• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.325-345
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• 2020

Determination of Best available technology (BAT) was suggested to reduce volatile organic compounds (VOCs) in a petrochemical industrial complex, by conducting human health risk, environmental, and economic assessment based on multimedia fugacity model. Fate and distribution of benzene, toluene, ethylbenzene, and xylene (BTEX) was predicted by the multimedia fugacity model, which represent VOCs emitted from the industrial complex in U-city. Media-integrated human health risk assessment and sensitivity analysis were conducted to predict the human health risk of BTEX and identify the critical variable which has adverse effects on human health. Besides, the environmental and economic assessment was conducted to determine the BAT for VOCs reduction. It is concluded that BTEX highly remained in soil media (60%, 61%, 64% and 63%), and xylene has remained as the highest proportion of BTEX in each environment media. From the candidates of BAT, the absorption was excluded due to its high human health risk. Moreover, it is identified that the half-life and exposure coefficient of each exposure route are highly correlated with human health risk by sensitivity analysis. In last, considering environmental and economic assessment, the regenerative thermal oxidation, the regenerative catalytic oxidation, the bio-filtration, the UV oxidation, and the activated carbon adsorption were determined as BAT for reducing VOCs in the petrochemical industrial complex. The suggested BAT determination methodology based on the media-integrated approach can contribute to the application of BAT into the workplace to efficiently manage the discharge facilities and operate an integrated environmental management system.

• Land and Housing Review
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• v.6 no.2
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• pp.67-77
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• 2015

Now that it is the current situation that the smooth supply and demand are necessary for 2nd phase of beginning construction and stable development of Gaesung Industrial Complex, this study was willing to offer the planning criteria and model to establish the lodging for the workers in Gaesung Industrial Complex based on the agreement that both South and North Korea agreed in 2007. Regarding the plan, its standard and the alternative were reviewed considering welfare of workers, economic efficiency, technical validity, possibility of agreement and long-term development. The exclusive area per capita was calculated through Labor Standards Act of Korea and status survey of lodging for the workers provided to border line area between China and North Korea and the economic alternative based on one room for 6 persons with the public restroom was compared with that of development type based on one room for 4 persons with indoor restroom. Especially regarding the proposed site, the area with the optimized position was set by considering gradient, accessibility and convenience of development out of the area of Dongchang-ri where was agreed already and the priority of the proposed site that can keep the existing building site and provide was offered. The necessary period for whole construction was set as approximately 36 months. Regarding construction method, RC Rahmen method was selected as the optimized alternative considering the workmanship of manpower of North Korea and conditions of supply and demand of materials and cluster-type vehicle allocation plan based on 4~6 units considering the efficiency of supplying service facilities and convenient facilities along the simultaneous accommodation of 15,000 people was offered. It was analyzed that total business expenses of approximately 80~100 billion Korean Won would required though there were the difference for each alternative in the charged rental way that the development business owner develops by lending the inter-Korea Cooperation Fund and withdraws the rent by the benefit principle. The possibility of withdrawing the rent was analyzed assuming that the period of withdrawing the investment is 30 years. Especially for the operation management after moving, the establishment of the committee of operating the lodging for the workers of Gaesung Industrial Complex (tentative name) was offered with the dualized governance that the constructor takes charge of operational management, collecting fees and management of infrastructure and human resource management is delegated to North Korea.

• Clean Technology
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• v.26 no.3
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• pp.228-236
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• 2020

Korea has an economy based on manufacturing industrial fields, which produce high amounts of hazardous wastes, in spite of few landfill candidates, and a significant concern for fine airborne particulates; therefore, traditional waste management is difficult to apply in this country. Moreover, waste collection and accumulation have recently been intensified by the waste import prohibitions or regulations in developing nations, the universalization of delivery services in Korea, and the global COVID-19 crisis. This study thus presents a domestic waste management strategy that aims to address the recent issues on waste. The contents of the strategy as the main results of the study include the (1) improvement of the compatibility of the classification codes between the domestic hazardous waste and the international ones such as those of the Basel Convention; (2) consideration of the mixed hazard indices to represent toxicity from low-content components such as rare earth metals often contained in electrical and electronic equipment waste; (3) management application based on risks throughout the life cycles of waste; (4) establishment of detailed material flow information of waste by integrating the Albaro system, Pollutant Release and Transfer Register (PRTR) system, and online trade databases; (5) real-time monitoring and prediction of the waste movement or discharge using positional sensors and geographic information systems, among others; and (6) selection and implementation of optimal treatment or recycling practices through Life Cycle Assessment (LCA) and clean technologies.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.88-95
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• 2011

An embedded mobile device mostly has lower computation power than a general purpose computer because of its relatively lower system specifications. Consequently, conventional face tracking and face detection methods, requiring complex algorithms for higher recognition rates, are unsuitable in a mobile environment aiming for real time detection. On the other hand, by applying a real-time tracking and detecting algorithm, we would be able to provide a two-way interactive multimedia service between an user and a mobile device thus providing a far better quality of service in comparison to a one-way service. Therefore it is necessary to develop a real-time face and eye tracking technique optimized to a mobile environment. For this reason, in this paper, we proposes a method of tracking horizontal face position of a user on a T-DMB device for enhancing the quality of 3D DMB content. The proposed method uses the orientation of edges to estimate the left and right boundary of the face, and by the color edge information, the horizontal position and size of face is determined finally to decide the horizontal face. The sobel gradient vector is projected vertically and candidates of face boundaries are selected, and we proposed a smoothing method and a peak-detection method for the precise decision. Because general face detection algorithms use multi-scale feature vectors, the detection time is too long on a mobile environment. However the proposed algorithm which uses the single-scale detection method can detect the face more faster than conventional face detection methods.

• Journal of the Korean GEO-environmental Society
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• v.9 no.6
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• pp.21-29
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• 2008

As household and industrial wastes continue to rapidly increase every year, the demands for landfill sites are also increasing. However, the construction of landfill sites causes many problems due to the high costs of liners, while the leachate from the landfills generates secondary contamination of surrounding lands and groundwater. The purpose of this study is to determine the proper mixing ratio to meet the liner conditions (must be less than $1{\times}10^{-7}cm/sec$), using the local soil as the main material and using fly ash, bentonite, and cement as the mixing materials. The possibility of using this mixture as the liner for landfill sites was examined. To determine the proper mixing ratio, this study conducted basic physical properties tests, compaction tests, consolidation tests, and uniaxial compression tests. It was found that the higher the ratio of bentonite, the lower the coefficient of permeability, and the higher the ratio of fly ash, the higher the coefficient of permeability. The reason for this is that, while bentonite expands and fills pores, fly ash cannot fill the pores because the particles have a round shape and do not have adhesion. In conclusion, the optimum coefficient of permeability that meets the landfill liner condition was obtained when the ratio of bentonite was 15% or higher. If fly ash was mixed, the landfill liner condition was met when the ratio of bentonite was 15% or higher and the ratio of fly ash was 20% or lower.

• Analytical Science and Technology
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• v.24 no.6
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• pp.533-543
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• 2011

The hERG (human ether-a-go-go related gene) ion channel is a main factor for cardiac repolarization, and the blockade of this channel could induce arrhythmia and sudden death. Therefore, potential hERG ion channel inhibitors are now a primary concern in the drug discovery process, and lots of efforts are focused on the minimizing the cardiotoxic side effect. In this study, $IC_{50}$ data of 202 organic compounds in HEK (human embryonic kidney) cell from literatures were used to develop predictive 2D-QSAR model. Multiple linear regression (MLR), Support Vector Machine (SVM), and artificial neural network (ANN) were utilized to predict inhibition concentration of hERG ion channel as machine learning methods. Population based-forward selection method with cross-validation procedure was combined with each learning method and used to select best subset descriptors for each learning algorithm. The best model was ANN model based on 14 descriptors ($R^2_{CV}$=0.617, RMSECV=0.762, MAECV=0.583) and the MLR model could describe the structural characteristics of inhibitors and interaction with hERG receptors. The validation of QSAR models was evaluated through the 5-fold cross-validation and Y-scrambling test.

• The Korean Journal of Pesticide Science
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• v.8 no.2
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• pp.79-87
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• 2004

3-Chloro-2-[4-chloro-2-fluoro-5-(5-methyl-3-phenyl-4,5-dihydroisoxazol-5-ylmethoxy)-phenyl]-4,5,6,7-tetrahy dro-2H-indazole(EK-5439) demonstrated rice selectivity and herbicidal activity on annual weeds, such as Echinochloa oryzicola, Monochoria vaginalis, Lindernia pyxidaria, Rotala indica, Aneilema keisak, Cyperus difformis, and Ludwigia prostrata at doses of 16-63 g a.i./ha. However, the application window was limited from pre-emergence to 5 days after transplanting. The control efficacy of EK-5439 on barnyardgrass was 4 times higher than that of oxadiazon. EK-5439 was excellently safe to the 16 different transplanted rice cultivars treated 2 days after transplanting. These compounds have the mechanism of action on the chlorophyll biosynthesis like protoporphyrinogen IX oxidase inhibitors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.330-335
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• 2017

The demand for electric motor fuel cells has surged in the automotive industry, leading to a recent increase in the demand for square aluminum cans used as fuel cell battery casings. The air vent located on the bottom of the rectangular battery casing prevents large explosions by intermittent pressure release prior to the accumulation of abnormally high pressures. Conventionally, the square cup battery casing is produced via six-step deep drawing, with the outer shape of the vent being manufactured by welding to the square battery casing. On the other hand, this study directly incorporated the air vent outlet into the bottom surface of the rectangular casing. The product of a coupled finite element analysis technique applying the thickness and contour generated from the square cup multi-step deep drawing formation analysis was used as the forging input shape. The results yielded increased prediction accuracy and the advanced prediction of defects, such as swelling and fracture. Based on the results of the initial analyses, two of the generated forging shapes were determined to be suitable, with the optimal forging shape being determined by molding analysis. The results presented here were validated by mold fabrication and a subsequent comparison of the actual and analytical results.