• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.148-154
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• 1999

This study was carried out to verify grinding performance of dental diamond bur and investigate the possibility of AE application in dentistry field. Workpieces were made of acryl and bovine respectively for the experiments in this study. Grinding test was conducted to get the data of grinding resistance and specific grinding energy of four different types of diamond bur by using tool dynamometer. AE signal was acquired to verify grinding process in the AE measuring system. Tool wear was observed to find parameters about grinding characteristics of diamond bur by means of SEM picture. It was found that the wear of dental diamond bur could be detected with polishing of grinding material, removal of adhesive parts, wear of particles neighboring cutting nose, loss of material and elevation of temperature. The wear of B, C, D type diamond bur is due to wear and fracture of grain size. Abnormal state can be found through the behavior of AE signal in the grinding working. As a result, it is expected that forecast of abnormal state is possible using AE equipments under real time process.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.263-273
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• 2010

Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood or as random variables and predicted by the conditional expectation of the unknown values given the data. The purpose of this study is to impute missing values which are regarded as the maximum likelihood estimator and random variable in incomplete data and to compare with two methods using ARMA and STAR model. For illustration, the Mumps data reported from the national capital region monthly over the years 2001~2009 are used, and estimate precision of missing values and forecast precision of future data are compared with two methods.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.3
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• pp.26-30
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• 1996

The successful development of the automobile industry in Korea is the firstfruit of the epochmaking automobile policy in 1973: Top-Down mass production of Korean model cars. In Top-Down system, indigenous model, which is the most important and difficult part of the automobile industry, is devised first, followed by the mass production of the major parts, such as bodies, engines, etc. This system is in contrast to the prevailing Bottom-up system in the third-world, which assembles automobiles by gradually adding up simple domestic parts. The Government, faced with a vicious circle of depen- dence on assembly of foreign cars, high prices, small demand and low production, decided it was time to move to the mass production of the indigenous models. It was hoped that the efficiencies of low cost Korean models would be epochally improved by overcoming the sway of foreign models and by strengthening the production capabilities of the main parts. In contrast to these develop- ment planning, assembled vehicles numbered only 26,300 units in 1973. In the year of 1995, the total number of automobile production have already passed 2,534,000. As steady growth in worldwide demand is forecast, Korea will able to play a major role as an important automobile maker of the next century.

• Journal of applied mathematics & informatics
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• v.40 no.5_6
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• pp.1151-1165
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• 2022

Key drive of information quarrying is to digest liked information starting possible information. With the colossal amount of realities kept in documents, information bases, and stores, in the medical care area, it's inexorably significant, assuming excessive, arising compelling resources aimed at examination besides comprehension like information on behalf of the withdrawal of gen that might assistance in independent direction. Classification is method in information mining; it's characterized as per private, passing on item toward a specific course established happening it is likeness toward past instances of different substances trendy the data collection. In pre-owned recycled four Classification algorithm that incorporate Multi-Layer perception, KSTAR, Bayesian Network and PART to fabricate the grouping replicas arranged the malaria data collection and analyze the replicas, degree their exhibition through Waikato Environment for Knowledge Analysis introduced to Java Development Kit 8, then utilizations outfit's technique trendy promoting presentation of the arrangement methodology. The outcome perceived that Bayesian Network return most elevated exactness of 50.05% when working on followed by Multi-Layer perception, with 49.9% when helping is half, then, at that point, Kstar with precision of 49.44%, 49.5% when supporting individually and PART have lesser precision of 48.1% when helping, The exploration recommended that Bayesian Network is awesome toward remain utilized on Malaria data collection in our sanatoriums.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• Current Photovoltaic Research
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• v.7 no.4
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• pp.85-96
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• 2019

Renewable energy is emerging as a reliable alternative source of energy, it is much safer, cleaner than conventional sources and has contributed significantly in this sector. However, there are still some challenges that needed to address this evolving technology. Artificial Intelligence (A. I.) can assess the past, optimize the present, and forecast the future. Therefore, A. I. will resolve most of these problems. Artificial intelligence is complex in nature, but it reduces error and aims to reach a greater degree of precision which make renewables smarter. This paper provides an overview of frequently used A. I. methods in solar energy applications. A sample algorithm is also provided for literature purposes and knowledge transfer.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.28-34
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• 2010

The spatial distribution characteristics of damaged trees by the pine wilt disease appear scattered spots spreading from single dead trees. That is the reason why it is difficult to early detect damage and to prevent from extensive damage. Thus, it is very important to forecast and analyze the damage occurrences, to establish strategies for prevention, and to supervise them. However, conventional survey which observes around roads or residential areas by naked eyes was impossible to investigate completely, missing target areas and dangerous areas. Therefore, aerial forecasting techniques on the damaged area were developed using GIS, GPS, and helicopters for an accurate observation of systematic and scientific approach in this study. Moreover, advantages of the techniques application were confirmed to survey 972 dead tree samples at 349 position-coordinates in 32 cities (about $28,810km^2$), 2005. This study is expected to apply widely to find dead trees and the causes, particularly by pine wilt disease.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.3
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• pp.323-328
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• 2014

Recently, there has been demand for the convergence of IT (Information and communication Technologies, ICT) with defense, as has already been achieved in civilian fields such as healthcare and construction. It is expected that completely new and common requirements would emerge from the civilian and military domains and that the shape of war field would change rapidly. Many military scientists forecast that future wars would be network-centric and be based on C4I(Command, Control, Communication & Computer, Intelligence), ISR(Intelligence, Surveillance & Reconnaissance), and PGM(Precision Guided Munitions). For realizing the smart defense concept, IT should act as a baseline technology even for simulating a real combat field using virtual reality. In this paper, we propose the concept of IT-based smart defense with a focus on accurate detection in real and cyber wars, effective data communication, automated and unmanned operation, and modeling and simulation.