• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.645-649
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• 2013

Objective: The prognostic role of vascular endothelial growth factor (VEGF) in bladder cancer remains controversial. This meta-analysis aimed to explore any association between overexpression and survival outcomes. Methods: We systematically searched for studies investigating the relationships between VEGF expression and outcome of bladder cancer patients. Study quality was assessed using the Newcastle-Ottawa Scale. After careful review, survival data were extracted from eligible studies. A meta-analysis was performed to generate combined hazard ratios (HRs) for overall survival (OS), disease-free survival (DFS) and disease-specific survival (DSS). Results: A total of 1,285 patients from 11 studies were included in the analysis. Our results showed that tissue VEGF overexpression in patients with bladder cancer was associated with poor prognosis in terms of OS (HR, 1.843; 95% CI, 1.231-2.759; P = 0.003), DFS (HR, 1.498; 95% CI, 1.255-1.787; P = 0.000) and DSS (HR, 1.562; 95% CI, 0.996-1.00; P = 0.052), though the difference for DSS was not statistically significant. In addition, there was no evidence of publication bias as suggested by Begg's and Egger's tests except for DFS (Begg's test, P = 0.221; Egger's test, P = 0.018). Conclusion: The present meta-analysis indicated elevated VEGF expression to be associated with a poor prognosis in patients with bladder cancer.

• Journal of Korea Multimedia Society
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• v.19 no.7
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• pp.1166-1178
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• 2016

In Internet of Things (IoT) environments, billions of interconnected devices and multimedia sensors generate a huge amount of multimedia traffic. Since the environment are in general deployed as a server-centric architecture wireless sensor networks could be bottlenecks between IoT gateways and IoT devices. The bottleneck causes high power consumption of the device and triggers very heavy network overload by transmission of sensing data. The deterioration could decrease the quality of multimedia streaming service due to delay, loss, and waste of device power. Thus, in this paper, we propose a context-based adaptive multimedia streaming scheme to support enhanced QoS and low power consumption in IoT environments. The goal of the scheme is to increase quality score per voltage of the streaming service, given an adaptation algorithm with context that are classified network and hardware such as throughput, RTT, and CPU usage. From the both context, the quality score per voltage is used in the comparison of a only network context-based adaptive multimedia streaming scheme, a fixed multimedia streaming and our scheme. As a result, we achieves a high improvement that means the quality score per voltage is increased up to about 4, especially in case of resolution change.

• Proceedings of the Korean Nutrition Society Conference
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• 2004.11a
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• pp.22-33
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• 2004

It has been more than three decades since the first assay assessing circulating 25(OH)D in human subjects was performed. That publication as well as several that followed it defined 'normal' nutritional vitamin D status in human populations. Recently, the wisdom by which 'normal' circulating 25(OH)D levels in human subjects were assigned in the past has come under question. It appears that sampling human subjects, who appear to be free from disease, and assessing 'normal' circulating 25(OH)D levels by plotting a Gaussian distribution is grossly inaccurate. There are many reasons why this method is inaccurate, including race, lifestyle habits, sunscreen usage, age, latitude, and inappropriately low dietary recommendations for vitamin D. For instance, a 400IU/day. AI for vitamin D is insignificant when one considers that a 10-15 minute whole body exposure to peak summer sun will generate and release up to 20,000 IU vitamin $D_3$ into the circulation. Recent studies, which orally administered up to 10,000 IU/day vitamin $D_3$ to human subjects for several months, have successfully elevated circulating 25(OH)D levels to those observed in individuals from sun-rich environments. Further, we are now able to accurately assess sufficient circulating 25(OH)D levels utilizing specific biomarkers instead of guessing what an adequate level is. These biomarkers include intact parathyroid hormone (PTH), calcium absorption, bone mineral density (BMD), insulin resistance and pancreatic beta cell function. Using the data from these biomarkers, vitamin D deficiency should be defined as circulating levels of $25(OH)D{\leq}30ng/mL$. In certain cases, such as pregnancy and lactation, significantly higher circulating 25(OH)D levels would almost certainly be beneficial to both the mother and recipient fetus/infant.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.5
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• pp.436-444
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• 2018

The purpose of this research is to assess the efficiency of the airline's route. The revenue source of low cost airline carriers is not various unlike regular airline carriers, because they are operating only domestic and international flights for a country of close proximity. In particular, domestic low-cost airlines in Korea can't provide cargo transport services but rely on passengers and additional services to generate profits. Therefore, it is absolutely important to maintain a low cost and effective passenger transport line. This study will suggest the way to improve efficiency of route operated by low-cost airlines. Analysis method is DEA. The input parameters and output results were selected by existing research. Based on the results of this study, it will be able to assist establishing routes and selling strategies of the low-cost airlines.

• Journal of the Korean Society of Costume
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• v.62 no.7
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• pp.79-96
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• 2012

Creativity is a rising topic in the current society. The emphasis on creativity is valued as a key factor for success in all areas including but not limited to politics, economy, culture, arts and design. The field of Fashion design is probably one of the few areas that talk about creativity as a necessary quality to survive. The purpose of this study is to introduce TRIZ(Teoriya Reshniya Izobretatelsskikh Sadatch) as a theoretical tool to generate creativity in fashion design. TRIZ is a creative method of problem solving based on data analysis of outcomes invented by engineering. The fundamental concept of TRIZ has been researched through documentary studies, and practical case studies of product designs are used. Fashion design cases from Comme des Garcons by Rei Kawakubo are used to apply TRIZ in fashion design. Rei Kawakubo's design philosophy has been studied through fashion writings and visual sources in books, exhibition catalog, www. style. com and online shopping mall sites. This study has selected four principles among forty inventive theories of TRIZ: segmentation; asymmetry; consolidation; and preliminary action to apply to Rei Kawakubo's fashion design. As a result, TRIZ can be applicable to fashion design as a creative thinking methodology. By using the four principles of TRIZ, this study shows how Rei Kawakubo's design enhanced its efficiency and aesthetics of the products and was distinguished from existing items. It is meaningful to demonstrate a possibility of adopting engineering based creative methodology in fashion design to widen the perspective and to raise a question for the need of interdisciplinary creative methodology with traditional aesthetic approach in fashion design.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.4
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• pp.255-262
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• 2016

There has been intense research on self-diagnosis systems in railway applications, since stability and reliability have become more and more significant issues. Wired sensors have been widely used in the railway vehicles, but because of the difficulty in their maintenance and accessibility, they ar not considered for self-diagnosis systems. To have a self-monitoring system, wireless data transmission and self-powered sensors are required. For this purpose, a thermoelectric energy harvesting module that can generate electricity from temperature gradient between the bogie axle box and ambient environment was introduced in this work. The temperature gradient was measured under actual operation conditions, and the behavior of the thermoelectric module with an external load resistance and booster circuits was studied. The proposed energy harvesting system can be applied for wireless sensor nodes in railroad vehicles with optimization of thermal management.

• Journal of Construction Engineering and Project Management
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• v.3 no.4
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• pp.12-19
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• 2013

Green Frame is an environmentally friendly column-beam system composed of composite PC members that can increase buildings' life spans while reducing resource consumption. Typically, connections of PC and RC columns occur at the boundaries of each floor, which is at the upper section of slabs, causing the boundary of each floor to generate the maximum moment. Although it is not optimal in terms of structural safety to connect members at a location where the moment is high, this approach is highly adopted due to its constructability. We propose that a superior approach that employs the concept of connecting columns at the low bending moment zone can be applied to quickly and safely install green columns, the main structural members of Green Frame. Connection of green columns at the low bending moment zone can be classified into three techniques, depending on the method of reinforcing the joints, which have different connection characteristics and construction methods. Research is needed to compare the features of each method of reinforcing the joints so that the most appropriate column connection method can be chosen for the site conditions. This study aims to confirm the structural safety of the connection component at the low bending moment zone and to compare and analyze the construction duration, unit price, quality and safety performance of each column connection method. The study results are anticipated to activate the use of composite precast concrete and to be used as development data in the future.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.385-395
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• 2005

Long sentence analysis has been a critical problem in machine translation because of high complexity. The methods of intra-sentence segmentation have been proposed to reduce parsing complexity. This paper presents the intra-sentence segmentation method based on maximum entropy probability model to increase the coverage and accuracy of the segmentation. We construct the rules for choosing candidate segmentation positions by a teaming method using the lexical context of the words tagged as segmentation position. We also generate the model that gives probability value to each candidate segmentation positions. The lexical contexts are extracted from the corpus tagged with segmentation positions and are incorporated into the probability model. We construct training data using the sentences from Wall Street Journal and experiment the intra-sentence segmentation on the sentences from four different domains. The experiments show about $88\%$ accuracy and about $98\%$ coverage of the segmentation. Also, the proposed method results in parsing efficiency improvement by 4.8 times in speed and 3.6 times in space.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1386-1399
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• 2004

This paper presents correlation-based automatic image captioning. Given a training set of annotated images, we want to discover correlations between visual features and textual features, so that we can automatically generate descriptive textual features for a new unseen image. We develop models with multiple design alternatives such as 1) adaptively clustering visual features, 2) weighting visual features and textual features, and 3) reducing dimensionality for noise sup-Pression. We experiment thoroughly on 10 data sets of various content styles from the Corel image database, about 680MB. The major contributions of this work are: (a) we show that careful weighting visual and textual features, as well as clustering visual features adaptively leads to consistent performance improvements, and (b) our proposed methods achieve a relative improvement of up to 45% on annotation accuracy over the state-of-the-art, EM approach.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.199-206
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• 2006

Sequential pattern mining is an important data mining task with broad applications. However, conventional methods may meet inherent difficulties in mining databases with long sequences and noise. They may generate a huge number of short and trivial patterns but fail to find interesting patterns shared by many sequences. In this paper, to overcome these problems, we propose the theme of approximate sequential pattern mining roughly defined as identifying patterns approximately shared by many sequences. The proposed method works in two steps: one is to cluster target sequences by their similarities and the other is to find consensus patterns that ire similar to the sequences in each cluster directly through multiple alignment. For this purpose, a novel structure called weighted sequence is presented to compress the alignment result, and the longest consensus pattern that represents each cluster is generated from its weighted sequence. Finally, the effectiveness of the proposed method is verified by a set of experiments.