• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.943-950
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• 2011

In this paper, we presented an attention measurement method in 2D and 3D image/video to be applied for image and video retargeting and compressive processing. 2D attention is derived from the three main components, intensity, color, and orientation, while depth information is added for 3D attention. A rarity-based attention method is presented to obtain more interested region or objects. Displaced depth information is matched to attention probability in distorted stereo images and finally a stereo distortion predictor is designed by integrating low-level HVS responses. As results, more efficient attention scheme is developed from the conventional methods and performance is proved by applying for video retargeting.

• Atmosphere
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• v.25 no.2
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• pp.367-374
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• 2015

Korean Peninsula has high potential for occurrence of aviation turbulence. A Korean aviation Turbulence Guidance (KTG) system focused on the Korean Peninsula, named Korean-Peninsula KTG (KP-KTG) system, is developed using the high resolution (horizontal grid spacing of 1.5 km) Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration (KMA). The KP-KTG system is constructed first by selection of 15 best diagnostics of aviation turbulence using the method of probability of detection (POD) with pilot reports (PIREPs) and the LDAPS analysis data. The 15 best diagnostics are combined into an ensemble KTG predictor, named KP-KTG, with their weighting scores computed by the values of area under curve (AUC) of each diagnostics. The performance of the KP-KTG, represented by AUC, is larger than 0.84 in the recent two years (June 2012~May 2014), which is very good considering relatively small number of PIREPs. The KP-KTG can provide localized turbulence forecasting in Korean Peninsula, and its skill score is as good as that of the operational-KTG conducting in East Asia.

• Journal of Korean Traditional Oncology
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• v.17 no.1
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• pp.1-7
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• 2012

Objective : The association of cancer survival and components of the systemic inflammatory response, combined to form inflammation-based prognostic scores (modified Glasgow Prognostic Score (GPS), Neutrophil Lymphocyte Ratio, Platelet Lymphocyte Ratio) is reviewed in this article. Methods and Results : With extensive research of papers in the PubMed, there is good evidence that preoperative measures of the systemic inflammatory response predict cancer survival, independent of tumor stage, in primary operable cancer. GPS also shows its prognostic value as a predictor of survival, independent of tumor stage, performance status and treatment in a variety of advanced cancer. GPS is associated with chemotherapy related toxicities as well as response to treatment and C-reactive protein shows its clinical value as a monitor of chemotherapy response. The systemic inflammatory response is closely related to cachexia and may be suitable measure for the clinical definition of cancer cachexia. Conclusion : Anticipated survival using the inflammation-based prognostic score is a major factor to be taken into consideration when deciding whether active intervention including surgery and chemotherapy or palliation therapy including acupuncture and herb medication is appropriate.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.299-320
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• 2005

To rapidly respond to uncertainties in the business environment whilst remaining competitive, every organization needs to be able to successfully introduce and manage organizational change. Cognizant of the role of information systems (IS) as an enabler of organizational change, many organizations have paid attention to Enterprise Resource Planning (ERP) systems for successful organizational change primarily because of their change-driving forces across organizations. In this study, we focus attention on the role of readiness for change in the ERP systems adoption. Readiness for change described as views about the need for organizational change is posited to be and antecedent of two expectancies about the need for organizational change is posited to be an antecedent of two expectancies about the system. performance expectancy and effort expectancy, which lead to actual system use. In order to further establish th relevance of readiness for change as a determinant of two expectancies, computer self-efficacy is considered to be other key predictor as well. In addition, this study proposes that the personal characteristics of organizational commitment and perceived personal competence play roles of important determinants of readiness for change. Based on data gathered from the users of the ERP systems, structural equation analysis using LISREL provides significant support for the proposed relationships. Theoretical and practical implications are discussed along with limitations.

• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.149-156
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• 2008

There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.303-308
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• 2017

Nowadays, living standard is improved and people have high interest to the personal health care problem. Accordingly, people desire to know the personal physical condition and the related medical treatment. Thus, there is the necessary of the personalized medical treatment, and there are many studies about the automatic disease diagnosis and the related services. Those studies focus on the particular disease prediction which is based on the related particular data. However, there is no studies about the medical treatment prediction. In our study, national health data based medical treatment predictor is built by using SVM, and the performance is evaluated by comparing with other prediction methods. The experimental results show that the health data based medical treatment prediction resulted in the average accuracy of 80%, and the SVM performs better than other prediction algorithms.

• Proceedings of the Polymer Society of Korea Conference
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• 2006.10a
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• pp.58-59
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• 2006

Less than a decade ago, most alternate membrane materials for fuel cells relied upon a post-sulfonation process to generate ionic groups capable of transporting protons from the anode to the cathode. These random post sulfonations showed some promise, but in general they produced materials that were not sufficiently stable or protonically conductive at ion exchange capacities where aqueous swelling could be restricted. Our group began to synthesize disulfonated monomers that could be used to incorporate into random copolymer proton exchange membranes. The expected limitation was that the aromatic polymers might not be stable enough to withstand fuel cell conditions. However, this was mostly based upon an accelerated test known was the Fenton's Reagent Test, which did not seem to this author as being a reliable predictor of performance. A much better approach has been to evaluate the open circuit voltage (OCV) for alternate membranes, as well as the benchmark perfluorosulfonic acid systems. When this is done, the aromatic ionomers of this study, primarily based upon disulfonated polyarylene ether sulfones, show up quite well. Real time 3000 hours DMFC results have also been generated. Obtaining conductive materials at low humidities is another major issue where alternate membranes have not been particularly successful. In order to address this problem, multiblock copolymers with relatively high water diffusion coefficients have been designed, which show promise for conductivity at lowered humidity.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.973-978
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• 2005

In this paper, we investigate an improved mobile robot localization method using Kalman filter. The highlight of the paper lies in the formulation of combined Kalman filter and its application to mobile robot experiment. The combined Kalman filter is a kind of extended Kalman filter which has an extra degree of freedom in Kalman filtering recursion. It consists of the standard Kalman filter, i.e., the predictor-corrector and the perturbation estimator which reconstructs unknown dynamics in the state transition equation of mobile robot. The combined Kalman filter (CKF) enables to achieve robust localization performance of mobile robot in spite of heavy perturbation such as wheel slip and doorsill crossover which results in large odometric errors. Intrinsically, it has the property of integrating the innovation in Kalman filtering, i.e., the difference between measurement and predicted measurement and thus it is so much advantageous in compensating uncertainties which has not been reflected in the state transition model of mobile robot. After formulation of the CKF recursion equation, we show how the design parameters can be determined and how much beneficial it is through simulation and experiment for a two-wheeled mobile robot under indoor GPS measurement system composed of four ultrasonic satellites. In addition, we discuss what should be considered and what prerequisites are needed to successfully apply the proposed CKF in mobile robot localization.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4143-4145
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• 2014

Background: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) Ewing sarcoma (ES) outcome data. The aim of this study was to identify and optimize ES-specific survival prediction models and sources of survival disparities. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ES. 1844 patients diagnosed between 1973-2009 were used for this study. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome (bone and joint specific death, yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. Results: The mean follow up time (S.D.) was 74.48 (89.66) months. 36% of the patients were female. The mean (S.D.) age was 18.7 (12) years. The SEER staging has the highest ROC (S.D.) area of 0.616 (0.032) among the factors tested. We simplified the 4-layered risk levels (local, regional, distant, un-staged) to a simpler non-metastatic (I and II) versus metastatic (III) versus un-staged model. The ROC area (S.D.) of the 3-tiered model was 0.612 (0.008). Several other biologic factors were also predictive of ES-specific survival, but not the socio-economic factors tested here. Conclusions: ROC analysis measured and optimized the performance of ES survival prediction models. Optimized models will provide a more efficient way to stratify patients for clinical trials.

• The Journal of Korean Academic Society of Nursing Education
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• v.13 no.2
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• pp.203-211
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• 2007

Purpose: The purpose of this study was to identify the factors influencing Health Promoting Behavior(HPB) of nursing students. Method: The sample consisted of 418 college nursing students in G city. data collection method was a structured questionnaire. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation, and stepwise multiple regression. Result: The mean score for HPB was 2.48. In the subcategories, the highest degree of performance was interpersonal relationship and the lowest degree was exercise. HPB was significantly different according to economic status of parents, health concern of parents, and body mass index. The most powerful predictor of HPB was self esteem(33%). A combination of self esteem, social support, self efficacy and perceived health status accounted for 43% of the variance in HPB of nursing students. Conclusion: This study suggests that self esteem, social support, self efficacy and perceived health status are significantly influencing factors in HPB of nursing students.