Average Matching Research Articles

Robotic Arm Control System Based on AI Wearable Acceleration Sensor

The position of mechanical arm in people’s life is getting higher and higher. It replaces the function of human arm, moving and moving in space. Generally, the structure is composed of mechanical body, controller, servo mechanism, and sensor, and some specified actions are set to complete according to the actual production requirements. The manipulator has flexible operation, good stability, and high safety, so it is widely used in industrial automation production line. With the development of science and technology, many practical production requirements for the function of the manipulator are more and more refined, especially in the high-end research field. For example, medical devices, automobile manufacturing, deep-sea submarines, and space station maintenance put forward higher requirements for it. In terms of miniaturization and precision, it can meet the needs of scientific research and actual production. But these are inseparable from the motion control system technology. This paper mainly introduces the research of manipulator control system based on AI wearable acceleration sensor, aiming to provide some ideas and directions for the research of wearable manipulator. This paper presents the research method of manipulator control system based on AI wearable acceleration sensor, including the establishment of manipulator kinematics model, common filtering algorithm, and PI algorithm of speed control system. It is used for the research and experiment of manipulator control system based on AI wearable acceleration sensor. The experimental results show that the average matching rate of the manipulator control system based on AI wearable acceleration sensor is as high as 88.89%, and the stability of the feature descriptor is high.

A turning point-based offline map matching algorithm for urban road networks

Offline map matching is a crucial step to facilitate many trajectory-based services in urban areas by finding vehicles’ travel paths from recorded and stored trajectory data. This paper proposes a novel turning point-based offline map matching algorithm, which introduces the concept of vehicle turning points to implement map matching piecewisely. The algorithm first separates the entire trajectory into multiple sub-trajectories using the identified turning points. It then selects the best-matched path for each sub-trajectory from the corresponding K-shortest paths. Extensive experiments are conducted to compare the performance of our algorithm with five state-of-the-art map matching algorithms in terms of four different criteria, including one correctly matched criterion, two incorrectly matched criteria, and one computation time-related criterion. Experimental results show that our algorithm has the best average matching accuracy and efficiency at different sampling intervals. Specifically, compared with the five benchmark algorithms, our algorithm can improve the correctly matched percentages by 1.43% to 34.66%, reduce the incorrectly matched percentages by 15.23% to 56.79%, and improve the matching speeds by 3.16–61.01 times.

Visual validation of the appearance of chromatic objects rendered from spectrophotometric measurements.

We validate a physically based and spectral rendering framework with improved color reproduction. With a recently developed model, we take into account both the colorimetric specifications of the rendering display as well as the spectral and angular characteristics of lighting and also the spectral reflectance of the objects. Therefore, it should provide much better color reproduction than those based on the common standard red, green, blue (sRGB) color space. In addition, it allows real-time rendering on modest hardware and displays. We evaluated the color reproduction of the new rendering framework by psychophysical tests using spectrophotometric measurements of 30 chromatic paint samples. They were rendered on an iPad display, as viewed inside the Byko-spectra effect light booth. We asked 16 observers to evaluate the color match by directly comparing the rendered samples with the physical samples, using two different psychophysical assessment methods. The color reproduction was found to be strongly improved with respect to results obtained with default sRGB color encoding space. The average color reproduction match was found to be equivalent to ΔE00=1.6, which is a small but noticeable color difference. In 80% of the visual assessments, the color reproduction was described as being at least as good as between "difference visible but still acceptable" and "difference visible, doubtful match."

A Structure Landmark-Based Radio Signal Mapping Approach for Sustainable Indoor Localization

Low cost and high reproducible is a key issue for sustainable location-based services. Currently, Wi-Fi fingerprinting based indoor positioning technology has been widely used in various applications due to the advantage of existing wireless network infrastructures and high positioning accuracy. However, the collection and construction of signal radio map (a basis for Wi-Fi fingerprinting-based localization) is a labor-intensive and time-cost work, which limit their practical and sustainable use. In this study, an indoor signal mapping approach is proposed, which extracts fingerprints from unknown signal mapping routes to construct the radio map. This approach employs special indoor spatial structures (termed as structure landmarks) to estimate the location of fingerprints extracted from mapping routes. A learning-based classification model is designed to recognize the structure landmarks along a mapping route based on visual and inertial data. A landmark-based map matching algorithm is also developed to attach the recognized landmarks to a map and to recover the location of the mapping route without knowing its initial location. Experiment results showed that the accuracy of landmark recognition model is higher than 90%. The average matching accuracy and location error of signal mapping routes is 96% and 1.2 m, respectively. By using the constructed signal radio map, the indoor localization error of two algorithms can reach an accuracy of 1.6 m.

RETRACTED: Human tracking of track and field athletes based on FPGA and computer vision

An essential issue that sports science faces in understanding the game's flow is to analyze the game's situation. The use of information technology can help to achieve this goal. Computing speed, the size of the system, consider the accuracy of the complex data analysis. From the practical application of views, technical problems can be divided into three significant respects. This article aims to accelerate image recognition and object tracking; propose a one-dimensional data pipeline architecture on a Field-Programmable Gate Array (FPGA). It is met by a small circuit considering calculation and the spatiotemporal data dependency between two high-velocity flows. The volleyball game has been selected as the target application. FPGA design, pre-processing, color filtering, digitization, noise reduction, including such as template matching. Design and implementation by training stations of the Spartan-6 FPGA Xilinx Atlys of the Spartan-6 FPGA LX45 'were evaluated. Computing power will reach per 100 frames at a resolution of SVGA 800 × 600 pixels. Design, excellent with the scalability, can more easily improve the performance in the case of using a large FPGA. The proposed system consists of the Atlys substrate and Atlys VmodCAM stereo camera board. The average accuracy rate before the game situation and the game with 87.1 percent and 65.7 percent. Since the streaming input data, you can improve the precision by taking into account the previous and the next frame. And 90.4 percent will be able to improve to 72.2 percent by using a moving average filter and template matching.

Intelligent colour matching method for 3D character animation based on texture features

In order to overcome the problems of low matching degree and long matching time in traditional intelligent colour matching methods of 3D character animation, this paper proposes a colour intelligent matching method based on texture features. Three parameters H, S and V are taken as the main parameters of 3D character animation colour recognition, and the animation colour is compared with the colour quantisation template. According to the comparison results and colour difference formula, the animation colour recognition is realised. On this basis, SIFT algorithm is used to obtain colour features of 3D character animation, and clonal selection algorithm is used to realise colour intelligent matching of 3D character animation. The experimental results show that the accuracy rate of colour feature extraction is always above 96%, the colour matching degree is always above 97%, and the average colour matching time is 0.4 s. The practical application effect is good.

The Rise of For-Profit Higher Education: A General Equilibrium Analysis

The growth of for-profit colleges has been historically aided by online instruction, and budget crunches at public institutions, circumstances which have resurfaced during the COVID-19 pandemic. We set up and calibrate a general equilibrium model of competition between public and for-profit institutions in the U.S. four-year college market. Our predicted levels of tuition, instructional spending and average student body ability match data counterparts well. In policy experiments, we vary the generosity of public support for higher education and we consider the effects of “gainful employment” legislation that would link access to federal funding for universities to their graduates’ debt-to-earnings ratios. We find that Pell Grant cap increases would benefit for-profit colleges, which flexibly decrease tuition and instructional spending to attract a higher number of low-income beneficiaries. Our simulations indicate for-profit colleges prefer to comply with gainful employment standards, but do so by lowering tuition and instructional quality.

User Behavior Fingerprinting With Multi-Item-Sets and Its Application in IPTV Viewer Identification

User activities in cyberspace leave unique traces for user identification (UI). Individual users can be identified by their frequent activity items through statistical feature matching. However, such approaches face the data sparsity problem. In this paper, we propose to address this problem by multi-item-set fingerprinting that identifies users not only based on their frequent individual activity items, but also their frequent consecutive item sequences with different lengths. We also propose a new similarity metric between fingerprint vectors that combines the advantages of Jaccard distance and relative entropy distance. Furthermore, we develop a fusion decision scheme by consolidating matching candidates generated by different similarity metrics. It improves the precision at the price of extra rejection. Our proposed approaches can be used in both one-by-one matching and bipartite graph group matching. Through extensive experiments on three real user datasets, in particular a large-scale Internet Protocol Television (IPTV) viewer dataset, we demonstrate that the proposed approaches outperform the state-of-the-art methods. The average matching precision reaches 93.8% for a dataset of 1,000 users and 100% for a dataset of 100 users. This work is of significance for information forensics and raises a new challenge for human privacy protection in cyberspace.

DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes

Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automated deep learning-based method for fast de novo multichain protein complex structure determination from high-resolution cryoelectron microscopy (cryo-EM) maps. We applied DeepTracer on a previously published set of 476 raw experimental cryo-EM maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer, and the rmsd value improved from 1.29 Å to 1.18 Å. Additionally, we applied DeepTracer on a set of 62 coronavirus-related cryo-EM maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average rmsd of 0.93 Å. Additional tests with related methods further exemplify DeepTracer's competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only 2 h. The web service is globally accessible at https://deeptracer.uw.edu.

Preliminary Research on a Comparison and Evaluation of FY-4A LMI and ADTD Data through a Moving Amplification Matching Algorithm

In this study, a new moving amplification matching algorithm was proposed, and then the temporal and spatial differences and correlation were analysed and evaluated by comparing the FengYun-4A Lightning Mapping Imager (FY-4A LMI) data and the China Meteorological Administration Lightning Detection Network Advanced TOA and Direction (CMA-LDN ADTD) system data of southwest China in July 2018. The results are as follows. Firstly, the new moving amplification matching algorithm could effectively reduce the number of invalid operations and save the operation time in comparison to the conventional ergodic algorithms. Secondly, LMI has less detection efficiency during the daytime, using ADTD as a reference. The lightning number detected by ADTD increased from 5:00 AM UTC (13:00 PM BJT, Beijing Time) and almost lasted for a whole day. Thirdly, the trends of lightning data change of LMI and ADTD were the same as the whole. The average daily lightning matching rate of the LMI in July was 63.23%. The average hourly lightning matching rate of the LMI in July was 75.08%. Lastly, the mean value of the spherical surface distance in the matched array was 35.49 km, and roughly 80% of the matched distance was within 57 km, indicating that the spatial threshold limit was relatively stable. The correlation between LMI lightning radiation intensity and ADTD lighting current intensity was low.

Stability in the hospitals/residents problem with couples and ties: Mathematical models and computational studies

In the well-known Hospitals/Residents problem (HR), the objective is to find a stable matching of doctors (or residents) to hospitals based on their preference lists. In this paper, we study HRCT, the extension of HR in which doctors are allowed to apply in couples, and in which doctors and hospitals can include ties in their preference lists. We first review three stability definitions that have been proposed in the literature for HRC (the restriction of HRCT where ties are not allowed) and we extend them to HRCT. We show that such extensions may bring undesirable behaviour and we introduce a new stability definition specifically designed for HRCT. We then introduce unified Integer Linear Programming (ILP) models, where only minor changes are required to switch from one definition to the other. We propose three improvements to decrease the average solution time of each ILP model based on preprocessing, dummy variables, and valid inequalities. We show that our models can be solved more than a hundred times faster when these improvements are used. In addition, we also show that the stability definition chosen has a minor impact on the solution quality (average matching size) and time required to obtain the solution, but for a specific set of instances, stable matchings are significantly less likely to exist for one particular definition compared to the other definitions. We also provide insights relating to how certain parameters such as the tie density, the number of couples, and the difference between the number of positions available in the hospitals and the number of doctors, might affect the average matching size.

Fingerprint restoration using cubic Bezier curve

BackgroundFingerprint biometrics play an essential role in authentication. It remains a challenge to match fingerprints with the minutiae or ridges missing. Many fingerprints failed to match their targets due to the incompleteness.ResultIn this work, we modeled the fingerprints with Bezier curves and proposed a novel algorithm to detect and restore fragmented ridges in incomplete fingerprints. In the proposed model, the Bezier curves’ control points represent the fingerprint fragments, reducing the data size by 89% compared to image representations. The representation is lossless as the restoration from the control points fully recovering the image. Our algorithm can effectively restore incomplete fingerprints. In the SFinGe synthetic dataset, the fingerprint image matching score increased by an average of 39.54%, the ERR (equal error rate) is 4.59%, and the FMR1000 (false match rate) is 2.83%, these are lower than 6.56% (ERR) and 5.93% (FMR1000) before restoration. In FVC2004 DB1 real fingerprint dataset, the average matching score increased by 13.22%. The ERR reduced from 8.46% before restoration to 7.23%, and the FMR1000 reduced from 20.58 to 18.01%. Moreover, We assessed the proposed algorithm against FDP-M-net and U-finger in SFinGe synthetic dataset, where FDP-M-net and U-finger are both convolutional neural network models. The results show that the average match score improvement ratio of FDP-M-net is 1.39%, U-finger is 14.62%, both of which are lower than 39.54%, yielded by our algorithm.ConclusionsExperimental results show that the proposed algorithm can successfully repair and reconstruct ridges in single or multiple damaged regions of incomplete fingerprint images, and hence improve the accuracy of fingerprint matching.

Factors Associated With Osteoarthritis Of The Knee In Former Professional Male Footballers In Bangladesh

Background:: Osteoarthritis is one of the commonest disabilities that affect human life. Knee joint is most commonly affected by osteoarthritis. The professional footballers are exposed to heavy and prolonged physical activities that often exceed normal health capacities during both training and competition and are at risk of developing knee osteoarthritis of the knee (KOA).
 Objective: To evaluate the factors related to KOA in former professional male footballers in Bangladesh.
 Materials and Methods: This was a multicenter cross-sectional study. Purposively Selected footballers subsequently underwent knee radiographs at Bangabandhu Sheikh Mujib Medical University (BSMMU) and Kurmitola General Hospital (KGH). Patients were examined at Sports Medicine Clinic of KGH and Department of Physical Medicine and Rehabilitation of BSMMU from January 2019 to December 2019.
 Results: The mean age of ex footballers was 59.49±9.19 years. We found 46.55% prevalence of KOA among footballers. Among 174 footballers 37.63% had history of familial OA and 8.62% had gout. An average matches played by a footballer was 497 and average training in career was 3924 hours. We found knee injury, BMI, family history of OA, gout and total matches played were significant risk factors for KOA. Other did not proved significant.
 Conclusion: Knee injury was the prime factor here for causing KOA later. So we need to give more attention in preventing knee injuries beside other strategies to reduce risk of developing KOA, moreover early diagnosis of KOA, modification of activities of daily living and exercise is needed.
 KYAMC Journal Vol. 11, No.-3, October 2020, Page 141-144

Learning through coworker referrals

In this paper, we study the role of coworker referrals for labor market outcomes. Using comprehensive Danish administrative data covering the period 1980 to 2005, we first document a strong tendency of workers to follow their former coworkers into the same establishments and provide evidence that these mobility patterns are likely driven by coworker referrals. Treating the presence of a former coworker in an establishment at the time of hiring as a proxy for a referral, we then show that referred workers initially earn 4.6 percent higher wages and are 2.3 percentage points less likely to leave their employers than workers hired through the external market. Consistent with a theoretical framework characterized by higher initial uncertainty in the external market but the possibility of subsequent learning about match-specific productivity, we show that these initial differences gradually decline as tenure increases. We structurally estimate a stylized model using indirect inference and find that the noise of the initial signal about a worker's productivity is 14.5 percent lower in the referral market than in the external market, and that firms learn about their workers' true match-specific productivity with a probability of 48.4 percent per year. Counterfactual simulations show that average wages are lower in the absence of a referral market, primarily because of lower average match productivity in the external market.

An improved semi-global matching method with optimized matching aggregation constraint

Stereo dense image matching (DIM) is a key technique in generating dense 3D point clouds at low cost, among which semi-global matching (SGM) is one of the best compromise between the matching accuracy and the time cost. Most commercial or open-source DIM software packages therefore adopt SGM as the core algorithm for the 3D point generation, which computes matching results in 2D image space by simply aggregating the matching results of multi-directional 1D paths. However, such aggregations of SGM did not consider the disparity consistency between adjacent pixels in 2D image space, which will finally decrease the matching accuracy. To achieve higher-accuracy while keep the high time efficiency of SGM, this paper proposes an improved SGM with a novel matching aggregation optimization constraint. The core algorithm formulates the matching aggregation as the optimization of a global energy function, and a local solution of the energy function is utilized to impose the disparity consistency between adjacent pixels, which is capable of removing noises in the matching aggregation results and increasing the final matching accuracy at low time cost. Experiments on aerial image dataset show that the proposed method outperformed the traditional SGM method and another improved SGM method. Compared with the traditional SGM, our proposed method can increase the average matching accuracy by at most 11%. Therefore, our proposed method can applied in some smart 3D applications, e.g. 3D change detection, city-scale reconstruction, and global survey mapping.

Examining queue-jumping phenomenon in heterogeneous traffic stream at signalized intersection using UAV-based data

This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic.

Design Method for a Wideband Resistive Voltage Divider Based on Average Impedance Matching With Optimal Solution Methods

This article proposes a design method for wideband resistive voltage dividers (WRVDs), working in the range of power frequencies to a few megahertz, with serial-parallel construction. It introduces an extended concept of the Hamon method into the WRVDs, not in a conventional way like balancing a bridge, but in a new way that involves impedance matching with optimal solution methods. With this method, average resistance matching and stray capacitance matching are simultaneously realized by an optimal arrangement of two element resistor groups as the input and output resistors. The surrounding stray capacitances between the resistors and chassis are also considered. The performance has been confirmed to improve by about 50 times, compared with that without the method.

Classification of STR allelic variation using massively parallel sequencing and assessment of flanking region power

The application of massively parallel sequencing (MPS) to forensic genetics has led to improvements in multiple aspects of DNA analysis, however, additional complexities are concurrently associated with these advances. In relation to short tandem repeat (STR) typing, the move to sequence rather than length-based methodologies has highlighted the extent to which previous allelic variation was masked – both within and outside of the repeat regions (the flanking regions). In order to fully implement MPS for autosomal STR analysis, sequence-based allelic frequencies must be available, and concordance with previous typing techniques needs to be assessed. In this work, a series of samples (n = 1007) from five different population groups were genotyped using the MiSeq FGx™ Forensic Genomics System. Results were compared to those obtained using capillary electrophoresis (CE), and sequence variation has been characterised both within and outside STR repeat regions, with allelic frequencies provided for all variants observed within this database. Analysing and characterising flanking region sequence is currently less straightforward than studying repeat region variation alone, and the added value of doing so remains largely unexplored – this paper provides data to show that the gain in polymorphism achieved when analysing flanking regions is less than might be expected. In the White British population for example, including the sequence variation within repeat regions of 26 autosomal STRs made the average combined random match probability (RMP) over 700 times lower than with length-based alleles alone. Including the sequence variation within the flanking regions only resulted in a combined RMP that was a further 4 times lower.

Injury and Player Availability in Women's International Pathway Cricket from 2015 to 2019.

This prospective cohort study aimed to describe injury and illness epidemiology within women's international pathway cricket, understanding what influences player availability in this unique context where players are contracted part-time. Approximately 8.4% of players were impacted by injury or illness during the year, with an average 2.3% of players completely unavailable on any given day. Most medical complaints occurred during training (111.2 injuries/100 players per year). Of all complaints, medical illness had the highest overall incidence (45.0 complaints/100 players), followed by hand injuries (24.7 injuries/100 players). Gradual onset injuries were most common. Overall average match time-loss complaint prevalence rate was 4.1% and average match time-loss injury incidence rate was 7.0 injuries/1000 days of play. Fielding (56.4 injuries/100 players per year) was the activity resulting in the highest average overall and time-loss injury incidence rates, though 'other' activities (e. g. those occurring outside of cricket participation) collectively accounted for 78.3 injuries/100 players per year. The high incidence of medical illness relative to other complaints may be a distinct feature of the women's cricket international pathway compared to other cricket samples. The high occurrence of injuries arising from 'other' activities, likely due to part-time participation, presents an opportunity for targeted injury prevention strategies.• The first study on an international women's cricket pathway, contributes to the empirical base for specific injury risks associated with the women's cricket game, which is an emerging research area for a developing sport.• Some of the findings may be a distinct feature of the women's cricket international pathway, highlighting potential opportunities for targeted prevention strategies.• With the upcoming development of an elite domestic structure these preliminary findings will provide a good starting point for physiotherapy and medical staff working in these contexts.

Intraocular Lens Power Calculations in Eyes with Previous Corneal Refractive Surgery: Review and Expert Opinion

Intraocular lens (IOL) power calculations are less accurate in eyes that have undergone corneal refractive surgery. A wide range of methods have been proposed. We reviewed the methods and outcomes of IOL power calculations in eyes with previous LASIK, excimer laser photorefractive keratectomy (PRK), or radial keratotomy (RK). The PubMed database was searched for articles that (1) discuss methods and outcomes of IOL power calculation in eyes with previous corneal refractive surgery and (2) evaluate the outcomes of toric, multifocal, or extended depth-of-focus (EDOF) IOLs in these eyes. We excluded review articles, case reports or case studies, and non-English reports. Seventy full-text articles were included in this review. Three categories of methods exist based on whether and how they use historical data acquired before the corneal refractive surgery. The American Society of Cataract and Refractive Surgery (ASCRS) postrefractive IOL calculator incorporates many commonly used methods. In eyes with previous myopic LASIK or PRK, hyperopic LASIK or PRK, and RK, 0% to 85%, 38.1% to 71.9%, and 29% to 87.5% of eyes, respectively, showed refractive prediction errors within ±0.5 diopter (D); in eyes with toric IOL implantation that met certain inclusion criteria, 80%, 84%, and 69% of eyes, respectively, achieved postoperative astigmatism of 0.50 D or less. Intraocular lenses with negative spherical aberration (SA) will reduce the positive corneal spherical aberration induced in eyes by myopic LASIK or PRK or by RK. Intraocular lenses with 0 SA on average best match corneal SA in eyes with prior hyperopic LASIK or PRK. Studies have reported excellent outcomes of postrefractive eyes implanted with multifocal or EDOF IOLs; however, corneal topographic enrollment criteria were not specified. Despite availability of new measurement technologies and development of new IOL calculation formulas, further advances are needed to improve outcomes of cataract surgery in eyes that have undergone corneal refractive surgery. Tools like the ASCRS postrefractive IOL calculator are useful for the clinician by incorporating a variety of formulas. Toric, EDOF, and multifocal IOLs may provideexcellent outcomes in selected cases that meet certain corneal topographic criteria.