• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.1-13
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• 2016

The increase of consumer needs for quality metal cutting related products with more precise tolerances and better product surface roughness has driven the metal cutting industry to continuously improve quality control of metal cutting processes. In this paper, two different approaches are discussed. First, design of experiments (DOE) is used to determine the significant factors and then fuzzy logic approach is presented for the prediction of surface roughness. The data used for the training and checking the fuzzy logic performance is derived from the experiments conducted on a CNC milling machine. In order to obtain better surface roughness, the proper sets of cutting parameters are determined before the process takes place. The factors considered for DOE in the experiment were the depth of cut, feed rate per tooth, cutting speed, tool nose radius, the use of cutting fluid and the three components of the cutting force. Finally the significant factors were used as input factors for fuzzy logic mechanism and surface roughness is predicted with empirical formula developed. Test results show good agreement between the actual process output and the predicted surface roughness.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.877-888
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• 2016

To project the effects of climate-induced change on aquatic environments, it is necessary to determine the thermal constraints affecting different fish species and to acquire time series of the current and projected water temperature (WT). Assuming that a nonlinear regression between the WT at individual stations and the ambient air temperature (AT) at nearby weather stations could represent the best relationship of air-water temperature, This study estimates future WT using a general circulation model (GCM). In addition, assuming that the grid-averaged observations of AT correspond to the AT output from GCM simulation, this study constructed a regression curve between the observations of the local WT and the concurrent GCM-simulated surface AT. Because of its low spatial resolution, downscaling is unavoidable. The projected WT under global warming scenario A2 (B2) shows an increase of about $1.6^{\circ}C$ ($0.9^{\circ}C$) for the period 2080-2100. The maximum/minimum WT shows an amount of change similar to that of the mean values. This study will provide guidelines for decision-makers and engineers in climate-induced river environment and ecosystem management.

• The Journal of Advanced Prosthodontics
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• v.3 no.2
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• pp.76-80
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• 2011

PURPOSE. Implant stability quotient (ISQ) values have been supposed to predict implant stability. However, the relationship between ISQ values and bone-to-implant contact ratio (BIC%) which is one of the predictors of implant stability is still unclear. The aim of the present study was to evaluate initial ISQ values in relation to BIC% using rabbit model. MATERIALS AND METHODS. Four New Zealand white rabbits received a total of 16 implants in their tibia. Immediately after implant placement ISQ values were assessed. The measurements were repeated at the time of sacrifice of the rabbits after 4 weeks. Peri-implant bone regeneration was assessed histomorphometrically by measuring BIC% and bone volume to total volume values (bone volume %). The relationships between ISQ values and the histomorphometric output were assessed, and then, the osseointegration prediction model via the initial ISQ values was processed. RESULTS. Initial ISQ values showed significant correlation with the BIC%. The bone volume % did not show any significant association with the ISQ values. CONCLUSION. In the limitation of this study, resonance frequency analysis is a useful clinical method to predict the BIC% values and examine the implant stability.

• Journal of Information Technology Applications and Management
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• v.23 no.3
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• pp.13-23
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• 2016

In recent years, big data has usefully been deployed by organizations with the aim of getting a better prediction for the future. Moreover, knowledge management systems are being used by organizations to identify and create knowledge. Here, the output from analysis of big data and a knowledge management system are used to develop a new model with the goal of minimizing the cost of implementing new recognized processes including staff training, transferring and employment costs. Strategies are proposed from big data analysis and new processes are defined accordingly. The company requires various skills to execute the proposed processes. Organization's current experts and their skills are known through a pre-established knowledge management system. After a gap analysis, managers can make decisions about the expert arrangement, training programs and employment to bridge the gap and accomplish their goals. Finally, deduction graph is used to analyze the model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.348-354
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• 1993

In this research, a multi-tree coder at 9.6Kbits/sec using a novel scheme for adaptation of the short-term coefficients is developed. The overall delay of the tree coder is maintained at 2.5 msec(16 samples at the 6.4KHz sampling frequency). This coder produces good quality speech over ideal channels, and it is very robust to channel errors up to a bit error rate (BER) of $10^{-3}$. This robustness is achieved by using a parallel adaptation scheme in combination with the use of a smoothed version of the received excitation sequence for adaptation of the short-term prediction coefficients. For the multi-tree coder, reconstructed output speech is evaluated using signal-to-quantization noise ratios (SNR), segmental SNRs, and informal listening tests.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.281-286
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• 2001

The radial turbine has been successfully applied to the systems which request relatively small output compared with the axial turbine, and has low manufacturing cost due to it's small size and simple structure. Recently, the researches on the development and the efficiency maximization of the radial turbine are in progress corresponding with the trend toward miniaturization in turbo machinery and the development of small dispersed power generation systems. The radial turbine is to be applied to our turbo refrigerator of which engine speed is 26,000 rpm and turbine efficiency is $88\%$. Also, as a heat exchanger is accepted instead of a combustor in our turbo refrigerator, the design of radial turbine has been performed to be appropriate to the circumstance of low temperature air, not high temperature combustor gas, into the turbine inlet . This radial turbine is being developed in consideration with not only the aero-dynamic performance but also the simplification of manufacturing and integration, and the durability at operating condition. This paper refer to the performance evaluation about the radial turbine design by comparison with consulting from Russia and the our evaluation about various design factors which are considered in aero-dynamic design process.

• The KSFM Journal of Fluid Machinery
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• v.14 no.5
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• pp.24-30
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• 2011

500W class MTG(Micro turbine generator) operating at 400,000 rpm is under development. From the cycle analysis, it is decided that the self-sustaining speed of MTG is 200,000rpm and the generating speed is 400,000 rpm. Therefore, motor should be designed so that it is able to rotate the rotor up to 200,000rpm and generator should designed so that it is able to generate 500W output at 400,000rpm. First step to design motor/generator is to determine the power and efficiency requirement. Not only the power into the compressor and from the turbine at the operating speed but also the mechanical and electrical losses should be considered in determining the power and efficiency requirement. This study presents the procedure and the results of determining the power and efficiency requirement considering the mechanical and electrical losses depending on the rotating speed which is measured from the experiment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.137-146
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• 2002

The predictions of the loading characteristics was performed by the neural networks which use the results through structural analysis. The momentum backperpagtion which can be modified the teaming rate and momentum coefficient, was developed. Input patterns of the neural networks are the 9 strains which positioned at the side of the shell and output layers is the loading characteristics. Hidden layers were increased from 1 layers to 3 layers. Developed program which were trained by 9 strains predict the loading characteristics under 0.5%. Inverse engineering can be applicable to the composite laminated cylindrical shells with developed neural networks.

• Journal of the Korean Solar Energy Society
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• v.36 no.5
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• pp.63-71
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• 2016

Installed PV module in field is affected by shading caused by various field environmental factors. Bypass diodes are installed in PV module for preventing a power loss and degradation of PV module by shading. But, Bypass diode is easily damaged by surge voltage and has often initial a defect. This paper propose the electric characteristic variation and the power prediction of PV module with damaged bypass diode. Firstly, the resistance for normal bypass diode and damaged bypass diode of resistance was measured by changing the current. When the current increases, the resistance of normal bypass diode is almost constant but the resistance of damaged bypass diode increases. Next, To estimate power of PV module by damaged bypass diode, the equation for the current is derived using solar cell equivalent circuit. Finally, the derived equation was simulated by using MatLab tools, was verified by comparing experimental data.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.7
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• pp.398-405
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• 2013

Small and medium-size buildings employ a multi-distributed individual air-conditioning system that utilizes package air conditioners instead of centralized cooling systems, which can allow easier building management and maintenance, along with a diversification of facility use. Inverter driven system heat pumps have been developed to achieve not only an easy distribution control, allowing free combination of indoor units with different models and different capacities, but also wide applications to intelligent air conditioning. However, the control algorithms of the system heat pump are limited in the open literature, due to complicated operating conditions. In this paper, an inverter-driven system heat pump having two indoor units with electronic expansion valves (EEV) was simulated in the cooling mode. An integral optimum regulating controller employing the state space control method was also simulated, and applied to the system-heat pump system, to obtain efficient control of the MIMO (multi input multi output) system. The simulation model for the controller yielded satisfactory prediction results. The new control model can be successfully utilized as a basic tool in controller design.