• Explosives and Blasting
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• v.41 no.3
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• pp.62-72
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• 2023

The aging of plant structures due to industrialization in the 1970s has increased the demand for blast demolition. While blasting can reduce exposure to environmental pollution by shortening the demolition period, improper blasting design and construction plans pose significant safety risks. Thus, it is vital to consider optimal blasting demolition conditions and other factors through collapse behavior simulation. This study utilizes a 3-D combined finite-discrete element method (FDEM) code-based 3-D DFPA to simulate the collapse of a chimney structure in a thermal power plant in Seocheon, South Korea. The collapse behavior from the numerical simulation is compared to the actual structure collapse, and the numerical simulation result presents good agreement with the actual building demolition. Additionally, various numerical simulations have been conducted on the chimney models to analyze the impact of the duct size in the pre-weakening area. The no-duct, duct, and double-area duct models were compared in terms of crack pattern and history of Z-axis displacement. The findings show that the elapse-time for demolition decreases as the area of the duct increases, causing collapse to occur quickly by increasing the load-bearing area.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.172-177
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• 2023

In this paper, 2-dimensional backtracking method for ultrasonic signals. Ultrasonic sensors are a common technology used in industrial fields as many studies have been conducted on distance measurement and indoor location tracking using transmission and reception devices in pairs. A method for tracking a signal of an arbitrary ultrasonic transmission device on a 2D plane using only a receiver of an ultrasonic signal is proposed. In order to track the ultrasonic signal, the receiver receives the signal by making at least three. The three receivers may calculate a direction and a distance using a time difference in which the ultrasound reception sound is reached. The existing method of tracking signal sources using ultrasonic waves has a problem of time synchronization of devices because the transceivers must be paired or installed independently for each sensor. In order to solve this problem, the distance of the ultrasonic receiver is minimized, and it is configured as one device. The sensor installed as one device may be processed by one operator, thereby solving the time synchronization problem. To increase time difference accuracy, high-speed 32-bit timers with high time resolution can be used to quickly calculate and track distances and directions.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.41-58
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• 2023

As naval warfare changes to composite warfare that includes simultaneous engagements against surface, underwater, and air enemies, performance and tactical analysis are required to respond to naval warfare. In particular, for practical analysis of composite warfare, it is necessary to study engagement simulations that can appropriately utilize the limited performance resources of the detection system. This paper proposes a DEVS (Discrete Event Systems Specifications)-based simulation model for composite warfare analysis. The proposed model contains generalized models of combat platforms and armed objects to simulate various complex warfare situations. In addition, we propose a detection performance allocation algorithm that can be applied to a detection system model, considering the characteristics of composite warfare in which missions must be performed using limited detection resources. We experimented with the effectiveness of composite warfare according to the strength of the detection system's resource allocation, the enemy force's size, and the friendly force's departure location. The simulation results showed the effect of the resource allocation function on engagement time and success. Our model will be used as an engineering basis for analyzing the tactics of warships in various complex warfare situations in the future.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.77-84
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• 2023

In the agricultural sector, power sources are being developed that use alternative energy sources such as electric tractors and hydrogen tractors, away from internal combustion engine tractors. As parts such as engines and transmissions used in conventional internal combustion engine tractors are replaced with motors and batteries, the center of gravity changes, and thus the risk of rollover should be considered. The purpose of this study is to analyze the overturn angle of the main parts of the electric tractor through dynamic simulation to minimize the overturn accident and to derive the optimal arrangement of parts to improve stability. A total of nine dynamics simulations were conducted by designing three components of the PTO motor, drive motor and the battery pack, and three factors of the arrangement method. As a result of the experiment, it was confirmed that Type3 Level3, in which the drive motor and the PTO motor are located at the front and rear of the tractor, and two battery packs are located in the middle of the tractor, has a high rollover angle. As a result of this study, the stability increased as the center of gravity was placed backward and located below. Future research needs to be done to find the optimal location of parts considering their performance and placement efficiency.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.1-10
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• 2023

Due to the development of the industrial revolution, regulations on exhaust emissions have been continuously strengthened to reduce the rapidly increasing greenhouse gas emissions. The use of environmentally friendly fuels is essential to meet these regulations. Hydrogen has been attracting attention as a future environmentally friendly fuel, but due to its material properties, it faces significant challenges in handling and storage. As an alternative, ammonia has been proposed. Ammonia can be easily liquefied at room temperature compared to hydrogen and has a high energy density. In order to examine the applicability of ammonia as an engine fuel, experiments were conducted to investigate the effects of changes in combustion control parameters in a direct injection ammonia combustion engine. The experiments were conducted by varying two variables: spark timing and excessive air ratio. Observations were made on combustion stability and the trends of exhaust emissions such as nitrogen oxides and unburned ammonia under the conditions of an engine speed of 1,500 rpm and medium to high loads (brake torque of 200 Nm). By optimizing the combustion control parameters, conditions for stable combustion even when using ammonia as the sole fuel were identified, and plans are underway to apply strategies for future expansion of the operating range.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.347-373
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• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.325-345
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• 2023

In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1143-1150
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• 2023

The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R² values.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.71-88
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• 2022

The purpose of this study is to develop the competencies to help micro entrepreneurs who have experienced failure to successfully re-challenge. To this end, relevant literature published from 1977 to 2022 was analyzed, behavioral event interviews (BEI) were conducted with 7 successful micro entrepreneurs, and focus group interviews (FGI) were conducted three times by inviting competency development and HRD experts. Based on these research activities, the draft about competencies for micro entrepreneurs who had have failure was derived. And then inviting 12 experts in related field for Delphi Analysis, the final competency model that helps micro entrepreneurs successfully recover were developed as follows : Competency Groups(small business owners, recovery from failure), 8 detailed competencies(seize business opportunities, business planning, business differentiation, operation management, market exploration, research and development of products and services, positive self-regulation, overcoming and coping with failure experiences), 22 competency factors, and 72 behavioral indicators. This study has an academic significance in that it developed the competencies required for micro entrepreneurs recovering from failure. In addition, the results of this study can be used to develop a competency-based education program for micro entrepreneurs and to select suitable candidates for support programs.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.1-16
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• 2022

This paper studies the impact of regulatory approaches on innovation and entrepreneurship. As technological progress and environmental changes avail new business opportunities to innovative startups, many governments find it difficult to regulate new and unprecedented businesses promoted by the innovative firms. In order to provide academic and practitional implications on the regulatory design with which to support innovation and entrepreneurship, this paper aims to review classical theories on the demand and supply of regulation as well as empirical research on the impact of regulation on market entry and incentives for innovation. Based on the findings, this paper discusses the recent controversies around the regulatory approaches on new businesses pursued by startups, which are as known as the "positive regulatory approach" vs. "negative regulatory approaches" among practitioners and policy makers in Korea. This paper claims that the Korean context provides an useful opportunity to investigate how the ongoing transition of the once "fast follower" economy into a pacesetter one changes the nature of businesses pursued by firms, investors, and related market players and, accordingly, calls for the changes in the way the government intervenes in markets to regulate businesses of firms. By doing so, this paper sheds light on the role of the government in establishing an entrepreneurial ecosystem where innovative ideas of startups can be tested and nurtured.