Features Standard Deviation Research Articles

Reduction of fluctuations in the calculation of nuclear reactivity using the Gauss-Legendre quadrature with a Savitzky-Golay filter

In this work, the reduction of fluctuations in the calculation of nuclear reactivity using Gauss-Legendre quadrature is presented, three quadratures of different order are implemented in the approximation of the integral and differential term contained in the inverse equation of the point kinetics. The fluctuations are simulated by assuming that noise has a Gaussian distribution around a mean value of the neutron population density with a characteristic standard deviation. The fluctuations are reduced using the Savitzky-Golay filter with different sampling windows. The results indicate that the proposed method is an alternative method that can be implemented in a digital reactivity meter.

Real-time porosity monitoring during laser welding of aluminum alloys based on keyhole 3D morphology characteristics

This research proposes a real-time porosity monitoring approach for aluminum (Al) alloys laser welding based on keyhole 3D morphology characteristics, realizing the prediction of the local porosity at each position of the weld. Building a multi-sensing signals monitoring platform consisting of a high-speed camera and a coherent optical system, the keyhole 3D morphology is measured. For the keyhole 3D morphological standard deviation (STD) features obtained by the algorithm of sliding window scan, the data processing based on ensemble empirical mode decomposition (EEMD) and principal component analysis (PCA) is adopted to acquire the input of an artificial neural network (ANN). The local porosity is acquired as the output of the ANN by scanning the weld with the sliding window and performing EEMD processing. A feedback mechanism is introduced into the ANN and the genetic algorithm (GA) is utilized to optimize the network parameters to improve the porosity prediction performance of the model. The prediction results show that the constructed optimized ANN can effectively and accurately monitor the porosity, and the generalization ability of the model is strong. In the corresponding relationship between the porosity and each STD feature, it is found that the formation position of the pore lags behind the fluctuation position of the keyhole, which can be explained by molten pool flow.

EVALUATING THE PERFORMANCE OF EMG BASED BACK PROPAGATION NEURAL NETWORK (BPNN) TIME DOMAIN FEATURES AND TIME ADVANCE FEATURES FOR KNEE JOINT ANGLE ESTIMATION

One of the challenges in lower limb rehabilitation robot design and control for assistance as needed robot is the interaction between the robot and the user. This can be overcome by quantifying the amount of assistance needed by the patient. Which attributed to the precision and accuracy of the estimated knee joint angle by the controller. In this research, the back propagation neural network (BPNN) was trained to estimate the amount of compensation needed by the patients who served as input to the robot. The Electromyogram (EMG) signals, time domain (TD) and time advance domain (TAD) were considered and root means square (RMS), mean absolute value (MAV), variance (VAR) and standard deviation (STD) features were extracted from each domain. Fourteen healthy subjects accepted to validate the experimental setup. However, the best eight subjects data were consider for this article. The features were used separately for training BPNN and the performance of each feature was evaluated. The EMG signals of the protagonist muscle (vastus lateralis) and antagonist muscles (semitendinosus) were used as the input signal to the BPNN after processing the signals. The electro-goniometer reading of the knee joint angle was used as the output to the network. The features were used separately for training BPNN and the performance of each feature was evaluated. The TAD RMSE values were significantly reduced compared to TD with 37.34% , 35.32% , 34.87% and 31.22% for RMS, MAV, VAR and STD features respectively. The result shows that the TAD features have better performance for estimating the knee joint angle.

Spatial differences in the luminescence sensitivity of quartz extracted from Carpathian Basin fluvial sediments

The luminescence sensitivity of a sample is the luminescence intensity measured in response to unit radioactive dose. Sensitivity is by no means a stable parameter, it might change during measurements, or in nature as well. The primary or natural magnitude of luminescence sensitivity is basically determined by mineralogical background (number of crystal impurities) and sedimentary prehistory (repeated exposure of the sediment to sunlight). In the present study we have investigated the luminescence properties and sensitivity of coarse-grain (90–150 μm) quartz samples related to four major rivers of the Carpathian Basin (River Danube, Tisza, Szamos and Maros). In case of each region of interest 5 previously dated Late Pleistocene and/or Holocene samples were selected, each representing similar sedimentary environments, i.e. coarse grain channel deposits related to point bars and medial bars. Sensitivity was investigated using CW-OSL, LM-OSL and TL techniques using a multi-grain approach. By determining the normalised luminescence response to the same regeneration dose administered after bleaching, sensitivity base values were obtained for each sample. Using repeated cycles of dosing laboratory sensitivity change was also recorded. The base values and sensitivity change of the 20 investigated samples were then compared on a regional basis to identify potential differences, which might be used later for fingerprinting the sediments of the investigated rivers. When considering mean sensitivity base values, calculated from several aliquots of the same sample, Danube related, mostly Alpine origin sediments exhibited 50–60% lower values compared to those with a Carpathian origin, and even at the considerable standard deviation obtained (coefficient of variation being 25–60%) they could be clearly separated using any of the measured luminescence sensitivity parameters. The discrimination of fluvial sediments with a Carpathian origin, but representing different catchments, is less straightforward, though, plotting against different sensitivity parameters can offer an opportunity to define fairly distinct groups of sample mean values. From this aspect total LM-OSL and fast component ratio seemed to be the best candidates, however, at the characteristic standard deviation and standard error separation can be unclear. No clear relationship was found in terms of sensitivity change, however some samples, related to River Maros showed practically no change during the laboratory sensitisation process. When plotting OSL ages against quartz sensitivity clear trends could be recognised, which can partly be explained by geomorphological reasons. Results in all, point to the possibility to differentiate Carpathian Basin fluvial sediments on the basis of their quartz luminescence sensitivity, a parameter that can be assessed easily during the routine dating process. • The OSL sensitivity of Carpathian Basin fluvial quartz shows spatial variability. • The quartz of Danube sediments with an Alpine background is outstandingly dim. • By combining sensitivity parameters sediment sourcing can be more efficient. • Relationship between age and sensitivity is also affected by morphological processes.

Triplet Loss with Channel Attention for Person Re-identification

The triplet loss function has seen extensive use within person re-identification. Most works focus on either improving the mining algorithm or adding new terms to the loss function itself. Our work instead concentrates on two other core components of the triplet loss that have been under-researched. First, we improve the standard Euclidean distance with dynamic weights, which are selected based on the standard deviation of features across the batch. Second, we exploit channel attention via a squeeze and excitation unit in the backbone model to emphasise important features throughout all layers of the model. This ensures that the output feature vector is a better representation of the image, and is also more suitable to use within our dynamically weighted Euclidean distance function. We demonstrate that our alterations provide significant performance improvement across popular reidentification data sets, including almost 10% mAP improvement on the CUHK03 data set. The proposed model attains results competitive with many state-of-the-art person re-identification models.

MO-DE-207B-07: Assessment of Reproducibility Of FDG-PET-Based Radiomics Features Across Scanners Using Phantom Imaging

Purpose: Use a NEMA-IEC PET phantom to assess the robustness of FDG-PET-based radiomics features to changes in reconstruction parameters across different scanners. Methods: We scanned a NEMA-IEC PET phantom on 3 different scanners (GE Discovery VCT, GE Discovery 710, and Siemens mCT) using a FDG source-to-background ratio of 10:1. Images were retrospectively reconstructed using different iterations (2–3), subsets (21–24), Gaussian filter widths (2, 4, 6mm), and matrix sizes (128,192,256). The 710 and mCT used time-of-flight and point-spread-functions in reconstruction. The axial-image through the center of the 6 active spheres was used for analysis. A region-of-interest containing all spheres was able to simulate a heterogeneous lesion due to partial volume effects. Maximum voxel deviations from all retrospectively reconstructed images (18 per scanner) was compared to our standard clinical protocol. PET Images from 195 non-small cell lung cancer patients were used to compare feature variation. The ratio of a feature's standard deviation from the patient cohort versus the phantom images was calculated to assess for feature robustness. Results: Across all images, the percentage of voxels differing by 3) were observed for routinely used SUV metrics (e.g. SUVmean and SUVmax) as well as some radiomics features (e.g. co-occurrence contrast, co-occurrence energy, standard deviation, and uniformity). Similar standard deviation ratios were observed across scanners. Conclusions: Our method enabled a comparison of feature variability across scanners and was able to identify features that were not robust to changes in reconstruction parameters.

Comparing Functional EMG Characteristics Between Zero-Order and First-Order Interface Dynamics

The optimal control scheme for powered prostheses can be determined using simulation experiments, for which an accurate model of prosthesis control is essential. This paper focuses on electromyographic (EMG) control signal characteristics across two different control schemes. We constructed a functional EMG model comprising three EMG signal characteristics-standard deviation, kurtosis, and median power frequency-using data collected under realistic conditions for prosthesis control (closed-loop, dynamic, anisometric contractions). We examined how the model changed when subjects used zero-order or first-order control. Control order had a statistically significant effect on EMG characteristics, but the effect size was small and generally did not exceed inter-subject variability. Therefore, we suggest that this functional EMG model remains valid across different control schemes.

RFLP Band Size Standards: Cell Line K562 Values from 1991 to 1997 Proficiency Studies

Cell line K562 is the defacto forensic control material for forensic restriction fragment length polymorphism (RFLP) DNA profiling in the U.S. Fifty-one proficiency tests conducted from 1991 through 1997 enable a detailed description of RFLP measurement performance during this period. Sufficient data are available to define reference distributions for all commonly utilized and many less commonly reported genetic loci, for both HaeIII- and HinfI-based RFLP systems. The average measured size of HaeIII locus D1S7 and D5S110 bands has varied slightly over time; while relatively small, these temporal changes add to the overall interlaboratory measurement uncertainty. The characteristic standard deviation for HinfI RFLP system measurements has a nearly identical dependence on expected band size as does the standard deviation for HaeIII measurements. The ellipsoidal distance, K, is suggested for use as an RFLP data quality metric; the critical threshold value that on average excludes 1% of plausibly valid proficiency data for a given polymorphic locus is K1% = 14.2.