• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.5
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• pp.29-43
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• 2016

The Lean Startup, a methodology for minimizing failure rate of startups, has been receiving attention since its publication in 2011. Although it has been receiving enormous attention as an effective methodology of startups' growth and the emergence of unicorn companies, it is undeniable that the theoretical research and cases on this topic have not been fully accumulated in Korea. Progress of management theory has been made when combining the theory and case studies. In this paper, we thus excavated the 'Cardoc' case, which has applied the lean startup concept to the entire process of service and customer development from the inception of its product design. The following are the findings of the case. First, for the successful application of lean startup, it is essential that all team members to understand the lean startup concept and are willing to apply it thoroughly to the business management. Second, the prompt launching of MVP(Minimum Viable Product) is more important than table discussion. Third, it is crucial to select the appropriate key metrics and analytic tools for effective learning. Fourth, startup must scale up promptly as soon as it verifies the product-market fit through the BML(Build-Measure-Learn) iteration cycle. Fifth, all new business expansion should be lean. Cardoc is currently testing new MVPs in order to move onto the next scale-up process with huge investments in newly added segments. This study is meaningful in that it elaborates the representative case of a Korean startup that has applied the lean startup strategy under the circumstance of insufficient discussion of Korean startup cases in comparison with growing attention both in concept development and case accumulation abroad. We hope that this paper can be a stepping stone for future relevant research on the implementation of lean startup methodology in Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Korean Home Economics Education Association
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• v.16 no.3
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• pp.131-146
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• 2004

The Purpose of this study is to suggest strategies for environmental education through the Practical Arts(TechnologyㆍHome economics) Subject in a viewpoint of the clothing & textiles resources to resolve problems in the clothing life area. For this, this study was carried out through review of literature which is related with the consumption, the environmental problems, the environmental policies, and regulations of the government and new environmental technologies, of clothing & textiles industries and environmental education. The major findings of the study were as follows; 1) The environmental education system model in a viewpoint of the Clothing & Textiles resources was developed. This model system is consisted with interactions on school, government, industry, home and non-government organizations. Thus, the fact that Practical Arts(TechnologyㆍHome economics) Subject were the most effective subject to teaching the environmental education viewpoint of the Clothing & Textiles resources was confirmed. 2) The standards were analysed out to analyse the contents in the clothing area of the Practical Arts(TechnologyㆍHome economics) Subject. It were consist of 4 factors and 12 elements under the factors: Awareness of clothing & textile resources(clothing consumption, production of clothing & textile and environmental problems). Planning and buying of clothing(planning, buying), Management of clothing(understand of textile. human body & environment, laundering and Environmental pollution, arrangement & conservation) Recycling & exhaust of clothing(contribution, redesign, recycling, exhaust) 3) Analysing the current Practical Arts (TechnologyㆍHome economics) subject from the Environmental education in the clothing section, the environmental education related with clothing were taught the most in the middle school course, and environmental contents were concentrated in the recycling factors. but not so much on other factors. 4) After analysing the Practical Arts (TechnologyㆍHome economics) subject, the strategies were suggested for reinforcing the environmental education in the clothing of the Practical Arts(TechnologyㆍHome economics) subject.