Quantifying tidal expiratory flow limitation using a vector-based analysis technique

Objective: Tidal expiratory flow limitation (EFLT) is commonly identified by tidal breaths exceeding the forced vital capacity (FVC) loop. This technique, known as the Hyatt method, is limited by the difficulties in defining the FVC and tidal flow-volume (TV) loops. The vector-based analysis (VBA) technique described and piloted in this manuscript identifies and quantifies EFLT as tidal breaths that conform to the contour of the FVC loop. Approach: The FVC and TV loops are interpolated to generate uniformly spaced plots. VBA is performed to determine the smallest vector difference between each point on the FVC and TV curves, termed the flow reserve vector (FRV). From the FVC point yielding the lowest FRV, the tangential angles of the FVC and TV segments are recorded. If the TV and FVC loops become parallel, the difference between the tangential angles tends towards zero. We infer EFLT as parallel TV and FVC segments where the FRV is <0.1 and the tangential angle is within ±18 degrees for ≥5% of TV. EFLT is quantified by the percent of TV loop fulfilling these criteria. We compared the presence and degree of EFLT at rest and during peak exercise using the Hyatt method and our VBA technique in 25 healthy subjects and 20 subjects with moderate-severe airflow obstruction. Main results: Compared to the Hyatt method, our VBA technique reported a significantly lower degree of EFLT in healthy subjects during peak exercise, and in obstructed subjects at rest and during peak exercise. In contrast to the Hyatt method, our VBA technique re-classified five subjects (one in the healthy group and four in the obstructed group) as demonstrating EFLT. Significance: Our VBA technique provides an alternative approach to determine and quantify EFLT which may reduce the overestimation of the degree EFLT and more accurately identify subjects experiencing EFLT.

Design and ARM-Based Implementation of Bitstream-Oriented Chaotic Encryption Scheme for H.264/AVC Video

In actual application scenarios of the real-time video confidential communication, encrypted videos must meet three performance indicators: security, real-time, and format compatibility. To satisfy these requirements, an improved bitstream-oriented encryption (BOE) method based chaotic encryption for H.264/AVC video is proposed. Meanwhile, an ARM-embedded remote real-time video confidential communication system is built for experimental verification in this paper. Firstly, a 4-D self-synchronous chaotic stream cipher algorithm with cosine anti-controllers (4-D SCSCA-CAC) is designed to enhance the security. The algorithm solves the security loopholes of existing self-synchronous chaotic stream cipher algorithms applied to the actual video confidential communication, which can effectively resist the combinational effect of the chosen-ciphertext attack and the divide-and-conquer attack. Secondly, syntax elements of the H.264 bitstream are analyzed in real-time. Motion vector difference (MVD) coefficients and direct-current (DC) components in Residual syntax element are extracted through the Exponential-Golomb decoding operation and entropy decoding operation based on the context-based adaptive variable length coding (CAVLC) mode, respectively. Thirdly, the DC components and MVD coefficients are encrypted by the 4-D SCSCA-CAC, and the encrypted syntax elements are re-encoded to replace the syntax elements of the original H.264 bitstream, keeping the format compatibility. Besides, hardware codecs and multi-core multi-threading technology are employed to improve the real-time performance of the hardware system. Finally, experimental results show that the proposed scheme, with the advantage of high efficiency and flexibility, can fulfill the requirement of security, real-time, and format compatibility simultaneously.

Change Capsule Network for Optical Remote Sensing Image Change Detection

Change detection based on deep learning has made great progress recently, but there are still some challenges, such as the small data size in open-labeled datasets, the different viewpoints in image pairs, and the poor similarity measures in feature pairs. To alleviate these problems, this paper presents a novel change capsule network by taking advantage of a capsule network that can better deal with the different viewpoints and can achieve satisfactory performance with small training data for optical remote sensing image change detection. First, two identical non-shared weight capsule networks are designed to extract the vector-based features of image pairs. Second, the unchanged region reconstruction module is adopted to keep the feature space of the unchanged region more consistent. Third, vector cosine and vector difference are utilized to compare the vector-based features in a capsule network efficiently, which can enlarge the separability between the changed pixels and the unchanged pixels. Finally, a binary change map can be produced by analyzing both the vector cosine and vector difference. From the unchanged region reconstruction module and the vector cosine and vector difference module, the extracted feature pairs in a change capsule network are more comparable and separable. Moreover, to test the effectiveness of the proposed change capsule network in dealing with the different viewpoints in multi-temporal images, we collect a new change detection dataset from a taken-over Al Udeid Air Basee (AUAB) using Google Earth. The results of the experiments carried out on the AUAB dataset show that a change capsule network can better deal with the different viewpoints and can improve the comparability and separability of feature pairs. Furthermore, a comparison of the experimental results carried out on the AUAB dataset and SZTAKI AirChange Benchmark Set demonstrates the effectiveness and superiority of the proposed method.

Spectral Stability Conditions for an Explicit Three-Level Finite-Difference Scheme for a Multidimensional Transport Equation with Perturbations

We study difference schemes associated with a simplified linearized multidimensional hyperbolic quasi-gasdynamic system of differential equations. It is shown that an explicit two-level vector difference scheme with flux relaxation for a second-order hyperbolic equation with variable coefficients that is a perturbation of the transport equation with a parameter multiplying the highest derivatives can be reduced to an explicit three-level difference scheme. In the case of constant coefficients, the spectral condition for the time-uniform stability of this explicit three-level difference scheme is analyzed, and both sufficient and necessary conditions for this condition to hold are derived, in particular, in the form of Courant type conditions on the ratio of temporal and spatial steps.

Comparative application of photogrammetry, handmapping and android smartphone for geotechnical mapping and slope stability analysis

With increasing awareness of geotechnical risks in civil and mining structures, taking advantage of smartphone technology to study rocky slopes can play a key role in the development of safe and economical structures for human welfare. In Malawi, there is a research gap on application of portable devices to collect geotechnical data. Geological engineers still use the unsafe tedious handmapping technique to collect geotechnical data. A road cut that experiences frequent rockfall is used as a case study to investigate if there is a role for smartphones in geotechnics by comparing set statistics of data clusters collected through photogrammetry, smartphone and clar inclinometer. Besides low cost, smartphone’ data capture speed is faster than clar inclinometer. Stereographic and kinematic analysis shows that the 75° dipping road cut is predominantly prone to wedge failure with minor planar failure. For slope stability, Q-slope suggests a new slope angle of 60–66°. An acceptable tolerance limit or error between handmapping and remote data capture systems should be less than ±15°. Set analysis on 111 comparable data points gave a maximum pole vector difference of 10.5°, with the minimum having a difference of 4.8°. For dip, the standard deviations vary from 4.9 to 9.5°, while their mean values vary from −2 to 2.75°. For dip directions, the standard deviations vary from 3.2 to 4.3°, while their mean values vary from −6 to 0.75°. Therefore, android smartphones have a role in geotechnics due to their allowable orientation errors, which show less variance in measured dip/dip direction.

Identifying The Key Variables for Assessing The Reclamation Success on Early Growth Vegetation in Ex-exploration of Oil and Gas Mining Areas

This paper examines the identification of key indicators that could be used to measure the success of reclamation plants in post-exploration oil and gas mining areas. The main objective of this research was to find key indicators or variables for evaluating the level success of reclamation results in the post-mining of oil and gas area. In this study, 44 environmental variables of the physical, biological, soil, water and air indicators were analyzed from 70 field plots of 6 reclamation and 2 natural forest sites. The analysis methods included (1) cluster analysis using the Agglomerative Hierarchical Clustering method with the Ward's method, and (2) quadratic discriminant analysis. The results of the clustering analysis showed that there were some clusters due to variation of biomass, water, soil and air conditions. The three clusters developed based on water and/or air variables provided high cophenetic correlation (0.80) with low within-cluster (14.5%) and high between-cluster variations (85.5%). Based on the multicollinearity analysis, average vector difference test, variance matrix variance test, unidimensional test of each variable and quadratic discriminant function, this study found that there were 3 key indicators determining variations of the quality of the reclamation plantations within the study sites, namely, biological indicator of biomass volume (Bio_B); soil indicator of P content in the soil (Tnh_P), saturation base of soil (Tnh_Kb), Manganese (Mn) content in the soil (Tnh_Mn), Sulfur content in the soil (Tnh_S), percentage of ash in the soil (Tnh_Ab), percentage of clay in the soil (Tnh_Li), and water indicator of chloride content in the surface water (Air_Cl). The examination on four classes of the reclamation quality showed that the classes were successfully classified having excellent cross-validation error matrix with overall accuracy more than 90%.

VECTOR-DIFFERENCE TEXTURE SEGMENTATION METHOD IN TECHNICAL AND MEDICAL EXPRESS DIAGNOSTIC SYSTEMS

The study shows the need for express systems, in which it is necessary to perform the analysis of texture images in various areas of diagnosis, for example, in medical express diagnostics of dermatologic disorders. Since the reliability of decision-making in such systems depends on the quality of image segmentation, which, as a rule, have the nature of spectral-statistical textures, it is advisable to develop methods for segmentation of such images and models for their presentation. A model of spectral-statistical texture is proposed, which takes into account the random nature of changes in the field variations and quasi-harmonics. On its basis, a vector-difference method of texture segmentation has been developed, which is based on the vector transformation of images of spectral and statistical textures based on vector algebra. The stages of the vector-difference method are the following: an evaluation of the spectral texture feature; an evaluation of the statistical texture feature; vector-difference transformation of texture images; a boundary detection of the homogeneous regions. For each pixel of the image in the processing aperture, the features of the spectral and statistical texture are evaluated. Statistical texture evaluation was performed by the quadratic-amplitude transformation. At the stage of vector-difference transformation of texture images, a vector of features of each pixel of an image is constructed, the elements of which are estimates of features of a spectral and statistical texture, and the modulus of the difference of two vectors is calculated. At the stage of boundary detection of homogeneous regions, Canny method was applied. The developed vector-difference texture segmentation method was applied both to model images of spectral-statistical texture and to texture images obtained in technical and medical diagnostics systems, namely, for images of psoriasis disease and wear zones of cutting tools. To compare the segmentation results, frequency-detector and amplitude-detector methods of texture segmentation were applied to these images. The quality of segmentation of homogeneous textured regions was evaluated by the Pratt's criterion and by constructing a confusion matrix. The research results showed that the developed vector-difference texture segmentation method has increased noise tolerance at a sufficient processing speed.