Comparative analysis shows that a speed-up factor of up to 70.59% is obtained when compared with the full mode search method with a negligible bit increment and a minimal loss of image quality.

• Ocean and Polar Research
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• v.34 no.3
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• pp.275-286
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• 2012

Over the last 20 years there have been more than 3000 peer-reviewed papers relating to climate change and biodiversity published, and still the numbers are increasing. However, most studies focused on the impacts of climate change at population or community levels, and the results invariably reveal that there has been, or will be, a negative effect on the structure and pattern of biodiversity. Moreover, the climate change models and statistical analyses used to test the impacts are only newly developed, and the analyses or predictions can often be misled. In this review, I ask why an individual's life history is considered in the study how climate change affects biodiversity, and what ecological factors are impacted by climate change. Using evidence from a range of species, I demonstrate that diverse life history traits, such as early growth rate, migration/foraging behaviour and lifespan, can be shifted by climate change at individual level. Particularly I discuss that the optimal decision under unknown circumstance (climate change) would be the reduction of the ecological fitness at individual level, and hence, a shift in the balance of the ecosystem could be affected without having a critical impact on any one species. To conclude, I summarize the links between climate changes, ecological decision in life history, the revised consequence at individual level, and discuss how the finely-balanced relationship affects biodiversity and population structure.