• 한국정밀공학회지
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• 제17권12호
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• pp.137-144
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• 2000

In order to achieve systematical method for improving motion accuracy of hydrostatic table, an algorithm using finite element method is proposed in this paper. Quantification of averaging effect of oil film on motion error is performed theoretically by analysis on the relationship between spacial frequency of rail form error and motion error of table. Influences of film stiffness and pocket size on the motion error of table are also analyzed theoretically. Validity of the algorithm is verified experimentally from the test on the motion error of table with three types of rail which have different form profile. Experimental results show that the algorithm is very effective to analyze theoretically the motion error of hydrostatic table.

• 한국정밀공학회지
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• 제24권11호
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• pp.52-58
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• 2007

A cutting device capable of generating various shapes of the cyclic elliptical trajectory of a cutting tool was proposed and micro v-grooving experiments were performed to investigate the characteristics of elliptical vibration cutting (EVC). The proposed cutting device is comprised of a pair of parallel piezoelectric actuators with which harmonic voltages of varying phase difference and magnitude are supplied, creating various shapes of the elliptical tool path. The attributes of the elliptical locus involving the direction of the axis of an ellipse, the rotational direction and amplitudes of a trajectory were fine-tuned for stable operation of the EVC. The EVC characteristics performed with brass and copper revealed reduction in the cutting resistance and suppression of burr formation, resulting in the enhancement of form accuracy of machined micro-features. While the effect of the EVC increases with the increase of excitation frequency and the amplitude, it is found that a change in the cutting force decreases as the amplitude of an elliptical locus increases.

• International Journal of Precision Engineering and Manufacturing
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• 제4권3호
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• pp.48-54
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• 2003

This paper deals with mirror grinding of a small-sized aspherical lens by a resin bonded diamond spherical wheel. Up to now, a spherical lens has been used for the lens of the optical communication optical part. However, recently, aspherical optical parts are mainly used in order to attempt the improvement in image quality and miniaturization of the optical device. It is possible to manufacture the aspherical lens which is presently being used in optical instrument through ultra-precision machining technology. Also, to realize compactness, efforts are being made to produce a micro aspherical lens, fur which the development of a high-precision, micro molding die is inevitable. Therefore, extensive research is being done on methods of producing a micro aspherical surface by high-precision grinding. In this paper, the spherical wheel was trued by cup-shaped truer and tool path was calculated by the radius of curvature of the wheel after truing and dressing. Then in the aspherical grinding experiment, WC material which is used as a melding die for the small-sized aspherical lens was ground. The results showed that a form accuracy of 0.1918 $\mu\textrm{m}$ P-V and a surface roughness of 0.064 $\mu\textrm{m}$ Rmax could be achieved.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
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• pp.469-470
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• 2006

The purpose of this research was to investigate and to find out the optimal annealing condition to mold an aspheric glass to be used for mobile phone module having 2 megapixel and $2.5{\times}$ zoom. Taking annealing rate and re-press temperature after molding as molding variables under the identical molding temperature and pressure, a glass lens was molded. And, Form Accuracy, Lens Thickness, Refractive Index, and Modulation Transfer Function(MTF) were measured in order to observe characteristics of molded lens, and then optimal annealing conditions were determined based on the resulting data. Properties of lens molded under the optimal conditions revealed Form Accuracy[PV] $0.2047\;{\mu}m$ in aspheric surface, and $0.2229\;{\mu}m$ in plane, and MTF value was 30.3 % under 80 lp/mm.

• 한국정밀공학회지
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• 제18권12호
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• pp.82-87
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• 2001

This paper deals with mirror grinding of a small-sized aspherical lens by the resin bonded diamond spherical wheel. Up to now, a spherical lens has been used for the lens of the optical communication optical part. However, recently, the aspherical optical parts are mainly used in order to attempt the improvement in image quality and miniaturization of the optical device. It is possible to manufacture the aspherical lens which is presently being used in optical instrument through ultra-precision machinery technology. Also, to realize compactability, efforts are being made to produce a micro aspherical lens, for which the development of a high-precision, micro molding die is inevitable. Therefore, extensive research is being done on methods of producing an micro aspherical surface by high-precision grinding. In this paper, the spherical wheel was trued by cup-type truer and tool path was calculated by the radius of curvature of wheel after truing and dressing. And then in the aspherical grinding experiment, WC material which is used as a molding die for the small-sized aspherical lens was ground. It results was that a form accuracy of 0.1918${\mu}m$ P-V and a surface roughness of 0.064${\mu}m$ Rmax.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.625-628
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• 2010

This paper proposes a novel feature extraction method for unsupervised multispectral image segmentation based in one dimensional combined neighborhood differences (1D CND). In contrast with the original CND, which is applied with traditional image, 1D CND is computed on a single pixel with various bands. The proposed algorithm utilizes the sign of differences between bands of the pixel. The difference values are thresholded to form a binary codeword. A binomial factor is assigned to these codeword to form another unique value. These values are then grouped to construct the 1D CND feature image where is used in the unsupervised image segmentation. Various experiments using two LANDSAT multispectral images have been performed to evaluate the segmentation and classification accuracy of the proposed method. The result shows that 1D CND feature outperforms the spectral feature, with average classification accuracy of 87.55% whereas that of spectral feature is 55.81%.

• 한국생산제조학회지
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• 제24권1호
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• pp.1-6
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• 2015

To improve the efficiency of a reverse engineering process, many researches have recently tried to develop efficient, automatic 3D scanning devices. A new automatic 3D scanning device using a spherical coordinate system mechanism is introduced in this study. This device incorporates a guide motion along the spherical coordinate to compound each 3D data point automatically. The experiments correlating the system assembling tolerance with the form accuracy were conducted to verify the efficiency of the system for the scanning of an object, including complex shapes and manifold sections. In addition, the required time and system accuracy, taken during the scanning process of complicated artifact models, were investigated. Further, based on these empirical results, it was ascertained that the superior productivity of this new device offers a more precise and efficient scan when compared to conventional methodologies.

• 소성∙가공
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• 제17권3호
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• pp.218-224
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• 2008

A recent trend in automotive parts has been an integration of sub-assemblies with unified shapes. Tube structures also have been integrated to one body structure by using a near net shape forming instead of adopting welding. A cylindrical elastomer-forming process can be utilized to form a steel tube compressed in a radial direction. This process has some advantages compared to a hydro-forming or a swaging process in the viewpoint of a lower investment and a higher productivity. In order to predict a feasible specification of products within a work capability of the elastomer-forming equipment developed previously, effects of geometrical parameters of a tube on its shape accuracy are examined. Two characteristic parameters to account for the shape accuracy are chosen. One is the curvature radius at the corner part and the other is the straight ratio of the formed region. Careful examination of two parameters has led that the shape accuracy can be easily predicted by the regression equation obtained from the response surface method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권1호
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• pp.277-290
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• 2019

The demand for indoor positioning is increasing day by day. However, the widely used positioning methods today cannot satisfy the requirements of the indoor environment in terms of the positioning accuracy and deployment cost. In the existing research domain, the localization algorithm based on three-dimensional space is less accurate, and its robustness is not high. Visible light communication technology (VLC) combines lighting and positioning to reduce the cost of equipment deployment and improve the positioning accuracy. Further, it has become a popular research topic for telecommunication and positioning in the indoor environment. This paper proposes a surface centroid TOA localization algorithm based on the VLC system. The algorithm uses the multiple solutions estimated by the trilateration method to form the intersecting planes of the spheres. Then, it centers the centroid of the surface area as the position of the unknown node. Simulation results show that compared with the traditional TOA positioning algorithm, the average positioning error of the surface centroid TOA algorithm is reduced by 0.3243 cm and the positioning accuracy is improved by 45%. Therefore, the proposed algorithm has better positioning accuracy than the traditional TOA positioning algorithm, and has certain application value.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.196-202
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• 2024

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease prediction. Due to breast cancer's favorable prognosis at an early stage, a model is created to utilize the Dataset on Wisconsin Diagnostic Breast Cancer (WDBC). Conversely, this model's overarching axiom is to compare the effectiveness of five well-known ML classifiers, including Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), and Naive Bayes (NB) with the conventional method. To counterbalance the effect with conventional methods, the overarching tactic we utilized was hyperparameter tuning utilizing the grid search method, which improved accuracy, secondary precision, third recall, and finally the F1 score. In this study hyperparameter tuning model, the rate of accuracy increased from 94.15% to 98.83% whereas the accuracy of the conventional method increased from 93.56% to 97.08%. According to this investigation, KNN outperformed all other classifiers in terms of accuracy, achieving a score of 98.83%. In conclusion, our study shows that KNN works well with the hyper-tuning method. These analyses show that this study prediction approach is useful in prognosticating women with breast cancer with a viable performance and more accurate findings when compared to the conventional approach.