Matching Performance Research Articles

Experimental Investigation of the Performance of a Novel Ejector–Diffuser System with Different Supersonic Nozzle Arrays

The supersonic–supersonic ejector–diffuser system is employed to suck supersonic low-pressure and low-temperature flow into a high-pressure environment. A new design of a supersonic–supersonic ejector–diffuser was introduced to verify pressure control performance under different operating conditions and vacuum background pressure. A 1D analysis was used to predict the geometrical structure of an ejector–diffuser with a rectangular section based on the given operating conditions. Different numbers and types of nozzle plates were designed and installed on the ejector to study the realizability of avoiding or postponing the aerodynamic choking phenomenon in the mixing section. The effects of different geometrical parameters on the operating performance of the ejector–diffuser system were discussed in detail. Experimental investigation of the effects of different types of nozzle plates and the back pressures on the pressure control performance of the designed ejector–diffuser system were performed in a straight-flow wind tunnel. The results showed that the position, type and number of the nozzle plates have a significant impact on the beginning of the formation of aerodynamic choking. The geometry of the ejector and the operating conditions, especially the backpressure and inlet pressure of the ejecting stream, determined the entrainment ratio of the two supersonic streams. The experimental results showed that long nozzle-plate had a better performance in terms of maintaining pressure stability in the test section, while short a nozzle-plate had a better pressure matching performance and could maintain a higher entrainment ratio under high backpressure conditions.

The importance of sensory-motor training in the quality of tactical performance in matches

The importance of sensory-motor training in the quality of tactical performance in matches

A Sheep Identification Method Based on Three-Dimensional Sheep Face Reconstruction and Feature Point Matching.

As the sheep industry rapidly moves towards modernization, digitization, and intelligence, there is a need to build breeding farms integrated with big data. By collecting individual information on sheep, precision breeding can be conducted to improve breeding efficiency, reduce costs, and promote healthy breeding practices. In this context, the accurate identification of individual sheep is essential for establishing digitized sheep farms and precision animal husbandry. Currently, scholars utilize deep learning technology to construct recognition models, learning the biological features of sheep faces to achieve accurate identification. However, existing research methods are limited to pattern recognition at the image level, leading to a lack of diversity in recognition methods. Therefore, this study focuses on the small-tailed Han sheep and develops a sheep face recognition method based on three-dimensional reconstruction technology and feature point matching, aiming to enrich the theoretical research of sheep face recognition technology. The specific recognition approach is as follows: full-angle sheep face images of experimental sheep are collected, and corresponding three-dimensional sheep face models are generated using three-dimensional reconstruction technology, further obtaining three-dimensional sheep face images from three different perspectives. Additionally, this study developed a sheep face orientation recognition algorithm called the sheep face orientation recognition algorithm (SFORA). The SFORA incorporates the ECA mechanism to further enhance recognition performance. Ultimately, the SFORA has a model size of only 5.3 MB, with accuracy and F1 score reaching 99.6% and 99.5%, respectively. During the recognition task, the SFORA is first used for sheep face orientation recognition, followed by matching the recognition image with the corresponding three-dimensional sheep face image based on the established SuperGlue feature-matching algorithm, ultimately outputting the recognition result. Experimental results indicate that when the confidence threshold is set to 0.4, SuperGlue achieves the best matching performance, with matching accuracies for the front, left, and right faces reaching 96.0%, 94.2%, and 96.3%, respectively. This study enriches the theoretical research on sheep face recognition technology and provides technical support.

Hollow engineering in CoNi@Air@C@MoS2 multicomponent composites derived from bimetallic CoNi Prussian blue analogs for ultra-wide bandwidth and strong electromagnetic wave absorption

In recent years, two-dimensional layered transition metal dichalcogenides-based multicomponent composites (MCCs) acting as electromagnetic wave (EMW) materials have received intensive investigations. However, the vulcanication of metal greatly hindered their enhancement of EMW absorption performances (EMWAPs). Herein, a combined metal-organic frameworks-derived and hydrothermal strategy was presented to produce yolk-shell structure (YSS) CoNi@Air@C@MoS2 MCCs. The results showed that the thermal and hydrothermal treatments resulted in the generation of YSS and two-dimensional MoS2 nanosheets, which maintained the original morphology of CoNi Prussian blue analogues. The protection of thick C layer well inhibited the vulcanization of inner CoNi alloy. The formed sheet-like MoS2 further optimized impedance matching characteristics, which led to the satisfactory EMWAPs of CoNi@Air@C@MoS2 MCCs. Furthermore, the EMWAPs could be further improved by optimizing the Ni:Co atom ratios CoNi@Air@C@MoS2 MCCs, which stemmed from their boosted impedance matching performances, EMW attention and polarization loss abilities. The absorption bandwidth and reflection loss values for YSS CoNi@Air@C@MoS2 MCCs are 8 GHz and −60.83 dB, which covered almost all C-Ku bands. In general, our research work provided a valid strategy to produce YSS magnetic CoNi@Air@C@MoS2 MCCs with high efficiency, which well avoided the vulcanization of metal nanoparticles, made best of hollow engineering and atomic ratio optimization strategy to boost the comprehensive EMWAPs.

Guardian of Image: Evaluating Corporate Reputation as a Shield Against COVID-19 Fallout on Firm Performance

The COVID-19 pandemic has wreaked havoc on the global economy and posed a significant challenge for companies to survive. This research provides empirical evidence on how the pandemic can adversely affect company performance. Furthermore, the study also unravels how a company's reputation can act as a shield amid the onslaught of the pandemic, thereby moderating the negative relationship between COVID-19 and company performance. The research utilizes 2,847 firm-year observations from non-financial companies listed on the Indonesia Stock Exchange from 2017 to 2022. The analysis employed in this study uses moderated regression analysis (MRA) with STATA software. The results indicate that a company's reputation can moderate, weakening the negative relationship between COVID-19 and company performance. These findings are reinforced by robustness testing using Coarsened Exact Matching (CEM) and alternative performance measurements. This information is highly valuable for companies and stakeholders, indicating that the risks arising from the COVID-19 pandemic can be mitigated by strengthening the company's reputation.

3D-printed multi-material pyramids for broadband electromagnetic wave absorption

Designing and manufacturing broadband electromagnetic wave-absorbing materials represents one of the significant approaches to address electromagnetic pollution issues. This study utilizes three different PLA-based composite absorbing materials to prepare multilayer pyramid structures employing 3D printing technology. Results indicate that with material composition Z1-GT6-N8, material layer height (h) of 6 mm, and pyramid base length (L) of 36 mm, the fabricated structure achieves a minimum reflection loss of −24.19 dB with an effective absorption bandwidth of 14.21 GHz, demonstrating outstanding absorption performance. It is noteworthy that regardless of the incident angle increasing from 0° to 50°, the equivalent absorption bandwidth (EAB) for both transverse electric (TE) and transverse magnetic (TM) polarizations remains greater than 10 GHz, indicating excellent angle stability. The broadband and efficient electromagnetic wave (EMW) absorption characteristics exhibited by this absorber can be attributed to its outstanding impedance matching performance and the integration of multiscale loss mechanisms.

Summarizing physical performance in professional soccer: development of a new composite index

The aims of this study were to create a composite index to measure the overall players’ physical performance in professional soccer matches and analyze the effect of individual playing time and positional differences on this composite index. A total of 830 official matches from LaLiga men’s first division and Spanish Copa del Rey were analyzed, which resulted in 24,980 match observations collected from 1138 male players (forwards, n = 286; midfielders, n = 441; defenders, n = 411). The physical performance variables, which represent the locomotor demands, were collected using electronic performance tracking systems. A Partial Least-Squares Structural Equation Model (PLS-SEM) was used to measure performance. The PLS-SEM output had three significant latent components, which explained 95% of the initial variability, that were related to the acceleration-specific performance (component 1), high-intensity running-related variables (component 2), and medium intensity actions variables (component 3). Also, a linear regression analysis was used to explore relationships between playing activity time (hours—X axis) and the composite index (10-point scale—Y axis), in which a strong and positive correlation was observed between individual playing time and the composite index (r = 0.76; p < 0.001; R2 = 0.58). Also, significant positive correlations were observed in forwards (r = 0.85; p < 0.001; R2 = 0.74), midfielders (r = 0.80; p < 0.001; R2 = 0.64), and defenders (r = 0.67; p < 0.001; R2 = 0.45). However, significant differences between playing positions with a small effect size (p < 0.05; eta-squared = 0.01) were found. From a practical perspective, this study may serve as a reference for sports performance practitioners to create a composite index that measures the overall players’ physical performance. The instructions to create this index are available in the manuscript.

End-to-end latent fingerprint enhancement using multi-scale Generative Adversarial Network

Latent fingerprint enhancement is paramount as it dramatically influences matching accuracy. This process is often challenging due to varying structured noise and background patterns. The prints may be of arbitrary sizes and scales with a high degree of occlusion. There is a need for creating an end-to-end system that handles different conditions reliably to streamline this often lengthy and tricky process. In this work, we propose a Generative Adversarial Network (GAN) based architecture that effectively captures multi-scale context using Atrous Spatial Pyramid Pooling (ASPP). We have trained the network on a synthetically generated dataset, carefully designed to represent real-world latent prints. By avoiding the reconstruction of spurious ridges and only enhancing valid ridges, we avoid the generation of false minutiae, leading to better matching performance. We obtained state-of-the-art results in Sensor to Latent matching using the IIITD MOLF and Latent to Latent Matching using IIITD Latent datasets.

A high-quality trajectory generation method for the multi-person tracking

Recently, Multi-Person Tracking (MPT) has experienced significant progress due to the emergence of innovative methods. However, congestion and occlusion persist as formidable challenges for MPT. In this study, we propose a Space Matching method, which systematically considers all the potential pedestrian detections within each spatial division. This method can effectively mitigate the erroneous matching problem and hence improve the matching performance. We enhance the update process of the Kalman filter by excluding distorted detections, which can realize a more accurate motion estimation. Further, we propose a Locally Weighted Interpolation method to reconstruct the missing bounding boxes on certain frames, which can significantly reduce the computation time, saving about 80% compared to the Gaussian process regression-based approach. With the help of these strategies, we can generate high-quality pedestrian trajectories, ultimately bringing state-of-the-art results on both MOT17 and MOT20 datasets.

Plasma IL-6 levels and their association with brain health and dementia risk: A population-based cohort study

BackgroundRecent studies have associated immune abnormalities with dementia. IL-6 is a crucial cytokine in inflammatory responses, and recent evidence has linked elevated IL-6 levels to changes in brain structure and cognitive decline. However, the connection between IL-6 levels, cognition, brain volumes, and dementia risk requires exploration in large prospective cohorts. MethodsThis study utilized a longitudinal cohort from the UK Biobank to analyze the correlation between IL-6 expression levels, cognitive performance, and cortical and subcortical brain volumes through linear regression. Additionally, we assessed the association between IL-6 levels and long-term dementia risk using Cox regression analysis. We also used one-sample Mendelian randomization to analyze the impact of genetic predisposition of dementia on elevated IL-6 levels. ResultsA total of 50,864 participants were included in this study, with 1,391 new cases of all-cause dementia identified. Higher plasma IL-6 levels are associated with cortical and subcortical atrophy in regions such as the fusiform, thalamus proper, hippocampus, and larger ventricle volumes. IL-6 levels are negatively associated with cognitive performance in pair matching, numeric memory, prospective memory, and reaction time tests. Furthermore, elevated IL-6 levels are linked to a 23–35 % increased risk of all-cause dementia over an average follow-up period of 13.2 years. The one-sample Mendelian randomization analysis did not show associations between the genetic predisposition of dementia and elevated IL-6 levels. ConclusionsIncreased IL-6 levels are associated with worse cognition, brain atrophy, and a heightened risk of all-cause dementia. Our study highlights the need to focus on the role of peripheral IL-6 levels in managing brain health and dementia risk.

Intelligent Matching Method for College Dormitory Roommates: Chameleon Algorithm Based on Optimized Partitioning

A chameleon algorithm based on optimized partitioning was studied to solve the intelligent matching problem of college dormitory roommates. Using quantitative research methods, data on personal preferences and lifestyle habits of college students were collected, and the K-center object chameleon algorithm was used for data analysis and roommate matching. Test the algorithm performance on the BBC dataset, compare clustering quality indicators such as entropy, purity, and RI value, and verify the effectiveness of the algorithm. This algorithm can accurately assign students to their respective dormitories, avoiding overlapping situations and achieving excellent matching results. In terms of matching accuracy and running time, the K-center object chameleon algorithm shows superior performance compared to other algorithms. In terms of clustering quality evaluation, comparisons were made from three dimensions: entropy value, purity, and RI value. The experimental results show that the closer the entropy value is to 0, the closer the purity and RI value are to 1, and the better the matching effect. This result further validates the effectiveness of the algorithm in the intelligent matching problem of college dormitory roommates. The matching accuracy of this algorithm on the BBC dataset reached 98.82%, showing better clustering quality than other algorithms in terms of entropy, purity, and RI values. The entropy value approached 0, while the purity and RI values approached 1, verifying the efficiency of matching quality. The chameleon algorithm based on optimized partitioning proposed in the study has shown excellent performance in intelligent matching of college dormitory roommates, with the characteristics of high-precision matching and fast running time. It has important practical significance for improving the quality of life and learning efficiency of college dormitory students, and provides new research methods and ideas for related fields.

A Sentence-Matching Model Based on Multi-Granularity Contextual Key Semantic Interaction

In the task of matching Chinese sentences, the key semantics within sentences and the deep interaction between them significantly affect the matching performance. However, previous studies mainly relied on shallow interactions based on a single semantic granularity, which left them vulnerable to interference from overlapping terms. It is particularly challenging to distinguish between positive and negative examples within datasets from the same thematic domain. This paper proposes a sentence-matching model that incorporates multi-granularity contextual key semantic interaction. The model combines multi-scale convolution and multi-level convolution to extract different levels of contextual semantic information at word, phrase, and sentence granularities. It employs multi-head self-attention and cross-attention mechanisms to align the key semantics between sentences. Furthermore, the model integrates the original, similarity, and dissimilarity information of sentences to establish deep semantic interaction. Experimental results on both open- and closed-domain datasets demonstrate that the proposed model outperforms existing baseline models in terms of matching performance. Additionally, the model achieves matching effectiveness comparable to large-scale pre-trained language models while utilizing a lightweight encoder.

Performance and configuration optimization for a Grid-Connected PV power supply system with Demand-Supply matching in a data center’s centralized Water-Cooling system

The cooling system of a data center accounts for a significant part of its energy consumption, and the adoption of solar energy can reduce its power demand from the grid. This paper investigated the optimal configuration of a grid-connected PV power supply system to a data center’s centralized water-cooling system. Firstly, mathematical models for photovoltaic panels and storage batteries were established. Then, two operating strategies were proposed, respectively, for two systems with and without storage batteries, and the supply–demand matching performances were studied. With storage batteries, mismatch problem between electricity generated by photovoltaic panels and electricity consumed by the water-cooling system can be significantly improved. Utilization ratio of electricity generated by photovoltaic panels was increased by up to 27.64 % in the discussed typical days. Annual utilization of electricity generated by photovoltaic panels can also be significantly increased, especially when heat dissipation density is small. Lastly, the optimal configurations were discussed. To reduce carbon emission, number of battery groups were recommended for different heat dissipation density and number of photovoltaic panels. Full life-cycle carbon reduction ranged from 1.77 to 3.71 tCO2/m2 and carbon emissions reduced from 14.23 to 62.14 % as compared with the traditional system. As for the economic performance, the recommended number of photovoltaic panels are 798, 1330 and 1589 for heat dissipation density being 500, 800 and 1100 W/m2, respectively. While the recommended number of batteries was 0 if unit price of batteries is higher than 11.1 ten thousand yuan/group.

VA-LOAM: Visual Assist LiDAR Odometry and Mapping for Accurate Autonomous Navigation.

In this study, we enhanced odometry performance by integrating vision sensors with LiDAR sensors, which exhibit contrasting characteristics. Vision sensors provide extensive environmental information but are limited in precise distance measurement, whereas LiDAR offers high accuracy in distance metrics but lacks detailed environmental data. By utilizing data from vision sensors, this research compensates for the inadequate descriptors of LiDAR sensors, thereby improving LiDAR feature matching performance. Traditional fusion methods, which rely on extracting depth from image features, depend heavily on vision sensors and are vulnerable under challenging conditions such as rain, darkness, or light reflection. Utilizing vision sensors as primary sensors under such conditions can lead to significant mapping errors and, in the worst cases, system divergence. Conversely, our approach uses LiDAR as the primary sensor, mitigating the shortcomings of previous methods and enabling vision sensors to support LiDAR-based mapping. This maintains LiDAR Odometry performance even in environments where vision sensors are compromised, thus enhancing performance with the support of vision sensors. We adopted five prominent algorithms from the latest LiDAR SLAM open-source projects and conducted experiments on the KITTI odometry dataset. This research proposes a novel approach by integrating a vision support module into the top three LiDAR SLAM methods, thereby improving performance. By making the source code of VA-LOAM publicly available, this work enhances the accessibility of the technology, fostering reproducibility and transparency within the research community.

OEM: An operation-aware event matching algorithm for content-based Pub/Sub systems

Due to the continuous expansion of the user base and the heightened demands for quality of service (QoS), real-time data distribution has encountered significant challenges in event matching within large-scale content-based publish/subscribe (CPS) systems. Many efficient algorithms have been proposed to enhance the matching performance. However, most existing algorithms scarcely consider operation characteristics, which often leads to performance degradation due to a multitude of repetitive operations, such as comparisons, additions, and assignments. In this paper, we propose an Operation-aware Event Matching algorithm called OEM, which takes into account the efficiency of CPU operations, SIMD instructions, and multi-thread architecture. First, we introduce a bitset-based subscription cache mechanism (SCM), which enables the efficient execution of bitwise OR operations during the matching process. Furthermore, we propose two optimizations, namely an optimal skewness-aware cell grouping (OSCG) strategy and an attribute-based clustering mechanism (ACM), to enhance the efficiency of OEM. These optimizations effectively address the challenges posed by data skewness, low cache efficiency, and high dimensionality. In addition, we establish a performance analysis model that characterizes the trade-off between memory consumption and performance improvement. We conducted extensive experiments to evaluate the performance of OEM. Compared to six state-of-the-art algorithms, namely REIN, Ada-REIN, TAMA, OpIndex, PEM and fgPEM, OEM achieves an average reduction in matching time by 40.4×, 38.5×, 12.0×, 33.1×, 27.8×, and 25.5×, respectively.

The Comparison of Position-Specific Match Performance between the Group and Knockout Stage of the UEFA Champions League

This study aimed to compare match performance in the group and knockout stage of the UEFA Champions League (UCL) for players in different playing positions. The information on physical and technical performances was collected during all UCL matches (n=125) in the 2022/23 season. Players’ observations (n=1387) were classified according to their playing positions as central defender (CD; n=471), fullback (FB; n=283), central midfielder (CM; n=376), winger (WM; n=137) and forward (FW; n=104). No differences in technical performance between the group and knockout stage were found for CDs, FBs, CMs, and WMs, while only FWs achieved significantly less shots on target (Cohen’s d (d=0.46), total passes (d=0.54), successful passes (d=0.49), and more duels (d=0.39) in the knockout compared to the group stage. The CDs, CMs, and WMs covered greater distance at moderate (d=0.46–0.63) and high (d=0.29–0.38) speeds in the knockout compared to the group stage, while no differences in physical performance between the group and knockout stage were found for FBs and FWs. This study demonstrated that (i) the technical performance of UCL players was in general stable irrespective of the competition stage, (ii) matches played in the knockout stage were characterized by greater match intensity compared to the matches played in the group stage of UCL for CDs, CMs, and WMs. These findings may help football coaches in the decision-making process when selecting the players for specific matches and designing training programs.

Validity of simple field tests as indicators of elite female field hockey match performance.

Due to the change in field hockey match format, the need exits for research to determine whether current fitness test are still valid indicators of match performance. This study aimed to determine the direct validity of the 5-m multistage shuttle test (5-m MST) and Yo-Yo Intermittent recovery level 1 test (Yo-Yo IR1) by correlating their results with external load measures in international field hockey matches. Nineteen female field hockey players completed the 5-m MST and Yo-Yo IR1 before nine matches. Players covered mean distances of 750.3 m±19.6 m (5-m MST) and 1649.7 m±277.6 m (Yo-Yo IR1). Average relative distance, relative player load, and high-intensity activity during matches were 107.8±16.3 m/min, 10.3±1.4 AU/min, and 10.0±3.0%, respectively. The 5-m MST showed small to moderate significant (P<0.05; r=0.21-0.5) correlations with relative distance and high-intensity activity, while the Yo-Yo IR1 only had a small negative significant (P<0.05; r=-0.27) correlation with high-intensity activity. Strong correlations (r>0.51) were found between the 5-m MST and Yo-Yo IR1. The tests demonstrated low direct validity for current field hockey matches due to weak relationships with relative load and running performance. Additionally, the strong correlation between the Yo-Yo IR1 and 5-m MST suggests that both tests may not be necessary to assess match readiness. Coaches should consider using better-validated fitness tests for this population and sport.

The Selection of Optimal Gas Production Rate using Dynamic Reservoir Simulation in Field X

Indonesian government has targeted a gas production rate of 12 BSCFD by 2030 to balance the energy demands and the carbon emission reduction. To achieve this goal, a comprehensive evaluation of a gas field will be carried out regarding Recovery Factor, Stable Production Period (Plateau Time), Total Production Period, and Profits using simulation programme. Dynamic Reservoir Simulation is an integrated field development simulation that combines physics, mathematics, reservoir engineering, and computer programming to analyze and predict the wells performance or how fluid flows through reservoir rocks to the surface over time under various operating conditions. There are stages in the simulation include Reservoir Model Creation, Initialization, History Matching, and Production Performance Forecasting. This research is a continuation of static reservoir modeling research done by LEMIGAS, which started by reinitializing the model and ended by forecasting the production performance of field X using several gas production flowrate scenarios to find out the optimal gas production flowrate for Field X in ten years period. The simulation result showed that the best gas production flowrate for a ten-year period is 3 mmscfd. It gives 78,505% recovery factors, with cumulative profit of $40,915,872 USD over a plateau period of 6.6 years.

Performance metrics that matter: assessing winning and losing teams in women’s Rugby union

ABSTRACT The aim of this study was to identify key performance indicators (KPI) that differentiated winning and losing teams, and how KPI may vary in balanced and unbalanced matches in Australian domestic women’s Rugby Union (RU). Four seasons of the Buildcorp Super W competition (2019–2022), round and final matches (n = 47) were analysed by an experienced performance analyst using computerised notational analysis software (Hudl SportsCode) to identify various KPI that occurred throughout a match. Findings showed that winning teams had greater ball-carrying efficiency, quick ruck speed, greater field-based tactics, greater successful conversions, and created more scoring opportunities while losing teams had poorer goal-kicking performance, greater number of rucks lost, and unsuccessful set piece performance. However, in balanced matches, only greater scoring opportunities, possession, and kicking performance discriminated between winning and losing teams. Winning teams in unbalanced matches had greater scoring opportunities, kicking performance, possession, territory, ball-carrying efficiency, and ruck performance, whilst losing teams had a greater number of rucks lost and lineouts lost. These results suggest some performance metrics can differ between balanced and unbalanced matches. Coaches may use these findings to help evaluate match performances based on scoring differential, as well as influence possession-in-territory, and kicking tactics, to increase scoring opportunities.

Developing a Soccer Player's Performance Index Model for Chinese Professional Football: Integrating Physical Condition, Match Performance and Team Circumstance

The study aims to develop a soccer player’s performance index (SPPI) model for Chinese professional football players by integrating their physical condition, match performance, and team circumstances. The model is intended to identify potential talents and address the challenge of evaluating unknown players in player selection. Moreover, the study found a non-linear relationship between age and SPPI, which suggests that future research on Chinese professional soccer players’ aging curves could benefit from using non-linear models. Overall, the findings of this study provide valuable insights for talent identification and player performance evaluation in Chinese professional soccer.