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Motion object detection (MOD) with freely moving cameras is a challenging task in computer vision. To extract moving objects, most studies have focused on the difference in motion features between foreground and background, which works well for dynamic scenes with relatively regular movements and variations. However, abrupt illumination changes and occlusions often occur in real-world scenes, and the camera may also pan, tilt, rotate, and jitter, etc., resulting in local irregular variations and global discontinuities in motion features. Such complex and changing scenes bring great difficulty in detecting moving objects. To solve this problem, this paper proposes a new MOD method that effectively leverages local and global visual information for foreground/background segmentation. Specifically, on the global side, to support a wider range of camera motion, the relative inter-frame transformations are optimized to absolute transformations referenced to intermediate frames in a global form after enriching the inter-frame matching pairs. The global transformation is fine-tuned using the spatial transformer network (STN). On the local side, to address the problem of dynamic background scenes, foreground object detection is optimized by utilizing the pixel differences between the current frame and the local background model, as well as the consistency of local spatial variations. Then, the spatial information is combined using optical flow segmentation methods, enhancing the precision of the object information. The experimental results show that our method achieves a detection accuracy improvement of over 1.5% compared with the state-of-the-art methods on the datasets of CDNET2014, FBMS-59, and CBD. It demonstrates significant effectiveness in challenging scenarios such as shadows, abrupt changes in illumination, camera jitter, occlusion, and moving backgrounds. [ABSTRACT FROM AUTHOR]

In existing adaptive neural control approaches, only when the regressor satisfies the persistent excitation (PE) or interval excitation (IE) conditions, the constant optimal weights of neural network (NN) can be identified, which can be used to establish uncertainties in nonlinear systems. This paper proposes a novel composite learning approach based on adaptive neural control. The focus of this approach is to make the NN approximate uncertainties in nonlinear systems quickly and accurately without identifying the constant optimal weights of the NN. Hence, the regressor does not need to satisfy the PE or IE conditions. In this paper, regressor filtering scheme is adopted to generate prediction error, and then the prediction error and tracking error simultaneously drive the update of NN weights. Under the framework of Lyapulov theory, the proposed composite learning approach can ensure that approximation error of the uncertainty and tracking error of the system states converge to an arbitrarily small neighborhood of zero exponentially. The simulation results verify the effectiveness and advantages of the proposed approach in terms of fast approximation. [ABSTRACT FROM AUTHOR]

The µW‐level power density of flexible piezoelectric energy harvesters (FPEHs) restricts their potential in applications related to high‐power multifunctional wearable devices. To overcome this challenge, a hierarchical design strategy is proposed by forming porous piezoceramics with an optimum microstructure into an ordered macroscopic array structure to enable the construction of high performance FPEHs. The porous piezoceramic elements allows optimization of the sensing and harvesting Figure of merit, and the array structure causes a high level of effective strain under a mechanical load. The introduction of a network of polymer channels between the piezoceramic array also provides increased device flexibility, thereby allowing the device to attach and conform to the curved contours of the human body. The unique hierarchical piezoceramic array architecture exhibits superior flexibility, a high open circuit voltage (618 V), high short circuit current (188 µA), and ultrahigh power density (19.1 mW cm−2). This energy density value surpasses previously reported high‐performance FPEHs. The ultrahigh power flexible harvesting can charge a 0.1 F supercapacitor at 2.5 Hz to power high‐power electronic devices. Finally, the FPEH is employed in two novel applications related to fracture healing monitoring and self‐powered wireless position tracking in extreme environments. [ABSTRACT FROM AUTHOR]

In this study, uniaxial compressive tests combined with the digital image correlation (DIC) method are used to investigate the mechanical properties, fracture process, and failure pattern of sandstone containing a circular inclusion. A DIC‐based methodology is proposed to quantitatively explain the crack initiation and propagation mechanism. The identification criterion of crack type is presented based on the nature of cracks and the development trends of relative displacement. Three crack types, including tensile cracks, tensile–shear cracks, and shear cracks, with different cracking mechanisms are identified. The inhibitory effect of the inclusions on crack initiation and propagation is revealed. The inclusion–matrix debonding mechanism is further investigated, and it is found that the inclusion interface consists of tensile concentration zones on the left/right sides and compressive concentration zones on the top/bottom sides. The tensile concentration zone is the main reason for debonding of the inclusions from the sandstone matrix. Highlights: The effect of an inclusion on opening‐containing sandstones is studied.A DIC‐based method to directly identify rock cracking properties is proposed.The crack types of the specimens under different filling conditions are identified.The inclusion–matrix debonding mechanism is quantitatively investigated. [ABSTRACT FROM AUTHOR]

The effects of different solar radiation intensities, heat flow density of indoor heat sources, outdoor wind speed, and the relative location of indoor heat sources on the natural ventilation performance of solar chimneys are investigated through three-dimensional numerical simulations. The mechanism of the mutual coupling of the solar chimney effect with the outdoor wind and indoor heat source heat plume is explored. The results of the study show that when the structural parameters of the solar chimney are the same, the heat flow density on the surface of the indoor heat source, the outdoor wind speed and the solar radiation intensity all have a gaining effect on the ventilation performance of the solar chimney and the effects of the three on the ventilation of the solar chimney promote each other, when the solar radiation intensity is 200 W/m2, the outdoor wind speed is 1.0 m/s, and the indoor heat source heat flow density increases from 0 to 1 500 W/m2, the solar chimney ventilation volume increases from 0.393 m3/s to 0.519 m3/s, the maximum value of the increase is 32.1%. In the other two cases, the maximum increase in solar chimney ventilation is 176.7% and 33.1%, respectively. Under the same conditions, solar chimney ventilation is optimal when the heat source is in the middle of the room. The presence of outdoor wind, however, affects the optimum design parameters of the solar chimney. Compared to the case where no outdoor wind is taken into account, the optimum inlet width of 0.2–0.3 m for the solar chimney no longer applies with outdoor wind, with the optimum value rising to 0.5 m. [ABSTRACT FROM AUTHOR]

Red soil is widely distributed in South America, Africa and Southeast Asia (approximately between the 30° S and 30° N latitudes). These soils are typically formed by the weathering of carbonate or other rocks rich in iron and aluminium oxides in hot-humid climates and susceptible to a large reduction in disintegration upon wetting or other conditions. This paper provides a state-of-the-art review on the red soil disintegration mechanism and intergranular suction with reference to red soil. The present paper reviews the research progress that has been made regarding the disintegration characteristics and testing methods of the intergranular suction of red soil, including (1) influencing factors of disintegration and the mechanism of action, (2) advantages and disadvantages of each intergranular suction testing method and (3) the intrinsic relationship between disintegration and intergranular suction. The study indicated that the research on the disintegration mechanism of red soil is still in the macro stage, involving the different moisture contents, temperatures and other directly influential conditions. Soil disintegration characteristics have not been extensively analysed from the micro perspective (including pore structure and distribution, fracture development degree and particle arrangements). When these problems are solved, disintegration studies of red soil will be advanced. Some limitations of the previous research are highlighted at the end of the paper, and suggestions are made for future research. [ABSTRACT FROM AUTHOR]

The organic flash cycle (OFC) is a novel power cycle with small exergy loss in the endothermic process. However, the low-pressure throttle valve in the cycle has a large throttling loss. Aiming to reduce the cycle exergy loss and improve the system performance, this study constructs a new configuration named the organic flash Rankine cycle (OFRC). Using the R600/R245fa mixture as the circulating working fluid and 200 °C geothermal water as the heat source, the effects of the change in working fluid composition on the thermal properties of the OFRC were studied based on the first and second laws of thermodynamics. Then, the economic performance of the proposed OFRC was investigated and then compared with that of the conventional OFC. The results show that the OFRC system has a significant improvement in thermal performance and economy compared with the OFC system. When the mole composition of the R600/R245fa mixture is 0.5/0.5, the net output work, thermal efficiency, and exergy efficiency of the OFRC system can reach a maximum at 146.39 kW, 21.51%, and 80.94%, respectively, which are 98.2 kW, 14.43%, and 54.3% higher than those of the OFC system. The dual heaters in the OFRC system can effectively reduce loss in the endothermic process. When the R600 mole composition is 0.5 in the OFRC system, the exergy loss of the heater is only 7.42%, and the power generation cost (0.3267 $·kW−1·h−1 only) is lower than that in the OFC system. [ABSTRACT FROM AUTHOR]

Identifying clusters, namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. By means of a lumped Markov chain model of a random walker, we propose two novel ways of inferring the lumped markov transition matrix. Furthermore, some useful results are proposed based on the analysis of the properties of the lumped Markov process. To find the best partition of complex networks, a novel framework including two algorithms for network partition based on the optimal lumped Markovian dynamics is derived to solve this problem. The algorithms are constructed to minimize the objective function under this framework. It is demonstrated by the simulation experiments that our algorithms can efficiently determine the probabilities with which a node belongs to different clusters during the learning process and naturally supports the fuzzy partition. Moreover, they are successfully applied to real-world network, including the social interactions between members of a karate club.

Finger-vein verification is an emerging biometrics technology. Its first task is extracting finger-vein patterns. Although existing algorithms can extract most finger-vein patterns robustly, some branch of these patterns always breaks, which leads to adverse effects for features extraction and matching. In this paper, a Direction-Variance-Boundary Constraint Search (DVBCS) model is presented to restore the broken finger-vein patterns. At the beginning, endpoints of broken finger-vein branches are located. Then, a direction constraint for searching candidate point set is demonstrated. Following the second stage, an optimal target point is selected from the candidate point set according to a minimum within-cluster variance criterion. Eventually, the boundary constraint and variance constraint are introduced as the termination conditions. Experimental results illustrate that, while maintaining low segmentation error, the proposed method can restore above 10% lost target points. Moreover, the equal error rate of finger-vein recognition is reduced from 0.57% to 0.29% when using the proposed method to restore finger-vein patterns. [ABSTRACT FROM AUTHOR]

Objective Detecting moving targets in moving camera environments from video stream is a fundamental step in many computer vision applications, such as intelligent visual surveillance, human-machine interaction, and content-based video coding. Background subtraction is generally regarded as an effective method for extracting foreground objects. Given the existence of extensive literature regarding background subtraction, most existing methods assume a stationary camera. This assumption limits the applicability of these methods to moving camera scenarios. Background is a complex environment that usually includes distracting motions, which make the task more challenging. In addition, with the development of coding techniques, high-definition videos have become widely used. Thus, extracting and updating background images become complex and time-consuming processes. To solve this problem, a fast target detection method is proposed on the basis of V motion vectors. Method The data format and decoding features of surveillance videos are analyzed in this study. Subsequently, methods by which to obtain motion vectors directly from a video stream are determined, and results confirm the method validity by comparing the motion vectors extracted through this method with those extracted using the H. 264 Visa business software. Moreover, the motion vectors are normalized by considering the reference frames, thus preventing the emergence of singular motion vectors and making the distribution of the motion vectors more reasonable. Global motion is detected according to 3σ theory, and different compensation algorithms are proposed for various scenarios. Finally, targets are extracted by analyzing the statistical property of motion vectors. Result Detecting moving targets from a moving camera is difficult. For conventional methods, moving background is not always considered, and systems that have a delayed response to background changes are unsuitable for this situation. To meet the real-time performance requirements of the system, motion vectors are used to detect global motion and extract motion targets, thus reducing redundant computation effectively. Test results show that the proposed method is superior to conventional methods. Conclusion To prove the validity of this algorithm, an extensive set of experiments are performed, and the proposed method is compared with some of the most recent approaches in the field by using publicly available datasets and a new annotated dataset. Results prove that the proposed approach can effectively extract high-speed moving targets from a moving camera. [ABSTRACT FROM AUTHOR]

An improved Harris corner detection algorithm is proposed based on Barron operator, since Harris corner detection algorithm has a poor accuracy in positioning complex corner detection and may miss certain real corners. Firstly, the image gradient is calculated by using Barron operator to reduce the calculation errors from Prewitt operator or Sobel operator. Secondly, the centre B-spline function is used to smooth image, filter noise, and retain the corners information better. Thirdly, a non-maximal inhibition and corners sieving method is used to determine whether the detected corners are real corners or not. A square window is centered at the pixel and eliminate the corner if the value of the corner response function is non-maximal in the window. And then divide the test image into several blocks so as to process each block independently, and use a cyclic iterative method to determine the threshold value to make sure that the real corners are accurately selected. Finally, experiments indicate the algorithm has relatively great noise proof ability and is able to extract complex corners effectively. [ABSTRACT FROM AUTHOR]

Abstract: One-dimensional α-MnO2 nanorods were fabricated by using low-temperature water-bathing chemical precipitation method at 80 °C. The crystalline structures, morphological evolution process and microwave absorption properties were systematically investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and measurement of electromagnetic parameters. The results show that the morphological structures and electromagnetic properties have close relationship with the reaction time. With the prolonging of the treatment time, the as-synthesized products turn from microspheres constituted of tiny dendrites to nanorods with diameters of 20–30 nm and lengths up to 1–2 μm. The electromagnetic characterization shows that the dielectric constants and magnetic permeability values show decreasing trends with the increasing frequency, however, the dielectric and magnetic loss tangents all increase with frequency. The electromagnetic absorption properties of the products have close relationship with the morphologies and thicknesses of the samples. With a thickness of 3 mm, an absorbing peak value of −25 dB was achieved for the sample treated for 24 h. The microwave absorption properties of MnO2 can be attributed mainly to interfacial polarization, space charge polarization and relaxation phenomena. [Copyright &y& Elsevier]

In this paper, an algorithm for smoke region of focus (ROF) detection based on surveillance video is proposed in order to solve the problem of limited application in scenes range and imaging environment of the traditional smoke detection algorithm. The frog vision perception model is used in this algorithm. First the suspect regions are detected, and then the static and the dynamic features of the regions are chosen for the smoke ROF detection. Experimental results show that the algorithm is efficient and significant for improving the operational rate of the detection. [ABSTRACT FROM AUTHOR]

Abstract: According to tunnel structure around joints, tunnel longitudinal deformation is analyzed and a three-dimensional finite element model is built based on segment dislocation mode. Tunnel structure stress analysis is conducted from two aspects of segment in the shear and bolt in the tension. The analysis results show: (1) Segment shear model. When segment dislocation reaches 0.03mm, the principal stressσ1 exceeds 3.0Mpa which is over concrete''s tensile strength. Therefore, when convex tenon and concave tenon generate shear, there must be horizontal slipping and bolt is tensioned. (2) Bolt tension model. When joint opening value reaches 2mm, bolt stress exceeds 640Mpa, which is bolt''s yield strength. When joint opening value reaches 6mm, which is the waterproof control standard for tunnel, bolt stress reaches 688.7Mpa, which is less than bolt''s failure strength. The subway tunnel''s structure safety should be controlled from the perspective of waterproof. [Copyright &y& Elsevier]

Abstract: Analysis the aerodynamic performance to concave building section through numerical simulation calculation, adopt two different turbulence models: Standard kɛ−& Realizable k ɛ − to simulate calculate the shape factor of the section from different wind angle, comparing with standard value in order to investigate the applicability of turbulence models for numerical simulation of blunt body flow around, and analysis the structure of flow field. Finally, get the wind environment characteristic of the section at different wind angle, and calculate to get the shape coefficients of the section at specific wind angle. [Copyright &y& Elsevier]

Abstract: The aerodynamic performance of wind turbine airfoils was an important foundation for the aerodynamic design and the performance analysis of the wind turbine. The method of numerical simulation was used in this paper, and the aerodynamic performance of NACA0018 wind turbine airfoil was analyzed, then the lift and drag coefficient of the airfoil under different turbulence models were discussed and compared with the experimental data. The applicability of the turbulence models for the different airfoils’ numerical simulation was investigated, and the flow field structure was analyzed. The calculation results provided a reference for the research and development of wind turbine airfoils. [Copyright &y& Elsevier]