Evaluation Points Research Articles

Defect detection method of magnetic disk image based on improved convolutional neural network

This paper proposes an efficient method for defect detection of magnetic disk image based on improved convolutional neural network. We build a model named DiskNet on the basis of VGGNet-19, in which the optimal activation function is selected predictively through a weighted probability learning curve model (WP-Model). First, we use Markov Chain Monte Carlo (MCMC) to infer the predicted value and determine prediction probability. Then, the evaluation point (EP) is determined by the effective information of training curve. In the process of DiskNet training, when the prediction probability is higher than the threshold, the neural network will select the current activation function. If the training epochs exceed the EP and the threshold is not reached, the original activation function will be used. The experimental results show that the accuracy of the proposed method in detecting defects on the magnetic disk image data set is 96.9%.

Assessment of Rock Aggregate Quality Through the Analytic Hierarchy Process (AHP)

The present study aimed to assess rock aggregate quality through the Analytic Hierarchy Process (AHP). In the context of the AHP analyses, four rock types (i.e., andesite, basalt, granodiorite, and gabbro), five evaluation criteria, and several technical requirements/suggestions for coarse aggregates related to bituminous paving mixtures were considered. In order to set over the evaluation criteria, detailed laboratory studies were conducted. For this purpose, various mineralogical, physical, and mechanical aggregate properties were determined for each rock type concerning their weathering grades. As a result of the laboratory studies, it was determined that the rock weathering processes have substantial negative impacts on the rock aggregate properties considered in this study. The AHP analysis results indicated that that different rock types have several advantages concerning various evaluation criteria. Based on the general evaluation point (EP) of the rocks, the gabbros were found to have the highest rock aggregate quality (EP = 0.393). In contrast, the andesites had the lowest quality (EP = 0.069). Besides, the basalts (EP = 0.271) and granodiorites (EP = 0.267) presented approximately the same quality for their use in bituminous pavement mixtures. It was also demonstrated that the AHP, with its specific methodology, can be utilized to represent different environmental and mechanical conditions by changing the relative weight of the evaluation criteria. In this way, the pros and cons of different rock types could be revealed quantitatively, which enables related engineers to select proper rock types for their use under different environmental and mechanical conditions. From this point of view, the present study could be declared a case study noted for combining theoretical and practical approaches on bituminous paving mixtures as a sign of rock aggregate quality.

Automatic extraction technique of CD‐SEM evaluation points to measure semiconductor overlay error

AbstractIn semiconductor device manufacturing process, it is necessary to measure overlay error between integrated layers. As semiconductor process design rules continue to shrink, small overlay error comes to lead to the fatal fault of the device electrical property. As a result, the needs for the dense overlay measurement in the chip with the use of circuit pattern increase. We propose an automatic extraction technique of the evaluation points (EPs) that are suitable for the overlay measurement by scanning electron microscopy using design data of the device pattern layout. The proposed algorithm extracts all measureable patterns by evaluation of the positional relationship between a segment pair on the upper and lower layers by plural selection indices. Simulation was performed to estimate the overlay error distribution within the shot area using the EPs automatically extracted by the proposed method. The standard deviations of estimation errors in the x‐ and y‐directions were 0.06 nm and 0.10 nm (3ó), respectively. It was confirmed that distortion in the exposure apparatus can be estimated automatically and highly accurately.

Contribution Determination for Multiple Unbalanced Sources at the Point of Common Coupling

Three-phase unbalance is an important power quality issue that can cause many negative effects to the power system. Effective mitigation and management of voltage unbalance will benefit from the knowledge of how the unbalanced sources contribute to the voltage asymmetry at the point of evaluation (POE). In this paper, a method is proposed to assess the overall unbalance contribution of the multiple unbalanced sources at the point of common coupling (PCC). Firstly, the equivalent circuit for analysis is established and the unbalance contribution indices are proposed. Then a method is proposed to determine whether the dominant unbalanced polluter is at the upstream or downstream of POE. If the main unbalanced source is identified to be downstream of POE, a procedure is further proposed to determine the individual contribution of the multiple unbalanced sources. Moreover, for the multiple unbalanced source condition, the current flowing in each feeder is proposed to be used for the contribution estimation instead of the current actually emitted by the unbalanced source. Finally, a method is proposed to estimate the equivalent negative sequence impedance of the aggregate loads. Simulation and field analysis results validate the effectiveness and accuracy of the method.

Calibration of hydrological models using flow-duration curves

Abstract. The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested – based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow and where peak-flow timing at sub-daily time scales is of high importance. The results suggest that the calibration method can be useful when observation time periods for discharge and model input data do not overlap. The method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.

Elastic-Plastic Non Linear Behaviors of Suddenly Loaded Structures

Problem statement: The adaptively shifted integration technique was applied to the elasticplastic analysis of framed structures under dynamic loading. Approach: This study used analysis of linear beam element, the reshifting of the of the integration points in the element is conducted in order to attain higher accuracy. Results: In nonlinear finite element analysis by the ASI technique, the highest computational efficiency has been achieved by shifting the numerical integration points for evaluation of stiffness matrices of linear Timoshenko beam element. A computer program has been Written by VBASIC for solve the problem of the steel frame, results of numerical examples demonstrate the validity of the computer program and study many parametric study, such as Time step and Mass of the structure. Conclusion/Recommendations: In the elastic analysis there is no distinction between the ASI technique and the conventional finite element method, but for elasticplastic nonlinear analysis under dynamic load Adaptive Shifted Integration (ASI) technique is capable of predicting with reasonable accuracy the behavior of steel frame structures.

Integrated evaluation of rape readiness for overwintering

Rape (Brassica napus L.) overwintering has been studied in Lithuania and elsewhere; however, data have been analysed separately without inetgration into a common evaluation system. In this work the chosen integrated evaluation method enabled us to make complex evaluation of rape readiness for overwintering in crops of different density. A comprehensive evaluation of rape readiness for overwintering in crops of different density was performed using experimental data of the years 2000–2002. The variances of the individual indicators were subdivided into scales of nine points, and means were assigned to these points. The resulting evaluation points (EP) were marked in a network diagram with the radius scaled from 1 to 9. Evaluation threshold (ET = 5 evaluation points) was also marked, indicating the border between positive and negative assessment. This method thus allows at one sight a distinct, reproducible illustration and evaluation of different indicators characterizing readiness for overwintering. Additionally, interactions between indicators and areas demarcated by the evaluation points of all indications are visualized in the network diagram. An integrated evaluation index (IEI), consisting of the average of evaluation points, its standard deviation and standard deviation of the average of the evaluation points below the ET, was calculated to make generalized data assessments. Comprehensive evaluation using 21 indicators of rape readiness for overwintering in crops of different density showed that importance of these indicators varied. Better plant readiness for overwintering in a crop of the lowest density was determined by high values of assessment of terminal bud height, root collar diameter and nutrient accumulation in the terminal bud compared with a more dense crop. The suitability of the integrated evaluation method in such cases highlights the establishment of very strong and significant correlation (r = 0.98, p≤0.01) between the number of plants that survived the winter and the average evaluation points of readiness for overwintering. The areas determined by values of all indicators, according to different crop densities and calculated integrated evaluation indices, showed that rape readiness for overwintering in a crop with a density of < 20 plants m−2 (IEI = 6.37–1.69–1.15) and with a density of 20.1–40 plants m−2 (IEI = 5.67–1.28–1.02) was better than the average one; in a crop with a density of 40.1–60 plants m−2 (IEI = 4.97–0.85–0.53) was equal to the average one; and in a crop with a density of 60.1–80 plants m−2 (IEI = 3.62–1.23–0.79) and with a density of 80.1–100 plants m−2 (IEI = 3.10–1.76–0.67) was worse than the average one. Very strong and significant correlation was established between the number of plants that survived winter and average of evaluation points of indicators determining rape overwintering.