• Annals of Rehabilitation Medicine
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• v.42 no.6
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• pp.804-813
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• 2018

Objective To elucidate the effect of a 12-week horizontal vibration exercise (HVE) in chronic low back pain (CLBP) patients as compared to vertical vibration exercise (VVE). Methods Twenty-eight CLBP patients were randomly assigned to either the HVE or VVE group. All participants performed the exercise for 30 minutes each day, three times a week, for a total of 12 weeks. Altered pain and functional ability were evaluated using the visual analog scale (VAS) and Oswestry Disability Index (ODI), respectively. Changes in lumbar muscle strength, transverse abdominis (TrA) and multifidus muscle thicknesses, and standing balance were measured using an isokinetic dynamometer, ultrasonography, and balance parameters, respectively. These assessments were evaluated prior to treatment, 6 weeks and 12 weeks after the first treatment, and 4 weeks after the end of treatment (that is, 16 weeks after the first treatment). Results According to the repeated-measures analysis of variance, there were significant improvements with time on VAS, ODI, standing balance score, lumbar flexor, and extensor muscle strength (all p<0.001 in both groups) without any significant changes in TrA (p=0.153 in HVE, p=0.561 in VVE group) or multifidus (p=0.737 in HVE, p=0.380 in VVE group) muscle thickness. Further, there were no significant differences between groups according to time in any of the assessments. No adverse events were noticed during treatment in either group. Conclusion HVE is as effective as VVE in reducing pain, strengthening the lumbar muscle, and improving the balance and functional abilities of CLBP patients. Vibrational exercise increases muscle strength without inducing muscle hypertrophy.

• Transactions on Electrical and Electronic Materials
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• v.12 no.3
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• pp.115-118
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• 2011

Process characterization of the chemical mechanical polishing (CMP) process for undensified phosphosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been addressed to experimenters to understand the relationship between input variables and responses of interest in a simple and efficient way. It is typically beneficial for determining the adequate size of experiments with multiple process variables and making statistical inferences for the responses of interests. Equipment controllable parameters to operate the machine include the down force (DF) of the wafer carrier, pressure on the backside of the wafer, table and spindle speed (SS), slurry flow rate, and pad condition. None of them is independent; thus, the interaction between parameters also needs to be indicated to improve process characterization in CMP. In this paper, we have selected the five controllable equipment parameters, such as DF, back pressure (BP), table speed (TS), SS, and slurry flow (SF), most process engineers recommend to characterize the CMP process with respect to material removal rate (RR) and film uniformity as a percentage. The polished material is undensified PSG. PSG is widely used for the plananization in multi-layered metal interconnects. We identify the main effect of DF, BP, and TS on both RR and film uniformity, as expected, by the statistical modeling and analysis on the metrology data acquired from a series of $2^{5-1}$ fractional factorial design with two center points. This revealed the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that the process control based on better understanding of the process is the key to success in semiconductor manufacturing, typically when the wafer size reaches 300 mm and is continuously scheduled to expand up to 450 mm in or little after 2012.

• Fibers and Polymers
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• v.7 no.4
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• pp.344-351
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• 2006

This paper is intended to determine the optimal processing parameters applied to the dyeing procedure so that the desired color strength of a raw fabric can be achieved. Moreover, the processing parameters are also used for constructing a system to predict the fabric quality. The fabric selected is the nylon and Lycra blend. The dyestuff used for dyeing is acid dyestuff and the dyeing method is one-bath-two-section. The Taguchi quality method is applied for parameter design. The analysis of variance (ANOVA) is applied to arrange the optimal condition, significant factors and the percentage contributions. In the experiment, according to the target value, a confirmation experiment is conducted to evaluate the reliability. Furthermore, the genetic algorithm (GA) is combined with the back propagation neural network (BPNN) in order to establish the forecasting system for searching the best connecting weights of BPNN. It can be shown that this combination not only enhances the efficiency of the learning algorithm, but also decreases the dependency of the initial condition during the network training. Most of all, the robustness of the learning algorithm will be increased and the quality characteristic of fabric will be precisely predicted.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.19 no.7
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• pp.624-630
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• 2006

ZnO deposition parameters are not independent and have a nonlinear and complex property. To propose a method that could verify and predict the relations of process variables, neural network was used. At first, ZnO thin films were deposited by using RF magnetron sputtering process with various conditions. Si, GaAs, and Glass were used as substrates. The temperature, work pressure, and RF power of the substrate were $50\sim500^{\circ}C$, 15 mTorr, and $180\sim210W$, respectively : the purity of the target was ZnO 4 N. Structural properties of ZnO thin films were estimated by using XRD (0002) peak intensity. The structure of neural network was a form of 4-7-1 that have one hidden layer. In training a network, learning rate and momentum were selected as 0.2, 0.6 respectively. A backpropagation neural network were performed with XRD (0002) peak data. After training a network, the temperature of substrate was evaluated as the most important parameter by sensitivity analysis and response surface. As a result, neural network could capture nonlinear and complex relationships between process parameters and predict structural properties of ZnO thin films with a limited set of experiments.

• Korean Journal of Materials Research
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• v.18 no.11
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• pp.571-576
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• 2008

The simulation program for solar cells, PC1D, was briefly reviewed and the device modeling of a multicrystalline Si solar cell using the program was carried out to understand the internal operating principles. The effects of design parameters on the light absorption and the quantum efficiency were investigated and strategies to reduce carrier recombination, such as back surface field and surface passivation, were also characterized with the numerical simulation. In every step of the process, efficiency improvements for the key performance characteristics of the model device were determined and compared with the properties of the solar cell, whose efficiency (20.3%) has been confirmed as the highest in multicrystalline Si devices. In this simulation work, it was found that the conversion efficiency of the prototype model (13.6%) can be increased up to 20.7% after the optimization of design parameters.

• Journal of Biomedical Engineering Research
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• v.14 no.3
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• pp.235-242
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• 1993

In the early stage of sacroilitis, it is'difficult to detect sacroiliac(Sl) abnormalities by conventional plain X-ray even though there are characteristic symptoms of ankylosing spondylitis. 3 dimensional volume rendering from the CT image was performed to make an early de tection of the structural changes of Sl joint. 2 cases who had clinical impression of ankylosing spondylitis without sacroilitis in plane X-ray and 1 case of typical ankylosing spondylitis as well as 1 case of normal control were studied. The Sl Joints were separated and each joint surface of sacrum and ilium was independently reconstructed by a special 3D manipulation program. All 2 patiant who complained of inflammatory lower back pain with no abnormal findings in the plain X-ray showed structural changes in 3 dimensionally reconstructed surface Image of the Sl joint compared to the normal control. Authors tried several parameters, such as fourler analysis of each surface and the mean and variance of Sl joint gap. We couldn't tell the statistical significance because of the limited number of cases. However, the parameters showed difference according to the progression of disease.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.980-986
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• 2003

As the ultra precision grinding can be applied to wafering process by the refinement of the abrasive, the development of high stiffness equipment and grinding skill, the conventional wafering process which consists of lapping, etching, Ist, 2nd and 3rd polishing could be exchanged to the new process which consists of precision surface grinding, final polishing and post cleaning. Especially, the ultra precision grinding of wafer improves the flatness of wafer and the efficiency of production. Futhermore, it has been not only used in bare wafer grinding, but also applied to wafer back grinding and SOI wafer grinding. This paper focused on the effect of the wheel path density and relative velocity on the characteristic of ground wafer in in-feed grinding with cup-wheel. It seems that the variation of the parameters in radial direction of wafer results in the non-uniform surface quality over the wafer. So, in this paper, the geometric analysis on grinding process is carried out, and then, the effect of the parameters on wafer surface quality is evaluated

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.2012-2021
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• 1995

An experimental study was performed for the analysis of dynamic characteristics of refrigeration system by controlling the evaporator superheat. Experimental data have been taken utilizing two different devices, thermostatic expansion valve(T.E.V.) and electronic expansion valve(E.E.V.), for the control of the evaporator superheat. The ranges of parameters, such as superheat, mass flow rate of refrigerant and inlet temperature of evaporator were 5-30.deg. C 90-170 kg/h and 10-25.deg. C, respectively. The data taken from the T.E.v.and E.E.v.were discussed with the control of the superheat, pressure drop, refrigerating capacity, compression work, evaporating temperature, condensing temperature and COP affecting performance characteristics of refrigeration system. In case of the refrigerant flow control with T.E..V., the superheat and pressure drop of the evaporator varied periodically, but the control with E.E.V., the parameters were very stable. In E.E.v.control, refrigerating capacity, compression work and evaporating temperature were decreased with increasing superheat, and the highest COP was obtained in the range of superheat from 5.deg. C to 15.deg. C.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.310-313
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• 2007

In roll forming process, a sheet metal is continuously progressively formed into a product with required cross-section and longitudinal shape, such as a circular tube with required diameter, wall-thickness and straightness, by passing through a series of forming rolls in arranged in tandem. In this process, each pair of forming rolls installed in a forming machine play a particular role in making up the required cross-section and longitudinal shape of the product. In recent years, that process is often applied to the bumper rail in the automotive industries. In this study, a optimal roll flower model and proper roll-pass sequence can be suggested by analyzing courcenter strain and longitudinal strain according to the roll-pass with FEM simulation. And also effects of the process parameters on the final shape formed by roll forming defects a evaluated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2313-2321
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• 2008

In order to develop reliable on-site partial discharge(PD) pattern recognition algorithm, the fuzzy neural network based on fuzzy set(FNN) and the polynomial network pattern classifier based on fuzzy Inference(PNC) were investigated and designed. Using PD data measured from laboratory defect models, these algorithms were learned and tested. Considering on-site situation where it is not easy to obtain voltage phases in PRPDA(Phase Resolved Partial Discharge Analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithms. As input vectors of the algorithms, PRPD data themselves were adopted instead of using statistical parameters such as skewness and kurtotis, to improve uncertainty of statistical parameters, even though the number of input vectors were considerably increased. Also, results of the proposed neuro-fuzzy algorithms were compared with that of conventional BP-NN(Back Propagation Neural Networks) algorithm using the same data. The FNN and PNC algorithms proposed in this study were appeared to have better performance than BP-NN algorithm.