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

• The Korean Journal of Archival Studies
• /
• no.32
• /
• pp.127-176
• /
• 2012

Metadata is well recognized as one of the foundational factors in archiving and long-term preservation of digital resources. There are several metadata standards for records management, archives and preservation, e.g. ISAD(G), EAD, AGRkMs, PREMIS, and OAIS. Consideration is important in selecting appropriate metadata standards in order to design metadata schema that meet the requirements of a particular archival system. Interoperability of metadata with other systems should be considered in schema design. In our previous research, we have presented a feature analysis of metadata standards by identifying the primary resource lifecycle stages where each standard is applied. We have clarified that any single metadata standard cannot cover the whole records lifecycle for archiving and preservation. Through this feature analysis, we analyzed the features of metadata in the whole records lifecycle, and we clarified the relationships between the metadata standards and the stages of the lifecycle. In the previous study, more detailed analysis was left for future study. This paper proposes to analyze the metadata schemas from the viewpoint of tasks performed in the lifecycle. Metadata schemas are primarily defined to describe properties of a resource in accordance with the purposes of description, e.g. finding aids, records management, preservation and so forth. In other words, the metadata standards are resource- and purpose-centric, and the resource lifecycle is not explicitly reflected in the standards. There are no systematic methods for mapping between different metadata standards in accordance with the lifecycle. This paper proposes a method for mapping between metadata standards based on the tasks contained in the resource lifecycle. We first propose a Task Model to clarify tasks applied to resources in each stage of the lifecycle. This model is created as a task-centric model to identify features of metadata standards and to create mappings among elements of those standards. It is important to categorize the elements in order to limit the semantic scope of mapping among elements and decrease the number of combinations of elements for mapping. This paper proposes to use 5W1H (Who, What, Why, When, Where, How) model to categorize the elements. 5W1H categories are generally used for describing events, e.g. news articles. As performing a task on a resource causes an event and metadata elements are used in the event, we consider that the 5W1H categories are adequate to categorize the elements. By using these categories, we determine the features of every element of metadata standards which are AGLS, AGRkMS, PREMIS, EAD, OAIS and an attribute set extracted from DPC decision flow. Then, we perform the element mapping between the standards, and find the relationships between the standards. In this study, we defined a set of terms for each of 5W1H categories, which typically appear in the definition of an element, and used those terms to categorize the elements. For example, if the definition of an element includes the terms such as person and organization that mean a subject which contribute to create, modify a resource the element is categorized into the Who category. A single element can be categorized into one or more 5W1H categories. Thus, we categorized every element of the metadata standards using the 5W1H model, and then, we carried out mapping among the elements in each category. We conclude that the Task Model provides a new viewpoint for metadata schemas and is useful to help us understand the features of metadata standards for records management and archives. The 5W1H model, which is defined based on the Task Model, provides us a core set of categories to semantically classify metadata elements from the viewpoint of an event caused by a task.

• Korean Journal of Construction Engineering and Management
• /
• v.15 no.5
• /
• pp.31-39
• /
• 2014

It has been a long time since cars had become important means of transportation in human life. Since 1970s, cars have been increasing steadily because of rising individual income and changing lifestyle toward leisure and convenience. The number of cars is just 1.8 per thousand populations in 1970s, however, in 2012, it has increased to 291.15. Forecasting the demand for cars would be useful to plan, construction or management in the field of motor industry, road building and establishing facilities. Our study predicts the demand of cars through estimating the growth curve model. Especially, we include ageing variables to forecasting identifying the effect of ageing on the demand of cars. The main findings are as follows. In 2045, the number of cars is expected to reach 486.8 per thousand populations with passing a primary saturation point at early 2020s. Also, due to effect of ageing, the predicted demand of cars is about 10% lower than in case of which if ageing effect not exist.

• Journal of The Korean Association For Science Education
• /
• v.36 no.1
• /
• pp.29-43
• /
• 2016

There have been much efforts to reconstruct the science curriculum focusing on Disciplinary Core Ideas(DCI) in many countries such as America and Europe, the most practical effort has been to design a curriculum with learning progressions(LPs). LPs describe stepwise how students can systematically move toward the understanding of more sophisticated ideas or scientific activities and explain in succession the process of understanding the ideas while the students learn. In this study, a LP for ecosystems has been developed, and the developed LP is then evaluated accordingly. The Ecosystem is one of the DCI of the life science in Next Generation Science Standards(NGSS). The development process of the LP was set at step 4(Development, Assessment, Analysis, and Amendment), and developed through an iterative process of sequences. As a result of analyzing the developed LP, an assessment based on the LP provides reliable information to identifying student ability. This study proposes the development process of the LP and its methodological aspects to use Core Achievement Standards, Ordered Multiple-Choice items and the Rasch model. In addition, using the empirically proven LP suggests a way of strengthening curriculum linked to educational content, teaching methods and assessment. Utilizing the proposed development process in this study will be to present the standard into the direction of becoming part of the curriculum. Currently, the state of domestic research for the LP is still lacking. This study determined the development process of the LP and the need to conduct future research on the LPs.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.43 no.3
• /
• pp.92-100
• /
• 2015

Unlike most other planning processes, brownfield planning generally requires a high level of technical and legal expertise due to potential site contamination. To successfully engage in inclusionary decision making, an adaptive collaboration strategy for brownfield planning is therefore critical. This study examines how a communicative planning approach can be used to overcome the challenge of enabling experts from different fields to work alongside lay people from the local community to achieve a properly balanced collaboration in brownfield planning. After identifying appropriate indicators for collaboration through a literature review of established communicative planning theory, these indicators are applied to the brownfield planning process, highlighting critical points of collaboration such as site prioritization, assessment, remediation, and redevelopment throughout. The results suggest the critical need for an adaptive model focusing on three aspects: 1. Facilitation of a balanced dialogue between the experts with social, cultural, and design-based knowledge and the ones with scientific and engineering-based knowledge, 2. Preparation of an appropriate tool for risk communication with the lay people, 3. Development of decision support system for the integration of expert-oriented technical data and public opinion-oriented subjective data.

• Journal of Korea Technology Innovation Society
• /
• v.16 no.4
• /
• pp.1109-1133
• /
• 2013

In an effort to discover new technologies and to forecast social changes of technologies, a number of technology life-cycle models have been developed and employed. The hype cycle, a graphical tool developed by a consulting firm, Gartner, is one of the most widely used models for the purpose and it is recognised as a practical one. However, more research is needed on theoretical frames, relations and empirical practices of the model. In this study, hype cycle comparisons in Korean and global search websites were performed by means of web-search traffic which is proposed as an empirical measurement of public expectation, analysed in a specific product or country in previous researches. First, search traffic and market share for new cars were compared in Korea and the U.S. with a view to identifying differences between the hype cycles in the two countries about the same product. The results show the similarity between the two countries with the statistical significance. Next, comparative analysis between search traffic and supply rate for several products in Korea was conducted to check out their patterns. According to the analysis, all the products seem to be at the "Peak of inflated expectations" in the hype cycles and they are similar to one another in the hype cycle. This study is of significance in aspects of expanding the scope of hype cycle analysis with web-search traffic because it introduced domestic web-search traffic analysis from Naver to analyse consumers' expectations in Korea by comparison with that from Google in other countries. In addition, this research can help to explain social phenomina more persuasively with search traffic and to give scientific objectivity to the hype cycle model. Furthermore, it can contribute to developing strategies of companies, such as marketing strategy.

• Journal of Digital Convergence
• /
• v.11 no.12
• /
• pp.169-183
• /
• 2013

As the issue of selling wine online has been raised in an attempt to implement FTA programs in a more effective way, wine will be available online in the near future in Korea. Thus, this study aimed at identifying key factors which will contribute to reduce various kinds of risks perceived by online customers, and investigating the structural relationships between those factors and perceived risks. Site quality of online wine shop(information quality, system quality), trust in online wine shop were selected as key predictors of perceived risks and research model was established using those factors. Data were collected from those who have experienced in using online wine store, and the research model was tested using valid data. Results of testing research hypotheses using data from survey respondents showed that information and system quality exerted an impact on trust in online wine shop. It was proven that information and system quality posited an impact on time risk whereas they was not related to performance and psychological risk. In addition, trust in online wine shop was shown to be related to time risk, performance risk, and psychological risk.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.8
• /
• pp.708-718
• /
• 2002

In this paper, the problems in identifying the noise sources by using the sound intensity technique are dealt with for the general radiated near-field from vibro-acoustic sources. For this purpose, a three-dimensional model structure resembling the engine room of a car or heavy equipment is considered. Similar to the practical situations, the model contains many mutually coherent and incoherent noise sources distributed on the complicated surfaces. The sources are located on the narrow, connected, reflecting planes constructed with rigid boxes, of which a small clearance exists between the whole box structure and the reflecting bottom. The acoustic boundary element method is employed to calculate the acoustic intensity at the near-field surfaces and interior spaces. The effects of relative source phases, frequencies, and locations are investigated, from which the results are illustrated by the contour map, vector plot, and energy streamlines. It is clearly observed that the application of sound intensity technique to the reactive or reverberant field, e.g., scanning over the upper engine room as is usually practiced, can yield the detection of fake sources. For the precise result for such a field, the field reactivity should be checked a priori and the proper effort should be directed to reduce or improve the reactivity of sound field.

• Korean Journal of Agricultural Science
• /
• v.31 no.2
• /
• pp.135-148
• /
• 2004

Rice is not only main food but also key farm income source of Korean farmers. In spite of the above facts, rice productivity was decreased on account of drought in every 2 or 3 years interval owing to the vulnerability of irrigation facilities throughout Korea in the past decades. As an context of the first five year economic development plan, all weather farming programme including 4 big river basin comprehensive development projects and large and medium sized irrigation water development projects were carried out successfully. Therefore the area of irrigated paddy were increased from 58% in 1970 to 76.2% in 1999. In the past decades, the Government had invested heavy financial funds to develop irrigation water but as an factor share analysis, the contribution rates of irrigation water and investment for farmland base development project have not been identified yet in national agricultural economic level. It is very scarce to find out the papers concerned to macro-economic factor share analysis or contribution rates of water and investment cost to rice production value in Korea considering the production function of the quantity of irrigation water and investment cost as independent variables. Accordingly this paper covered and aimed at identifying (1) derivation of rice production function with the time serial data from 1965 to 1999 and the contribution rates of irrigation water and total investment cost for farmland base development project. The analytical model of the contribution rates was adapted the famous Cobb-Douglass production function. According to the model analysis, the contribution rate of irrigation water to rice production in Korea was shown 37.8% which was equivalent to 0.28 of the production elasticity of water. The contribution rate of farmland base development project cost was revealed 22% and direct production cost of rice was contributed 60% in the growth of rice production and farm mechanization costs contributed to 18% of it respectively. The two contribution rates comparing with the direct production cost were small but without irrigation water and farmland base development, application of high-pay off inputs and farm mechanization might be impossible. Considering the food security and to cope with the frequent drought, rice farming and investment for the irrigation water development should be continued even in WTO system.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.4
• /
• pp.499-505
• /
• 2015

Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake.