Flexible Parameters Research Articles

Overview of FLASHlab@PITZ: the new R&D platform for FLASH radiation therapy and radiation biology

An R&D platform for electron FLASH radiation therapy and radiation biology is being prepared at the Photo Injector Test facility at DESY in Zeuthen (FLASHlab@PITZ). This platform is based on the unique beam parameters available at PITZ: ps scale electron bunches of up to 22 MeV with up to 5 nC bunch charge at MHz bunch repetition rate in bunch trains of up to 1 ms in length repeating at 1 to 10 Hz. It works together with the Technical University of Applied Sciences Wildau (TH Wildau) as partner in close vicinity for the biological resources.A startup beamline has been installed to allow dosimetry studies and irradiation experiments on chemical, biochemical and biological samples after a 60-degree dispersive arm. The measured dose and dose rates under different beam conditions and first experimental results will be reported in this paper. In addition, a dedicated beamline for FLASHlab@PITZhas been designed for better control of the high brightness electron beams. This includes a dogleg to translate the beam and a 2D kicker system to scan the tiny beam focused by quadrupoles across the samples within less than 1 ms. Simulation studies will be presented to demonstrate the extremely flexible dose parameters with various irradiation options for electron FLASH radiation therapy and radiation biology studies.

A Multi-Dimensional Node Importance Evaluation Method Based on Graph Convolutional Networks

This paper addresses the problem of identifying, evaluating, and ranking key nodes in complex networks by introducing a novel Multi-Parameter Control Graph Convolutional Network (MPC-GCN) for assessing node importance. Drawing inspiration from the multidimensional and hierarchical interactions between nodes in physical systems, this approach integrates the automatic feature learning capabilities of Graph Convolutional Networks (GCNs) with a comprehensive analysis of nodes’ intrinsic properties, their interactions with neighbors, and their roles within the broader network. The MPC-GCN model offers an innovative framework for key node identification, leveraging GCNs to iteratively aggregate node and neighbor features across layers. This process captures and combines local, global, and positional characteristics, enabling a more nuanced, multidimensional assessment of node importance. Moreover, the model incorporates a flexible parameter adjustment mechanism, allowing the relative weights of different dimensions to be tuned, thereby adapting the evaluation process to various network structures. To validate the model’s effectiveness, we first tested the influence of model parameters on randomly generated small networks. We then conducted extensive simulations on eight large-scale networks using the Susceptible-Infected-Recovered (SIR) model. Evaluation metrics, including the M(R) score, Kendall’s tau correlation, the proportion of infected nodes, and the relative size of the largest connected component, were used to assess the model’s performance. The results demonstrate that MPC-GCN outperforms existing methods in terms of monotonicity, accuracy, applicability, and robustness, providing more precise differentiation of node importance. By addressing the limitations of current methods—such as their reliance on single-dimensional perspectives and lack of adaptability—MPC-GCN offers a more comprehensive and flexible approach to node importance evaluation. This method significantly improves the breadth and applicability of node ranking in complex networks.

Enhancing safety and risk management through an integrated spherical fuzzy approach for managing laboratory errors

Hospital hazards and human errors pose a significant and complex problem, with rising incidents and irreversible consequences. Managing laboratory errors and risks is vital due to the presence of chemicals, electrical equipment, and the involvement of students, professors, and staff. The high value of laboratory equipment further underscores the need for robust risk management strategies. To address these challenges, researchers have explored the Failure Mode and Effects Analysis (FMEA) method for risk identification and assessment in healthcare settings. However, recognizing its limitations, this study aims to prioritize and evaluate laboratory errors using an integrated approach that combines the Best-Worst Method (BWM) and Complex Proportional Assessment with a Fuzzy Spherical Environment (CoCoSo-FSE). By applying the BWM, criteria such as severity, detectability, and occurrence probability are weighted to account for the nature of laboratory errors. The CoCoSo-FSE is then employed to evaluate and prioritize 18 identified laboratory errors, reducing uncertainty and enhancing decision-making. The fuzzy spherical set is used to address uncertainties by providing a flexible framework for decision-makers to define membership functions in specific spherical regions, enhancing the representation of knowledge and decision-making information. The proposed approach is compared with other decision-making methods, namely MOORA and COPRAS, demonstrating reliable ranking results. Sensitivity analysis confirms the stability of the approach's ranking when adjusting the flexibility parameter. This integrated approach offers a reliable and robust decision-making technique for managing laboratory errors, providing valuable insights to enhance laboratory safety and risk management for stakeholders, managers, and policymakers.

End-to-End Optimized Image Compression With Deep Gaussian Process Regression

End-to-end optimization via deep neural networks has facilitated lossy image compression. Existing neural network-based entropy models for end-to-end optimized image compression are limited by parameterized Gaussian distributions with deterministic mean and variance and cannot achieve accurate rate estimation for bottleneck representation with varying statistics. In this paper, we propose a novel entropy model based on deep Gaussian process regression (DGPR) to address this problem. Specifically, the proposed entropy model leverages autoregressive DGPR to flexibly predict the channel-wise posterior distributions of high-dimensional bottleneck representation for entropy coding. Consequently, we develop a well-established bit-rate estimation scheme via posterior inference of DGPR using the learned probabilistic distribution. Furthermore, scalable training is achieved via tensor train decomposition and Monte Carlo sampling to enable tractable variational inference of DGPR. To our best knowledge, this paper is the first attempt to develop the learnable probabilistic model for flexible parameter estimation in entropy modeling. Experimental results show that the proposed model outperforms conventional image compression methods ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g</i> ., JPEG2000 and BPG) as well as recent end-to-end optimized methods on the Kodak and Tecnick datasets in terms of rate-distortion performance.

Method and Application of High-Precision Open-Loop Velocity Measurement of Tianwen-1 Probe

In view of the requirements of Tianwen-1 missions on precision orbit determination and scientific application, this paper proposes a high-precision open-loop velocity measurement method based on ground-based radio. At first, relying on space–ground TT&amp;C resources of the Tianwen-1 probe, the paper designs an open-loop velocity measurement strategy based on China’s deep-space network. Then, it proposes a core algorithm of open-loop velocity measurement based on local cross-correlation reconstruction to obtain instantaneous Doppler frequency observables. This algorithm is characterized by a high ability to avoid phase lock loss, convenient and efficient implementation, and flexible parameter configuration and is suitable for high-precision velocity measurement in the case of high dynamics and low signal-to-noise ratios. On this basis, the similarity and difference of velocity observables between open-loop and baseband velocity measurements are analyzed comparatively. Finally, on the basis of the open-loop velocity measurement method, the paper carries out tests on high precision orbit determination with independent support of velocity measurement, as well as on Mars radio occultation. According to the research results, the accuracy of open-loop velocity measurement can reach 0.05 mm/s (in 1-s integration time), which is 2 to 3 times better than that of baseband velocity measurement. Open-loop velocity measurement can independently support orbit determination accuracy of 50 m of the Tianwen-1 probe and effectively support autonomous retrieval of Martian ionospheric electron density profiles. Thus, this method can be effectively applied to future missions of deep-space exploration and research of planetary radio science.

An Investigation of the Effects of an 8-Week Zumba Exercise Program on Physical Fitness Components in Sedentary Women

This study aimed to investigate the effects of an 8-week Zumba exercise program on weight, body fat percentage (BFP), body muscle mass (BMM), grip strength, back strength, flexibility, and MaxVo2 parameters in sedentary women. Twenty-four women (age: 21.54±1.84, height: 163.75±4.15) who did not engage in regular physical activity and had no history of illness or sports injuries volunteered to participate in the study. The participants were randomly divided into two groups: an experimental group (12 participants) and a control group (12 participants). The experimental group underwent 60-minute Zumba exercises three days a week. Weight, height, BFP, BMM, grip strength (right and left), flexibility, and MaxVo2 were measured. The data were analyzed using SPSS 25 statistical software package. Wilcoxon Test was used for intra-group pre-test and post-test comparisons, and a significance level of p0.05 was accepted. In the experimental group, significant differences were observed in weight, BFP, BMM, flexibility, back strength, and MaxVo2 values between the pre-test and post-test, while there was no statistically significant difference in grip strength (right and left) with p0.05. In the control group, a significant difference was observed in BFP. However, no statistically significant differences were found in weight, BMM, flexibility, grip strength (right and left), back strength, and MaxVo2 with p0.05. In conclusion, based on the results of this study and considering the literature, it can be stated that Zumba exercises, which are widely practiced today, expose individuals to high-intensity physical activity. Consequently, an 8-week Zumba exercise program may positively affect weight, body fat percentage, body muscle mass, MaxVo2, flexibility, and strength parameters.Keywords: Exercise, Physical Fitness, Strength, Zumba

Application of COMSOL Multiphysics for Fiber Beam Profiling

Fiber optic beam profiling is essential across scientific and engineering realms, demanding precise characterization of light beams for optimized system performance, accurate alignment, and efficient resource utilization. This study employs COMSOL Multiphysics to comprehensively analyze single-mode and multimode fiber beam profiles, encompassing diverse parameters such as wavelengths and modal distributions. The investigation of beam profiles is based on 850nm, 1310nm and 1550nm wavelengths; with three different modes (1, 5, and 20). COMSOL Multiphysics enhances beam profiling by providing precise numerical techniques, multiphysics modeling, and flexible parameter analysis. Its user-friendly interface facilitates efficient research, while validation and innovative possibilities underscore its value in photonics advancements. The research addresses the need for advanced profiling techniques, offering a robust methodology that captures intricate modal interactions and boundary conditions. Key findings include distinctive beam waist evolution, mode distribution patterns, and beam shaping behaviors, impacting data transmission, medical procedures, and manufacturing. By integrating computational power, this study advances our understanding of photonics, providing practical insights for future fiber optic technologies and their broader implications.

The Effect Of Preschool Chıldren's Partıcıpatıon In Sportıve Recreatıonal Actıvıtıes On Balance And Flexıbılıty Performance

This study was conducted to compare the developmental status of balance and flexibility, which are the physical fitness parameters of preschool children receiving sportive recreation education. The participant group of the study consisted of a total of 60 children, 30 of whom were experimental and 30 of whom were control groups, who were studying in preschool education between the ages of 4-6. The study lasted a total of 8 weeks and experimental method with control group and pre-test-post-test design was used in the study. While a 40-minute sportive recreation education program was applied to the experimental group 3 days a week for 8 weeks, the control group continued its normal curriculum. In the study, sit and reach test for flexibility and flamingo balance test for balance were used as data collection tools. A normality test was applied to decide on the tests to be applied. Due to the normal distribution of the data, Independent Samples T-Test was used to determine whether the difference between the groups was significant, and Paired Samples T-Test was used to determine whether there was a significant difference between the pre-test and post-test within the group, and the significance value was accepted as p &lt; 0.05. After the 8-week sportive recreation education program, there was a advanced significant difference in the pre-test-post-test values of flexibility and balance parameters in the experimental group (p 0.05). When the experimental group and the control group were compared, a significant difference was found in the flexibility and balance test values in favor of the experimental group after the sportive recreation activity program (p

Optimization of GMr (1,1) Model and Its Application in Forecast the Number of Tourist Visits to Quang Ninh Province

Currently, many researchers pay more attention to improving the accuracy of the Grey forecasting model. One of tendency is focused on the modification of the accumulated generating operation. In 2015, some scholars used the r-fractional order accumulation to improve the accuracy. However, With the desire of users to have a set of forecasting tools as accurate as possible. This paper based on the flexibility parameter of r-accumulated generation operation proposed the systematic approach by optimizing the number of r for improving the precision. To verify the performance in advance of the proposed approach, three case examples were used, the simulation results demonstrated that the proposed systematic approach provides very remarkable predictive performance with the accuracy performance of the proposed approach being higher than other models in comparison. Furthermore, the real case in forecasting the number of tourism visits to Quang Ninh was also conducted to compare the performance of models. The empirical results show that the proposed model will get a higher accuracy performance with the lowest MAPE =19.722%. This result offers valuable insights for Quang Ninh policymakers in building and developing policies regarding tourism industry management in the future.

Multi-loop Nesting Algorithm and Response Analysis of Cable Forces of Long Span Cantilever Cast Arch Bridges during Construction

The existing calculation process of the cantilever cast arch-cable force has a poor fit with the actual process, leading to the lack of good parameter corrections. To improve the overall control quality of the linearity and stress of the arch ring, there is an urgent need for a solution method with higher flexibility and better practicability. Combined with the existing research results, this study proposes a multi-loop nesting algorithm. The algorithm decomposes the whole construction process into individual subsystem control modules, and sets the control indexes of stress and displacement in individual control modules. Subsequently, the analysis and calculation of other modules are completed according to the construction sequence until structure closure. Finally, we determine whether the overall construction control indexes meet the requirements. According to the findings, the results obtained by this algorithm meet the design requirements, and its applicability is verified. Compared with other algorithms, the algorithm is more effective in controlling the stress and deformation of the arch ring during the construction process. This algorithm solves the dispersion between structural systems in previous calculations and has more flexible parameter and control index settings. Additionally, the calculation control idea of this algorithm can be further extended to the construction control of the “cable-beam” cantilever structure.

Investigation on local monitoring paradigms of in-situ conformally fabricated piezopolymer coating-based array transducers: Ultrasonic bulk waves and local ultrasonic resonances

Realistic structures with complex features have been intricate challenges for structural health monitoring (SHM) with permanently installed transducers. Poor conformability of conventional rigid and brittle piezoceramic wafers is a typical issue of applications on surfaces with complex geometry. Moreover, the accompanied high-stress concentration requires high-sensitivity defect detection which is difficult to achieve with large-area monitoring methods like lamb waves at tens to hundreds kHz. Previously, in-situ conformally fabricated piezopolymer coating-based array transducers (PCATs) have been developed to build large-area, lightweight, flexible, and tunable Lamb wave networks. In this study, two novel local monitoring methods were investigated with PCATs, namely ultrasonic bulk wave array inspection and local ultrasonic resonance spectroscopy. For thick structures, ultrasonic bulk waves were generated and detected by PCATs with broadband operating frequencies (1–10 MHz) and flexible array parameters. Simulation tools and imaging algorithms of array inspection in non-destructive testing (NDT) were well implemented based on the analogous directivity pattern and normal-pressure coupling mechanism. As proof of concept, PCATs were applied on example structures with flat, concave, and convex surfaces for internal defect imaging. For thin-walled and/or multilayer structures, PCATs were used to measure local ultrasonic resonances, comparable to conventional non-contact methods. With negligible influence on local mechanical properties and broadband frequency response, multiple resonance peaks from 0 to 25 MHz were identified as zero group velocity (ZGV) Lamb modes and thickness vibration modes of host structures, which can be used as damage indices for local monitoring of corrosion, delamination, stiffness degradation, etc. Through embracing advanced NDT techniques with PCATs, high-sensitivity and quantitative local monitoring could be achieved with conformal networks, offering the possibility to integrate with large-area monitoring as multi-scale SHM for complex structures.

Uncertainty analysis of intra-module environmental stress parameter design in light use efficiency-based gross primary productivity estimation models

Terrestrial gross primary productivity is a key part in the carbon cycle, and the light use efficiency model is a widely employed tool for its estimation. However, since the specific designs of environmental stress parameters in light use efficiency models have obvious disparities, even for a single module (e.g., the temperature stress module), the uncertainties related to intra-module environmental stress parameters in light use efficiency models remain unclear. Thus, we gathered mainstream temperature and water stress parameters in light use efficiency models from existing publications, and employed a compatible framework to assess them from three perspectives: (1) identifying similarities and differences of environmental stress parameters; (2) evaluating the error propagation effect of input data under different environmental stress parameter combinations; and (3) assessing the generalization ability of environmental stress parameters. The results showed that the temperature stress parameters exhibited general homogeneity (shared 67.87% variance), while water stress parameters displayed noticeable internal variations (shared variance below 1.0%). Meanwhile, we revealed that the current flexible parameter combination method in light use efficiency model construction should be more cautious, since the flexible environmental stress parameter combinations would influence the error propagation effect from input data to final gross primary productivity estimations. In addition, our analysis found that the variance of environmental stress parameters was closely coupled to model estimation accuracy, and there was a positive relationship between the unique variance of temperature stress parameters and the ability of temperature stress parameters to describe gross primary productivity variation. Overall, the current environmental stress parameters demonstrated acceptable performance across most situations, except for biomes with high temperatures. This study provided a foundation towards the development of future parameter design, which may also inspire the application of empirical environmental factors in other gross primary productivity models.

Direct Construction of CZCS With Flexible Parameters for Channel Estimation in SM-MIMO System

Direct Construction of CZCS With Flexible Parameters for Channel Estimation in SM-MIMO System

Grey Wolf Optimization Algorithm: A Survey

The Gray Wolf Optimizer (GWO) is a population-based meta-heuristic algorithm that belongs to the family of swarm intelligence algorithms inspired by the social behavior of gray wolves, in particular the social hierarchy and hunting mechanism. Because of its simplicity, flexibility, and few parameters to be tuned, it has been applied to a wide range of optimization problems. And yet it has some disadvantages, such as poor exploration skills, stagnation at local optima, and slow convergence speed. Therefore, different variants of GWO have been proposed and developed to address these disadvantages. In this article, some literature, especially from the last five years, has been reviewed and summarized by well-known publishers. First, the inspiration and the mathematical model of GWO were explained. Subsequently, the improved GWO variants were divided into four categories and discussed. After that, each variant's methodology and experiments were explained and clarified. The study ends with a summary conclusion of the main foundation of GWO and suggests some possible future directions that can be explored further.

A suboptimal control scheme based on integrated real-time nonlinear estimation-identification approach for developed flexible joint manipulators structure

As the safety of human-robot interaction is of great interest in various applications, the flexibility of machine joints becomes increasingly important. In this paper, a general model is developed for electrically driven flexible-joint robots (ED-FJR), in which the coupled phenomena of stiffness-damping and friction in the joints are modeled as nonlinear and time-varying parameters. Because the output torque of the actuator mounted on the link cannot be measured, its state variables are estimated by the suboptimal estimator. Furthermore, the unknown parameters of joint flexibility are identified by the identification algorithm based on time-varying nonlinear least-squares error (TV-NLS), which are then used in the proposed control algorithm to compensate for negative effects and errors. The state-dependent Riccati equation (SDRE) method is developed in this paper using the combined estimator-identifier approach. The novel proposed method for a 3-degree-of-freedom (3-DOF) mechanical arm with electrically driven flexible joints is implemented and validated. The obtained results show that the system's performance has improved by 83% in terms of modeling accuracy. Furthermore, when compared to other methods, the proposed algorithm reduces tracking error by 59%, making it easier to reach the target point.

Impact of roots on the hydrogeological properties of silty soil covers

Mine tailings storage poses significant environmental risks such as the formation of acid mine drainage. Engineered covers offer a solution by controlling water ingress. Their performance is based on specific soil hydrogeological properties (SHPs). They must support vegetation which can impact saturated hydraulic conductivity ( ksat) and water retention curve (WRC). This study assesses the impact of 4-year-old willow root colonization on silty soil covers using flexible wall parameters and water retention tests. The obtained SHPs were compared with root traits. The results suggested that the hydrogeological properties of the studied in situ samples were not significantly affected by roots. The variation of measured and predicted ksat values spanned an order of magnitude, regardless of the root colonization intensity, up to a root length density (RLD) of 2.98 cm/cm3. RLD showed a significant and positive linear relationship with measured ksat values ( R2 = 0.54). However, when root colonization was low (RLD &lt; 1 cm/cm3), RLD was negatively correlated with the nvG ( R2 = 0.44) parameter of the van Genuchten WRC model, while the opposite relationship was observed for samples with RLD &gt; 1 cm/cm3 ( R2 = 0.61). Additionally, RLD and the coarse root (diameter &gt; 1 mm) volume to fine root volume (C/F ratio) influenced WRCs. Over time, coarser roots may have a more pronounced impact on SHPs; further research is needed.

Applying centrifugal propulsion to enable asteroid deflection

To date, asteroid trajectory modification techniques employ the “big bang” approach. An impulsive deflection is imparted by slamming one or more high-speed kinetic impactor spacecraft into the object or by detonation of a nuclear device in its proximity. This is a “hit it once and hope for the best” approach.Instead of relying on this restrictive method, centrifugal propulsion offers an alternative, where a centrifuge and power supply land on a threatening asteroid to collect and incrementally project portions of the asteroid, using momentum transfer of the recoil to gradually adjust the trajectory away from Earth.This process sequentially allows “ejection, measurement, and repetition” to gradually fine-tune the trajectory needed for course correction. This offers flexible operation parameters that can be varied for convenience and optimization, including the location of the landing site, weight of each ejected payload, launch speed, direction, cadence, timing of successive ejections, and the relationship to the asteroid's velocity vector and spin axis. Once landed on an asteroid, the centrifugal system requires no consumables. Operating entirely on electrical power, it can operate indefinitely without additional support.This approach addresses aspects of Goal 3 of the 2018 U S. government's “National Near-Earth Object (NEO) Preparedness Strategy and Action Plan”—“Develop Technologies for NEO Deflection and Disruption Missions.” The centrifuge approach adds a sustainable and repeatable slow-push tool to the planetary defense toolbox, mitigating the risk and uncertainty of single-impulse methods.An on-site centrifuge could deflect Chelyabinsk and Tunguska-sized asteroids to miss Earth within a few weeks’ operation. The asteroid Bennu could be deflected in a few years of continuous spinner operation, depending upon the parameters chosen, which would be sufficient to eliminate a potential collision with Earth in the late 22nd century.The innovation of a self-contained power and kinetic launch capability without consumables opens new vistas for cost-effective asteroid deflection and other commercial, scientific, government, and international space missions.

Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions

Public transportation frameworks assume a critical role in the metropolitan region, especially in huge urban communities, where they offer a feasible answer for easing gridlock, moderating commotion contamination, and diminishing CO2 discharges. This paper presents some novel Fermatean fuzzy Heronian mean operators based on Archimedean t-norms, specifically the generalized Fermatean fuzzy Archimedean Heronian mean (GFFAHM) and the Fermatean fuzzy Archimedean geometric Heronian mean (FFAGHM). The study investigates different unique instances of these operators while exploring their essential properties. Besides, a powerful multiattribute decision-making (MADM) method is developed using the proposed operators. This approach offers a key asset for handling complex decision-making problems. Overcoming the capabilities of conventional BM operators, the GFFAHM and FFAGHM operators effectively minimize the potential redundancy in interrelationships during the decision-making process. The inclusion of the flexible parameters ρ and ϕ, which have a big impact on the decision-making process’ outcomes, increases the adaptability and resilience of the Archimedean t-based operators. To depict the feasibility of the proposed MADM method, a thorough quantitative model is introduced, outlining its useful execution. Through an exhaustive case study, the predominance of the proposed approach over existing strategies is experimentally established. Remarkably, the study uncovers that reducing fares is the most compelling factor in expanding the public transport framework, subsequently advancing sustainable urban transport. This study’s findings provide useful insights into decision-making processes and practical implications for policymakers, allowing them to make informed and impactful changes to the public transportation system. The proposed MADM method can play a vital role in upgrading the public transport framework, making way for remarkable strategy interventions in urban transport sustainability.

INVESTIGATING THE ECONOMIC IMPLICATIONS OF LABOUR MARKET TRENDS ON BUSINESS HIRING PRACTICES

Labour is a unique and vital resource for a business. Every countrys regulations, or the institutional mechanisms that make up its labour market, establish the framework for all labour contracts. The main focus of our research is the criticism of the increasing gap between the requirements of businesses and the actual implementation of employment contracts under present regulations. Whether the labour market and the firms regulatory institutional mechanism design are appropriate for the needs of the particular firm and the nations economy is the main economic matter at hand. The flexibility of contract between employers and employees was diminished during the 20th century as a result of the majority of employment regulations being tightened under the pretext of increased worker protection. The exact opposite was what businesses required and demanded: more flexible employment contracts. Because it controls employment relationships and establishes the parameters of contract flexibility, employment regulation is a crucial component of the legal business framework. These factors affect a firms ability to compete internationally as well as the overall health of the economy. We hypothesised that because regulations cause businesses to put off hiring, an employment climate that is less flexible will be less beneficial. We look into the labour markets challenges and the regulatory practises in a few areas of Vellore District. Flexibility in the labour market is a composite measure of a few chosen variables that are thought to eventually affect a countrys economic performance. Finding the variables that affect labour market flexibility and the chosen output variables like employment and productivity, among others is our goal. KEY WORDS: Labour, Economic conditions, Market, Chi-square, Employment

The Effect of Gymnastics and Taekwondo Trainings on Balance, Flexibility and Jumping Parameters in Primary School Students

Bu çalışma 8-10 yaş aralığındaki ilkokul öğrencilerine uygulanan 8 haftalık cimnastik ve taekwondo antrenmanlarının denge, esneklik ve sıçrama parametrelerine etkisini incelemek amacıyla yapılmıştır. Çalışmaya toplamda 30 öğrenci katıldı ve öğrenciler rastgele yöntemle cimnastik grubu (CG=10, X̄yaş=8.70±0,48), taekwondo grubu (TG=10, X̄yaş=8,20±0,42) ve kontrol grubu (KG=10, X̄yaş=9,50±0,52) olarak ayrıldı. CG ve TG 48 saat aralıklarla haftada 2 gün ve toplamda 8 hafta boyunca branşa özgü antrenmanlarını gerçekleştirdi. KG ise 8 hafta boyunca herhangi bir sportif aktiviteye katılmadı. Performansların değerlendirilmesi için katılımcılara Y dinamik denge testi, esneklik testi ve dikey sıçrama testi 8 haftanın öncesinde ve sonrasında uygulandı. Verilerin normallik dağılımını belirlemek için Shapiro-Wilk testi uygulandı. Verilerin normal dağılım göstermesi üzerine grup içi farkı belirlemek için Paired Sample T Test, gruplar arasındaki farkın belirlenebilmesi için ise Independent Sample T Test kullanıldı. Çalışma sonucunda CG ve TG’nin grup içi esneklik ve sıçrama ön ve test sonuçlarında anlamlı farklılıklar tespit edilirken (p&amp;lt;0,05), KG’de ise anlamlı fark bulunmadı. Grupların alt ve üst ekstremite dinamik denge grup içi karşılaştırma sonuçlarında CG lehine anlamlı farklılıklar bulunmasına karşın, TG’nin sadece sağ bacak anterior değerinde anlamlı farklılık tespit edildi (p&amp;lt;0,05). KG’de ise herhangi bir anlamlı farklılık bulunmadı. Gruplar arası karşılaştırma sonucunda alt ekstremite sol bacak composite değişkeninde CG lehine anlamlı bir fark tespit edilirken (p&amp;lt;0,05), diğer bütün değişkenlerde istatistiksel açıdan bir fark bulunmadı. Cimnastik antrenmanlarının taekwondo antrenmanlarına kıyasla denge, esneklik ve dikey sıçrama parametreleri üzerinde olumlu etkisinin daha yüksek olduğu sonucuna varıldı.