• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.202-211
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• 2015

Companies build the factory automation system to improve management effectiveness and productivity as prime strategies for sustainable growth. But most companies undergo various trials and errors while carrying out the project without elaborate preparation stage for factory automation. In this study, we tried to verify what factors are critical to effectively building distribution automation system, which is a branch of factory automation system. A consulting model for setting up a Material Handling Automation System by utilizing the Stage-Gate Process, which is product development process was studied. 29 material handling automation projects carried out between the year 1990 to 2013 at K-Company were selected. Interviews with the project managers, operators and maintenance personnels, various records and current status of the projects were used as data for structural equations based on the Milan consulting model and existing researches of factory automation, CIM for material handling automation. Creating effective basis of production, material handling system and energy saving system with expert review, when preparing a material handling automation project, help promote the project planning thus contributing to the performance of the resulting system, which appears though rather weakly in our data. Also the effect of material handling automation can be enhanced through sufficient and effective links to the relevant environments such as production logistics management and automated warehouses. More detailed planning characteristics of project promotion or some time-series data of effective Material Handling Automation System could enhace furthur studies. We propose a consulting model for setting up an efficient material handling automation system.

• Journal of Food Hygiene and Safety
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• v.36 no.5
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• pp.376-381
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• 2021

Red beet (Beta vulgaris L.) is a root vegetable and a popular functional food ingredient of dark red-purple appearance due largely to betacyanins, principally betanine (75-95%) and its isomer, isobetanine (15-45%). This study developed an analytical method for beet red in terms of betanine and isobetanine in processed food products labeled with beet red as a food additive. High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) was used with a C₁₈ column. Linearity, limit of detection (LOD), limit of quantitation (LOQ), accuracy, precision and uncertainty in measurement were calculated for method validation. Matrix-matched calibration was applied to the candy, ice cream, and cocoa product, respectively, and R² was ≥0.9998, showing a high level of linearity. The LOD and LOQ were 0.16 to 0.32 and 0.48 to 0.97 mg/L, respectively. As a result of repeated intra-day and interday experiments to validate the accuracy and precision of the analytical method, the recovery rates were 96.0-103.1% and 100.0-102.2%, respectively and the RSD% was 0.5-3.3% and 0.9-3.8%, respectively. Moreover, the measurement uncertainty was estimated to be 1.71-12.43% depending on the matrix and the measured concentration. In this study, betanine and isobetanine were quantified (8.4-3,823.4 mg/kg) by applying the developed analytical method to processed food products (n= 26; e.g., candy, ice cream, and other processed foods) labeled with beet red as a food additive.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.185-192
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• 2019

DXA is the most commonly used BMD examination equipment with the best performance on reflecting the biological alteration with tiny change of bone density. In spite of the importance of the quality control to maintain the accuracy and precision of the examination, considerable number of hospitals are not conducting QC due to the difficulty and high cost of the phantom product. This study develops the cross revision phantom with 3D printer and the change of the degree of infilling filaments which can be readily secured, and provides the usefulness assessment of the developed phantom by comparing with existing products. The Hounsfield Units of ABS, TPU, PLA, 30% Cu-PLA, and 30% Al-PLA are assessed. The Hounsfield Units result at infilling rate 100% was $-149.74{\pm}2.36$, $-55.62{\pm}7.14$, $-7.68{\pm}3.82$, $87.53{\pm}1.07$, and $1795.20{\pm}16.15$. The L1, L2, L3 BMD of 3D printing phantom with linear regression model were $0.620{\pm}0.010g/cm^2$, $1.092{\pm}0.025g/cm^2$, $1.554{\pm}0.026g/cm^2$ which are statistically relevant to the existing phantom products. This result provides the base line data for various medical phantom produce and capability of proper quality control of DXA equipment.

• Membrane Journal
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• v.29 no.3
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• pp.173-182
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• 2019

Much research has been made for finding new and eco-friendly alternative sources of energy to solve the problems related with the pollution caused by emissions of greenhouse gases such as carbon dioxide as the use of fossil fuels increases worldwide. Among them, fuel cells draws particular interests as an eco-friendly energy generator because only water is obtained as a by-product. Anion exchange membrane-based alkaline fuel cell (AEMFC) that uses anion exchange membrane as an electrolyte is of increased interest recently because of its advantages in using low-cost metal catalyst unlike the PEMFC (potton exchange membrane fuel cell) due to the high-catalyst activity in alkaline conditions. The main properties required as an anion exchange membrane are high hydroxide conductivity and chemical stability at high pH. Recently we reported a chemically crosslinked poly(2-dimethyl-1,4-phenylene oxide) (PPO) by reacting PPO with N,N,N',N'-tetramethyl-1,6-hexanediamine as novel anion exchange membranes. In the current work, we further developed the same crosslinked polymer but having enhanced physicochemical properties, including higher conductivity, increased mechanical and dimensional stabilities by using the PPO with a higher molecular weight and also by increasing the crosslinking density. The obtained polymer membrane also showed a good cell performance.

• Analytical Science and Technology
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• v.32 no.2
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• pp.35-47
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• 2019

In this study, high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was employed to detect 26 antidiabetic compounds in adulterated dietary supplements using a simple, selective method. The work presented herein may help prevent incidents related to food adulteration and restrict the illegal food market. The best separation was obtained on a Shiseido Capcell Pak(R) C18 MG-II ($2.0mm{\times}100mm$, $3{\mu}m$), which improved the peak shape and MS detection sensitivity of the target compounds. A gradient elution system composed of 0.1 % (v/v) formic acid in distilled water and methanol at a flow rate of 0.3 mL/min for 18 min was utilized. A triple quadrupole mass spectrometer with an electrospray ionization source operated in the positive or negative mode was employed as the detector. The developed method was validated as follows: specificity was confirmed in the multiple reaction monitoring mode using the precursor and product ion pairs. For solid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL, and for liquid samples, LOD ranged from 0.16 to 20.00 ng/mL and LOQ ranged from 0.50 to 60.00 ng/mL. Satisfactory linearity was obtained from calibration curves, with $R^2$ > 0.99. Both intra and inter-day precision were less than 13.19 %. Accuracies ranged from 80.69 to 118.81 % (intra/inter-day), with a stability of less than 14.88 %. Mean recovery was found to be 80.6-119.0 % and less than 13.4 % RSD. Using the validated method, glibenclamide and pioglitazone were simultaneously determined in one capsule at concentrations of 1.52 and 0.53 mg (per capsule), respectively.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Journal of Bio-Environment Control
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• v.32 no.2
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• pp.139-147
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• 2023

This study aims to select eggplant cultivars adaptive to the hot temperature period greenhouse climate by water consumption, and growth performance of plants and fruits of different European eggplant cultivars, including 'Bartok (BA)', 'Bowie (BO)', 'Black Pearl (BP)', 'Ishbilia (I)', 'Mabel (M)', 'Vestale (VE)' and 'Velia (VL)', in substrate hydroponic cultivation under hot and humid greenhouse conditions. On the 118 DAT, the leaf number and stem dry weight were highest in 'VL', followed by 'M', and there was no significant difference in leaf dry weight among cultivars. The marketable fruit number per plant was 16.4 for 'M', which was higher than other cultivars, and 'VE' and 'VL' were 8.5 and 8.8, respectively. The weight per fruit was low for 'M' at 136 g, and the highest in 'VE' and 'VL' at 332 and 281 g, respectively. There was no significant difference in fruit production per plant. In this study, 'M', which has high water use efficiency and a large number of fruits, and 'VL', which required less quantity to water consumption for producing 200 g of fruit and had a high product weight, will have excellent adaptability in the UAE greenhouse condition.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.109-141
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• 2014

Recently, the interests of consumers in firms that implement the social commitment activities have been consistently growing. Consumers' evaluation about the level of corporate social responsibility(CSR) can affect the overall image for product or service of corporation. This recent changes make a marketer to have to consider direct and indirect effects of CSR efforts on the market performance. This phenomena is also found in the franchise industry. The importance of CSR is more critical rather than other industries since each franchisor should care franchisees as well as end users. Franchisors' execution of CSR could increase satisfaction of end user through consonance of activities provided by franchisees. However most franchisor stay in focusing on the traditional CSR activities. Therefore, this study aims to enhance the understanding the CSR in franchise and provide the phase model of CSR development for general firms including franchise. After diagnosis the firms with the proposed model, the study found many franchisors have huge gap between current CSR activities and higher level of CSR policies that franchisor have to make facing. This study call franchisors to reduce this gap by implementing new CSR efforts. If they answer for this calling, franchise industry could leap for making the best practice of creating shared value with other stakeholders.

• Knowledge Management Research
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• v.24 no.4
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• pp.103-129
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• 2023

This study aims to analyze the network structure of technological innovation resources in SMEs, especially manufacturing firms, and reveal the differences between innovative and non-innovative firms. The study first analyzes connection centrality, flow-mediated centrality, and power centrality for all firms, and derives structural equivalence through CONCOR analysis. Then, the network structure of innovative and non-innovative firms was compared and analyzed according to innovation performance and creation. The results show that entrepreneurship and corporate innovation strategy have a significant impact on the analysis of technological innovation resources of all firms. According to the CONCOR analysis, the innovation resources of SMEs are organized into seven clusters, which can be defined as intrinsic product innovation resources, competitive advantage promotion resources, cooperative activities resources, information system resources, and innovation protection resources. The network analysis of innovative and non-innovative firms showed that innovative firms focused on enhancing competitiveness and improving quality, while non-innovative firms tended to focus more on existing products and customers. In addition, innovative firms had eight clusters, while non-innovative firms had six clusters, suggesting that innovative firms utilize resources diversely to pursue structural change and new value creation, while non-innovative firms operate technological innovation resources in a more stable form. This study emphasizes the importance of entrepreneurship and corporate innovation strategy in SMEs' technological innovation, and suggests that strong internal efforts are needed to increase innovativeness. These findings have important implications for strategy formulation and policy development for technological innovation in SMEs.