• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.217-233
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• 2020

This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.228-240
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• 2022

A comprehensive safety management system will be required in accordance with the implementation of the Major Disaster Punishment Act for close-up safety management of construction sites. Safety management level evaluation management requires a comprehensive relationship between safety management under the Construction Technology Promotion Act and health and health management system under the Industrial Safety and Health Act. Purpose: Safety under the Serious Accidents Punishment Act. The ultimate goal is to study the comprehensive analysis and relationship of health management and to improve the safety evaluation level of health and health management. Methods: The feasibility of the questionnaire was confirmed through the second Delphi analysis of construction site experts and safety managers, and the regression coefficient and path analysis of potential variants in safety management, safety management, health management and safety inspection were confirmed. Result and Conclusion: In the structural model, the regression coefficient (89%) from safety management, health system, and safety management to safety inspection execution and lambda values of appropriate observation variables were confirmed. In the path analysis, the total effect (.809) was confirmed by mediating health hygiene in the relationship between health plan establishment adequacy and post-inspection management, and the path coefficient (.82) of temporary structure safety was confirmed.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.2
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• pp.12-22
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• 2022

The purpose of this study is to design a farming model for Hanwoo start-up farmers. I prepared a Hanwoo production plan model according to the growth cycle of Hanwoo using EXCEL. The Hanwoo production plan model was simulated in two model: Model 1 (a model that only purchases Hanwoo calf) and Model 2 (a model that purchases both Hanwoo cow and Hanwoo calf). Next, I reviewed the profits and costs of two Hanwoo simulation models. As a result of the analysis, Model 2 has the following characteristics compared to Model 1. First, Model 2 requires a lot of initial investment. Second, Model 2 is advantageous in terms of farm cash balance because imports occur every year. Third, Model 2 can efficiently use facilities and machines.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.117-124
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• 2023

Through reorganization in 2008, The ministry of Agriculture, Food and Rural Affairs integrated management of the food industry by transferred functions which was scattered in the Ministry of Health and Welfare, and established comprehensive policies covering the primary, secondary, and tertiary industries. In the agricultural industry sector, new business concepts such as smart farm and food tech have recently emerged alongside the fourth industrial revolution. In order for the Ministry of Agriculture, Food, and Rural Affairs to develop appropriate policies for the fourth industrial revolution, it is necessary to accurately estimate the size of agricultural and livestock-related businesses. In 2017, the Ministry of Agriculture, Food, and Rural Affairs initiated research for the agriculture, livestock and food industry's special classification, which was approved by the National Statistical Office in 2020. The estimation of the agriculture, livestock and food industry's size based on special classification is crucial because it has a substantial impact on the formulation and significance of policies. In this paper, the appropriate rate was derived from samples extracted from the special classification and the Korean standard industrial classification. Proposed are a method for estimating the population of the agricultural and livestock food industry, as well as a method for calculating the appropriate rate that more accurately reflects the population than the method currently in use.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.259-266
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• 2023

It is very difficult to measure the performance of the machine learning model in the business service stage. Therefore, managing the performance of the model through the operational department is not done effectively. Academically, various studies have been conducted on the concept drift detection method to determine whether the model status is appropriate. The operational department wants to know quantitatively the performance of the operating model, but concept drift can only detect the state of the model in relation to the data, it cannot estimate the quantitative performance of the model. In this study, we propose a performance prediction model (PPM) that quantitatively estimates precision through the statistics of concept drift. The proposed model induces artificial drift in the sampling data extracted from the training data, measures the precision of the sampling data, creates a dataset of drift and precision, and learns it. Then, the difference between the actual precision and the predicted precision is compared through the test data to correct the error of the performance prediction model. The proposed PPM was applied to two models, a loan underwriting model and a credit card fraud detection model that can be used in real business. It was confirmed that the precision was effectively predicted.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.219-227
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• 2017

Current military command information system uses electronic equipment a lot on which semiconductor chip is attached. It seems its' importance will increase more with latest information communication technology developing. Electronic equipment which uses electricity contains regular tolerance to high output electric signal. And EMC specification is the standardized of this electronic equipment's tolerance. On the other hand, the Institute of Atomic Energy Research has ever declared that high output electromagnetic pulse(EMP) will be broken out within the radius of 170Km when 10kt nuclear explosion occurs at an altitude of 40Km above Seoul. Then, the region suffer from the damage of most electronic equipments. Therefore, the norm to protect the influences in that case is defined by EMP protection specification. Most common electronic equipments meet the EMC norm, but there is no way to check whether they meet the EMP norm or not. That is because it is difficult to check whether they meet EMP protection norm and is on the matter of cost. Except inevitable cases, there is no review of checking whether they meet the norm or not. Considering the above, in this research, we speculate about the measures to improve military EMP protection ability by analyzing the EMC-EMP correlation and checking the EMP protection ability of general electronic equipment through the analysis.

• Journal of Technology Innovation
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• v.31 no.3
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• pp.139-169
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• 2023

This study analyzes the effects of firms' technology innovation(patent applications) on employment(number of workers and proportion of high-skilled workers) and corporate performance(sales per worker), while considering the two-way causal relationships between these variables. We used the three-stage least squares(3SLS) estimation to examine system of equations in which the dependent variables affect each other with a two-year lag wherever relevant, and applied it to firm-level panel data of Korean manufacturers with 100 or more workers. Our data covered the period of 2005-2017. Exogenous variables, such as firms' managerial and other characteristics, were controlled as explanatory variables. The identification variables for each equation included firms' R&D intensity, labor cost per worker(or operation of firms' own R&D center), and investment on worker training. We find that firms' patent applications increased number of workers, proportion of high-skilled workers, and sales per worker; the causal relationships in the opposite direction were also significant. Evidently, firms' technology innovation is critical to the growth and quality improvement of employment as well as sustainable corporate growth.

• Information Systems Review
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• v.19 no.3
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• pp.1-21
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• 2017

The Internet of Things (IoT) analysis aims to verify the technical characteristics, performance expectations, and adoption intentions of IoT. This work refers to IoT data from foreign and domestic publications and websites as well as aims to benefit related organizations by referring to reports from agencies. The literature review summarizes the relevant theories and background of the unified theory of acceptance and use of technology. The SPSS 22.0 software and structural equation models (smart PLS 2.0) are used in the data analysis. Technical statistics analysis, reliability analysis, validity analysis, structural equation models, and statistical methods are employed to test the research hypotheses, that is, the technical characteristics of IoT will have positive effects on its performance expectations. This study introduces the characteristics and expected performance of IoT to present relevant IoT guidelines for companies that aim to adopt such technology.