• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• Design & Manufacturing
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• v.17 no.2
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• pp.22-26
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• 2023

As Light-Emitting Diodes(LEDs) continue to advance in performance, their application in automotive lamps is increasing. Automotive LEDs utilize light guides not only for aesthetics but also to control light quantity and direction. Light guides employ patterns of a few hundred micrometers(㎛) to regulate the light, and the surface roughness(Ra) of these patterns can reach tens of nanometers(nm). Given that these light guides are produced through injection molding, mold processing technology with high surface quality micro-patterns is required. This study serves as a preliminary investigation into the development of high surface quality micro-pattern processing technology. It examines the surface roughness of the workpiece based on the cutting direction of the pattern and the cutting fluid type when cutting micro-patterns on STAVAX steel using cubic Boron Nitride(cBN) tools. The experiments involved machining a step-shaped micro-pattern with a height of 60 ㎛ and a pitch of 400 ㎛ in a 22×22 mm area under identical cutting conditions, with only the cutting direction and cutting fluid type being varied. The machining results of four cases were compared, encompassing two cases of cutting direction(parallel to the pattern, orthogonal to the pattern) and two cases of cutting fluid type (flood, mist). Consequently, the Ra value was found to be the highest(Ra 128.33 nm) when machining with the flood type in parallel to the pattern, while it was the lowest(Ra 95.22 nm) when machining with the mist type orthogonal to the pattern. These findings confirm that there is a difference of up to 25.8 % in the Ra value depending on the cutting direction and cutting fluid type.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.268-274
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• 2023

In this case, a CAD-CAM complete denture that can be easily remanufactured and reduced the number of visits was decided in consideration of the fact that it was difficult to visit the dental hospital and many existing dentures were lost because the patient was inpatient in a nursing hospital. In order to reflect the shape, vertical dimension, and maxillomandibular relationship of the existing provisional dentures adapted by the patient to the fabrication of the final denture, the existing provisional dentures were scanned and closed mouth impression was taken with the printed individual tray. After digital facebow transfer using UTS CAD and arranging artificial teeth in CAD software, the maxillary and mandibular complete dentures were fabricated by milling the denture base and artificial teeth at once with the monolithic disc.

• Design & Manufacturing
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• v.17 no.4
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.

• The Journal of Korean Academy of Prosthodontics
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• v.50 no.1
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• pp.44-52
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• 2012

Purpose: In this paper we tried to evaluate the most appropriate surface for rhBMP-2 coating among 4 rough titanium surfaces. Materials and methods: We used machined surface as a control group and anodized, RBM and SLA surfaces as test groups. We coated rhBMP-2 on the 4 surfaces and with uncoated surfaces for each case, we cultured human mesenchymal stem cells on all 8 surfaces. 24 hours after we measured the stem cell' attachment with SEM, and on 3rd, 7th, and 14th days, we checked the cell proliferation and differentiation by using MTT and ALP activity assay. And on the 7th day after the culture, we performed RT-PCR assay to determine whether the expression levels of Type I collagen, osteocalcin, osteopontin were changed. Results: We observed with SEM that 4 rhBMP-2 coated surfaces exhibited wider and tighter cell attachment and more cell process spreading than uncoated surfaces. The anodized rhBMP-2 surface caused robustest effects. In MTT assay we could not find any meaningful difference. In ALP assay there was a significant increase (P<.05) in the ALP activity of anodized rhBMP-2 coated surface compared with that of the control (3rd and 14th days) and with that of the RBM rhBMP-2 coated surface (14th day). In RT-PCR assay there was increased expressions in the anodized rhBMP-2 coated surface for osteocalcin, and osteopontin. Conclusion: We found that the anodized rhBMP-2 coated surface were most prominent stem cell attachment and differentiation in compared to control and Machined rhBMP-2 coated, RBM rhBMP-2 coated surface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.188-198
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• 2005

The Goldschmidt iterative algorithm for finding a floating point square root calculated it by performing a fixed number of multiplications. In this paper, a variable latency Goldschmidt's square root algorithm is proposed, that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the square root of a floating point number F, the algorithm repeats the following operations: $R_i=\frac{3-e_r-X_i}{2},\;X_{i+1}=X_i{\times}R^2_i,\;Y_{i+1}=Y_i{\times}R_i,\;i{\in}\{{0,1,2,{\ldots},n-1} }}'$with the initial value is $'\;X_0=Y_0=T^2{\times}F,\;T=\frac{1}{\sqrt {F}}+e_t\;'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 28 for the single precision floating point, and 58 for the doubel precision floating point. Let $'X_i=1{\pm}e_i'$, there is $'\;X_{i+1}=1-e_{i+1},\;where\;'\;e_{i+1}<\frac{3e^2_i}{4}{\mp}\frac{e^3_i}{4}+4e_{r}'$. If '|X_i-1|<2^{\frac{-p+2}{2}}\;'$ is true, $'\;e_{i+1}<8e_r\;'$ is less than the smallest number which is representable by floating point number. So, $\sqrt{F}$ is approximate to $'\;\frac{Y_{i+1}}{T}\;'$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal square root tables ($T=\frac{1}{\sqrt{F}}+e_i$) with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a square root unit. Also, it can be used to construct optimized approximate reciprocal square root tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

• Ocean and Polar Research
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• v.36 no.1
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• pp.13-24
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• 2014

We established the first complete ice core processing method and analytical procedures for fundamental proxies, using a 40.2 m long ice core drilled on the Mt. Tsambagarav glacier in the Mongolian Altai mountains in July 2008. The whole core was first divided into two sub ice core sections and the measurements of the visual stratigraphy and electrical conductivity were performed on the surface of these sub core sections. A continuous sequence of samples was then prepared for chemical analyses (stable isotope ratios of oxygen ($^{18}O/^{16}O$) and hydrogen ($^2H/^1H$), soluble ions and trace elements). A total of 29 insoluble dust layers were identified from the measurement of visual stratigraphy. The electrical conductivity measurement (ECM) shows 11 peaks with the current more than 0.8 ${\mu}A$ Comparing the profiles of $SO_4{^{2-}}$ and $Cl^-$ concentrations to correlate with known volcanic eruptions, the first two ECM peaks appear to be linked to the eruptions (January and June 2007) of Kliuchevskoi volcano on the Kamchatka Peninsula of Russia, which supports the reliability of our ECM data. Finally, the composition of stable isotopes (${\delta}^{18}O$ and ${\delta}D$) shows a well-defined seasonal variation, suggesting that various chemical proxies may have been well preserved in the successive ice layers of Tsambagarav ice core. Our ice core processing method and analytical procedures for fundamental proxies are expected to be used for paleoclimate and paleoenvironmental studies from polar and alpine ice cores.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.380-389
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• 2005

The Goldschmidt iterative algorithm for a floating point divide calculates it by performing a fixed number of multiplications. In this paper, a variable latency Goldschmidt's divide algorithm is proposed, that performs multiplications a variable number of times until the error becomes smaller than a given value. To calculate a floating point divide '$\frac{N}{F}$', multifly '$T=\frac{1}{F}+e_t$' to the denominator and the nominator, then it becomes ’$\frac{TN}{TF}=\frac{N_0}{F_0}$'. And the algorithm repeats the following operations: ’$R_i=(2-e_r-F_i),\;N_{i+1}=N_i{\ast}R_i,\;F_{i+1}=F_i{\ast}R_i$, i$\in${0,1,...n-1}'. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than ‘$e_r=2^{-p}$'. The value of p is 29 for the single precision floating point, and 59 for the double precision floating point. Let ’$F_i=1+e_i$', there is $F_{i+1}=1-e_{i+1},\;e_{i+1}',\;where\;e_{i+1}, If '$[F_i-1]<2^{\frac{-p+3}{2}}$ is true, ’$e_{i+1}<16e_r$' is less than the smallest number which is representable by floating point number. So, ‘$N_{i+1}$ is approximate to ‘$\frac{N}{F}$'. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables ($T=\frac{1}{F}+e_t$) with varying sizes. 1'he superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a divider. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc

• The Journal of Korean Academy of Prosthodontics
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• v.51 no.3
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• pp.190-198
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• 2013

Purpose: The purposes of this study were to investigate osseointegration around zirconia implants which had machined or alumina sandblasted surface, and to compare the results with titanium implants. Materials and methods: The study was performed on the tibia of 6 pigs. Three types of implants were investigated: group T-titanium implant, group Z-machined zirconia implant, group ZS-alumina sandblasting treated zirconia implant. Zirconia implants were manufactured from yttria-stabilized tetragonal zirconia polycrystalline (Acucera Inc., Pocheon, Korea). A total of 36 implants were installed in pigs' tibias. After 1, 4 and 12 weeks of healing period, the periotest and the histomorphometric analysis were performed. The data were analyzed using one-way ANOVA and significance was assessed by the Scheffe test (${\alpha}=.05$). Results: In the measurement of surface roughness, highest Ra value was measured in group T with significant difference. No significant differences were found among groups regarding Periotest values. After 1 week, in comparison of bone to implant contact (BIC), group Z showed higher value with significant difference. In comparison of bone area (BA), group T and group Z showed higher value with significant difference than group ZS. After 4 weeks, in comparison of BIC, group T showed higher value with significant difference. Comparison of BA showed no significant difference among each implant. After 12 weeks, the highest mean BIC values were found in group T with significant difference. Group ZS showed higher BIC value with significant difference than group Z. In comparison of BA, group T and group ZS showed higher value with significant difference than group Z. Conclusion: Zirconia implant showed low levels of osseointegration in this experiment. Modification of surface structure should be taken into consideration in designing zirconia implants to improve the success rate.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.413-420
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• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal square mot calculates it by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal square root algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the rediprocal square root of a floating point number F, the algorithm repeats the following operations: '$X_{i+1}=\frac{{X_i}(3-e_r-{FX_i}^2)}{2}$, $i\in{0,1,2,{\ldots}n-1}$' with the initial value is '$X_0=\frac{1}{\sqrt{F}}{\pm}e_0$'. The bits to the right of p fractional bits in intermediate multiplication results are truncated and this truncation error is less than '$e_r=2^{-p}$'. The value of p is 28 for the single precision floating point, and 58 for the double precision floating point. Let '$X_i=\frac{1}{\sqrt{F}}{\pm}e_i$, there is '$X_{i+1}=\frac{1}{\sqrt{F}}-e_{i+1}$, where '$e_{i+1}{<}\frac{3{\sqrt{F}}{{e_i}^2}}{2}{\mp}\frac{{Fe_i}^3}{2}+2e_r$'. If '$|\frac{\sqrt{3-e_r-{FX_i}^2}}{2}-1|<2^{\frac{\sqrt{-p}{2}}}$' is true, '$e_{i+1}<8e_r$' is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to '$\frac{1}{\sqrt{F}}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications Per an operation is derived from many reciprocal square root tables ($X_0=\frac{1}{\sqrt{F}}{\pm}e_0$) with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal square root unit. Also, it can be used to construct optimized approximate reciprocal square root tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.