• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.2
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• pp.38-44
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• 2008

Titanium and its alloys, due to their superior properties of high specific strength and excellent corrosion resistance, are increasingly used in living applications in the 21century. The applications in aerospace and medical industries demand machining process more frequently to obtain a desired product. But unfortunately, this material is one of the most difficult-to-cut. In the turning process of titanium alloys, the key point for successful work is to select proper tool materials and cutting conditions. This study suggests a guidance for selecting the tool materials and the cutting speeds to improve tool life and surface integrity in Ti-6Al-4V titanium turning process. The experiments investigate the change of surface roughnesses, cutting forces and flank wear with various cutting parameters of tool materials, depth of cuts and feeds. As the results, K10 type of insert tip was assured as the best for turning of Ti-6Al-4V titanium alloy.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.770-802
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• 2022

With the development of deep learning techniques, text mining is producing breakthrough performance improvements, promising future applications, and practical use cases across many fields. Likewise, even though several attempts have been made in the field of financial information, few cases apply the current technological trends. Recently, companies and government agencies have attempted to conduct research and apply text mining in the field of financial information. First, in this study, we investigate various works using text mining to show what studies have been conducted in the financial sector. Second, to broaden the view of financial application, we provide a description of several text mining techniques that can be used in the field of financial information and summarize various paradigms in which these technologies can be applied. Third, we also provide practical cases for applying the latest text mining techniques in the field of financial information to provide more tangible guidance for those who will use text mining techniques in finance. Lastly, we propose potential future research topics in the field of financial information and present the research methods and utilization plans. This study can motivate researchers studying financial issues to use text mining techniques to gain new insights and improve their work from the rich information hidden in text data.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.86-102
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• 2024

Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.327-332
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• 2021

Materials used for education include SM20C, Al6061, and acrylic. SM20C materials are used a lot in certification tests and functional competitions as carbon steel, but they are also used in industrial sites. Al6061 is said to be a material that produces a lot of tools because it has lower hardness than carbon steel and is highly flexible. When practical guidance is given to students using acrylic materials, it is a material that causes vibration and tool damage due to excessive cutting. In this process, we examine how impact on the 5-axis equipment 2NC head can affect precision control. The weakest part of a five-axis equipment is the head that controls the AC axis. In the event of precision and cumulative tolerances in this area, the precision of all products is reduced. Thus, a key part of the 2NC head, the spindle housing was carried out using Al7075 T6 (U.S. Alcoasa) material and the entire body using FCD450 (spherical graphite cast iron). In the vibration and cutting process acting on these two materials, the analysis was carried out to determine the value of applying the force as a finite element analysis under extreme conditions. We hope that using these analytical data will help students see and understand the structure of 5-axis machining rather than 5-axis cutting.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.61-74
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• 2022

Recently, youth unemployment, especially the unemployment problem of university graduates, has emerged as a social problem. Unemployment of university graduates is both a pan-national issue and a university-level issue, and each university is making many efforts to increase the employment rate of graduates. In this study, we present a model that predicts employment availability of D-university graduates by utilizing Machine Learning. The variables used were analyzed using up to 138 personal information, admission information, bachelor's information, etc., but in order to reflect them in the future curriculum, only the data after admission works effectively, so by department / student. The proposal was limited to the recommended ability to improve the separate employment rate. In other words, since admission grades are indicators that cannot be improved due to individual efforts after enrollment, they were used to improve the degree of prediction of employment rate. In this research, we implemented a employment prediction model through analysis of the core ability of D-University, which reflects the university's philosophy, goals, human resources awards, etc., and machined the impact of the introduction of a new core ability prediction model on actual employment. Use learning to evaluate. Carried out. It is significant to establish a basis for improving the employment rate by applying the results of future research to the establishment of curriculums by department and guidance for student careers.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.267-277
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• 2022

Achievement at university is recognized in a comprehensive sense as the level of qualitative change and development that students have embodied as a result of their experience in university education. Therefore, the academic achievement of university students will be given meaning in cooperation with the historical and social demands for diverse human resources such as creativity, leadership, and global ability, but it is practically an indicator of the outcome of university education. Measurement of academic achievement by such credits involves many problems, but in particular, standardization of academic achievement by credits based on evaluation methods, contents, and university rankings is a very difficult problem. In this study, we present a model that uses machine learning techniques to predict whether or not academic achievement is excellent for D-University graduates. The variables used were analyzed using up to 96 personal information and bachelor's information such as graduation year, department number, department name, etc., but when establishing a future education course, only the data after enrollment works effectively. Therefore, the items to be analyzed are limited to the recommended ability to improve the academic achievement of the department/student. In this research, we implemented an academic achievement prediction model through analysis of core abilities that reflect the philosophy, goals, human resources image, and utilized machine learning to affect the impact of the introduction of the prediction model on academic achievement. We plan to apply the results of future research to the establishment of curriculum and student guidance conducted in the department to establish a basis for improving academic achievement.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.1
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• pp.19-34
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• 1997

The goals of this study are to suggest the guidance for automated clothing manufacture by analysis the technology of the automated manufacturing facilities and to propose how improve the efficiency of the production planning and management for automated clothing manufacture In this study, the research about the automated clothing manufacturing machines and the analysis about the modules and functions of apparel information systems were performed. In order to understand the factory automation of the larger clothing firms, the case study method was used. The case study samples were 3 clothing firms. The results and suggestions are as follows: 1. An information technology for automated clothing manufacture has enabled the computer integrated manufacturing system to connect production planning and management part with each work station on the factory floor. 2. The apparel information system to integrate and manage manufacturing informations from each workstation and the apparel CAD system are used in the department of production planning. At the cutting room, there are automated manufacturing machines like an automatic spreading system and an automatic cutting system. Sewing room has the computer controlled unit production system and semi-automated sewing machines. In addition, in the finishing room, an automatic packing machine and a press system are used and besides a warehousing system has been developed. Considering these available technology, for better product efficiency, it is necessary to consider and utilize the specific character of these automatic manufacturing machines and computer system whether they proper to each product style. 3. Most of the clothing manufacturers are in the stage of semi-automated manufacture. In order to improve the manufacturing environment, it is needed to gradual procedure of manufacturing automation with considering the firm's financial condition, existing facilities and staffs operating machines. The case study sample firms are in the high degree of manufacturing automation. They can accomplish the flexible manufacturing system to link the information system with each work station menufacturing system by computerized control. For the case of the firm having already used the computer integrated manufacturing and managing system, it is necessary that the function to deal with drawing information is added to the retaining module of the apparel system.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.31-38
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• 2020

In this paper, we compare and analyze smart technologies and present six obstacle detection features to help visually impaired people walk. Traditionally, visually impaired people walk with the white cane or a guide dog. With the development of IoT technology, various smart walking aids systems have been developed. Those intelligent walking aids systems have obstacle-detecting systems and route-guidance systems. Many researchers are developing the walking aids system, which detects an obstacle and provides the obstacle information by haptic feedback. Also, they are designing the database server system to share the obstacle information. Particularly the composed system can quickly give an obstacle-avoidance route using shared obstacle information. Smart walking aids systems for visually impaired people will advance more rapidly by applying machine learning and intelligent systems.

• Journal of Korean Library and Information Science Society
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• v.48 no.2
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• pp.215-236
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• 2017

The purpose of this study is to develop an automatic classification system for recommending appropriate books of 9 enneagram personality types, using book information data reviewed by librarians. Data used for this study are book review of 501 recommended titles for children and young adults from National Library for Children and Young Adults. This study is implemented on the assumption that most people prefer different types of books, depending on their preference or personality type. Performance test for two different types of machine learning models, nonlinear kernel and linear kernel, composed of 360 clustering models with 6 different types of index term weighting and feature selections, and 10 feature selection critical mass were experimented. It is appeared that LIBLINEAR has better performance than that of LibSVM(RBF kernel). Although the performance of the developed system in this study is relatively below expectations, and the high level of difficulty in personality type base classification take into consideration, it is meaningful as a result of early stage of the experiment.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.583-590
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• 2019

The purpose of this study is to develop an educational program for learning deep learning concepts for elementary school students. The model of education program was developed the deep-learning teaching method based on CT element-oriented teaching and learning model. The subject of the developed program is the artificial intelligence image recognition CNN algorithm, and we have developed 9 educational programs. We applied the program over two weeks to sixth graders. Expert validity analysis showed that the minimum CVR value was more than .56. The fitness level of learner level and the level of teacher guidance were less than .80, and the fitness of learning environment and media above .96 was high. The students' satisfaction analysis showed that students gave a positive evaluation of the average of 4.0 or higher on the understanding, benefit, interest, and learning materials of artificial intelligence learning.