• 현장농수산연구지
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• 제13권1호
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• pp.3-17
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• 2011

Pipelines of processor have been growing deeper and issue widths wider over the years. If this trend continues, branch misprediction penalty will become very high. Branch misprediction is the single most significant performance limiter for improving processor performance using deeper pipelining. Therefore, more accurate branch predictor becomes an essential part of modem processors for FAFF(Food, Agriculture, Forestry, Fisheries)Information Processing. In this paper, we propose a branch prediction mechanism, using variable length history, which predicts using a bank having higher prediction accuracy among predictions from five banks. Bank 0 is a bimodal predictor which is indexed with the 12 least significant bits of the branch PC. Banks 1,2,3 and 4 are predictors which are indexed with different global history bits and the branch PC. In simulation results, the proposed mechanism outperforms gshare predictors using fixed history length of 12 and 13, up to 6.34% in prediction accuracy. Furthermore, the proposed mechanism outperforms gshare predictors using best history lengths for benchmarks, up to 2.3% in prediction accuracy.

• Journal of Positioning, Navigation, and Timing
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• 제12권2호
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• pp.167-176
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• 2023

This study presents the performance analysis of real-time orbit determination and prediction for navigation message generation of Regional Navigation Satellite System (RNSS). Since the accuracy of ephemeris and clock correction in navigation message affects the positioning accuracy of the user, it is essential to construct a ground segment that can generate this information precisely when designing a new navigation satellite system. Based on a real-time architecture by an extended Kalman filter, we simulated orbit determination and prediction of RNSS satellites in order to assess the accuracy of orbit and clock prediction and signal-in-space ranging errors (SISRE). As a result of the simulation, the orbit and clock accuracy was at 0.5 m and 2 m levels for 24 hour determination and six hour prediction after the determination, respectively. From the prediction result, we verified that the SISRE of RNSS for six hour prediction was at a 1 m level.

• ETRI Journal
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• 제46권3호
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• pp.538-549
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• 2024

A conventional codec aims to increase the compression efficiency for transmission and storage while maintaining video quality. However, as the number of platforms using machine vision rapidly increases, a codec that increases the compression efficiency and maintains the accuracy of machine vision tasks must be devised. Hence, the Moving Picture Experts Group created a standardization process for video coding for machines (VCM) to reduce bitrates while maintaining the accuracy of machine vision tasks. In particular, in-loop filters have been developed for improving the subjective quality and machine vision task accuracy. However, the high computational complexity of in-loop filters limits the development of a high-performance VCM architecture. We analyze the effect of an in-loop filter on the VCM performance and propose a suboptimal VCM method based on the selective activation of in-loop filters. The proposed method reduces the computation time for video coding by approximately 5% when using the enhanced compression model and 2% when employing a Versatile Video Coding test model while maintaining the machine vision accuracy and compression efficiency of the VCM architecture.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.290-297
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• 2024

We investigate the efficacy of ensemble learning methods, specifically the soft voting technique, for enhancing heart disease prediction accuracy. Our study uniquely combines Logistic Regression, SVM with RBF Kernel, and Random Forest models in a soft voting ensemble to improve predictive performance. We demonstrate that this approach outperforms individual models in diagnosing heart disease. Our research contributes to the field by applying a well-curated dataset with normalization and optimization techniques, conducting a comprehensive comparative analysis of different machine learning models, and showcasing the superior performance of the soft voting ensemble in medical diagnosis. This multifaceted approach allows us to provide a thorough evaluation of the soft voting ensemble's effectiveness in the context of heart disease prediction. We evaluate our models based on accuracy, precision, recall, F1 score, and Area Under the ROC Curve (AUC). Our results indicate that the soft voting ensemble technique achieves higher accuracy and robustness in heart disease prediction compared to individual classifiers. This study advances the application of machine learning in medical diagnostics, offering a novel approach to improve heart disease prediction. Our findings have significant implications for early detection and management of heart disease, potentially contributing to better patient outcomes and more efficient healthcare resource allocation.

• Tribology and Lubricants
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• 제15권3호
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• pp.257-264
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• 1999

Recently as electronics and semi-conductor industry develop, ultra-precision machine tools that use air-spindle with externally pressurized air bearing appear in need of ultra-precision products which demand high precision property. Effects of air compressibility absorbs the vibration of shaft, this is called averaging effect, however, the higher running accuracy is demanded by degrees, the more important factor is machining errors that affect running accuracy of shaft. Actually, it would be very important in the view points of running accuracy to understand effects of machining errors on the running accuracy of the spindle system quantitatively to design and manufacture precision spindle system in the aspect that efficiency in manufacturing spindle system and performance in operation. So fu, there are some researches on the effects that machining error affect running accuracy. However, because these researches deal with one bearing of spindle system, these results aren't enough to explain how much machining errors affect running accuracy in the typical spindle system overall. In this study, we investigate the effects of the perpendicularity error of bearing and shaft on running accuracy of spindle system that consists of journal and thrust bearing theoretically, and suggest design guideline about shape tolerances.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1144-1149
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• 2003

It is very important to measure circular motion accuracy of NC lathes it affects accuracy, performance, interchange ability and quality of machine parts machined by the NC lathes in industries. So, in this study, measuring units system to measure circular motion accuracy two axes circular motion accuracy of NC lathes was composed of two optical linear scales installed on the z and x-axes of work coordinate system on NC lathe and a computer inserted with PC counter card enables to obtain measuring data. Here, ATC(Automatic Tool Changer) and moving part of linear scales are fixed with magnet bases in order to measure circular motion accuracy of the ATC of NC lathe. And next, computer software was developed in order to measure the circular motion accuracy of NC lathe under resolution of 0.1 $\mu\textrm{m}$ using two linear scales, and also computer softwares were developed so that measuring data could be modeled on plots and be analyzed numerically,

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.1358-1361
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• 2008

Several different techniques currently exist for measuring display view angle performance. These include conoscopes, goniometric systems, and, most recently introduced to the market, instruments based on Imaging Sphere technology. This paper will compare measurement accuracy and speed of these various methodologies with different FPD types and even 3-D displays.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 춘계학술대회 초록집
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• pp.207.1-207.1
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• 2011

The performance of a francis turbine is studied by applying a new performance evaluation tester. the performance of a francis turbine is predicted under several operating conditions and the prediction results are compared with model test data. As a result, it is demonstrated that the present method can predict the performance of a francis turbine with high accuracy and has usefullness as an engineering tool on the performance of hydraulic turbines.

• 한국기계가공학회지
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• 제13권5호
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• pp.64-69
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• 2014

This article presents machining experiments to assess the relationship between the profile accuracy and the workpiece hardness using a natural diamond tool on an ultra-precision diamond turning machine. The study is intended to secure a corner cube prism pattern for reflective film capable of high-quality outcomes. The optical performance levels and edge images of corner cubes having various hardness levels of the copper-coated layer on a carbon steel plate are analyzed. The hardness of the workpiece has a considerable effect on the profile accuracy. The higher the hardness of the workpiece, the better the profile accuracy and the worse the edge wear of the diamond tool.

• 한국공작기계학회논문집
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• 제11권2호
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• pp.65-70
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• 2002

The rotational performance off machine tool spindle has a direct influence upon the surface finish of the finished workpiece. This running accuracy of the spindle is improved by increasing preload on the bearings, while it results in higher temperature rise and larger thermal deformation. Therefore, finding the optimal preload condition for high speed spindle is very important factors in spindle motion. in spindle motion. In this study, the effect of the preload on the roundness accuracy has been examined at the different cutting conditions. Experiments were carried out to investigate the effects of the bearing preload on the running accuracy of high speed spindle which was supported by two angular contact bearings.