• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.05a
• /
• pp.851-852
• /
• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.11a
• /
• pp.879-880
• /
• 2010

• Science of Emotion and Sensibility
• /
• v.12 no.2
• /
• pp.233-242
• /
• 2009

Recently the studies on user-centered design and form-development have become issues of general interest as the key methods for successful design. For form analysis on user it is important needs that an integrated approach of existing methods and development of expert tool for designer. Moreover analysis methods and tools have to meet with the designers needs of visual result, clear direction, concrete formative factor, user's emotional response and designer-friendly interface. This study proposed the main concepts of form analysis tool based on the user's emotional response ; integrated management, variables set-up, visual result of analysis, in-depth analysis with data mining and correlation, and reinforcement of user-centered analysis. Specific analysis tool consists of 5 functions: Project Management, Analysis Frame Set-up, Data Input-output, Basic Analysis, and In-depth Analysis. The feasibility of proposed tool was verified by a case study of mobile phone design in under-graduate class.

• Knowledge Management Research
• /
• v.23 no.4
• /
• pp.69-89
• /
• 2022

As we enter a super-aged society, senior citizens' health issues are affecting a variety of fields, including medicine, economics, society, and culture. In this study, we intend to draw implications from unstructured data analysis such as text mining and social network analysis in order to apply digital health care service design for improving the cognitive ability of senior citizens. The research procedure of this study improved the service design methodology into a process suited to the analysis of unstructured data, and six steps were applied. Related keywords that exist on social media, focusing on cognitive improvement and healthcare for senior citizens, were collected and analyzed, and based on these results, the direction of healthcare service design for improving on the cognitive abilities of senior citizens was derived. The results of this study are expected to have academic and practical implications for expanding the scope of the use of big data analysis methods and improving existing healthcare service development methodologies.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.25 no.2
• /
• pp.111-122
• /
• 2023

This study aims to collect Big Data related to DIY clothing, analyze the results on a year-by-year basis, understand consumers' perceptions, the status, and reality of DIY clothing. The reference period for the evaluation of DIY clothing trends was set from 2012 to 2022. The data in this study was collected and analyzed using Textom, a Big Data solution program certified as a Good Software by the Telecommunications Technology Association (TTA). For the analysis of fabric-related DIY products, the keyword was set to "DIY clothing", and for data cleansing following collection, the "Espresso K" module was employed. Also, via data collection on a year-by-year basis, a total of 11 lists were generated and the collected data was analyzed by period. The following are the findings of this study's data collection on DIY clothing. The total number of keywords collected over a period of ten years on search engines "Naver" and "Google" between January 1, 2012 and December 31, 2022 was 16,315, and data trends by period indicate a continuous upward trend. In addition, a keyword analysis was conducted to analyze TF-IDF (Term Frequency-Inverse Document Frequency), a statistical measure that reflects the importance of a word within data, and the relationship with N-gram, an analysis of the correlation concerning the relationship between words. Using these results, it was possible to evaluate the popularity and growing tendency of DIY clothing products in conjunction with the evolving social environment, as well as the desire to explore DIY trends among consumers. Therefore, this study is valuable in that it provides preliminary data for DIY clothing research by analyzing the status and reality of DIY products, and furthermore, contributes to the development and production of DIY clothing.

• The KIPS Transactions:PartC
• /
• v.11C no.4
• /
• pp.455-462
• /
• 2004

Network attacks are various types with development of internet and are a new types. The existing intrusion detection systems need a lot of efforts and costs in order to detect and respond to unknown or modified attacks because of detection based on signatures of known attacks. In this paper, we present a design and implementation for mining prototype system to predict unknown or modified attacks through network protocol attributes analysis. In order to analyze attributes of network protocols, we use the association rule and the frequent episode. The collected network protocols are storing schema of TCP, UDP, ICMP and integrated type. We are generating rules that can predict the types of network attacks. Our mining prototype in the intrusion detection system aspect is useful for response against new attacks as extra tool.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.1
• /
• pp.97-101
• /
• 2012

Objective: With the background of aging population in China and advances in clinical medicine, the amount of operations on old patients increases correspondingly, which imposes increasing challenges to critical care medicine and geriatrics. The study was designed to describe information on the length of ICU stay from a single institution experience of old critically ill gastric cancer patients after surgery and the framework of incorporating data-mining techniques into the prediction. Methods: A retrospective design was adopted to collect the consecutive data about patients aged 60 or over with a gastric cancer diagnosis after surgery in an adult intensive care unit in a medical university hospital in Shenyang, China, from January 2010 to March 2011. Characteristics of patients and the length their ICU stay were gathered for analysis by univariate and multivariate Cox regression to examine the relationship with potential candidate factors. A regression tree was constructed to predict the length of ICU stay and explore the important indicators. Results: Multivariate Cox analysis found that shock and nutrition support need were statistically significant risk factors for prolonged length of ICU stay. Altogether, eight variables entered the regression model, including age, APACHE II score, SOFA score, shock, respiratory system dysfunction, circulation system dysfunction, diabetes and nutrition support need. The regression tree indicated comorbidity of two or more kinds of shock as the most important factor for prolonged length of ICU stay in the studied sample. Conclusions: Comorbidity of two or more kinds of shock is the most important factor of length of ICU stay in the studied sample. Since there are differences of ICU patient characteristics between wards and hospitals, consideration of the data-mining technique should be given by the intensivists as a length of ICU stay prediction tool.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.390-395
• /
• 2004

A semiconductor manufacturing process is the complicate and dynamic process, and consists of many sub-processes. An etching process is the most important process in the semiconductor fabrication. In this paper, the decision support system based upon data mining and knowledge discovery is an important factor to improve the productivity and yield. The proposed decision support system consists of a neural network model and an inference system based on fuzzy logic Firstly, the product results are predicted by the neural network model constructed by the product patterns that represent the quality of the etching process. And the product patters are classified by expert's knowledge. Finally, the product conditions are estimated by the fuzzy inference system using the rules extracted from the classified patterns. Prediction of product qualities can be linked to each input and process variables. We employ data mining and intelligent techniques to find the best condition of the etching process. The proposed decision support system is efficient and easy to be implemented for the process management based upon expert's knowledge.

• Geomechanics and Engineering
• /
• v.20 no.1
• /
• pp.1-7
• /
• 2020

In structures excavated in rock mass, load progressively increases to a level and remains constant during the construction. Rocks display different elastic properties such as E_i and ʋ under different loading conditions and this requires to use the true values of elastic properties for the design of safe structures in rock. Also, rocks will undergo horizontal and vertical deformations depending on the amount of load applied. However, under constant loads, values of E_i and ʋ will vary in time and induce variations in the behavior of the rock mass. In some empirical equations in which deformation modulus of the rock mass is taken into consideration, elastic parameters of intact rock become functions in the equation. Hence, the use of time dependent elastic properties determined under constant loading will yield more reliable results than when only constant elastic properties are used. As well known, rock material will play an important role in the deformation mechanism since the discontinuities will be closed due to the load. In this study, E_i and ʋ values of intact rocks were investigated under different constant loads for certain rocks with high deformation capabilities. The results indicated significant time dependent variations in elastic properties under constant loading conditions. E_i value obtained from deformability test was found to be higher than the E_i value obtained from the constant loading test. This implies that when static values of elastic properties are used, the material is defined as more elastic than the rock material itself. In fact, E_i and ʋ values embedded in empirical equations are not static. Hence, this workattempts to emerge a new understanding in designing of safer structures in rock mass by numerical methods. The use of time-dependent values of E_i and ʋ under different constant loads will yield more accurate results in numerical modeling analysis.

• Structural Engineering and Mechanics
• /
• v.58 no.5
• /
• pp.869-886
• /
• 2016

Non-Deformable Support System (NDSS) is one of the support system analysis methods. It is likely seen as numerical analysis. Obviously, numerical modeling is the key tool for this system but not unique. Although the name of the system makes you feel that there is no deformation on the support system, it is not true. The system contains some deformation but in certain tolerance determined by the numerical analyses. The important question is what is the deformation tolerance? Zero deformation in the excavation environment is not the case, actually. However, deformation occurred after supporting is important. This deformation amount will determine the performance of the applied support. NDSS is a stronghold analysis method applied in full to make this work. While doing this, NDSS uses the properties of rock mass and material, various rock mass failure criteria, various material models, different excavation geometries, like other methods. The thing that differ NDSS method from the others is that NDSS makes analysis using the time dependent deformation properties of rock mass and engineering judgement. During the evaluation process, NDSS gives the permission of questioning the field observations, measurements and timedependent support performance. These transactions are carried out with 3-dimensional numeric modeling analysis. The goal of NDSS is to design a support system which does not allow greater deformation of the support system than that calculated by numerical modeling. In this paper, NDSS applied to the problems of Tunnel 34 of the same Project (excavated with NATM method, has a length of 2218 meters), which is driven in graphite schist, was illustrated. Results of the system analysis and insitu measurements successfully coincide with each other.