• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.101-109
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• 2014

It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.

• Journal of Agricultural Extension & Community Development
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• v.19 no.4
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• pp.961-987
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• 2012

The present study is to investigate the characteristics and determinants of spatial distribution of strong small farm by defining the term, strong small farm (SSF) extracting the SSF households data dealing with apples, from 2010 Census of Agriculture, Forestry and Fisheries, Korea. Spatial distribution and concentration of SSF are analyzed based on spatial clustering techniques. We construct discrete dependent variables on strong and non-strong small farms and then analyze the determinants of the SSFs using probit model, with independent variables including population and economic characteristics and management characteristics. As of 2010, the apple SSFs, 1,529 households in total, are geographically concentrated in Gyeonsangbuk-do according to the analysis results. The determinants of SSF are similar to those of farms' earnings. When located in the apple producing area, and participating in producers organization while selling products directly, the farm is highly likely an SSF. The findings and results of the present study are expected to provide fundamental information helpful for preparing and implementing policies for SSFs in that the present study investigates the characteristics of SSF, which is a prerequisite step for SSF-related policies.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.119-130
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• 2011

On the point of data quality management, data quality is influenced by quality policy, quality organization, business process, and business rule. Business rules, guide of data manipulation, have effects on data quality directly. In case of building an integration database among distributed databases, defining business rule is more important because data integration needs to consider heterogeneous structure, code, and data standardization. Also data value has various figures depended on data type, unit, and transcription. Finally, database structure and data value problem have to be solved to improve data quality. For handling them, it is needed to draw database integration model and cleanse data in integrated database. NTIS(stands for National science and Technology Information Service) has an aim to serve users who need all information about national R&D by internet, and for that aim, it has a integrated database which has been made with several database sources. We prove that database integration model and data cleansing are needed to build a successful integrated database through NTIS case study.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.143-163
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• 2019

The purpose of this study is to identify acceptance factors and influencing factors of respondents' adoption of smart IoT technology to companion animal health based on the integrated technology acceptance model. Based on the previous studies, we constructed the hypotheses by defining the technical factors, social factors, control variables, and mediating variables (UTAUT), and set the hypotheses between the independent variables of each factor and the dependent intention. A research model was designed to verify the relationship between variables. We developed questionnaires on the items and verified them through data collected from 494 people. As a result, product design, quality of service, product performance, and quality service of technological factors had a significant effects on performance expectancy and effort expectancy. However, product safety, product function awareness, and product price did not significantly affect performance expectancy and effort expectancy. Social influence had significant effects on cognitive effect, welfare system, and welfare facilities. In conclusion, the comparative analysis of technical factors and social factors showed that social factors have more significant effects on welfare systems and facilities.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.355-375
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• 2022

This study is to grasp LRM's feature and applications plan to reflect LRM to cataloging related standards and individual system through comparing and analyzing LRM with the FR model in terms of entities, attributes, and relationships. The application plan is suggested as follows. First, the entity can be extended by defining sub-entities of each entity in the standards and the individual system in order to reflect LRM, even though entities such as families, groups, identifiers, authorized access points, concepts, objects, events, agency and rules have been deleted in LRM. Second, the attribute should be subdivided in the standards and the individual system in order to apply LRM, though many attributes have been changed to relationships for linked data and decreased in LRM. In particular, more specific and detailed property names in the standards and the individual system should be clearly presented, and the vocabulary encoding scheme corresponding to each property should be also developed, since properties with similar functions or repetition in various entities, and material specific properties are generalized and integrated into comprehensive property names. Third, the relationship should be extended through newly declaring the refinement or subtype of the relationship and considering a multi-level relationship, since the relationship itself is general and abstract under increasing the number of relationships in comparing to the property. This study will be practically utilized in cataloging related standards and individual system for applying LRM.

• Journal of Industrial Convergence
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• v.20 no.8
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• pp.77-84
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• 2022

This study aims to present a method for implementing a decision support system that can be used for selecting emerging technologies by applying a machine learning-based automatic classification technique. To conduct the research, the architecture of the entire system was built and detailed research steps were conducted. First, emerging technology candidate items were selected and trend data was automatically generated using a big data system. After defining the conceptual model and pattern classification structure of technological development, an efficient machine learning method was presented through an automatic classification experiment. Finally, the analysis results of the system were interpreted and methods for utilization were derived. In a DTW-kNN-based classification experiment that combines the Dynamic Time Warping(DTW) method and the k-Nearest Neighbors(kNN) classification model proposed in this study, the identification performance was up to 87.7%, and particularly in the 'eventual' section where the trend highly fluctuates, the maximum performance difference was 39.4% points compared to the Euclidean Distance(ED) algorithm. In addition, through the analysis results presented by the system, it was confirmed that this decision support system can be effectively utilized in the process of automatically classifying and filtering by type with a large amount of trend data.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.831-846
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• 2023

The Jucheon-Pyeongchang area in the northwestern Taebaeksan Zone of the Okcheon fold-thrust belt preserved several thrust faults placing the Precambrian basement granite gneisses of the Gyeonggi Massif on top of the Early Paleozoic Joseon Supergroup and the age-unknown Bangrim Group. Especially, the thrust faults in the study area show the closed-loop patterns on the map view, showing older allochthonous strata surrounded by younger autochthonous or para-autochthonous strata. These basement-involved thrusts including Klippes will provide important information on the hinterland portion of the fold-thrust belt. For defining Klippe geometry in the thrust fault terrains of the Jucheon-Pyeongchang area by older on younger relationship, the stratigraphic position of the age-unknown Bangrim Group should be determined. The Middle Cambrian maximum depositional age by the detrital zircon SHRIMP U-Pb method from this study, together with field relations and previous research results suggest that the Bangrim Group overlies the Precambrian basement rocks by nonconformity and underlies the Cambrian Yangdeok Group (Jangsan and Myobong formations). The structural geometric interpretation of the Pyeongchang area based on newly defined stratigraphy indicates that the Wungyori and Barngrim thrusts are the same folded thrust, and can be interpreted as a Klippe, having Precambrian hanging wall granite gneisses surrounded by younger Cambrian strata of the Joseon Supergroup and the Bangrim Group. Further detailed structural studies on the Jucheon-Pyeongchang area can give crucial insights into the basement-involved deformation during the structural evolution of the Okcheon Belt.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.910-914
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• 2023

With the technological innovation owing to the 4th industrial revolution, the maritime transportation is rapidly being developed with autonomous ships and systems. Particularly, autonomous ships will partially replace the manned ships and navigation among them remotely upon the degree of autonomy suggested by IMO. Accordingly, the remote operator and related research have increased as well. However, the data on the minimum required manpower for remote operators are lacking such as considering engage required situations and their co-occurrence probability. Therefore, this study proposes a simulation model that calculates the number of remote engage required situations by defining restricted water area and remote engage required situation as close-quarter situations based on accumulated trajectory data of actual ships. The findings are expected to be used as background materials to establish the appropriate manpower distribution of remote operators in remote operation centers.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Journal of Food Hygiene and Safety
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• v.14 no.4
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• pp.319-326
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• 1999

Recently, it is continuously rising to concern about the health risk being induced by microorganisms in food such as Escherichia coli O157:H7 and Listeria monocytogenes. Various organizations and regulatory agencies including U.S.FPA, U.S.DA and FAO/WHO are preparing the methodology building to apply microbial quantitative risk assessment to risk-based food safety program. Microbial risks are primarily the result of single exposure and its health impacts are immediate and serious. Therefore, the methodology of risk assessment differs from that of chemical risk assessment. Microbial quantitative risk assessment consists of tow steps; hazard identification, exposure assessment, dose-response assessment and risk characterization. Hazard identification is accomplished by observing and defining the types of adverse health effects in humans associated with exposure to foodborne agents. Epidemiological evidence which links the various disease with the particular exposure route is an important component of this identification. Exposure assessment includes the quantification of microbial exposure regarding the dynamics of microbial growth in food processing, transport, packaging and specific time-temperature conditions at various points from animal production to consumption. Dose-response assessment is the process characterizing dose-response correlation between microbial exposure and disease incidence. Unlike chemical carcinogens, the dose-response assessment for microbial pathogens has not focused on animal models for extrapolation to humans. Risk characterization links the exposure assessment and dose-response assessment and involve uncertainty analysis. The methodology of microbial dose-response assessment is classified as nonthreshold and thresh-old approach. The nonthreshold model have assumption that one organism is capable of producing an infection if it arrives at an appropriate site and organism have independence. Recently, the Exponential, Beta-poission, Gompertz, and Gamma-weibull models are using as nonthreshold model. The Log-normal and Log-logistic models are using as threshold model. The threshold has the assumption that a toxicant is produce by interaction of organisms. In this study, it was reviewed detailed process including risk value using model parameter and microbial exposure dose. Also this study suggested model application methodology in field of exposure assessment using assumed food microbial data(NaCl, water activity, temperature, pH, etc.) and the commercially used Food MicroModel. We recognized that human volunteer data to the healthy man are preferred rather than epidemiological data fur obtaining exact dose-response data. But, the foreign agencies are studying the characterization of correlation between human and animal. For the comparison of differences to the population sensitivity: it must be executed domestic study such as the establishment of dose-response data to the Korean volunteer by each microbial and microbial exposure assessment in food.