• Korean Journal of Radiology
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• v.21 no.7
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• pp.812-828
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• 2020

Objective: To provide an evidence-based guide for the MRI interpretation of complete tumor response after neoadjuvant chemoradiation therapy (CRT) for rectal cancer using visual assessment on T2-weighted imaging (T2) and diffusion-weighted imaging (DWI). Materials and Methods: PubMed MEDLINE, EMBASE, and Cochrane Library were searched on November 28, 2019 to identify articles on the following issues: 1) sensitivity and specificity of T2 or DWI for diagnosing pathologic complete response (pCR) and the criteria for MRI diagnosis; 2) MRI alone vs. MRI combined with other test(s) in sensitivity and specificity for pCR; and 3) tests to select patients for the watch-and-wait management. Eligible articles were selected according to meticulous criteria and were synthesized. Results: Of 1615 article candidates, 55 eligible articles (for all three issues combined) were identified. Combined T2 and DWI performed better than T2 alone, with a meta-analytic summary sensitivity of 0.62 (95% confidence interval [CI], 0.43-0.77; I² = 80.60) and summary specificity of 0.89 (95% CI, 0.80-0.94; I² = 92.61) for diagnosing pCR. The criteria for the complete response on T2 in most studies had the commonality of remarkable tumor decrease to the absence of mass-like or nodular intermediate signal, although somewhat varied, as follows: (near) normalization of the wall; regular, thin, hypointense scar in the luminal side with (near) normal-appearance or homogeneous intermediate signal in the underlying wall; and hypointense thickening of the wall. The criteria on DWI were the absence of a hyperintense signal at high b-value (≥ 800 sec/mm²) in most studies. The specific algorithm to combine T2 and DWI was obscure in half of the studies. MRI combined with endoscopy was the most utilized means to select patients for the watch-and-wait management despite a lack of strong evidence to guide and support a multi-test approach. Conclusion: This systematic review and meta-analysis provide an evidence-based practical guide for MRI assessment of complete tumor response after CRT for rectal cancer.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.93-98
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• 2012

This study was to analyze the influences of various factors on the u-health service. Data was surveyed from experienced of u-Health service sectors. We measured legal support, IT-infra, user education, the user education, and the u-Health solution, are the critical success factors for the u-Health service. Also we evaluated u-Health services by survey data from the users. We did also the research to evaluate the validity and reliability of these factors. After that the Analytical Hierarchy Process (AHP) was applied to measure the weights among these factors. Factor analysis resulted in 6 major factors (Eigenvalue > 1.0). The AHP analysis showed the list of Critical Success Factors weighted by its significance priorities. The results of this paper could be the valuable references for the policy making process of the u-Health system in Korea.

• IE interfaces
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• v.17 no.spc
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• pp.111-121
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• 2004

In this paper, we propose an urgency and efficiency based wireless packet scheduling (UEPS) algorithm that is able to schedule real time (RT) and non-real time (NRT) traffics at the same time. The proposed UEPS algorithm is designed to support wireless downlink packet scheduling in the OFDMA system which is a strong candidate wireless system for the next generation mobile communications. The UEPS algorithm uses the time-utility function as a scheduling urgency factor and the relative status of the current channel to the average one as an efficiency indicator of radio resource usage. The design goal of the UEPS algorithm is to maximize throughput of NRT traffics with satisfying QoS requirements of RT traffics. The simulation study shows that the proposed UEPS algorithm is able to give better throughput performance than existing wireless packet scheduling algorithms such as proportional fair (PF) and modified-largest weighted delay first (M-LWDF) while satisfying QoS requirements of RT traffics such as the average delay and the packet loss rate under various traffic loads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3378-3393
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• 2014

We have witnessed the rapid development of information technology in recent years. One of the key phenomena is the fast, near-exponential increase of data. Consequently, most of the traditional data classification methods fail to meet the dynamic and real-time demands of today's data processing and analyzing needs--especially for continuous data streams. This paper proposes an improved incremental learning algorithm for a large-scale data stream, which is based on SVM (Support Vector Machine) and is named DS-IILS. The DS-IILS takes the load condition of the entire system and the node performance into consideration to improve efficiency. The threshold of the distance to the optimal separating hyperplane is given in the DS-IILS algorithm. The samples of the history sample set and the incremental sample set that are within the scope of the threshold are all reserved. These reserved samples are treated as the training sample set. To design a more accurate classifier, the effects of the data volumes of the history sample set and the incremental sample set are handled by weighted processing. Finally, the algorithm is implemented in a cloud computing system and is applied to study user behaviors. The results of the experiment are provided and compared with other incremental learning algorithms. The results show that the DS-IILS can improve training efficiency and guarantee relatively high classification accuracy at the same time, which is consistent with the theoretical analysis.

• Nutrition Research and Practice
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• v.4 no.1
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• pp.69-74
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• 2010

There has been little data on the prevalence of supplement use and the characteristics of the dietary supplement users in the Republic of Korea. This study presents the prevalence and the details of any dietary supplement use and the characteristics of the adults who use dietary supplements in the Republic of Korea. Between May 18 and June 16, 2006, nationwide and population-weighted personal interviews with 6,201 adult aged from 30 to 69 years were conducted and the final sample consisted of 3,000 people with a 49.8% response rate. We examined the prevalence and details of the use of dietary supplements and the characteristics of those who use the dietary supplement among adults. About sixty two percent of adults had taken any dietary supplement during the previous 12-month period in 2006. The most commonly reported dietary supplement was ginseng, followed by multivitamins, glucosamine, probiotics, and vitamin C. Female (versus male), an older age group, a higher family income, those living in metropolitan cities, those with marital experience, those with a higher level of education, and those having medical problems had a greater likelihood of reporting the use of any dietary supplements. The particular relationships differed depending on the type of supplement. The most Korean adults took one more dietary supplement and the dietary supplement users had different demographic and health characteristics compared to those of the nonusers. Research on diet supplements by the medical community is needed in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.558-567
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• 2017

In this research, we developed an efficient real-time human exercise pose estimation system using multiple Kinects. The main objective of this system is to measure and recognize the user's posture (such as knee curl or lunge) more accurately by employing Kinects on the front and the sides. Especially it is designed as an extensible and modular method which enables to support various additional postures in the future. This system is configured as multiple clients and the Unity3D server. The client processes Kinect skeleton data and send to the server. The server performs the multiple-Kinect calibration process and then applies the pose estimation algorithm based on the Kinect-based posture recognition model using feature extractions and the weighted averaging of feature values for different Kinects. This paper presents the design and implementation of the human exercise pose estimation system using multiple Kinects and also describes how to build and execute an interactive Unity3D exergame.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.229-236
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• 2017

An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.256-260
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• 2004

As a large portion of defence budget are alloted for military facility construction, reasonable budget estimation in the planning stage has been officers' main concerns. However the proper estimation of construction cost is difficult to be carried out due to the absence of systematic criteria. To improve the budget estimation for military facility construction, this study proposes a cost index model which can convert historical cost to current cost. Thus the developed cost index would enhance effectiveness of budget estimation process 3nd support reasonable decision making. This cost index model is developed by analyzing historical cost data with statistical methodology The study is executed by following process. First, factors which affect construction cost for the most are selected by analyzing historical cost data. second, the selected factors are categorized material cost, labor cost and equipment cost, and weights of those factors are calculated by dividing the cost of each factor by total item costs. Last, cost index is developed by using weighted average method.

• Physical Therapy Korea
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• v.3 no.2
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• pp.55-76
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• 1996

The objective of this study was to identify the immediate effects of the short leg brace on the weight bearing distribution and gait patterns of hemiplegic patients. The subjects of this study were 18 hemiplegic patients who had been hospitalized or visited out-patient department of Rehabilitation Hospital, Yonsei University College of Medicine, from January 5, 1996 through March 23, 1996. PLS(Posterior Leaf Spring) on and off changes in gait patterns were measured using ink foot print as well as by recording weight bearing distribution using a limb load monitor. The data were analyzed by the correlation and paired t-test. The findings were as follows: 1. Eighteen subjects were more weighted on the affected leg when PLS was put off(42.74%) than on(40.08%). 2. The defference in gait patterns between PLS on and off was statistically significant, with an increase in step length by 1.7cm on the involved side; a decrease in foot angle by 4.41 degree on the involved side; and a narrowing of base of support by 1.46cm when PLS were off. In conclusion, this study showed that PLS did not affect the weight bearing distribution and gait patterns of hemiplegic patients. Since, the evaluation method used in this study has limitations in regard to temporal distance gait values. Further studies are required to numerous experiments for subject and extensive study.