• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.378-381
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• 2003

Efficient development of method on a performance evaluation for machine tools has been regarded as the most important work for accuracy and quality enhancement to every user and manufacturer. A evaluation method of accuracy for machine tools has been studied recently according to the rapid increase of interest in precision machine tools. To this point of view, the circular interpolation test of machine tools is recognized as the most useful method to distinguish a dynamic accuracy of NC machine tools by ISO and ANSI/ASME, etc. In this paper, we have studied and developed the form measurement system with grid encoder to analyse the final accuracy of NC machine tools. we have analyzed the servo system error and geometric error of NC machine tools through measuring a dynamic error signal by this system. and then we verified the experimental result and enhanced the reliability by means of comparing the characteristics of the developed system with the kinematic ball-bar system.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.21-31
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• 2023

In this paper, we focused on the problem of evaluating multi-class classification accuracy and simulation of multiple classifier performance metrics. Multi-class classifiers for sentiment analysis involved many challenges, whereas previous research narrowed to the binary classification model since it provides higher accuracy when dealing with text data. Thus, we take inspiration from the non-linear Support Vector Machine to modify the algorithm by embedding dynamic hyperplanes representing multiple class labels. Then we analyzed the performance of multi-class classifiers using macro-accuracy, micro-accuracy and several other metrics to justify the significance of our algorithm enhancement. Furthermore, we hybridized Enhanced Convolution Neural Network (ECNN) with Dynamic Support Vector Machine (DSVM) to demonstrate the effectiveness and efficiency of the classifier towards multi-class text data. We performed experiments on three hybrid classifiers, which are ECNN with Binary SVM (ECNN-BSVM), and ECNN with linear Multi-Class SVM (ECNN-MCSVM) and our proposed algorithm (ECNNDSVM). Comparative experiments of hybrid algorithms yielded 85.12 % for single metric accuracy; 86.95 % for multiple metrics on average. As for our modified algorithm of the ECNN-DSVM classifier, we reached 98.29 % micro-accuracy results with an f-score value of 98 % at most. For the future direction of this research, we are aiming for hyperplane optimization analysis.

• 반도체디스플레이기술학회지
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• 제22권3호
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• pp.90-95
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• 2023

We describe an optimal alignment method for improving accuracy of dynamic spectroscopic polarimeter based on monolithic polarizing interferometer. The dynamic spectroscopic polarimeter enables real-time measurements of spectral ellipsometric parameters by using a spectral carrier frequency concept. However, the non-polarizing beam splitter used in the monolithic polarizing interferometer cannot maintain the polarization state perfectly due to phase retardation caused by optical anisotropic characteristics of the non-polarizing beam splitter, resulting in degraded measurement accuracy. The effect of the beam splitter can be minimized through optimal alignment of the polarizers used in the polarizing interferometer and the analyzer. We demonstrate how much the proposed alignment method can enhance the measurement accuracy by comparing with previous alignment approach.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.61.5-61
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• 2001

The laser tracking system(LTS) presents the most promising technique for dynamic position measurement of industrial robots. This system combine the advantage of high accuracy with a contactless measurement technique. It is the measurement system of position in three dimensions using distance data obtained by laser interferometer and real time angle by tracking mirror assembly. After measuring the tracking error of the beam projected on the center of retroreflector in robot end effector, this system tracks the end effector continuously by adjusting tracking mirror angle to minimize this error ...

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권12호
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• pp.439-446
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• 2016

본 논문에서는 예측기반 병렬 이벤트구동 게이트수준 타이밍 시뮬레이션의 성능 개선을 위한 효율적인 예측정확도 향상 전략을 제안한다. 제안된 기법은 병렬 이벤트구동 로컬시뮬레이션들의 입력값과 출력값에 대한 예측을 이중으로 예측할 뿐만 아니라, 특별한 상황에서는 동적으로 예측할 수 있게 한다. 이중 예측은 첫번째 예측이 틀린 경우에 두번째 정적 예측 데이터로써 새로운 예측을 시도하게 되며, 동적 예측은 실제의 병렬 시뮬레이션 실행 과정 도중에 동적으로 축적되어진 지금까지의 시뮬레이션 결과를 예측 데이터로 활용하는 것이다. 제안된 두가지의 예측정확도 향상 기법은 병렬 시뮬레이션의 성능 향상의 제약 요소인 동기 오버헤드 및 통신 오버헤드를 크게 감소시킨다. 이 두가지 중요한 예측정확도 향상 방법을 통하여 6개의 디자인들에 대한 예측기반 병렬 이벤트구동 게이트수준 타이밍 시뮬레이션이 기존 통상적 방식의 상용 병렬 멀티-코어 시뮬레이션에 비하여 약 5배의 시뮬레이션 성능이 향상됨을 확인할 수 있었다.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.711-718
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• 2022

In this paper, an accurate segmentation algorithm of video dynamic background image (VDBI) based on improved wavelet transform is proposed. Based on the smooth processing of VDBI, the traditional wavelet transform process is improved, and the two-layer decomposition of dynamic image is realized by using two-dimensional wavelet transform. On the basis of decomposition results and information enhancement processing, image features are detected, feature points are extracted, and quantum ant colony algorithm is adopted to complete accurate segmentation of the image. The maximum SNR of the output results of the proposed algorithm can reach 73.67 dB, the maximum time of the segmentation process is only 7 seconds, the segmentation accuracy shows a trend of decreasing first and then increasing, and the global maximum value can reach 97%, indicating that the proposed algorithm effectively achieves the design expectation.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.79-88
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• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 추계 학술대회논문집
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• pp.24-25
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• 2006

An unstructured mesh method has been developed for the simulation of steady and time-accurate flows around helicopter rotors. A dynamic and quasi-unsteady solution-adaptive mesh refinement technique was adopted for the enhancement of the solution accuracy in the local region of interest involving highly vortical flows. Applications were made to the 2-D blade-vortex interaction aerodynamics and the 3-D rotor blades in hover. The interaction between the rotor and the airframe in forward flight was investigated by introducing an overset mesh technique.

• Asian Pacific Journal of Cancer Prevention
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• 제16권18호
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• pp.8335-8338
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• 2016

Purpose: To make a comparison of single voxel magnetic resonance spectroscopy (SV-MRS) and dynamic contrast enhancement (DCE) MRI for differentiation of benign and malignant breast lesions in a sample of Iranian women. Materials and Methods: A total of 30 women with abnormal breast lesions detected in mammography, ultrasound, or clinical breast exam were examined with DCE and SV-MRS. tCho (total choline) resonance in MRS spectra was qualitatively evaluated and detection of a visible tCho peak at 3.2 ppm was defined as a positive finding for malignancy. Different types of DCE curves were persistent (type 1), plateau (type 2), and washout (type 3). At first, lesions were classified according to choline findings and types of DCE curve, finally being compared to pathological results as the standard reference. Results: this study included 19 patients with malignant lesions and 11 patients with benign ones. While 63.6 % of benign lesions (7 of 11) showed type 1 DCE curves and 36.4% (4 of 11) showed type 2, 57.9% (11of 19) of malignant lesions were type 3 and 42.1% (8 of 19) type 2. Choline peaks were detected in 18 of 19 malignant lesions and in 3 of 11 benign counterparts. 1 malignant and 8 benign cases did not show any visible resonance at 3.2 ppm so SV-MRS featured 94.7% sensitivity, 72.7 % specificity and 86.7% accuracy.Conclusions: The present findings indicate that a combined approach using MRS and DCE MRI can improve the specificity of MRI for differentiation of benign and malignant breast lesions.

• 한국의학물리학회지:의학물리
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• 제19권3호
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• pp.143-149
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• 2008

본 연구의 목적은 디지털 방사선 흉부영상의 개선을 위한 영상처리방법을 제안하고 임상적 유용성을 평가하는 것이다. 흉부영상의 edge를 보존하면서 산란성 노이즈 제거를 위한 비선형의 반복 필터가 고안되었다. 영상의 다이나믹 레인지 (dynamic_range)의 조절이 이루어 졌으며, 해부학적 영역과 주변픽셀과의 호환성을 바탕으로 적응적 영상증강이 이루어졌다. 종격동 영역에서의 영상증강과 더불어, 폐 영역에서의 혈관조직, 기관지, 폐 조직 등이 적절하게 증강되었다. 3명의 판독의에 의한 임상평가가 이루어 졌으며, PA 영상에서는 11개, 그리고 Lateral 영상에서는 9개의 해부학적 영역이 면밀하게 관찰되었다. 각각 100장의 영상들이 ITU (International Telecommunication Union) recommendation 500에 따라 평가되어졌으며, 그 결과는 good과 adequate중간인 3.4의 평균치를 보였다. 이는 제안한 영상처리의 임상적 유용성이 최소한 양호함 이상의 가치가 있음을 의미한다. 유용한 해부학적 정보의 손실을 방지하기 위해, 영상표시장치와 인간의 인지계를 고려하면서 영상개선이 이루어졌다. 디지털 방사선기기의 등장으로 진단의 정확성을 향상시키기 위한 지속적인 영상 개선연구가 필요하다.