• Journal of Information Processing Systems
• /
• 제19권3호
• /
• pp.370-376
• /
• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

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

• 소성∙가공
• /
• 제15권4호
• /
• pp.281-288
• /
• 2006

Most of automobile member parts experience severe springback problems because of their complicated shape and high yielding strength. Now it becomes imperative to develop an effective method to resolve these problems. However, there remain several obstacles to get accurate estimation of dimensional shape. Especially the effective algorithms to simulate sheet metal forming processes including drawing, trimming, flanging and springback is demanded for the multi stage simulation of automobile member parts. In this study, for the purpose of accurate springback calculation, a simulation program which is robust in springback analysis is developed. Favorable enhancement in computation time for springback analysis by using latest equation solving technique and robust solution convergence by continuation method are achieved with the program. In analysis, the multi processes of rear side member are simulated to verify the system. For the evaluation of springback accuracy practically, all conditions including boundary conditions for springback analysis and inspection conditions for dimensional accuracy are applied. The springback results of simulations show good agreement with the experiments.

• The Journal of the Acoustical Society of Korea
• /
• 제29권2E호
• /
• pp.86-99
• /
• 2010

This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

• 조명전기설비학회논문지
• /
• 제29권6호
• /
• pp.27-34
• /
• 2015

There has been a critical issue in optical simulation of phosphors in LEDs due to their light-reabsorption properties. To improve the accuracy of optical modeling for a white LED package, we utilized the spectrum data of the phosphor-dispersed encapsulant film instead of the phosphor powder. By measuring white LED packages with green and red phosphors, the maximum difference between simulation and experimental results of a color temperature, a color rendition index number and a color coordinate corresponds to ${\Delta}T=95K$, ${\Delta}Ra=1.7$ and ${\Delta}xy=0.007$, respectively. Based on those results, the proposed method can well explain the change of emission spectra of white LEDs with more than two phosphors which introduce the complex optical phenomena such as absorption, reabsorption, light emission, reflection and scattering, etc.

• 한국CDE학회논문집
• /
• 제4권3호
• /
• pp.247-258
• /
• 1999

With the contemporary CAD/CAM system, where the tool path is generated and verified purely based on the geometric operation, geometric accuracy of the machined surface cannot be guaranteed dut to the cutting mechanics, meaning that the cutting mechanics should be incorporated in some fashion. In this paper, we incorporate the instantaneous cutting force and the tool deflection phenomena in predicting the machined surface for the finish-cut and milling operation. For the given NC dat including cutting conditions, the developed algorithm computes cutting force and deflection amount along the tool trajectory, and outputs the 3D graphic model of the machined surface together with error analysis. The validity and accuracy of the presented method has been tested by the actual cutting experiments. Experimental results and accuracy enhancement method together with implementing architecture of the VMCS (Virtual Machining CAM System) are discussed in the paper.

• 한국국방경영분석학회지
• /
• 제30권2호
• /
• pp.63-80
• /
• 2004

This paper develops a methodology which can be used to quantify the combat effectiveness of the army C2A system by modifying C2 theory and using Air Defense Engagement Simulation. In this paper, by using Schutzer's C2 theory and Measures of Effectiveness, we modified the MOE formula he designed. Because the combat effectiveness by enhancement of C2(Command and Control) system will increase combat power of individual asset independently. In addition, we developed simulation analysis of air defense scenario by using Air Defense Engagement Simulation. The results show that modified the MOE formula is proper as compared with Air Defense Engagement Simulation method. The combat effectiveness can be obtained as a result of improved probability of detection and information accuracy through real-time information sharing and coordination by C2A system.

• Journal of Positioning, Navigation, and Timing
• /
• 제1권1호
• /
• pp.1-6
• /
• 2012

For a Global Positioning System (GPS) receiver, it is known that a Vector Delay Locked Loop (DLL) in which the code signals of each satellite are tracked in parallel by using navigation results shows better performance in the aspect of the tracking accuracy and the robustness than that of a Scalar DLL. However, the quantitative analysis and the logical grounds for that performance enhancement of the Vector DLL are not sufficient. This paper, therefore, proposes the structure of the GPS receiver with the Vector DLL and analyzes the performance of it. The tracking and the positioning accuracy of the Vector DLL are theoretically analyzed and confirmed by simulation results. From the simulation results, it can be seen that the tracking and positioning accuracy has been improved about 30% in case that the receiver is static and the positioning is conducted for every Pre-detection Integration Time (PIT) while C/N0 is 45 dB-Hz.

• Journal of Electrical Engineering and Technology
• /
• 제8권3호
• /
• pp.638-648
• /
• 2013

Together with the GPS-based approach, geo-location through mobile communication networks is a key technology for location-based service. To save the cost, most geo-location system is implemented on the existed network service, which has a cellular structure. Still, multilateration is limited in cellular structure because it is difficult for the mobile terminal to acquire distance measurements from multiple base stations. This low hearability in the receiver is caused by co-channel interference and multipath environment. Therefore, hearability enhancement is necessary for multilateration under multipath and interference environment. Former time domain based hearability methods were designed for real signals. However, orthogonal frequency division multiplexing (OFDM) signal, which its usage has been increased in digital wireless communication, is a complex signal. Thus, different hearability enhancement method is needed for OFDM signals. This paper proposes a hearability enhancement method for forward-link multilateration using OFDM signals, which employ interference cancellation and multipath mitigation. A novel interference cancellation and multipath mitigation strategy for complex-valued OFDM signals is presented that has an iterative structure. Simulation results show that the proposed multilateration method provides the user's position with an accuracy of less than 80m through the mobile WiMAX cellular network in multipath environment.

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