• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.187-195
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• 2023

This study propose to develop artificial intelligence liberal arts courses for college students in the humanities and social sciences majors using the entry artificial intelligence model. A group of experts in computer, artificial intelligence, and pedagogy was formed, and the final artificial intelligence liberal arts course was developed using previous research analysis and Delphi techniques. As a result of the study, the educational topics were largely composed of four categories: image classification, image recognition, text classification, and sound classification. The training consisted of 1) Understanding the principles of artificial intelligence, 2) Practice using the entry artificial intelligence model, 3) Identifying the Ethical Impact, and 4) Based on learned, team idea meeting to solve real-life problems. Through this course, understanding the principles of the core technology of artificial intelligence can be directly implemented through the entry artificial intelligence model, and furthermore, based on the experience of solving various real-life problems with artificial intelligence, and it can be expected to contribute positively to understanding technology, exploring the ethics needed in the artificial intelligence era.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.641-647
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• 2023

In the fintech environment, ensuring secure financial transactions with smartphones requires authenticating the device owner. Smartphone authentication techniques encompass a variety of approaches, such as passwords, biometrics, SMS authentication, and more. Among these, password-based authentication is commonly used and highly convenient for user authentication. Although it is a simple authentication mechanism, it is susceptible to eavesdropping and keylogging attacks, alongside other threats. Security keypads have been proposed to address vulnerabilities in password input on smartphones. One such innovation is a group keypad, resistant to attacks that guess characters based on touch location. However, improvements are needed for user convenience. In this study, we aim to propose a method that enhances convenience while being resistant to eavesdropping and recording attacks on the existing group keypad. The proposed method uses new signs to allow users to verify instead of the last character confirmation easily and employs dragging-to-touch for blocking recording attacks. We suggest diverse positioning methods tailored for domestic users, improving efficiency and security in password input compared to existing methods.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.121-131
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• 2024

This research explores the potential of leveraging unstructured data from construction supervision documents, which contain detailed inspection insights from independent third-party monitors of building construction processes. With the evolution of analytical methodologies, such unstructured data has been recognized as a valuable source of information, offering diverse insights. The study introduces a framework designed to assess cost performance by applying advanced analytical methods to the unstructured data found in final construction supervision reports. Specifically, key phrases were identified using text mining and social network analysis techniques, and these phrases were then analyzed through binomial logistic regression to assess cost performance. The study found that predictions of cost performance based on unstructured data from supervision documents achieved an accuracy rate of approximately 73%. The findings of this research are anticipated to serve as a foundational resource for analyzing various forms of unstructured data generated within the construction sector in future projects.

• Information Systems Review
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• v.20 no.2
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• pp.189-207
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• 2018

This study aims to analyze price information system and pricing label operation process, which are important information delivery systems of retail stores. This study also intends to identify the problems in store operation and identify academic and practical methods. In-depth interviews, direct observation, and service blueprint techniques were used to define problems in the existing business operation process, and an operating process based on the electronic shelf label (ESL) system is designed as an alternative to problem solving. The changes of the operating process before and after introduction were compared. Results of this study suggest practical implications that the ESL system can be used to solve the problems of the current price management process. The study also suggests the academic significance of presenting a complex research method of problem finding, cause analysis, and alternative presentation by using each research method complementarily.

• Journal of Physiology & Pathology in Korean Medicine
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• v.38 no.2
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• pp.49-58
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• 2024

The rapid advancement of generative large language models has revolutionized various real-life domains, emphasizing the importance of exploring their applications in healthcare. This study aims to examine how generative large language models are implemented in the medical domain, with the specific objective of searching for the possibility and potential of integration between generative large language models and East Asian medicine. Through a comprehensive current state analysis, we identified limitations in the deployment of generative large language models within East Asian medicine and proposed directions for future research. Our findings highlight the essential need for accumulating and generating structured data to improve the capabilities of generative large language models in East Asian medicine. Additionally, we tackle the issue of hallucination and the necessity for a robust model evaluation framework. Despite these challenges, the application of generative large language models in East Asian medicine has demonstrated promising results. Techniques such as model augmentation, multimodal structures, and knowledge distillation have the potential to significantly enhance accuracy, efficiency, and accessibility. In conclusion, we expect generative large language models to play a pivotal role in facilitating precise diagnostics, personalized treatment in clinical fields, and fostering innovation in education and research within East Asian medicine.

• Journal of Distribution Science
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• v.22 no.4
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• pp.11-22
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• 2024

Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.

• The Journal of Fisheries Business Administration
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• v.16 no.1
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• pp.91-124
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• 1985

Mariculture is contrasted with inland aqua-culturing fisheries. It is defind as the Industry of rearing Aquaorganism in limited coastal area relatively shallow in depth. Then, It's coming into being realization of Mariculture in it is long in history that Mariculture was realized in Korea. But it is from the early part of 1960s, that this industry has normally developed. Owing to 200 miles economy-zone problems of coastal countries, the development of deep sea fishing was limited, so the Korean Government has now appreciated the importance of cultured industries in the field of coastal fisheries. And the Korean Mariculture the output of which was only 18, 000 M/T in '60s attained 540, 000M/T in 1980s, has now occupied its relative importance in Korean Fisheries Industry. So the purpose of this report is to suggest the prospect of technical development of mariculture in the future of Korea, through the analysis of the various problems that affect upon the individual management '||'&'||' fishing ground utilization, along with the appreciation of "how to extend of those technical innovation" and "how the fishermen's technique level is extended at this stage. According to this study, the result is summarized as follows. First, Maricultural technique is classified into 8 sub-techniques as follows, as shown in fig. 1.Fig. 1. The Formation structure of mariculture technique Second, the change of technical method of mariculture in coastal area of Korea has made as 5 stages; 1) Scattering of culturing organism 2) Culturing by putting stone and installing bamboo 3) Culturing by installing rope and seeding 4) Culturing of putting objectives in cages 5) Culturing fish by feed Third, the maricultural fisheries of Korea has about 70 years long in history. It began from 1910s. But at that time there was no special technique in aquaculture and its technique was confined in searching out the object of species. The species was laver, oyster ect.Forth, although realization of mariculture in Korea has been long time, it is of late from 1960s that this has been industrial with normal development, and its technique of mariculture has mainly has developed from 1970s. Its result not only contributed to the high growth in Korean ecconomy along with the well balanced development between industires, but also it played a great role for the resolution of nation's food problem. Especially maricultural production has shown its sustained annual increase of 13.8% during the last 20 years. So the portion of mariculture among total fisheries stucture was extended from 4.1% in the early 1960s to 22.4% in 1980s.Fifth, it could be safely said that such development in maricultural field is resulted from the activity of aquacultural institutes such as Fisheries Reseach '||'&'||' Development production of major kinds such as Oyster, Sea-mustard, and Laver etc. As well as in the innovation of aquaculturing method with synthetic fiber utilization. FRDA has played important role in the efficient propargation of new aquacultural technique.Sixth, as for the change in aquaculture structure and its during period between 1970s and 1980s, the private management participation shown 25% increase from household number of 45, 173 to 56, 268 in total number. And in the respect of the management scale, of their management decreased, while it showed an increase in relative large scale management, the increase over 3 employees compared with other fisheries field between '70s and 80s. This must be an major trait to be recorded, Now the data above mentioned are shown as in table 1 and 2.Table 1. The maricultural fishing ground development situation in 982.Table 2. The mariculture management as seen in the employmnet size in high seasion.Owing to the technical innovation, of the mariculture in coastal area new income of fishermen increased and it also is true that the number of fishermen participating in its industrialization increased. But the problem being from now on is the self-discharge of the destruction fishing ground considered resulted from rapid expansion in aquaculture industry and the preventive system of sentility of fishing ground. sentility of fishing ground.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).