• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.1
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• pp.55-65
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• 2020

The use of underfill materials in semiconductor packages is not only important for stress relieving of the package, but also for improving the reliability of the package during shock and vibration. However, in recent years, as the size of the package becomes larger and very thin, the use of the underfill shows adverse effects and rather deteriorates the reliability of the package. To resolve these issues, we developed the package using a solid epoxy material to improve the reliability of the package as a substitute for underfill material. The developed solid epoxy was applied to the package of the application processor in smart phone, and the reliability of the package was evaluated using thermal cycling reliability tests and numerical analysis. In order to find the optimal solid epoxy material and process conditions for improving the reliability, the effects of various factors on the reliability, such as the application number of solid epoxy, type of PCB pad, and different solid epoxy materials, were investigated. The reliability test results indicated that the package with solid epoxy exhibited higher reliability than that without solid epoxy. The application of solid epoxy at six locations showed higher reliability than that of solid epoxy at four locations indicating that the solid epoxy plays a role in relieving stress of the package, thereby improving the reliability of the package. For the different types of PCB pad, NSMD (non-solder mask defined) pad showed higher reliability than the SMD (solder mask defined) pad. This is because the application of the NSMD pad is more advantageous in terms of thermomechanical stress reliability because the solderpad bond area is larger. In addition, for the different solid epoxy materials with different thermal expansion coefficients, the reliability was more improved when solid epoxy having lower thermal expansion coefficient was used.

• Korean Journal of Microbiology
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• v.47 no.2
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• pp.137-142
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• 2011

$TiO_2$-coated bamboo activated carbon has been prepared and utilized under UV irradiation as a pretreatment method for an effective biodegradation of the recalcitrant polyaromatic hydrocarbons (PAHs). The anatase $TiO_2$ was successfully coated on the bamboo activated carbon (AC) and it showed the highest photoactivity against methylene blue. In the absence of the PAHs-degrading bacteria PAHs having low molecular weight (i.e., naphthalene, acenaphthylene, acenaphthene, and fluorene) were degraded by 9.8, 76.2, 74.1, and 40.5%, respectively. Higher molecular weight PAHs, however, maintained high residual concentrations of PAHs (400-1,000 ${\mu}g$/L) after the same treatment. On the other hand, the overall concentrations of PAHs became lower than 340 ${\mu}g$/L when the pretreated PAHs were subjected to biodegradation by a PAH-degrading consortium for a week. Herein, phenanthrene, anthracene, fluoranthene, and pyrene were removed by 29.3, 61.4, 27.0, and 44.3%, respectively, indicating the facilitated potential biodegradation of PAHs. Activated carbon coated with $TiO_2$ appeared to inhibit growth of PAH degraders on the surface of AC, indicating planktonic degraders were dominantly involved in the PAH biodegradation in presence of the $TiO_2$-coated bamboo AC. It was proposed that an effective remediation technology for the recalcitrant PAHs could be developed when an optimum pretreatment process is further established.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Preventive Medicine and Public Health
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• v.30 no.3 s.58
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• pp.567-576
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• 1997

To evaluate the effects of reflected glare on eyes, authors assessed the periodic health examination(1991-1996) & self-administered questionnaire data of a semiconductor producing company. The 13 lead frame(LF) department workers have been exposed to high reflected glare in the process for examining the silver plating products. We compared the data of connector(14) and clerical(12) workers as the non-exposed ones. Among LF department workers, 100% felt their visual acuity worsened(connector:81.8%, clerical:85.7%), and 70% had worn the glasses o. contact lenses(connector : 14.3%, clerical :40%) since working at the company. Major ophthalmic symptoms of the LF workers are asthenopia, tearing, decreased visual acuity, congestion and glare. Decrease of visual acuity by Hahn's line change of the LF workers is significantly high during a 5-year follow-up(p<0.05 by simple regression) compared with connector clerical workers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.16-19
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• 2019

A thinner film has superior electrical properties and a better amorphous structure. Amorphous structures can be effective in improving conductivity through a depletion effect. Research is needed on the Schottky contact, where potential barriers are formed, as a way to identify these characteristics. $SiO_2/SnO_2$ thin films were prepared to examine the amorphous structure and Schottky contact, $SiO_2$ thin films were prepared using Ar = 20 sccm. $SnO_2$ thin films were deposited using mixed gas with a flow rate of argon and oxygen at 20 sccm, and $SnO_2$ thin films were added by magnetron sputtering and treated at $100^{\circ}C$ and $150^{\circ}C$. To identify the conditions under which the amorphous structure was constructed, the XRD patterns were investigated and C-V and I-V measurements were taken to make Al electrodes and perform electrical analysis. The depletion layer was formed by the recombination of electrons and holes through the heat treatment process. $SiO_2/SnO_2$ thin films confirmed that the pores were well formed when heat treated at $100^{\circ}C$ and an electric current was applied over the micro area. An amorphous $SiO_2/SnO_2$ thin film with heat treatment at $100^{\circ}C$ showed no reflection at $33^{\circ}\;2{\theta}$ in the XRD pattern, and a reflection at $44^{\circ}2\;{\theta}$. The macroscopic view (-30 V

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.