Matching Speed Research Articles

Parallel optimization of tridimensional deformation measurement based on correlation function constraints of a multi-camera network.

This study primarily investigates the low accuracy and redundant time-consuming problem of speckle registration in the full-field deformation measurement of slender and biggish specimens. To solve these problems, a parallel optimization of the tridimensional deformation measurement method is proposed based on what we believe is a novel correlation function constraints of a multi-camera network. First, a neotype correlation function is built based on the joint constraint relationship among the multiple cameras, which is capable of accurately restricting the search for homologous points in image pairs to the epipolar line, instead of the entire image, while significantly narrowing the search space and accelerating the search. The multiple cameras are bundled as a whole, thus reducing the dimension of the Jacobian matrix and the normalized matrix to a certain extent. Subsequently, more speckle images can be calculated in one iteration. Furthermore, the decomposition of the derived correlation function and the scheme of the parallel algorithm are decomposed via the kernel function based on the GPU parallel mechanism of the compute unified device architecture source program, thus increasing the subpixel search speed of speckle matching and ensuring the calculation performance of the stereo deformation measurement method to reach a higher level. Lastly, the experimental results revealed that the proposed strategy could allow the calculation speed-up ratio of speckle sequence and stereo registration to reach 20.390 times and 17.873 times, respectively, while ensuring the out-of-plane displacement average measuring accuracy to be higher than 0.179mm within the spatial range of [2m, 2m, 3m]. As a result, the proposed approach has crucial applications in rapid and stable tridimensional deformation measurement.

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Abstract. Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds often significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, as of the Weather Research and Forecasting model v4.3.3, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. We simulate a wind plant in pseudo-steady states under idealized stable, neutral, and unstable conditions with matching hub-height wind speeds using two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, average hub-height wind speed losses within the plant differ between PBL schemes by between −0.20 and 0.22 m s−1, and correspondingly, capacity factors range between 39.5 %–53.8 %. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.

Offset-FA: A Uniform Method to Handle Both Unbounded and Bounded Repetitions in Regular Expression Matching.

With the exponential growth of cyber–physical systems (CPSs), security challenges have emerged; attacks on critical infrastructure could result in catastrophic consequences. Intrusion detection is the foundation for CPS security protection, and deep-packet inspection is the primary method for signature-matched mechanisms. This method usually employs regular expression matching (REM) to detect possible threats in the packet payload. State explosion is the critical challenge for REM applications, which originates primarily from features of large character sets with unbounded (closures) or bounded (counting) repetitions. In this work, we propose Offset-FA to handle these repetitions in a uniform mechanism. Offset-FA eliminates state explosion by extracting the repetitions from the nonexplosive string fragments. Then, these fragments are compiled into a fragment-DFA, while a fragment relation table and a reset table are constructed to preserve their connection and offset relationship. To our knowledge, Offset-FA is the first automaton to handle these two kinds of repetitions together with a uniform mechanism. Experiments demonstrate that Offset-FA outperforms state-of-the-art solutions in both space cost and matching speed on the premise of matching correctness, and achieves a comparable matching speed with that of DFA on practical rule sets.

An Improved ASIFT Image Feature Matching Algorithm Based on POS Information.

The affine scale-invariant feature transform (ASIFT) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). However, there are many problems in the matching process, such as the low efficiency and mismatching. In order to improve the matching efficiency, this algorithm firstly simulates image distortion based on the position and orientation system (POS) information from real-time UAV measurements to reduce the number of simulated images. Then, the scale-invariant feature transform (SIFT) algorithm is used for feature point detection, and the extracted feature points are combined with the binary robust invariant scalable keypoints (BRISK) descriptor to generate the binary feature descriptor, which is matched using the Hamming distance. Finally, in order to improve the matching accuracy of the UAV images, based on the random sample consensus (RANSAC) a false matching eliminated algorithm is proposed. Through four groups of experiments, the proposed algorithm is compared with the SIFT and ASIFT. The results show that the algorithm can optimize the matching effect and improve the matching speed.

Detecting logical relationships in mechanical, electrical, and plumbing (MEP) systems with BIM using graph matching

The increasingly complex design has gained difficulty in conducting the rule compliance checking for the Mechanical, Electrical and Plumbing (MEP) system in the design phase. Useful rule-checking systems could contribute to a quicker project delivery time. Currently, an efficient method for checking the logical relationship is still lacking. This study aims to propose an MEP rule checking framework using the subgraph matching technology. First, the MEP components in the BIM model are extracted by utilizing the application programming interface (API), and a graph database is established with point-based and curve-based instances being nodes and relationships, respectively. Second, the graph database is simplified to increase the speed of graph matching. Third, the rules, which regulate how the MEP components should be connected, are represented by a knowledge graph. Finally, rule checking is achieved by comparing the graph database against the knowledge graph, and the critical path in a sub-system is detected by calculating the betweenness centrality. A case study with a rail station is used to evaluate the approach where the overall model checking and rule checking are conducted on the original and simplified graph databases sequentially. The results show that the proposed approach could achieve the rule compliance checking at a high speed, and 6 unconnected instances along with 155 problematic pipe fittings have been found. Besides, the critical path for the selected ACS system is from the water-cooled chiller to the condenser water pump. The proposed framework could help in the overall model checking and rule checking process, improving the efficiency of BIM engineers. This research demonstrates that converting a BIM model into a graph database can benefit conventional BIM analysis methods by incorporating advanced technologies (e.g., artificial intelligence) to enable a more flexible and accurate MEP design process.

Interior Distance Ratio to a Regular Shape for Fast Shape Recognition

A fast shape recognition method based on regular graphic is proposed in this paper. It is the Interior Distance Ratio to a regular Shape (minimum bounding rectangle (MBR) or minimum circumscribed circle (MCC)) (SIDR). Regular shapes themselves have either axisymmetric or origin symmetry, which gives them regularity. Shape, as a feature of an object, plays a significant role in computer vision and image analysis. The shape descriptor is widely used to compute remarkable features of the visual image, especially in image understanding and analysis. SIDR is a new remarkable feature of the shape, which is the distribution of the interior distance between the shape contour points and its minimum bounding rectangle or minimum circumscribed circle. It can provide more effective performance support for practical application fields of computer vision, such as object detection and recognition. The minimum bounding rectangle or minimum circumscribed circle can change according to the change in a shape’s position, scale and direction, which is extremely suitable for describing a shape that has deformation. In addition, the rectangularity and circularity derived from them also have the potential peculiarity to describe the shape feature. Therefore, this paper uses the interior distance ratio of the shape to represent the shape feature. First, the minimum bounding rectangle or minimum circumscribed circle of the shape is selected according to the rectangularity and circularity of the shape. Then, the interior distance proportional distribution from the shape contour point to the minimum bounding rectangle or minimum circumscribed circle is obtained. Finally, a histogram is used to represent the distribution feature, and shape matching and recognition are carried out. A self-built dataset and three international generic datasets are used to verify the validity of the method. The performance exhibits the sophisticated property (accuracy and matching speed) of the proposed method. It is worth mentioning that this simple method has a recognition rate of close to 100% on the self-built dataset and has achieved excellent results for other datasets compared with some international state-of-the-art methods.

Optimal Design of Harvesting Speed and Forward Speed of Harvester Based on Adaptive Control System

The working efficiency of the combine harvester is still very low. It is an important way to realize mechanization to optimize the cutting speed of the harvester and the forward speed of the cutter without increasing economic input. In view of this, the present study briefly summarized the current structure of combine harvester systems. A new type of adaptive control system of combine harvesters was designed from the angle of cutting speed and forward speed of cutter. The sugarcane test base was taken as the test field, and the best matching speed was obtained with the goal of high efficiency of combine harvester and minimum sugarcane damage rate. In the test of cutting speed and forward speed of combine harvester, the optimal cutting speed under different forward speed conditions was recorded. The test results showed that the designed adaptive control system of the combine harvester could control the cutting speed and forward speed of the cutter well. The cutting speed and forward speed adaptive control system can realize the response to the input parameters and meet the design requirements of the harvester. This study can improve the economic benefits of the combine harvester and the quality of the harvested crops.

The pattern speeds of vertical breathing waves

ABSTRACT We measure and compare the pattern speeds of vertical breathing, vertical bending, and spiral density waves in two isolated N-body+SPH simulations, using windowed Fourier transforms over $1 \mbox{$\:{\rm Gyr}$}$ time intervals. We show that the pattern speeds of the breathing waves match those of the spirals but are different from those of the bending waves. We also observe matching pattern speeds between the bar and breathing waves. Our results not only strengthen the case that, throughout the disc, breathing motions are driven by spirals but indeed that the breathing motions are part and parcel of the spirals.

Design of laser scanning binocular stereo vision imaging system and target measurement

Binocular stereo vision is an important scheme of road environment perception for intelligent driving, because it can provide image information and spatial three-dimensional position information. However, binocular stereo matching is often disturbed by the environment, and noise, shadow, light transformation, and so on, will all cause mismatching, therefore it is impossible to carry out accurate 3D reconstruction. In this paper, an active imaging perception and target measurement method combining laser scanning and binocular vision is proposed. The binocular vision structure is used to simulate the human eye's observation of the environment in front of the vehicle. At the same time, through the laser lines scanned to the target, the strong characteristics of binocular matching are provided to enhance the anti-interference of binocular matching, and calculate the three-dimensional point cloud data of the front object according to the binocular stereo vision theory. Firstly, this paper studies the influence of the parameters changing of the system on the accuracy of object depth value in indoor environment, and then selects the most suitable system parameters to carry out three-dimensional reconstruction experiment on the actual target object in indoor environment. Finally, the scene experiment in outdoor environment is carried out. In the outdoor environment, the red spectrum laser equipped in the system can still effectively reconstruct the target surface radian, but there are some limitations due to the limitation of outdoor light intensity. This paper preliminarily summarizes the current structural design and experiment, and further discusses the follow-up research and improvement ideas. Research and experiments show that the laser scanning binocular stereo vision imaging system proposed in this paper has the function of forward target ranging, especially under some bad imaging environment, this method can also effectively match the binocular images, and present the three-dimensional information of the internal details of the target. Under the indoor experimental environment, the minimum relative error is 1.42 % for the target with a distance of about 1.5 m, and in the evening outdoor environment, the minimum the minimum relative error is 0.87 % for the target with a distance of about 3 m. Due to the advantages of laser line intensity feature matching, it can accelerate the speed of binocular matching, and has potential application prospects in autonomous system.

A Star Pattern Recognition Algorithm Based on the Radial Companion-Circumferential Feature

Attitude measurement is an important core technology of vehicle flight. It is of great significance to ensure the vehicle’s accurate orbit entry and orbit change, high-performance flight, reliable ground communication, high-precision ground observation, and successful completion of various space missions. Star sensor is the core component to realize an autonomous attitude measurement of the vehicle. Autonomous star map recognition is a key technology in star sensor technology, and it is also the focus and difficulty of research. When the star sensor enters the initial attitude acquisition mode, according to the algorithm, the star sensor can quickly obtain the initial attitude and enter the normal working mode. This paper proposes a star pattern recognition algorithm based on the radial companion-circumferential feature with a noise compensation code to address the low recognition rate caused by position noise in the process of constructing star patterns in the traditional star pattern recognition algorithm based on the radial feature. In order to solve the problem of slow matching search speed, a maximum matching number algorithm has been innovatively adopted, which can improve the search efficiency in the process of star pattern recognition. Thus, the capacity of the star pattern recognition feature library is effectively reduced, and the stability and recognition rate of the improved star pattern recognition algorithm are further improved. The improved star pattern recognition algorithm first establishes radial and circumferential feature vectors based on the bit vector, then adds the noise compensation code according to the companion star position error, then modifies the radial and circumferential feature vectors, and finally calculates the minimum similarity difference between the feature vector of the star pattern observed by the star sensor and the feature vector of the navigation star in the feature library to obtain the unique star pattern recognition result. The identification star database adopts the maximum matching number algorithm, which can improve the search efficiency, reduce the amount of redundant matching, and shorten the matching time. The simulation results show that even in the presence of star position and magnitude noise, the improved star pattern recognition algorithm with radial companion-circumferential feature maintains a high recognition rate of more than 97 percent, demonstrating that the algorithm’s robustness is superior to other algorithms. The revised method described in this work outperforms the classic triangle algorithm and the radial feature star pattern recognition algorithm without compensation code in terms of algorithm robustness, recognition success rate, and recognition time.

Concept Tree-Based Event Matching Algorithm in Publish/Subscribe Systems

Semantic-based publish/subscribe system has attracted a lot of attention in recent years due to its powerful description ability in message dissemination scenarios. As a key part of semantic-based publish/subscribe systems, event matching needs to understand the semantic meaning of subscriptions, especially the hierarchy of concepts. However, existing event matching algorithms are severely affected by the complexity of concept hierarchy trees, some even cannot run due to high memory occupation. This article proposes an event matching algorithm called CTPS (concept tree-based publish/subscribe system) to address it; specifically, we build subscription indexes on concept hierarchy trees for the first time, employ bit arrays to avoid unnecessary matches, and use faster bit operations to accelerate the matching speed. Experiments show that, compared with previous algorithms, CTPS has less memory occupation and shorter event matching time, and its performance is not sensitive to the height of the concept hierarchy tree.

Backstepping-Sliding Mode Control Combined with Load Torque Neural Network Observer for a Two – Mass System

This paper describes the design and the simulation of a non-linear controller for a two-mass system (TMS) based on the backstepping-sliding mode control combined with a load torque neural network observer. The aim is to control the actual angular speed matching with the angular reference speed. The backstepping-sliding mode controller is designed based on the Lyapunov standard. The proposed neural network can torque estimate to approximate an appropriate value for unknown factors even when it is affected by the bounded disturbance.

Climate matching with the climatchR R package

Climate matching allows comparisons of climatic conditions between different locations to understand location and species range climatic suitability. The approach may be used as part of horizon scanning exercises such as those conducted for invasive species. We implemented the CLIMATCH algorithm into an R package, climatchR. The package allows automated and scripted climate matching exercises across all steps from downloading data to summarizing species climate matches. We also show how climatchR may be used with high-throughput computing to process many species. For example, we were able to calculate climate scores for over 8,000 species in less than 3 days using this package. This automation allows high-throughput processing of species data, a new development for improving the efficiency and speed of climate matching and horizon scanning.

The relationship between energy cost of walking, ankle push-off and walking speed in persons with multiple sclerosis

BackgroundThe energy cost of walking (ECw) is an important indicator of walking dysfunction in persons with multiple sclerosis (PwMS). However, its underlying causes and its relation with ankle push-off and walking speed are not well understood. Research questionWhat is the contribution of ankle push-off and walking speed to increased ECw in PwMS? MethodsTen PwMS with walking limitations and 10 individually gender- and age-matched healthy controls (HC) were included. All participants performed two 6-min walking trials on a treadmill at comfortable walking speed (CWS of PwMS) and fast walking speed (FWS, 130 % of CWS of PwMS). Kinetics and metabolic cost were evaluated. Generalized estimating equations were performed to investigate effects of group and walking speed, and their interaction. Spearman correlations were conducted to examine whether ECw was related to ankle push-off in PwMS, controlling for differences in walking speed in PwMS. ResultsECw at matched walking speed was significantly higher in PwMS compared to HC. Kinetic parameters were not different between the most impaired leg in PwMS and HC at matched walking speed, but asymmetry between both legs of PwMS was observed. At FWS, ECw reduced and ankle push-off increased similarly in both groups. ECw was inversely related to peak ankle power of the most impaired leg in PwMS at CWS. SignificanceSlow walking speed is one factor that contributes to increased ECw in PwMS. Furthermore, PwMS who had a higher ECw showed a lower peak ankle power, independent of walking speed. This indicates that ankle push-off could be a contributor to increased ECw.

Construction of Automatic Matching Recommendation System for Web Page Image Packaging Design Based on Constrained Clustering Algorithm

With the rapid development of artificial intelligence technology, computer vision science has also gained new opportunities. As the foundation of computer vision and numerous artificial intelligence applications, image matching technology has received extensive attention from researchers and companies around the world. However, in web design, the research on the image matching system is not mature enough, which results in a series of problems such that the web design is not beautiful enough, and the figures do not conform to the design theme. Therefore, it is the current trend to deeply study the structure of the automatic matching recommendation system for web page image packaging design. The purpose of this paper is to use the constrained clustering algorithm to study how to construct an automatic matching recommendation system for web page image packaging design. This paper first gives a general introduction to the classification of constrained clustering algorithms. Then, the operation mechanism and model establishment of SURF feature description operator, SIFT feature description operator, and ORB feature description operator are described in detail. Then, through experiments, the matching accuracy of the web page image matching system based on the constrained clustering algorithm and the influence of parameter changes are compared with other algorithms. Finally, a comparative experiment is carried out on the image matching effects of the three feature description operators. The matching speed, noise sensitivity, and rotation type experiments are introduced respectively. By constructing the web page image packaging design of the constrained clustering algorithm to automatically match the algorithm model of the recommender system and experimenting with the model, the advantages of the constrained clustering algorithm in the model construction are proved. The experimental results show that the constrained clustering algorithm has higher image matching efficiency and matching accuracy, and the accuracy of image feature extraction is better than other algorithms. However, when the network structure division attribution threshold is ϕ = 0.4 , the clustering performance of the constrained clustering algorithm is better. Compared with the parameter 100, when the parameter is 500 and 1000, the accuracy of the constrained clustering algorithm can be improved, and the calculation accuracy is increased by 0.317.

3D Reconstruction Method based on Medical Image Feature Point Matching.

Medical 3D image reconstruction is an important image processing step in medical image analysis. How to speed up the speed while improving the accuracy in 3D reconstruction is an important issue. To solve this problem, this paper proposes a 3D reconstruction method based on image feature point matching. By improving SIFT, the initial matching of feature points is realized by using the neighborhood voting method, and then the initial matching points are optimized by the improved RANSAC algorithm, and a new SFM reconstruction method is obtained. The experimental results show that the feature matching rate of this algorithm on Fountain data is 95.42% and the matching speed is 4.751 s. It can be seen that this algorithm can shorten the reconstruction time and obtain sparse point clouds with more reasonable distribution and better reconstruction effect.

Fast Shape Recognition via the Restraint Reduction of Bone Point Segment

In computer science, and especially in computer vision, the contour of an object is used to describe its features; thus, the shape descriptor plays an indispensable role in target detection and recognition. Further, Fourier is an important mathematical description method, and the Fourier transform of a shape contour has symmetry. This paper will demonstrate the symmetry of shape contour in the frequency domain. In recent years, increasing numbers of shape descriptors have come to the fore, but many descriptors ignore the details of shape. It is found that the most fundamental reason affecting the performance of shape descriptors is structural restraints, especially feature structure restraint. Therefore, in this paper, the restraint of feature structure that intrinsically deteriorates recognition performance is shown, and a fast shape recognition method via the Bone Point Segment (BPS) restraint reduction is proposed. An approach using the inner distance to find bone shapes and segment the shape contour by these bones is proposed. Then, Fourier transform is performed on each segment to form the shape feature. Finally, the restraints of the shape feature are reduced in order to build a more effective shape feature. What is commendable is that its discriminability and robustness is strong, the process is simple, and matching speed is fast. More importantly, the experiment results show that the shape descriptor has higher recognition accuracy and the matching speed runs up to more than 1000 times faster than the existing description methods like CBW and TCD. More importantly, it is worth noting that the recognition accuracy approaches 100% in the self-build dataset.

Investigation and implementation for forming lead screw by through-feed rolling process with active rotation

A through-feed rolling process with active rotation for manufacturing lead screw has been developed, where the speed matching and stable motion between workpiece and the rolling die during the whole rolling process can be ensured. Its process control, die structure and rolling equipment are relatively simple, and the accuracy of pitch for rolled lead screw can be effectively ensured. The motion characteristic during through-feed rolling process was analyzed, and then the general design criteria for the die were set up. The feasibility of the through-feed rolling process with active rotation was verified by experiment and finite element method (FEM). The verified results indicated that the error of lead-screw pitch between experimental value and designed value is about 0.125 %, and the error between the FEM value and the experimental and designed values is less than 1 %. According to the deformation characteristics of lead screw rolling and the distribution of field variables, the workpiece can be divided into non-deformation zone, entry-angle zone (incremental forming zone), correction zone, exit-angle zone, and full-formed zone. The same position of workpiece will undergo those five forming states in turn. The FEM results indicated that the effective stress and effective strain both gradually increase from the entry-angel zone to the correction zone, and the strain in the exit-angle zone and full-deformed zone are almost quite; the effective stress and effective strain in thread root are larger, and both gradually decrease along thread flank to thread crest; the distributions of stress and strain have a certain periodicity along the axial direction. The results in this study provide a basis for high-efficiency and precise rolling forming of threaded parts with large diameter such as the lead screw.

Structural design and dynamics optimization for heald frame made by carbon fiber reinforced composites

For improving the performance defects of traditional heald frame, the carbon fiber reinforced composites was applied to technical upgrading of the heald frame. On the basis of the theory analysis of composites laminates, the symmetrical ply scheme suitable for manufacturing of the heald frame in overall laminated was constructed, and a type of parametric program for finite element modeling was developed by ANSYS Parametric Design Language (APDL). The optimal mathematical model of the composites heald frame was proposed, and then the thickness parameter ( t) and direction parameters (α, θ) of fiber layer were dynamic optimized by using of Sub-problem method. The work increased the fundamental frequency (ω1) of the heald frame by 10.38%. Besides, the harmonic response frequency was also increased from 48.41 Hz to 53.77 Hz, which conductive to further improve dynamics properties of the composites heald frame. This paper provides technical guidance for innovative design of new heald frame, and is helpful to solve the problem of speed matching between heald frame and high-speed loom.

Photonic sampling analog-to-digital conversion based on time and wavelength interleaved ultra-short optical pulse train generated by using monolithic integrated LNOI intensity and phase modulator.

High-speed analog-to-digital conversion (ADC) is experimentally demonstrated by employing a time and wavelength interleaved ultra-short optical pulse train to achieve photonic sampling and using wavelength division demultiplexing to realize speed matching between the fast optical front-end and the slow electronic back-end. The sampling optical pulse train is generated from a cavity-less ultra-short optical pulse source involving a packaged device that monolithically integrates an intensity modulator and a phase modulator into a chip based on lithium niobate on insulator (LNOI). In the experiment, the fiber-to-fiber insertion loss of the packaged modulation device is measured to be 6.9 dB. In addition, the half-wave voltages of the Mach-Zehnder modulator and the phase modulator in the LNOI-based modulation device are measured to be 3.6 V and 3.4 V at 5 GHz, respectively. These parameters and the device size are superior to those based on cascaded commercial devices. Through using the packaged modulation device, two ultra-short optical pulse trains centered at 1541.40 nm and 1555.64 nm are generated with time jitters of 19.2 fs and 18.9 fs in the integral offset frequency range of 1 kHz to 10 MHz, respectively, and are perfectly time interleaved into a single pulse train with a repetition rate of 10 GHz and a time jitter of 19.8 fs. Based on the time and wavelength interleaved ultra-short optical pulse train, direct digitization of microwave signals within the frequency range of 1 GHz to 40 GHz is demonstrated by using a two-channel wavelength demultiplexing photonic ADC architecture, where the effective number of bits are 5.85 bits and 3.75 bits for the input signal at 1.1 GHz and 36.3 GHz, respectively.