• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.8
• /
• pp.1709-1715
• /
• 2005

This paper describes the development of 3-D web graphic library for dynamic web graphic design. The 3-D web graphic library developed in this per supports creation of 3-D objects like cube and sphere objects, elimination of hidden line and surface, and the shading of diffuse and specular reflections. It provides, in drawing, perspective projection of an object depth first sort of multiple objects, and wire frame and solid models. It also supports texture mapping function for realistic and dynamic web application in application software. Each created 3-D object gives functions for the scaling, translation, and rotation of itself. It can be used for the development of dynamic web application software and the advertisement of information for business and tourism as a 3-D web graphic library engine. It is written in 'Java' language and runs on web browsers with Java virtual machine without any dependancy of client computer system.

• Biomedical Engineering Letters
• /
• v.8 no.4
• /
• pp.337-344
• /
• 2018

Additive manufacturing (AM) is an alternative metal fabrication technology. The outstanding advantage of AM (3D-printing, direct manufacturing), is the ability to form shapes that cannot be formed with any other traditional technology. 3D-printing began as a new method of prototyping in plastics. Nowadays, AM in metals allows to realize not only net-shape geometry, but also high fatigue strength and corrosion resistant parts. This success of AM in metals enables new applications of the technology in important fields, such as production of medical implants. The 3D-printing of medical implants is an extremely rapidly developing application. The success of this development lies in the fact that patient-specific implants can promote patient recovery, as often it is the only alternative to amputation. The production of AM implants provides a relatively fast and effective solution for complex surgical cases. However, there are still numerous challenging open issues in medical 3D-printing. The goal of the current research review is to explain the whole technological and design chain of bio-medical bone implant production from the computed tomography that is performed by the surgeon, to conversion to a computer aided drawing file, to production of implants, including the necessary post-processing procedures and certification. The current work presents examples that were produced by joint work of Polygon Medical Engineering, Russia and by TechMed, the AM Center of Israel Institute of Metals. Polygon provided 3D-planning and 3D-modelling specifically for the implants production. TechMed were in charge of the optimization of models and they manufactured the implants by Electron-Beam Melting ($EBM^{(R)}$), using an Arcam $EBM^{(R)}$ A2X machine.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.4
• /
• pp.510-518
• /
• 2022

The diagnostic evaluation conducted at the national level is very important to detect underachievers in school early. This study used an artificial intelligence method to find the characteristics of underachievers that affect learning development for middle school students. In this study an artificial intelligence model was constructed and analyzed to determine whether the Busan Education Longitudinal Data in 2020 by entering data from the first year of middle school in 2019. A predictive model was developed to predict basic middle school Korean, English, and mathematics education with machine learning algorithms, and it was confirmed that the accuracy was 78%, 82%, and 83%, respectively, in the prediction for the next school year. In addition, by drawing an achievement prediction decision tree for each middle school subject we are analyzing the process of prediction. Finally, we examined what characteristics affect achievement prediction.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1295-1302
• /
• 2021

As the market size of 3D printers increases, the precision of the printout and the speed of operation by the motor are very important issues. In this parer, G-code of each output was generated using a CURA program to compare whether the output of the PLC equipment is the same as that of the Arduino CNC. And after conversion to NC File, a pen was attached to each device to output a result to A4 paper. As a result, the output time was measured to be 1m 39s for PLC equipment and 2m 5s for Arduino CNC. In addition, it was confirmed that the 2D output was equally from the two equipments.

• Journal of The Korean Association of Information Education
• /
• v.26 no.5
• /
• pp.417-425
• /
• 2022

The 'Comprehensive Plan for Nurturing Digital Talents' reported at the Cabinet meeting of the Ministry of Education in August 2022 focuses on qualitative and quantitative expansion of informatics education centered on SW, AI education. With the advent of the era of artificial intelligence, data science education is also drawing attention as a field of informatics education. Data science is originally a field where various studies are fused, and advanced technologies are being used for data analysis, modeling, and machine learning. This study devised a draft of the instructional model of data science education through literature research and analysis of previous studies, and developed a final instructional model through usability test and expert validation.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.4
• /
• pp.1-7
• /
• 2009

This paper presents a process routing (PR) algorithm with multiple objectives. PR determines the optimum sequence of operations for transforming a raw material into a completed part within the available machining resources. In any computer aided process planning (CAPP) system, selection of the machining operation sequence is one of the most critical activities for manufacturing a part and for the technical specification in the part drawing. Here, the goal could be to generate the sequence that optimizes production time, production cost, machine utilization or with multiple these criteria. The Pareto Stratum Niche Cubicle (PS NC) GA has been adopted to find the optimum sequence of operations that optimize two conflicting criteria; production cost and production quality. The numerical analysis shows that the proposed PS NC GA is both effective and efficient to the PR problem.

• Journal of Korean society of Dental Hygiene
• /
• v.22 no.6
• /
• pp.467-475
• /
• 2022

Objectives: This study aimed to understand the definitions, types, and principles of computer-aided design/computer-aided manufacturing (CAD/CAM) and scanners due to the introduction of digital workflows. Methods: This study was based on information from the government's law and articles published in academic journals. Results: CAD/CAM is a technology that measures the shape three-dimensionally, saves it as data, designs it into the desired shape, and processes the product. Scanners, which are classified as intraoral and extraoral scanners, measure teeth and the intraoral environment three-dimensionally and convert them into three-dimensional (3D). A 3D printer is a machine that creates a 3D object by layering materials based on a 3D drawing. It can be classified into four types according to the method: extrusion, powder bonding, lamination, and photopolymerization methods. The most used 3D printer methods in dentistry are stereolithograhpy and digital light processing, and they are widely used in prosthetic, surgical, and orthodontic fields. Conclusions: As the dental system is digitized, it is expected that the government will classify the dental hygienist scope of work and the universities will reflect the curriculum; it is necessary to develop excellent dental hygienists, diversify the educational pathways, and establish policies to meet the needs of the increasing number of patients.

• Geomechanics and Engineering
• /
• v.37 no.3
• /
• pp.223-241
• /
• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.

• Science of Emotion and Sensibility
• /
• v.25 no.4
• /
• pp.45-52
• /
• 2022

Recently, interest in and demand for sensors that recognize physical activity and their products are increasing. In particular, the development of wearable materials that are flexible, stretchable, and able to detect the user's biological signals is drawing attention. In this study, an experiment was conducted to improve the dip-coating efficiency of a single-walled carbon nanotube dispersion solution after fine holes were made in a hydrophobic material with a micro needle. In this study, dip-coating was performed with a material that was not penetrated, and comparative analysis was performed. The electrical conductivity of the sensor was measured when the sensor was stretched using a strain universal testing machine (Dacell Co. Ltd., Seoul, Korea) and a multimeter (Keysight Technologies, Santa Rosa, CA, USA) was used to measure resistance. It was found that the electrical conductivity of a sensor that was subjected to needling was at least 16 times better than that of a sensor that was not. In addition, the gauge factor was excellent, relative to the initial resistance of the sensor, so good performance as a sensor could be confirmed. Here, the dip-coating efficiency of hydrophobic materials, which have superior physical properties to hydrophilic materials but are not suitable due to their high surface tension, can be adopted to more effectively detect body movements and manufacture sensors with excellent durability and usability.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.149-169
• /
• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."