The problem of using normalized rms in a sliding window to compare seismic tracesDISCUSSIONOn: “Imaging the Aquistore reservoir after 36 kilotonnes of CO2 injection using distributed acoustic sensing.” Harris, K., White, D.J., Samson, C., 2017. Geophysics 82 (6), M81–M96and “Initial 4D seismic results after CO2 injection start-up at the Aquistore storage site.” Roach, L.A.N., White, D.J., Roberts, B., Angus, D., 2017. Geophysics 82 (3), B95–B107.

Two papers published in Geophysics use the normalized rms (NRMS) calculation in a sliding window to compare traces and to create a ‘difference nrms’ volume. The authors use the derived difference volume to show the presence of apparent time-lapse anomaly between two seismic surveys. In this discussion we point out that the used methodology does not allow a robust comparison of seismic traces. We recommend the use of simple amplitude difference calculation between volumes to show the presence of time-lapse anomalies, instead of the used methodology.

Non-stationary local slope estimation via forward-backward space derivative calculation

The local slope estimated from seismic images has a variety of meaningful applications. Slope estimation based on the plane-wave destruction (PWD) method is one of the widely accepted techniques in the seismic community. However, the PWD method suffers from its sensitivity to noise in the seismic data. We propose an improved slope estimation method based on the PWD theory that is more robust in the presence of strong random noise. The PWD operator derived in the Z-transform domain contains a phase-shift operator in space corresponding to the calculation of the first-order derivative of the wavefield in the space domain. The first-order derivative is discretized based on a forward finite difference in the traditional PWD method, which lacks the constraint from the backward direction. We propose an improved method by discretizing the first-order space derivative based on an averaged forward-backward finite-difference calculation. The forward-backward space derivative calculation makes the space-domain first-order derivative more accurate and better anti-noise since it takes more space grids for the derivative calculation. In addition, we introduce non-stationary smoothing to regularize the slope estimation and to make it even more robust to noise. We demonstrate the performance of the new slope estimation method by several synthetic and field data examples in different applications, including 2D/3D structural filtering, structure-oriented deblending, and horizon tracking.

Organoleptic Properties, Proximate Compositions, and Antioxidant Activity of Carrot – Navel Orange Marmalade

BACKGROUND: Oxidative stress due to free radicals leads to degenerative diseases such as cardiovascular disease. For prevention, high antioxidants food content is needed. AIM: The study aimed to identify the antioxidant activity, proximate compositions, and organoleptic properties of carrot – navel orange marmalade. METHODS: It was an experimental study with five formulations of marmalades, that is, F1 (100 g orange: 0 g carrot), F2 (100 g orange: 25 g carrot), F3 (100 g orange: 50 g carrot), F4 (100 g orange: 75 g carrot), and F5 (100 g orange: 100 g carrot). The organoleptic test assessment was executed through the visual analog scale instrument on hedonic and hedonic quality parameters. The measurement of proximate compositions was conducted according to the Association of Official Analytical Chemists. The carbohydrate was used by difference calculation, while the Brix measured by refractometer. The antioxidant activity was identified by the 1,1-Diphenyl-2-picrylhydrazyl method. RESULTS: The addition of juice and shredded carrot into navel orange marmalade tended to increase organoleptic values. Based on the sensory evaluation, the hedonic value of marmalade F1 had the lowest sensory acceptance value. The marmalade F2 (25% carrot) was dedicated as the most acceptable product with a medium bright color, quite pleasant aroma, a bit sweet, quite thick texture, and overall was quite attractive. Furthermore the carrot added significantly influenced the proximate (carbohydrate, protein, fat, fiber, water, and ash) (p < 0.05) and significantly increased the Brix (p < 0.05). The combination of carrot and orange resulted in a high antioxidant marmalade, with IC50 ranged 16.54 ± 0.02–19.83 ± 0.04 ppm. CONCLUSION: This study revealed that carrot – navel orange marmalade could be a suitable source of antioxidants.

AdaMM: Adaptive Object Movement and Motion Tracking in Hierarchical Edge Computing System

This paper presents a novel adaptive object movement and motion tracking (AdaMM) framework in a hierarchical edge computing system for achieving GPU memory footprint reduction of deep learning (DL)-based video surveillance services. DL-based object movement and motion tracking requires a significant amount of resources, such as (1) GPU processing power for the inference phase and (2) GPU memory for model loading. Despite the absence of an object in the video, if the DL model is loaded, the GPU memory must be kept allocated for the loaded model. Moreover, in several cases, video surveillance tries to capture events that rarely occur (e.g., abnormal object behaviors); therefore, such standby GPU memory might be easily wasted. To alleviate this problem, the proposed AdaMM framework categorizes the tasks used for the object movement and motion tracking procedure in an increasing order of the required processing and memory resources as task (1) frame difference calculation, task (2) object detection, and task (3) object motion and movement tracking. The proposed framework aims to adaptively release the unnecessary standby object motion and movement tracking model to save GPU memory by utilizing light tasks, such as frame difference calculation and object detection in a hierarchical manner. Consequently, object movement and motion tracking are adaptively triggered if the object is detected within the specified threshold time; otherwise, the GPU memory for the model of task (3) can be released. Moreover, object detection is also adaptively performed if the frame difference over time is greater than the specified threshold. We implemented the proposed AdaMM framework using commercial edge devices by considering a three-tier system, such as the 1st edge node for both tasks (1) and (2), the 2nd edge node for task (3), and the cloud for sending a push alarm. A measurement-based experiment reveals that the proposed framework achieves a maximum GPU memory reduction of 76.8% compared to the baseline system, while requiring a 2680 ms delay for loading the model for object movement and motion tracking.

Deep Learning-Driven Gaussian Modeling and Improved Motion Detection Algorithm of the Three-Frame Difference Method

To enhance the effect of motion detection, a Gaussian modeling algorithm is proposed to fix holes and breaks caused by the conventional frame difference method. The proposed algorithm uses an improved three-frame difference method. A three-frame image sequence with one frame interval is selected for pairwise difference calculation. The logical “OR” operation is used to achieve fast motion detection and to reduce voids and fractures. The Gaussian algorithm establishes an adaptive learning model to make the size and contour of the motion detection more accurate. The motion extracted by the improved three-frame difference method and Gaussian model is logically summed to obtain the final motion foreground picture. Moreover, a moving target detection method, based on the U-Net deep learning network, is proposed to reduce the dependency of deep learning on the number of training datasets. It helps the algorithm to train models on small datasets. Next, it calculates the ratio of the number of positive and negative samples in the dataset and uses the reciprocal of the ratio as the sample weight to deal with the imbalance of positive and negative samples. Finally, a threshold is set to predict the results for obtaining the moving object detection accuracy. Experimental results show that the algorithm can suppress the generation and rupture of holes and reduce the noise. Also, it can quickly and accurately detect movement to meet the design requirements.

Number Sense Makes All the Difference: Calculation Using Number Sense by Pupils With and Without Learning Difficulties in Math

The research examined the calculation methods used by pupils in Grades 3–6 when they were presented with problems that could be worked out efficiently and flexibly by applying number sense. The study was conducted with a convenience sample of 179 pupils between the ages 7 years and 10 months to 12 years and 10 months. in mainstream education in Israel, who attended schools belonging to different sectors and situated in different areas of the country with varied socioeconomic profiles. The test included addition, subtraction, multiplication, and division problems that pupils were asked to solve mentally, in writing and by identifying correctly and incorrectly solved problem. Some of the problems presented pupils with opportunities to apply number sense. As expected, the research findings showed significant differences in calculation accuracy between pupils with and without learning difficulties, especially in multiplication and division tasks. Still, the performance of pupils with difficulties in the accuracy variable was above average, and there was high variance within this group. We found significant differences between pupils with and without difficulties in the calculation-speed variable in all tasks and in all calculation modalities. One of the implications is that pupils, and especially those with difficulties, should be afforded enough time to work out problems, and should be presented with tasks that would enable them to use number sense in order to retrieve prior knowledge and apply it.

Visual Variations between Pairs of SARS-CoV-2 Genomes on Integrated Density Matrix

This paper is the B2 module of the MAS. The quantification matrix is formed according to the four-base arrangement in the genome sequence. The differences in new coronavirus genome sequencing sequences in different samples were demonstrated by using the most concise methods. Using 4 primitive variable value measures, changes in the virus genome sequence base order conditions were deter-mined. When two relatively large genomic sequences are slightly different, the integrated distribution of the difference calculation is subtly similar to the Bose-einstein distribution, while the sum calculation shows a powerful distribution complexity. It can be formed under the macroscopic angle and can distinguish 16 combinations of supersymmetric structures. In view of the abundant transformation structure in this kind of transformation system, the detailed exploration remains to be followed by the systematic expansion of theory and medical application.

Visual Variations between Pairs of SARS-CoV-2 Genomes on Integrated Density Matrix

This paper is the B2 module of the MAS. The quantification matrix is formed according to the four-base arrangement in the genome sequence. The differences in new coronavirus genome sequencing sequences in different samples were demonstrated by using the most concise methods. Using 4 primitive variable value measures, changes in the virus genome sequence base order conditions were determined. When two relatively large genomic sequences are slightly different, the integrated distribution of the difference calculation is subtly similar to the Bose-Einstein distribution, while the sum calculation shows a powerful distribution complexity. It can be formed under the macroscopic angle and can distinguish 16 combinations of supersymmetric structures. In view of the abundant transformation structure in this kind of transformation system, the detailed exploration remains to be followed by the systematic expansion of theory and medical application.