Maximum Gradient Value Research Articles

Strain-controlled electrophysiological wave propagation alters in silico scar-based substrate for ventricular tachycardia.

Introduction: Assessing a patient's risk of scar-based ventricular tachycardia (VT) after myocardial infarction is a challenging task. It can take months to years after infarction for VT to occur. Also, if selected for ablation therapy, success rates are low. Methods: Computational ventricular models have been presented previously to support VT risk assessment and to provide ablation guidance. In this study, an extension to such virtual-heart models is proposed to phenomenologically incorporate tissue remodeling driven by mechanical load. Strain amplitudes in the heart muscle are obtained from simulations of mechanics and are used to adjust the electrical conductivity. Results: The mechanics-driven adaptation of electrophysiology resulted in a more heterogeneous distribution of propagation velocities than that of standard models, which adapt electrophysiology in the structural substrate from medical images only. Moreover, conduction slowing was not only present in such a structural substrate, but extended in the adjacent functional border zone with impaired mechanics. This enlarged the volumes with high repolarization time gradients (≥10ms/mm). However, maximum gradient values were not significantly affected. The enlarged volumes were localized along the structural substrate border, which lengthened the line of conduction block. The prolonged reentry pathways together with conduction slowing in functional regions increased VT cycle time, such that VT was easier to induce, and the number of recommended ablation sites increased from 3 to 5 locations. Discussion: Sensitivity testing showed an accurate model of strain-dependency to be critical for low ranges of conductivity. The model extension with mechanics-driven tissue remodeling is a potential approach to capture the evolution of the functional substrate and may offer insight into the progression of VT risk over time.

Method for detecting soil total nitrogen contents based on pyrolysis and artificial olfaction

Soil nitrogen is an essential nutrient element for crop growth and development, and an important indicator of soil fertility characteristics. This study proposed a method based on pyrolysis and artificial olfaction to quickly and accurately determine the soil total nitrogen (STN) content. A muffle furnace was used to pyrolyze the soil samples, and ten different types of oxide semiconductor gas sensors were used to construct a sensor array to detect the soil samples’ pyrolysis gas. The response curves of the sensors were tested at pyrolysis temperatures of 200°C, 300°C, 400°C, and 500°C and at pyrolysis times of 1 min, 3 min, 5 min, and 10 min to obtain the optimal pyrolysis state of the soil samples. The optimal pyrolysis temperature was 400°C, and the pyrolysis time was 3 min. The response area, maximum value, average differential coefficient, variance value, maximum gradient value, average value, and 8th-second transient value of the sensor response curve were extracted to construct an artificial olfactory feature space of 121×10×7 (121 soil samples, ten sensor numbers, seven extracted eigenvalues). Back-propagation neural network algorithm (BPNN), partial least squares regression algorithm (PLSR), and partial least squares regression combined with back-propagation neural network algorithm (PLSR-BPNN) were used to establish a prediction model of artificial olfactory feature space and STN content. Moreover, coefficient of determination (R2), root mean square error (RMSE), and the ratio of performance to deviation (RPD) were used as the performance indicators of the prediction results. The test results showed that the R2 of the PLSR, BPNN, and PLSR-BPNN models were 0.89033, 0.81185, and 0.92186, and the RMSE values were 0.24297, 0.37370, and 0.21781, and the RPD were 2.9964, 1.9482, and 3.3426, respectively. The model established by the PLSR-BPNN algorithm has the highest R2 and RPD and the smallest RMSE, can achieve the accurate prediction of STN content, and therefore the model is rated as “excellent”. The detection method in this study achieves a low-cost, rapid, and accurate determination of STN content, and provides a new reference for the measurement of STN. Keywords: pyrolysis, artificial olfactory system, soil total nitrogen, gas sensor array, prediction methods DOI: 10.25165/j.ijabe.20221503.7086 Citation: Li M W, Zhu Q H, Liu H, Xia X M, Huang D Y. Method for detecting soil total nitrogen contents based on pyrolysis and artificial olfaction. Int J Agric & Biol Eng, 2022; 15(3): 167–176.

Calculation of Encircled Energy as Optical Quality Assessment Parameter for Image System

In this paper a theoretical investigation of the Encircled Energy of an annular pupil (with different obscuration ratio ε = 0.25, 0.5, 0.75) for diffraction limited and defocus (optical system suffers from focal shift) optical system. The numerical evaluation was carried out using pupil function technique in Cartesian coordinates which has the advantage of introducing any kind and amount of aberration in the optical system. Another quality criterion for measuring the efficiency of optical systems is the Gradient determination. The maximum gradient value is near the center of the Encircled Energy curve in the image plane and will be decreases when the wave front aberration increases in the image plane. The presented results shows beater information when the optical system has a large amount of focal shift, and shows a clear reduction in the Encircled Energy values with increasing obscuration ratio This indicates that the central spot in the central ring group contains only a fraction of the total energy, so the whole set of central rings considered as the Effective Image Element.

Fast blind deconvolution using a deeper sparse patch-wise maximum gradient prior

In this study, we propose a patch-wise maximum gradient (PMG) prior for effective blind image deblurring. Our work is motivated by the fact that the maximum gradient values of non-overlapping local patches are significantly diminished by blurring; we demonstrate this inherent property both theoretically and using real data. Based on this, we propose a blur kernel estimation model using an L0-regularized PMG prior and L0-regularized gradient prior. Compared with previous image priors, our PMG prior exhibits a stronger ability to distinguish between clear and blurred images. It also has a deeper sparseness, which significantly reduces the computational cost. To solve the proposed PMG and L0-regularized gradient terms, we design an efficient optimization algorithm by introducing a linear operator and improving the iteration strategy. Visual and quantitative experimental results show that our method can achieve excellent performance and is superior to state-of-the-art methods in terms of computational efficiency and recovery quality in various specific scenarios such as natural, face, saturated, and text images.

Dynamic Scene Change Detection in Video Coding

Video compression has become a source of different research studies. It is necessary in order to address channel bandwidth limitations and growing video demand, including digital libraries and streaming media delivery via the Internet. A video is a number of frames captured by a camera while a scene is a series of consecutive frames captured from a specific narrative viewpoint. To compress a video, firstly, the intra frames are separated from inter frames using scene change detection methods. Then, block-based motion estimation algorithms are used to eliminate the temporal redundancy between successive frames. This paper describes some scene change detection methods for use on the uncompressed video to detect scene types such as cut, dissolve, wipe, etc. Absolute Frame Difference (AFD), Mean Absolute Frame Differences (MAFD), Mean Histogram Absolute Frame Difference (MHAFD), and Maximum Gradient Value (MGV) techniques are adaptively tested on different video types to identify accurate scene change in both low and high object motion scenes. Test results show that the proposed approach (MHAFD) obtains a better accuracy, F1-scor measure of 100%, especially for cuts and gradual transitions (wipe) video types. Dissolve scene change is detected with a high precision of 100% (i.e., no false detection) with the (MAFD) detector. Besides, in terms of time complexity for analyzing all the video samples, the proposed method (MHAFD ) provides the best result compared to the selected detectors.

Morphology of Ionospheric Sporadic E Layer Intensity Based on COSMIC Occultation Data in the Midlatitude and Low‐Latitude Regions

AbstractIonospheric sporadic E layer is thin irregularity with much higher plasma density in the ionospheric E region (~90‐120 km). Morphology of sporadic E intensity is investigated by using the COSMIC radio occultation data during 2007‐2012. Maximum gradient value of total electron content fluctuation is defined as Smax index, and it shows good linear relationship with the sporadic E intensity parameter (ordinary critical frequency, foEs) in the low‐latitude and midlatitude regions. By using this Smax index as the sporadic E layer intensity, distribution of sporadic E intensity is obtained. Some known features are confirmed such as the hemisphere summer enhancement, diurnal and semidiurnal behavior, and intensity depression anomaly regions. New findings are also obtained, especially the different behavior pattern in the low‐latitude region. (1) Both positive and negative correlations exist between sporadic E intensity and solar activity, and this correlation also shows complex magnetic latitude dependency. (2) Weaker seasonal variation is found in the low‐latitude region. Besides, hemisphere asymmetries of sporadic E intensity/location are also found during the equinox. (3) Longitudinal wave number‐4 feature of sporadic E intensity is prominent in the lower latitude region, which may be related to the diurnal eastward wave number‐3 tide. In a word, it is feasible to investigate the sporadic E layer intensity distribution based on radio occultation data, which also allows for a global morphology analysis.

Research on Distinguishing Fish Meal Quality Using Different Characteristic Parameters Based on Electronic Nose Technology.

In this paper, a portable electronic nose, that was independently developed, was employed to detect and classify a fish meal of different qualities. SPME-GC-MS (solid phase microextraction gas chromatography mass spectrometry) analysis of fish meal was presented. Due to the large amount of data of the original features detected by the electronic nose, a reasonable selection of the original features was necessary before processing, so as to reduce the dimension. The integral value, wavelet energy value, maximum gradient value, average differential value, relation steady-state response average value and variance value were selected as six different characteristic parameters, to study fish meal samples with different storage time grades. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), and five recognition modes, which included the multilayer perceptron neural network classification method, random forest classification method, k nearest neighbor algorithm, support vector machine algorithm, and Bayesian classification method, were employed for the classification. The result showed that the RF classification method had the highest accuracy rate for the classification algorithm. The highest accuracy rate for distinguishing fish meal samples with different qualities was achieved using the integral value, stable value, and average differential value. The lowest accuracy rate for distinguishing fish meal samples with different qualities was achieved using the maximum gradient value. This finding shows that the electronic nose can identify fish meal samples with different storage times.

Variation of Magnetic Memory Signals in Fatigue Crack Initiation and Propagation Behavior

To monitor fatigue crack initiation and propagation, and to judge the fatigue damage status of ferromagnetic material, fatigue bending tests of four-point single edge notch bend (SENB4) specimens were carried out. Metal magnetic memory signals were measured during the whole fatigue process. The results showed that the fatigue process could be divided into four stages by observing the morphology of the fracture surface. With the increase of fatigue loading cycles, the tangential component of the magnetic field (Hx) and the normal component of the magnetic field (Hy) increased. At the notch Hx presented a “trough” shape and had a maximum value at the midpoint, while Hy at the notch rotated clockwise around the midpoint. Compared with the tangential characteristic parameters, the variation of normal characteristic parameters (i.e., maximum gradient value of Hy (Ky-max) and the variation range of Hy at the notch (∆Hyn), with the fatigue loading cycles are more similar to the variation of fatigue crack length with loading cycles), both Ky-max and ∆Hyn had a good linear relationship with fatigue crack length. Plastic deformation accumulated on both sides of the fatigue crack, and metal magnetic memory (MMM) signals measured from the specimens were able to indicate the location of the fatigue crack and the variation of the fatigue crack length. Furthermore, the distribution of magnetic signals was analyzed according to the theories of stress magnetization and magnetic flux leakage.

Analysis of Relationships Between Three-Dimensional Magnetic Memory Signals and Artificial Defects Under Tensile Load

Abstract This paper mainly discusses the relationships between three-dimensional magnetic memory signals and artificial defects under different load levels. The correlations between the defect signal characteristic parameters and applied stress were analyzed. The magnetic signals at the surface of FV520B steels were measured by a 3D magnetic sensor. It has been concluded that three-dimensional magnetic signals had different detection sensitivity to the defects in different directions, and the defects can be accurately recognized based on the distinctive signal features. Additionally, the peak value of the tangential component and the peak-to-peak value of the normal component (i.e., Bxp and Bzp-p) presented different characteristics in elastic and plastic deformation stages with the increase of applied stress. The amplitude changes of the tangential component and maximum gradient value of the normal component (i.e., ΔBx and KG) were capable of estimating the mechanical damage degree of ferromagnetic materials.

Metal magnetic memory technique used to predict the fatigue crack propagation behavior of 0.45%C steel

Monitoring fatigue crack propagation behavior of ferromagnetic components is very important. In this paper, the tension–tension fatigue tests of center cracked tension (CCT) specimens were carried out; the variation regularity of both tangential and normal components of magnetic signals during fatigue process were investigated. The results showed that the initial abnormal signals which appeared at the notch were reversed after cyclic loading. The abnormal magnetic signals became more significant with the increase of fatigue cycles and reversed again after failure. The characteristic parameters, i.e., the peak value of tangential component, Btp, and maximum gradient value of normal component, Km, showed similar variation trends during the fatigue process, which can be divided into three different stages. An approximate linear relationship was found between the characteristic parameters and fatigue crack length 2a. The feasibility of predicting the fatigue crack propagation using the abnormal magnetic signals was discussed. What's more, the variation and distribution of the magnetic signals were also analyzed based on the theory of magnetic charge.

Seasonal dynamics in capillary filtration of plasma proteins in eastern redfins of the genus Tribolodon (Cyprinidae)

A wide range of the osmotic gradient created by plasma and tissue fluid proteins in relation to the capillary wall in redfins of the genus Tribolodon during an annual cycle was revealed. The maximum gradient values are close to those in mammals. The plasma protein distribution between the intraand extravascular body fluids depends on the annual cycle period in the particular season (spawning and feeding completion) and the barrier properties of the capillary wall (peritoneum, brain, and white muscles). Among the osmotic reflection coefficient values characterizing the barrier properties of the capillary wall, those corresponding to its absolute impermeability were not found. This strategy can be explained by the fact that fish have to sustain the fluctuations in the intravascular fluid volume and its rapid recovery after hypovolemia, as well as by the features of protein metabolism in fish.

Fusion of multiple features to produce a segmentation algorithm for remote sensing images

This letter presents an edge direction adaptive watershed segmentation method for remote sensing images. First, the maximum gradient value among different directions is chosen as the single band gradient value of the pixel, and a compound gradient value is then calculated based on the gradient value in each band. Second, the marker-based watershed segmentation is implemented to produce initial over-segmentation result to avoid under-segmentation. Finally, the adjacent objects with high similarity values are merged to reduce over-segmentation, which improves segmentation accuracy. The performance of the proposed method is validated on two satellite images. Experimental results show that, compared with the multi-resolution segmentation method embedded in the eCognition software and the traditional multi-band watershed segmentation method, the proposed method can decrease over-/under-segmentation and thus produce satisfactory segmentation results.

Kirsch Directional Derivatives Based Shot Boundary Detection: An Efficient and Accurate Method

The segmentation of video into its basic structural unit is an essential step for video content analysis. In this paper, we propose a shot transition detection approach based on Kirsch directional derivatives. The ability of Kirsch operator to capture the maximum gradient value amongst different orientations is explored for the task of shot transition detection. Each frame of a given video is convolved with Kirsch operator in eight orientations and compute first and second order moments. These moments are used as features for shot boundary detection. Experiments are conducted on a subset of TRECVID dataset and comparison is done with some common shot boundary detection algorithms to exhibit the performance of the proposed approach.

Cardiac electrical activity imaging of patients with CRBBB or CLBBB in magnetocardiography

A new method for the imaging of cardiac electrical activity in patients with complete right bundle branch block (CRBBB) or complete left bundle branch block (CLBBB) is investigated using magnetocardiographic recordings of the surface of the body. This is based on the assumption that an equivalent single-current dipole moves along the unblocked bundle branch, whose position in the measurement plane is expressed in terms of the maximum and minimum, as well as the maximum gradient value of the measured magnetic field. The trajectory of the moving dipole on the measurement plane is indicative of the excitation conduction of the CRBBB or CLBBB subject during ventricular depolarization and repolarization, which is deduced by comparing each change between the dipole moment and the maximum current density in a corresponding pseudo-current density map. In summary, this method can distinguish CRBBB from CLBBB subjects by means of the dipole depth and two dipole moment components. The possibility of visualizing the excitation conduction in a CRBBB or CLBBB subject during ventricular depolarization and repolarization is then discussed.

Singularity Detection of Magnetic Memory Signal of Steel-Cord Conveyor Belt

Metal magnetic memory technology was an important method for detecting the steel-cord conveyor belt early fault, characteristics of magnetic memory signal extraction is critical for judging of the conveyor belt failure. Generally using of magnetic memory signal maximum gradient value can quickly judge the stress concentration zone, but the magnetic memory signal is susceptible to effected by environmental and noise; In view of the weak and non-stationary characteristics of magnetic memory signal, this paper has proposed the singularity detection method based on wavelet transform modulus maximum for metal magnetic memory signal, the method could exactly judged the stress concentration zone of joints and located the fault points of the steel-cord belt, the characteristic gradient of magnetic memory signal and the Lipschitz exponent were extracted. The result of simulation indicated the technology was effectively for judging the stress concentration zone and fault point. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.2866

Fully automated gradient based breast boundary detection for digitized X-ray mammograms

Accurate segmentation of the breast from digital mammograms is an important pre-processing step for computerized breast cancer detection. In this study, we propose a fully automated segmentation method. Noise on the acquired mammogram is reduced by median filtering; multidirectional scanning is then applied to the resultant image using a moving window 15×1 in size. The border pixels are detected using the intensity value and maximum gradient value of the window. The breast boundary is identified from the detected pixels filtered using an averaging filter. The segmentation accuracy on a dataset of 84 mammograms from the MIAS database is 99%.

Factors influencing rearfoot kinematics during a rapid lateral braking movement

Understanding the morphological, movement, and biomechanical characteristics that influence rearfoot motion during lateral movements is necessary for footwear design and for the determination of injury mechanisms. The purpose of this study was to identify factors related to rearfoot kinematics during a lateral braking movement. Seven highly skilled male tennis players performed 24 trials of side shuffle movements at various speeds. A rear view of the right leg performing a braking step onto a force platform was filmed. The neutral-O landing style was most commonly demonstrated. Average movement velocity, foot velocity at touchdown, and body mass were variables demonstrating weak or nonsignificant correlations with the rearfoot parameters. Although structural inversion was correlated significantly with the maximum rearfoot angle and velocity (r = -0.52 and -0.69), the results were affected by movement speed and sample size. The biomechanical characteristics displayed the greatest influence on the various rearfoot kinematic parameters. The magnitude of the significant (P less than 0.0001) correlations generally decreased in the following order: maximum horizontal and vertical force gradients, corresponding times to the maximum gradient values, maximum horizontal and vertical forces, and the corresponding times to maximum forces. In conclusion, the gradient-associated parameters were the most useful biomechanical parameters for predicting changes in rearfoot kinematics.

Computerized processing of two-dimensional echocardiograms for the quantification of left ventricular regional contractility.

A new practical method of computer digital image processing of two-dimensional echocardiograms was developed for the quantification of the left ventricular regional contractility. Short axis, cross-sectional images of the left ventricle at the levels of the mitral valve, papillary muscle and apex were recorded by a phased array sector scanner. The echo data recorded on video tape were transfered to a minicomputer through the interface circuits and digitized and processed automatically. Automatic edge detection of the endocardial and epicardial walls was performed by applying sequential steps, including smoothing, dynamic thresholding, region growing and filling small holes. The rationale for edge detection depended upon the assumptions that the abrupt changes of the gray levels occurred at the boundaries and that the points with the maximum gradient values are boundaries of the left ventricular wall. Best-fit contours of endocardial and epicardial edges were drawn by fitting a spline. The short axis cross-sectional left ventricular wall at each level was divided into eight segments, with the center of gravity of enddiastolic left ventricular cavity and the axis connecting this with the posterior end of the right side of the septum being used as the reference point and line. The segmental hemiaxis, area and wall thickness were measured every 33 msec from end-diastole during the cardiac cycle and the systolic percent changes were calculated automatically by a computer. Regional contractility of the left ventricle was evaluated by systolic percent changes of the segmental hemiaxis, area and wall thickness. The measured values in a patient with dilated cardiomyopathy were lower than those of a normal subject, probably reflecting myocardial damage of the left ventricle. Although there are some points to be improved, including a better system for transferring echo data to the computer and the evaluation of the validity of this fixed reference system, it is likely that computer analysis of the short axis cross-sectional echocardiogram of the left ventricle will be useful in a clinical setting.

The maximum-slope method for the interpretation of electrical soundings over two horizontal layers

Using the Carpenter configuration, in which the distances between the successive electrodes of a four-electrode system are kept at r, s and r (as shown in Fig. 1), where r = ma and s = la, or the Wenner-Carpenter configuration, in which r = s, the corresponding formulae for the apparent resistivities ρ A α , ρ A β and ρ A γ for the α, β and γ configurations are used to compute maximum gradient values for various values of the reflection coefficient K. For any observed curve for these resistivity types, the maximum slope is determined. A set of standard curves is presented which, provided that K is known, then allows the thickness of the top layer to be determined. In the case that K is unknown, another set of standard curves is presented allowing determination of K provided that the maximum slopes of any two of the three resistivity curves are known. The method has been tested for both field and laboratory observations. Discrepancies between the observed and actual values of resistivity are noted and attributed partly to instrumental errors.