• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.584-595
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• 2012

Recently, 3D stereoscopic video and HTTP adaptive streaming technologies have received a lot of attention from relevant industrial fields and markets in terms of multimedia contents and delivery services, respectively. It is expected that promising and marketable service models can be created by means of these noticeable two technologies. However, current standard specifications do not provide a method for organized connection between those two technologies. 3D stereoscopic video services are weighted in broadcasting and storage services that are only available under environments in which the network bandwidth is guaranteed or free. Also, HTTP adaptive streaming technologies only provide plain 3D service methods that are dependent on particular Codec. Therefore, this paper proposes 3D video delivery format for HTTP adaptive streaming service which enables stable and seamless display for various stereoscopic video sequences over internet networks. The proposed technology is designed on the basis of Stereoscopic Video Application Format which is a service-oriented standard specification for storing stereoscopic video sequences. Also, this delivery format is directly applicable over DASH that is the representative standard technology for HTTP adaptive streaming services. The delivery format proposed in this paper has been submitted to MPEG and it has been accepted as a working draft, thus it expected to pave the way for practical industrialization in relevant fields from now on.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.27-36
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• 2015

The purpose of this study was to investigate the influence relationships among individual career orientation, preparation of old age, social networks, and the entrepreneurial intention of the potential entrepreneurs. 408 numbers of structured questionnaire were collected from the potential entrepreneurs who live in Seoul through the online Google survey method and offline face to face method. And the collected data was analyzed on frequency analysis, validity analysis, t-test, ANOVA, and regression analysis etc. using the SPSS WIN 21.0 program. The results are as follows. Firstly, innovation, entrepreneurial creativity, and autonomy orientation affect on entrepreneurial intention positively(+), but security orientation has a negative(-) effect on entrepreneurial intention in the influence relationships between individual career orientation and entrepreneurial intention. Secondly, economical and emotional preparation have positive(+) influences on entrepreneurial intention in the influence relationships between individual career orientation and entrepreneurial intention. Thirdly, the sub-variables of social networks, that is, assist and role models exert a positive(+) influence on entrepreneurial intention in the influence relationships between social networks and entrepreneurial intention. Fourthly, social networks plays a moderating role only on the relationship between security orientation and entrepreneurial intention in the analysis about the moderating effects of social networks on the influence relationships among individual career orientation, preparation of old age, and entrepreneurial intention. Fifth, a social network of relationships to help prepare the old establishment has been found to help regulate effective analysis of whether or not the results of adjustment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.5
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• pp.131-154
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• 2018

While strong investments on startup and venture ecosystem prosper worldwide, growing interest on nurturing startup ecosystem in Korea is also on its way. However, korean entrepreneurial ecosystem currently results few successful business models with those continuous development of itself compared to the one in China, which is breeding more than 50% of unicorns internationally. Accordingly, this study examined how people in the venture ecosystem, especially in IT industry feel about themselves and startup itself and compared startup ecosystem in Seoul, Korea to the one in Chengdu, China considering each of economic, social and administrational environment. The study tried to provide an implication about the future orientation of Korea's starup and venture ecosystem to policy makers and the ones inside the environment to make a better one. Therefore, the study choose Seoul, Korea and Chengdu, China as geological specimens of startup ecosystem and conduct qualitative study by interviewing selected ones who work in startup incubator, accelerator specified to IT industry and started their own business in IT industry funded by startup reward program. The study categorize the result in social, economic, and administrative parts and screens whether the interviewees from both Korea and China have similar opinions toward each of questions and can be translated to have tendency or not in each part of study. According to the study, the national recognition of startup should be moved from means of maintenance such as restaurants, franchise business to IT startup especially based on software business for the sustainable flourish in Korean venture ecosystem. Investors including accelerator, Angel investors and VCs should be less risk-aversion and therefore prefer stake purchase to solely giving subsidies. The role of governors should be limited to be a middleman of the network, connecting each people in need inside the ecosystem and their reward program should focus on nurturing the growing ones, not just multiplying the numbers of startups to expand the size of entrepreneurial ecosystem. Since this study indicated that entire revision of startup ecosystem should be applied to make a better one, it could be used to design future entrepreneurial infrastructure and the ways of activating startup ecosystem elsewhere in Korea.

• Journal of Korea Water Resources Association
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• v.42 no.7
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• pp.525-535
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• 2009

In this paper a heuristic method for identifying individual pipes in water pipe networks to determine specific sections of the pipes that need to be replaced due to deterioration. An appropriate minimum pipe length is determined by selecting the pipe length that has the greatest variance of the average cumulative break number slopes among the various pipe lengths used. As a result, the minimum pipe length for the case study water network is determined as 4 m and a total of 39 individual pipe IDs are obtained. The economically optimal replacement times of the individual pipe IDs are estimated by using the threshold break rate of an individual pipe ID and the pipe break trends models for which the General Pipe Break Prediction Model(Park and Loganathan, 2002) that can incorporate the linear, exponential, and in-between of the linear and exponetial failure trends and the ROCOFs based on the modified time scale(Park et al., 2007) are used. The maximum log-likelihoods of the log-linear ROCOF and Weibull ROCOF estimated for the break data of a pipe are compared and the ROCOF that has a greater likelihood is selected for the pipe of interest. The effects of the social costs of a pipe break on the optimal replacement time are also discussed.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.673-679
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• 2017

In this paper a method for estimating the 'service life' and 'residual life' of a water pipe based on the Water Pipe Network Performance Evaluation(WPNPE) results of Water Supply Technical Diagnosis was developed for efficient maintenance of water pipes. The residual life of a pipe was defined as the difference between the service life and elapsed time since installation. The service life was defined as the time when a pipe reaches the reference score for determining deteriorated pipes that was used in the WPNPE. The pipe evaluation criteria and deterioration scores used in the WPNPE for the case study area were considered as independent variables in the multiple regression model for estimating the service life and residual life of the pipes in the area. To estimate the service life for the pipes the reference scores for determining deteriorated pipes were used as the values of the variables that represent the deterioration scores in the constructed regression models. Subsequently, the statistics of the service life and residual life of the pipes in the case study area were presented and analyzed in comparison with the service life defined by the Local Public Enterprizes Act.

• Journal of KIISE
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• v.43 no.10
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• pp.1085-1093
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• 2016

Community-based Question Answering system is a system which provides answers for each question from the documents uploaded on web communities. In order to enhance the capacity of question analysis, former methods have developed specific rules suitable for a target region or have applied machine learning to partial processes. However, these methods incur an excessive cost for expanding fields or lead to cases in which system is overfitted for a specific field. This paper proposes a multiple machine learning method which automates the overall process by adapting appropriate machine learning in each procedure for efficient processing of community-based Question Answering system. This system can be divided into question analysis part and answer selection part. The question analysis part consists of the question focus extractor, which analyzes the focused phrases in questions and uses conditional random fields, and the question type classifier, which classifies topics of questions and uses support vector machine. In the answer selection part, the we trains weights that are used by the similarity estimation models through an artificial neural network. Also these are a number of cases in which the results of morphological analysis are not reliable for the data uploaded on web communities. Therefore, we suggest a method that minimizes the impact of morphological analysis by using character features in the stage of question analysis. The proposed system outperforms the former system by showing a Mean Average Precision criteria of 0.765 and R-Precision criteria of 0.872.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.846-851
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• 2005

In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.

• Journal of Distribution Science
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• v.14 no.6
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• pp.107-118
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• 2016

Purpose - Over 90% of Domestic logistics industry is small enterprise and they are experiencing growth stagnation due to price-based competition structure rather than constructing logistics service of high added value. In order to get over this situation and pursue the development of logistics industry, strengthening its competitiveness, through inter-enterprise cooperative network build-up, would be a key alternative. Therefore, in this study, an index for measuring inter-enterprise cooperation level of Joint logistics business will be developed as a typical collaborative business model in logistics industry. Moreover, a strengthening competitiveness method suggests a developmental step and a key management index to mature in logistics industry. Research Design, Data, Methodology - This study is an index development research for measuring inter-enterprise cooperation level of logistics industry. Such a level was measured by performing a survey by targeting enterprises that participated in Joint logistics business. The targeting enterprises are typical cooperative models in logistics industry. Measurement items were developed which were based on the presented items in existing research. Question items were composed of selection type questions as answering Yes/No. They measures implementation status of corporate activity and detailed activity items measuring qualitative level. Total samples were based on 116 enterprise samples including 90 logistics enterprises and 26 shippers. In addition, by evaluating the importance for Joint logistics business recognition with personnel working level, the weight of measuring variable was extracted. This study has built an assessment tools (LPCI) on Joint logistics business cooperation level in a situation where there are no previous studies on joint logistics business, this study is meaningful for other studies. Results - As a result of analyzing LPCI presented in this study, the score of logistics enterprise was represented as 59.9 points based on full score of 100 points and that of shippers as 47.2 points and cooperation level among enterprises participated in Joint logistics business was revealed to be very low. In particular, as a result of measuring the importance between logistics enterprise and shippers, the difference by each measurement standard was represented among those enterprises. This difference is considered to be a key factor that cooperative operational conformity between logistics enterprises and shippers is represented to be low. Conclusions - As most joint logistics business, being promoted at present, is sharing facility and information with joint logistics business, it is hard to find such a joint logistics business in reality based on cooperative business model in main cooperation agents. Therefore, competitiveness of logistics industry could be strengthened by promoting joint logistics business based on their mutual cooperation among enterprises. In other words, it is to secure sustainable competitiveness of joint logistics business together with creation of new market by inter-enterprise cooperation based on integration of basic logistics business.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.27-36
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• 2017

SNS has been emerged as an effective educational tool in college and many studies on various teaching models and methodologies have been made in order to utilize SNS in education. The purpose of this paper is to empirically investigate the effect of affecting factors of SNS on learner's attitude, intention to re-use and performance in converging college educational environment. Self-efficacy on media usage, educational expectancy, subjective norm, habit, and enjoyment were identified as affecting factors based on prior researches. An empirical analysis was attempted by survey targeting college students. The results of structural equation model using Smart PLS shows that educational expectancy, subjective norm, and enjoyment are significantly related to the learner's attitude on use of SNS in college education, but Self-efficacy on media usage and habit are not. Learner's attitude on SNS in college education was found to be significantly related to the intention to continuous use and performance. This study implicates that using SNS in university class makes learner's attitude positively and finally lead to good performance. The analysis results can provide a guideline of effective strategy for SNS utilization in college education.