간행물
한국산업경영시스템학회지 KCI 등재 Journal of Society of Korea Industrial and Systems Engineering
- 발행기관 한국산업경영시스템학회
- 자료유형 학술지
- 간기 계간
- ISSN 2005-0461 (Print)2287-7975 (Online)
- 수록기간 1978 ~ 2024
- 주제분류 공학 > 산업공학 공학 분류의 다른 간행물
- 십진분류KDC 530DDC 620
권호리스트/논문검색
Vol. 46 No. 1 (2023년 3월) 12건
1.
2023.03
구독 인증기관 무료, 개인회원 유료
This study is a leading case of empirical analysis of whether, when corporate stakeholders (government, investors, customers, managers, employees) put pressure on companies for ESG management, it affects the introduction and implementation of ESG activities (environmental, social, governance) and affects business performance. As for the research method, a sustainability report was published, and a web survey of Korea Research Inc. was conducted from May 10 to May 20, 2022 targeting ESG management managers of 192 companies, and analyzed through the PLS structural equation model. As a result of the study, it was found that the introduction and execution of ESG is closely influenced by the pressure from the government, investors, managers, and employees, and in particular, the internal pressure of current managers and executives and employees has a great impact on the introduction and implementation of environmental, social, and governance activities. In particular, although external pressure also has some influence, it is practical to suggest that strong internal pressure is necessary for continuous activities and performance. And, methodologically, the main activity indicators of the GRI Reporting Guidelines, which are the most representative ESG management indicators, were developed as a questionnaire, and reliability, validity, and model fit were secured through comparison with indicators of multiple systems and expert reviews. The limitations of this study are that more in-depth analysis by industry or size is possible when ESG management is mature and sufficient samples are secured, and complex ESG pressure factor modeling is possible when more diverse stakeholders are added.
4,600원
2.
2023.03
구독 인증기관 무료, 개인회원 유료
An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.
4,000원
3.
2023.03
구독 인증기관 무료, 개인회원 유료
Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.
4,000원
4.
2023.03
구독 인증기관 무료, 개인회원 유료
Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald’s (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.
4,000원
5.
2023.03
구독 인증기관 무료, 개인회원 유료
With rapid urbanization, the importance of urban warfare is increasing, and it is also required to reflect the characteristics of cities in wargame models. However, in the military's wargame models, the urbanization factor was calculated and used without theoretical basis. In this study, we investigate techniques for estimating the urbanization factor using Fractal dimension theory. The urbanization factor we propose can suggest a logical and valid representative value when used in conjunction with Agent Based Model and other methodologies.
4,000원
6.
2023.03
구독 인증기관 무료, 개인회원 유료
Guided missiles are a one-shot system that finishes their purpose after being used once, and due to the long-term storage until launch, the storage reliability is calculated during development, and performance is maintained through periodic inspections until the life cycle arrives. However, the reliability standards applied in the development of guided missiles were established by analyzing data accumulated by the United States during long-term operation in the country, and since they are different from our environment, the 00 guided missiles that have been deployed in the armed forces for more than 10 years under the premise that there is a difference from actual reliability. As a result of verifying the appropriateness of the current inspection cycle by analyzing the actual reliability of the missile, the necessity of changing the inspection period was derived because it was higher than the predicted reliability. It is proposed to build and utilize a lifespan management system that can systematically collect all data such as shooting and maintenance results by classification, and to establish a reliable reliability standard based on the accumulated data.
4,000원
7.
2023.03
구독 인증기관 무료, 개인회원 유료
Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.
4,500원
8.
2023.03
구독 인증기관 무료, 개인회원 유료
In an automotive plant, an automated storage and retrieval system (ASRS) synchronizes material handling flows from a part production line to an auto-assembly line. The part production line transfers parts on small-/large-sized pallets. The products on pallets are temporarily stored on the ASRS, and the ASRS retrieves the products upon request from the auto-assembly line. Each ASRS aisle is equipped with narrow-/wide-width racks for two pallet sizes. An ASRS aisle with narrow-/wide-width racks improves both storage space utilization and crane utilization while requiring delicate ASRS aisle design, i.e., the locations of the narrow-/wide-width racks in an ASRS aisle, and proper operation policies affect the ASRS performance over demand fluctuations. We focus on operation policies involving a common storage zone using wide-width racks for two pallet sizes and a storage-retrieval job-change for a crane based on assembly-line batch size. We model a discrete-event simulation model and conduct extensive experiments to evaluate operation policies. The simulation results address the best ASRS aisle design and suggest the most effective operation policies for the aisle design.
4,000원
9.
2023.03
구독 인증기관 무료, 개인회원 유료
Recently, the development of computer vision with deep learning has made object detection using images applicable to diverse fields, such as medical care, manufacturing, and transportation. The manufacturing industry is saving time and money by applying computer vision technology to detect defects or issues that may occur during the manufacturing and inspection process. Annotations of collected images and their location information are required for computer vision technology. However, manually labeling large amounts of images is time-consuming, expensive, and can vary among workers, which may affect annotation quality and cause inaccurate performance. This paper proposes a process that can automatically collect annotations and location information for images using eXplainable AI, without manual annotation. If applied to the manufacturing industry, this process is thought to save the time and cost required for image annotation collection and collect relatively high-quality annotation information.
4,000원
10.
2023.03
구독 인증기관 무료, 개인회원 유료
ASL estimation of public building is based on how appropriate the maximum age of the asset is derived based on the age record of the asset in the statistical data owned by public institutions. This is because we get a 'constrained' ASL by that number. And it is especially true because other studies have assumed that the building is an Iowa curve R3. Also, in this study, the survival rate is 1% as the threshold value at which the survival curve and the predictable life curve almost coincide. Rather than a theoretical basis, in the national statistical survey, the value of residual assets was recognized from the net value of 10% of the acquisition value when the average service life has elapsed, and 1% when doubling the average service life has elapsed. It is based on the setting mentioned above. The biggest constraint in fitting statistical data to the Iowa curve is that the maximum ASL is selected at R3 150%, and the 'constrained' ASL is calculated by the proportional expression on the assumption that the Iowa curve is followed. In like manner constraints were considered. First, the R3 disposal curve for the RCC(reinforced cement concrete) building was prepared according to the discarding method in the 2000 work, and it was jointly worked on with the National Statistical Office to secure the maximum amount of vintage data, but the lacking of sample size must be acknowledged. Even after that, the National Statistical Office and the Bank of Korea have been working on estimating the Iowa curve for each asset class in the I-O table. Another limitation is that the asset classification uses the broad classification of buildings as a subcategory. Second, if there were such assets with a lifespan of 115 years that were acquired in 1905 and disposed of in 2020, these discarded data would be omitted from this ASL calculation. Third, it is difficult to estimate the correct Iowa curve based on the stub-curve even if there is disposal data because Korea has a relatively shorter construction history, accumulated economic wealth since the 1980’s. In other words, “constrained” ASL is an under-estimation of its ASL. Considering the fact that Korea was an economically developing country in the past and during rapid economic development, environmental factors such as asset accumulation and economic ability should be considered. Korea has a short period of accumulation of economic wealth, and the history of 'proper' architectures faithful to building regulations and principles is short and as a result, buildings 'not built properly' and 'proper' architectures are mixed. In this study, ASL of RCC public building was estimated at 70 years.
4,000원
11.
2023.03
구독 인증기관 무료, 개인회원 유료
The records system is believed to have started in Italy in the 14th century in line with trade developments in Europe. In 1491, Luca Pacioli, a mathematician, and an Italian Franciscan monk wrote the first book that described double-entry accounting processes. In many countries, including Korea, the government accounting standards used single-entry bookkeeping rather than double-entry bookkeeping that can be aggregated by account subject. The cash-based and single-entry bookkeeping used by the government in the past had limitations in providing clear information on financial status and establishing a performance-oriented financial management system. Accordingly, the National Accounting Act (promulgated in October 2007) stipulated the introduction of double-entry bookkeeping and accrual accounting systems in the government sector from January 1, 2009. Furthermore, the Korean government has also introduced International Financial Reporting Standards (IFRS), and the System of National Accounts (SNA). Since 2014, Korea owned five national accounts. In Korea, valuation began with the 1968 National Wealth Statistics Survey. The academic origins of the valuation of national wealth statistics which had been investigated by due diligence every 10 years since 1968 are based on the 'Engineering Valuation' of professor Marston in the Department of Industrial Engineering at Iowa State University in the 1930s. This field has spread to economics, etc. In economics, it became the basis of capital stock estimation for positive economics such as econometrics. The valuation by the National Wealth Statistics Survey contributed greatly to converting the book value of accounting data into vintage data. And in 2000 National Statistical Office collected actual disposal data for the 1-digit asset class and obtained the ASL(average service life) by Iowa curve. Then, with the data on fixed capital formation centered on the National B/S Team of the Bank of Korea, the national wealth statistics were prepared by the Permanent Inventory Method(PIM). The asset classification was also classified into 59 types, including 2 types of residential buildings, 4 types of non-residential buildings, 14 types of structures, 9 types of transportation equipment, 28 types of machinery, and 2 types of intangible fixed assets. Tables of useful lives of tangible fixed assets published by the Korea Appraisal Board in 1999 and 2013 were made by the Iowa curve method. In Korea, the Iowa curve method has been adopted as a method of ASL estimation. There are three types of the Iowa curve method. The retirement rate method of the three types is the best because it is based on the collection and compilation of the data of all properties in service during a period of recent years, both properties retired and that are still in service. We hope the retirement rate method instead of the individual unit method is used in the estimation of ASL. Recently Korean government’s accounting system has been developed. When revenue expenditure and capital expenditure were mixed in the past single-entry bookkeeping we would like to suggest that BOK and National Statistical Office have accumulated knowledge of a rational difference between revenue expenditure and capital expenditure. In particular, it is important when it is estimated capital stock by PIM. Korea also needs an empirical study on economic depreciation like Hulten & Wykoff Catalog A of the US BEA.
4,600원
12.
2023.03
구독 인증기관 무료, 개인회원 유료
Recently, research on prediction algorithms using deep learning has been actively conducted. In addition, algorithmic trading (auto-trading) based on predictive power of artificial intelligence is also becoming one of the main investment methods in stock trading field, building its own history. Since the possibility of human error is blocked at source and traded mechanically according to the conditions, it is likely to be more profitable than humans in the long run. In particular, for the virtual currency market at least for now, unlike stocks, it is not possible to evaluate the intrinsic value of each cryptocurrencies. So it is far effective to approach them with technical analysis and cryptocurrency market might be the field that the performance of algorithmic trading can be maximized. Currently, the most commonly used artificial intelligence method for financial time series data analysis and forecasting is Long short-term memory(LSTM). However, even t4he LSTM also has deficiencies which constrain its widespread use. Therefore, many improvements are needed in the design of forecasting and investment algorithms in order to increase its utilization in actual investment situations. Meanwhile, Prophet, an artificial intelligence algorithm developed by Facebook (META) in 2017, is used to predict stock and cryptocurrency prices with high prediction accuracy. In particular, it is evaluated that Prophet predicts the price of virtual currencies better than that of stocks. In this study, we aim to show Prophet's virtual currency price prediction accuracy is higher than existing deep learning-based time series prediction method. In addition, we execute mock investment with Prophet predicted value. Evaluating the final value at the end of the investment, most of tested coins exceeded the initial investment recording a positive profit. In future research, we continue to test other coins to determine whether there is a significant difference in the predictive power by coin and therefore can establish investment strategies.
4,000원
