Calculation Technique Research Articles

Combined Displacement/Intercalation Mechanism of Ag0.33V2O5 Cathode for Rechargeable Zinc‐Ion Batteries

Zinc‐ion batteries are gaining recognition as viable options for energy storage systems due to their air stability, abundance, affordability, and ease of use. However, existing zinc‐storage materials primarily consist of intercalation cathode materials, necessitating the development of host structures with enhanced performance. Herein, the use of silver vanadate, Ag0.33V2O5, as a cathode material is explored and its detailed displacement/intercalation mechanism is elucidated, encompassing silver, proton, and zinc‐ion storage behaviors. Electrochemical behavior, structural analysis, and diffusion barrier calculation techniques are used to delineate cation diffusion pathways. Additionally, 3D electron density mapping is performed to visualize the cation reaction mechanism. The proposed material demonstrates an impressive reversible capacity of about 303 mAh g−1 at a current of 0.1 A g−1, along with outstanding cycle retention stability even at high current densities.

Evaluating Sustainability: A Comparison of Carbon Footprint Metrics Evaluation Criteria

The two biggest environmental issues the world is currently dealing with are global warming and climate change. Minimizing energy consumption will help to cut down on greenhouse gas emissions, which is our responsibility. Companies choose ‘Carbon Footprint’ as a tool to calculate greenhouse gas emissions to show the impact of their activities on the environment. The techniques and procedures used in the analysis of carbon footprints are the primary focus of this study. Several criteria for evaluating carbon footprints were compared to one another to uncover parallels, variances, and deficiencies. Carbon footprints of companies and items were analyzed, and their objectives, ideas, topics of inquiry, calculation techniques, data choices, and additional elements were investigated. Standards for both organizations (ISO14064 and the GHG protocol) and products were compared and contrasted to arrive at accurate carbon footprint estimates. The most important aspects of a carbon footprint and assessment criterion are the research of GHG, system settings, measurement and carbon footprint, date, and treatment of individual emissions. Especially true for commercial enterprises and consumer goods. Guidelines have been produced for these challenges based on valuation criteria that have been used up to this point; nonetheless, they should be enhanced. This study highlights the need to formulate policies to reduce greenhouse gas emissions.

Space-time tree: a spatiotemporal construct for efficient similarity matrix calculations among network-constrained trajectories

Data mining of network-constrained trajectories has broad applications in the GIScience field. The calculation of a complete trajectory similarity matrix is a key step in various data mining algorithms. However, computing this matrix is computationally intensive for large datasets, as it involves numerous point-to-point shortest-path (PPSP) queries. To tackle this issue, we propose a new spatiotemporal construct called the space-time tree, which directly delineates the network distance from a query trajectory to any network space-time point. By constructing the space-time tree, we can efficiently compute the trajectory similarity matrix without additional PPSP queries. The space-time tree supports several similarity metrics, including closest pair distance, furthest pair distance, longest common subsequence (LCSS), and distance-weighted LCSS. It can further integrate with advanced spatiotemporal query techniques for scalable partial trajectory similarity matrix calculations. A case study using real datasets was conducted to apply the space-time tree in the trajectory clustering application. The results show that the space-time tree completed the clustering task on 0.5 million trajectories within 49 minutes, achieving a nearly 147-fold speedup compared to state-of-the-art methods.

Tuning a secondary dose verification software for a CT-guided online adaptive delivery system.

Quality assurance (QA) remains unstandardized for CT-guided online adaptive radiotherapy (CTgART) platforms (Ethos, Varian Medical Systems, Inc., Palo Alto, CA), as they become more clinically prevalent. A secondary dose calculation software (Mobius3D, Varian Medical Systems, Inc., Palo Alto, CA) is provided for this closed CTgART system. However, the clinical impact of tuning dosimetric leaf gap (DLG) correction values for specific delivery techniques for CTgART secondary dose calculations remains uninvestigated. Tuning the DLG correction value for different delivery techniques of the independent secondary dose verification software for adaptive online QA. A total of 31 volumetric arc therapy (VMAT) and 13 fixed-gantry intensity modulated radiation therapy (IMRT) plans were selected from representative anatomical sites treated in our clinic. All plans were evaluated on a patient CT dataset and a QA dataset of a solid water phantom with an embedded ion chamber placed at the center in both primary treatment planning systems (TPS) and secondary dose verification software. Primary TPS plan doses were compared with secondary calculation doses on patient CT by calculating 3D gamma passing criteria under different DLG correction values ranging from -2 to 2mm to determine the optimal DLG correction range. Ion chamber verification measurements were then compared to secondary calculation dose to determine the optimal DLG correction value by minimizing the difference for IMRT and VMAT plans, separately. The optimal DLG correction values for VMAT and IMRT techniques were -0.3 and 0.4mm respectively for the selected clinical cohort of patients. The mean gamma passing rate between primary and secondary doses for VMAT and IMRT were 99.0%±1.0% and 99.9%±0.1% with 3%/2mm and excluding 10% low dose criteria. The mean ion chamber agreement for VMAT and IMRT were 0.0%±2.1% and 0.2%±1.4%. DLG correction value should be tuned for each delivery technique (VMAT and IMRT) separately to maximize the robustness of CTgART online QA programs.

Prediction of axial compressive capacity and interpretability analysis of web perforated Σ-shaped cold-formed steel

The Σ-shaped cold-formed steel with web opening (ΣSCFSWWO) is a critical component in modern structural systems, and accurate calculations of its axial compressive capacity are essential for ensuring the overall stability and safety of structures. However, traditional finite element analysis (FEA) and experimental methods are often inefficient and require complex modeling techniques for capacity calculations. Moreover, the interaction between section design parameters and structural capacity remains unclear. This study integrates FEA, experimental methods, and machine learning to propose a novel approach for predicting capacity and analyzing parameter interpretability. A dataset comprising 1000 numerical simulation results and 260 experimental data points was established. Machine learning techniques, including BP (Backpropagation) neural networks, RBF (Radial Basis Function) neural networks, Decision trees, Random Forests, and XGBoost algorithms, were employed to develop predictive models for capacity. The SHapley Additive exPlanation (SHAP) method was utilized for interpretability analysis. Results indicate a good correlation between FEA and experimental outcomes, effectively simulating the mechanical behavior of the components. Comparative analysis reveals that the XGBoost model demonstrates the highest predictive accuracy and generalization capability. SHAP analysis elucidates the influence of various input parameters on axial compressive capacity predictions and clarifies the interactions among these parameters. This research provides a novel reference for calculating the axial compressive capacity of ΣSCFSWWO, and the proposed methodologies can be extended to other similar components.

A COMPARATIVE EVALUATING NUMERICAL MEASURE VARIATIONS IN K-MEDOIDS CLUSTERING FOR EFFECTIVE DATA GROUPING

The K-Medoids Clustering algorithm is a frequently employed technique among researchers for data categorization. The primary difficulty addressed in this investigation pertains to the extent of optimality achieved when varying distance computation methodologies are applied within the framework of K-Medoids Clustering. This study is primarily concerned with the application of K-Medoids Clustering, employing a multitude of distance calculation methods, specifically those involving numerical metrics. The aim is to undertake a comparative analysis of Davies-Bouldin Index (DBI) values in order to ascertain the most productive distance calculation technique. In this research, the distance calculation methodologies include Manhattan Distance, Jaccard Similarity, Dynamic Time Warping Distance, Cosine Similarity, Chebyshev Distance, Canberra Distance and Euclidean Distance. The dataset consists of sales data from Devi Cosmetics, covering the period between January and April 2022 and comprising 56 distinct sales items. The research provides an exhaustive evaluation of numerical metrics concerning the K-Medoids Clustering algorithm. The findings indicate that the optimal clustering is achieved using the Chebyshev distance, resulting in 9 clusters with a DBI value of 166.632. The study's contribution is that it can improve more optimal data grouping to help make decisions correctly.

Constrained Control of Autonomous Underwater Gliders Based on Disturbance Estimation and Tracking Back Calculation

ABSTRACTThis article presents an anti‐disturbance constrained control scheme for the pitch channel of autonomous underwater gliders subject to internal and external disturbances, as well as actuator saturation. First, the integral control technique is employed to develop a disturbance observer to estimate the overall effect of possible uncertainties and disturbances on the nominal vehicle model, which is referred to as the mismatched lumped disturbance. Then, a disturbance rejection control law is constructed based on the disturbance observer. Following that, a straightforward anti‐windup modification is proposed to handle potential input constraints by using the tracking back calculation technique. Specifically, the difference between saturated and unsaturated control input signals is utilized to create a feedback signal that addresses the disturbance observer input, thereby alleviating system windup during actuator saturation events. Furthermore, the stability of the overall closed‐loop system is established in term of the Lyapunov stability theorem, demonstrating that the tracking error is ultimately bounded. Compared with some existing anti‐windup control schemes, the suggested approach offers intuitive design guidelines, resulting in a simple controller that can be easily implemented. Finally, the effectiveness and robustness of the proposed control scheme are verified through simulation results.

Technical note: A GPU-based shared Monte Carlo method for fast photon transport in multi-energy x-ray exposures.

The Monte Carlo (MC) method is an accurate technique for particle transport calculation due to the precise modeling of physical interactions. Nevertheless, the MC method still suffers from the problem of expensive computational cost, even with graphics processing unit (GPU) acceleration. Our previous works have investigated the acceleration strategies of photon transport simulation for single-energy CT. But for multi-energy CT, conventional individual simulation leads to unnecessary redundant calculation, consuming more time. This work proposes a novel GPU-based shared MC scheme (gSMC) to reduce unnecessary repeated simulations of similar photons between different spectra, thereby enhancing the efficiency of scatter estimation in multi-energy x-ray exposures. The shared MC method selects shared photons between different spectra using two strategies. Specifically, we introduce spectral region classification strategy to select photons with the same initial energy from different spectra, thus generating energy-shared photon groups. Subsequently, the multi-directional sampling strategy is utilized to select energy-and-direction-shared photons, which have the same initial direction, from energy-shared photon groups. Energy-and-direction-shared photons perform shared simulations, while others are simulated individually. Finally, all results are integrated to obtain scatter distribution estimations for different spectral cases. The efficiency and accuracy of the proposed gSMC are evaluated on the digital phantom and clinical case. The experimental results demonstrate that gSMC can speed up the simulation in the digital case by ∼37.8% and the one in the clinical case by ∼20.6%, while keeping the differences in total scatter results within 0.09%, compared to the conventional MC package, which performs an individual simulation. The proposed GPU-based shared MC simulation method can achieve fast photon transport calculation for multi-energy x-ray exposures.

Penerapan Metode Just In Time dalam Upaya Meningkatkan Efisiensi Biaya Produksi Optimal pada UD. Rambak Dudung di Desa Ambal Ambil

A trading business is a business that is engaged in buying and selling products. Trading businesses can engage in various types of products that are sold for consumer, business, or government purposes. One of them is UD. Rambak Dudung is trying to buy raw materials in large quantities to keep in store if the supply runs out and demand in the market increases. With the excess of raw materials, it can cause storage costs, which can reduce UD's profits. aforementioned. So this shows that the supply of raw materials is a fairly big problem. This study aims to determine the application of the Just in time method to UD. Rambak Dudung and knew the role of the Just in time method in improving production cost efficiency in UD. Rambak Dudung. The type of research used is a descriptive method with a quantitative approach. Data collection was carried out by interviews, internet searches and library studies. The data processed is the purchase and use of raw materials. The calculation technique used is to calculate the total production cost based on company policies, the EOQ method, and the JIT/EOQ method. Based on the results of the calculation, it was concluded that the inventory policy carried out by the company has not been maximally seen from the total production costs incurred of Rp.5,853,500,- compared to the JIT/EOQ method of Rp.2,588,436,- so that the total cost saved is Rp.3,265,064.

Modeling and Energy Flow Calculation of Integrated Energy System Based on Partial Differential Equation Model

This paper discusses the modeling and energy flow calculation method of integrated energy system based on partial differential equation model. By constructing a model that integrates power, heat, and natural gas networks, we analyze in detail the process of energy transmission, conversion, and storage in the system. In the process of modeling, the influence of compressor in constant compression ratio, constant outlet pressure and constant natural gas flow is specially considered, and the accuracy of the model is verified by specific data. In terms of energy flow calculation methods, we compare the performance of the unified solution method and the decomposition solution method. Data analysis shows that the non-gradient descent iterative method, gradient descent iterative method and decomposition solution method show consistency in calculation accuracy, that is, the calculation results of the three methods are the same. However, in terms of computational efficiency, the gradient descent iterative method shows significant advantages. Specifically, under identical computing conditions, our analysis reveals that the gradient descent iterative method exhibits a convergence rate approximately 30% faster than the decomposition solution method, resulting in a notable reduction of around 25% in computational time. This pivotal observation serves as a solid foundation for selecting a more computationally efficient approach in practical applications. To further enhance the computational efficiency, we have delved into deriving the Jacobian matrix of the model and subsequently proposed an advanced gradient descent iterative calculation technique. Through the actual test, this method not only improves the calculation speed, but also ensures the stability and accuracy of the calculation. The research in this paper not only provides a strong theoretical support for the optimal operation of the integrated energy system, but also provides a valuable reference for future research in related fields. Through specific data analysis, we prove the effectiveness and practicability of the proposed method, laying a solid foundation for the sustainable development of integrated energy systems.

Simulated Surface‐Column NO2 Connections for Satellite Applications

AbstractObservations of near‐surface NO2 show a diurnal pattern with midday minima and daily maxima in the morning and evening. These surface cycles are dependent on chemical processing, transport, and emissions. We evaluate these cycles with the United States Environmental Protection Agency (EPA) community multiscale air quality (CMAQ) model data from the EPA Air Quality Time Series (EQUATES) project, compared with ground‐based measurements from the EPA air quality system, two Pandora measurement sites, and satellite data from TROPOMI. We find that the morning vertical column density (VCD) lags surface concentrations by 1 hr on average, where this lag varies with location and day. The peak VCD can also lead the surface maximum concentration, especially in the evening, responding to transport and afternoon compression of the boundary layer. Modeled NO2 VCD is sensitive to column calculation technique. With hourly daytime satellite‐based NO2 observations newly available from the TEMPO instrument, the timing and magnitude of cycles in near‐surface NO2 versus column NO2 will help inform the utilization of hourly satellite data. This work will help inform the timing of surface‐column connections to better interpret new hourly satellite observations for health and air quality applications, including emissions characterization.

Selection of aerodynamic characteristics and engine parameters of a maneuverable aircraft under epistemic uncertainty

At the preliminary stage of aircraft design, it is usually required to solve the problem of insufficient initial data for applying traditional algoristic-type mathematical programming models. In many cases, numerous input parameters cannot be accurately specified at the time of making design decisions. If the inaccuracy of parameters is not taken into account, the actual values of target functions may differ significantly from the calculated ones when solving optimization problems. In this regard, the issue of current interest is the development of algorithms to improve the reliability of design decisions under conditions of epistemological uncertainty when experts engage in the formation of initial data. The paper considers the problem of selecting aerodynamic characteristics and engine parameters of maneuverable aircraft under conditions of uncertainty associated with inaccuracy of expert data. The applied problem under consideration is further complicated by the necessity to include “black box” models in the algorithms being developed. The paper proposes algorithms that apply the uncertainty theory together with “black box” models that implement optimization calculation techniques derived from previous engineering practice of aircraft design. Using these algorithms, experts are able to set uncertain parameters whereby the lack of data is factored in using uncertainty distribution functions. In cases of monotonicity of uncertain parameters in target functions, application of the uncertainty theory provides a significant reduction in computational costs compared to the method of statistical modeling in optimization calculations. The paper presents the results of computational studies of the developed algorithms. A genetic algorithm (mathematical optimization solver) is used to optimize the search for design solutions. Pareto frontiers are obtained for different confidence levels enabling to make design decisions including values of aerodynamic characteristics and engine parameters of maneuverable aircraft.

A predictive model for the estimation of industrial [formula omitted] emissions for IoT-based devices

The paper is devoted to solving the problem, associated with increasing the forecasting accuracy of pollutant concentration level based on PM2.5 dust. The LANN model (LANN – Lagrange powered Artificial Neuron Network), proposed in the paper, allows you to take into account the mutual influence of pollution sources on the concentration level at monitoring points, which, on the one hand, allows to manage the volume of emissions from industrial enterprises in such a way as to avoid penalties and, on the other hand, allows the regulatory agencies to determine points for environmental control, at which permissible standards will be most likely exceeded. The suggested solution makes it possible to use low-cost IoT-based air quality monitoring devices, which were primarily considered not applicable due to their low accuracy and exposure to the influence of short-term stochastic factors; besides, no models were available, which would be capable to provide the necessary accuracy and forecast horizon on the base of IoT data. At the same time, the obtained model has low requirements for computing resources compared to dispersion models and is dependent on the accuracy of weather information; besides, the model allows you to take into account trends and obtain better forecast values in terms of accuracy than the models, that use regression methods, neural network models and ML models, stochastic models and their ensembles. The application of the model improves well-known pollutant dispersion estimation calculation techniques through the use of measurement data flow and dynamic adaptation to changing conditions. The model was trained on the dataset over the period 2022–2023 collected from 5 monitoring devices, which were installed in the catchment area of the group, incl. 13 industrial points of PM2.5 pollutant sources.

Choi representation of completely positive maps in brief

Abstract The Choi representation of completely positive trace preserving (CPTP) maps, i.e. quantum channels is often used in the context of quantum information and computation as it is easy to work with. It is a correspondence between CPTP maps and quantum states also termed as the Choi–Jamiołkowski isomorphism. It is especially useful if a parametrization of the set of CPTP maps is needed in order to consider a general map or optimize over the set of these. Here we provide a brief introduction to this topic, focusing on certain useful calculational techniques which are presented in full detail.

Association Between Measurable Residual Levels and Infection Mortality in Acute Myeloid Leukemia

Abstract Background Acute myeloid leukemia (AML) outcomes have improved over the years. Better AML disease risk classification, achieved by measuring minimal residual disease (MRD) levels, has contributed to improved treatment and survival. Even though the role of MRD in survival is still preliminary, results are promising. However, infections are still a problem to circumvent. In our previous protocol LMA-GATLA 2007 we found a 30% incidence of sepsis related death (SRD), and they were more frequent during or after first induction. The overall survival of that study was 51.4 % (0.38). In this study, we aimed to analyze the mortality rates due to infection; and determine if there is an association of the MRD levels and infection mortality rates; also, we will analyze overall outcomes of AML. Methods Patients were accrued form the National Registry GATLA LMA 2021 protocol. Disease risks were classified based on cytogenetics and molecular abnormalities as standard risk (SR), high risk (HR), and very high risk (VHR). MRD determinations were performed using flow cytometry after 1st induction with mitoxantrone, anthraciclines and etoposide (MAE) protocol, at day 22 and 29 and after 2nd induction with high dose citarabine and mitoxantrone (HAM). We used descriptive statistics (analysis by frequency), compared categorical variables using chi-square or χ2 test and Fisher test, and time to event calculation techniques. Results 95 patients have been accrued, 51.6 % were males. The median age was 9 years of age (IQR 3-13), and 31% were SR, 22% HR, and 47% VHR. MRD levels < 0.1% were seen in 55.5% post first induction, 92% post intensification and 85% post consolidation. Estimated probability of overall survival was 65% (ES 0.6) at 45.7 (2.7) months, (CI 95% 40.3-51,1). 23 pts (24%) died; 11 (48 %) for progression, 7 (30%) for sepsis, for non-sepsis toxicity 3 (13%), other causes 2 pts (9%). Hazard ratio of death with MRD > 0.1% was 2.35 (p=0.06, 95% CI 0.043-1.756). The incidence of SRD was 7.4%, 4 patients had sepsis with MRD < 0.1% (57 %), after HAM /consolidation phase; and 3 patients with > 0.1% (43%) when in relapse (p= 0.028). The SRD episodes were independent from MRD levels, however patients on remission showed SRD as late events, because no patient developed SRD during or after first induction. Conclusion Overall survival results have improved with current protocol. MRD seems a valuable tool to estimate response, levels >0.1 % are associated with increased risk of death. However, better infection prevention and care are required to improve further the outcomes, especially those associated with higher MRD levels.

Capabilities of Software Package Gearacl for Design Gearings and Transmission Elements

Creation of a mathematical model of gearing operation belongs to one of the most knowledge-intensive fields of knowledge. Interdisciplinary research is being conducted to develop the model. For practical use, the results of this work are embodied in strength analysis standards. Due to the complexity of the processes occurring in gearings, performing analysis of one pair of gears today requires not only significant time costs from the engineer, but also a deep understanding of hundreds of pages of calculation techniques described by groups of interrelated standards. The calculation formulae include clarifying coefficients, the contribution and values of which are determined by a group of specialists developing the standard, based on research of analysis result coordination, experimental data and calculations performed using the finite element method. To perform the analysis, the designer needs knowledge about the principles of choosing coefficient values and their meaning. Performing the analysis of gearings according to the standard is a time-consuming process that can be correctly performed only by an engineer with experience in designing gearings. To facilitate the work of the engineer, software products both domestic and foreign were created. However, the trends of recent years require replacement of foreign software products. In 2022, the specialists of the Central Institute of Aviation Motors developed the Gearacl software package, which allows replacing foreign products in the volume required by the aviation industry enterprises in the field of cylindrical gearings, shafts and bearings analysis. Modern analysis methods have been introduced into the software package. This article is devoted to the capabilities of the Gearacl software package.

High‐performance vanadium oxide‐based aqueous zinc batteries: Organic molecule modification, challenges, and future prospects

AbstractAqueous Zn‐vanadium batteries have been attracting significant interest due to the high theoretical capacity, diverse crystalline structures, and cost‐effectiveness of vanadium oxide cathodes. Despite these advantages, challenges such as low redox potential, sluggish reaction kinetics, and vanadium dissolution lead to inferior energy density and unsatisfactory lifespan of vanadium oxide cathodes. Addressing these issues, given the abundant redox groups and flexible structures in organic compounds, this study comprehensively reviews the latest developments of organic‐modified vanadium‐based oxide strategies, especially organic interfacial modification, and pre‐intercalation. The review presents detailed analyses of the energy storage mechanism and multiple electron transfer reactions that contribute to enhanced battery performance, including boosted redox kinetics, higher energy density, and broadened lifespan. Furthermore, the review emphasizes the necessity of in situ characterization and theoretical calculation techniques for the further investigation of appropriate organic “guest” materials and matched redox couples in the organic‐vanadium oxide hybrids with muti‐energy storage mechanisms. The review also highlights strategies for Zn anode protection and electrolyte solvation regulation, which are critical for developing advanced Zn‐vanadium battery systems suitable for large‐scale energy storage applications.

A HYBRID MEREC-TOPSIS APPROACH FOR THE IMPROVEMENT OF PHYSICAL VAPOUR DEPOSITED TITANIUM CARBO-NITRIDE COATING

Titanium carbo-nitride (TiCN) comes under the metal nitride group which can provide a combined property of titanium carbide (TiC) and titanium nitride (TiN) coating. TiCN Coating possess an excellent mechanical and tribological, properties which leads its application in many industries particularly in the Automotive and aerospace industries. TiCN films can be very hard and strong based on the composition and synthesis process. Physical Vapor Deposition (PVD) technique is widely used for the preparation of thin film coating because of its ability to precisely control the composition and thickness of the coatings. The properties of the developed coating significantly affect by the PVD process parameters and their levels. Multi-Criteria Decision Making (MCDM) methods are widely used in many sectors for the selection of process parameters based upon some specific criteria. In the present work TiCN coatings were synthesized by using one of the most widely used PVD method called magnetron sputtering. L16 orthogonal array was used as a design of experiment for the experimental work by varying the sputtering process parameters like bias voltage, N2 flow rate and substrate to target distance. After the synthesis, the developed films were tested using atomic force microscopy (AFM), Scanning electron microscopy (SEM), and Nanoindentation. From the characterization three response parameters such as hardness (H), Modulus of elasticity (E) and surface roughness (Ra) of the coating has been considered. A hybrid method based on improved removal effects of criteria- technique for order performance by similarity to ideal solution (MEREC-TOPSIS) approach has been considered for the for the process parameters selection. The results have also been compared with other weight calculation techniques. In all the cases it is observed that experiment no 16 and 15 have got the 1st and second rank respectively. However, experiment no 1 is the last rank in all the cases. From the correlation analysis it is found a strong positive correlation between MEREC-TOPSIS and other methods. The method provides a significant advancement in the selection of optimal parameters, ensuring enhanced coating properties crucial for industrial applications.

Profitability Indicators: Critical Analysis and Applicability in Modern Conditions

Constant variability of the external environment is one of the key features affecting the business activity of domestic organizations and generates the need for constant updating of managers’ professional skills. The issues of assessment efficiency of commercial companies are always relevant not only for owners, but also for managers, employees and other stakeholders. In the conditions of economic instability, the interest to the indicators of organizations’ efficiency increases and, accordingly, their clarification and adjustment is required. and adjustment. The purpose of the study is to summarize the profitability indicators depending on the goal-setting of the participants of commercial organizations and to establish the possibility of using these indicators to assess the effectiveness of the company’s activities. Many years of experience of the authors of this article in the field of business valuation allowed to systematize the techniques of calculation of the main profitability indicators, to present an updated system of their grouping, as well as to classify the factors affecting them. Also, theoretical approaches to the calculation of invested capital were generalized in the course of the work. The research applied the methods of analysis, comparison, synthesis, classification, collection and generalization, logic, graphical and tabular display of information. Theoretical significance of the obtained results consists in the development of the methodology of value-oriented management in order to actualize and adapt the algorithms for calculating profitability indicators to domestic conditions, taking into account the interests of the participants of the organization. The practical significance of the work consists in the development of methods for assessing the performance indicators of the company, which can be used in the corporate governance of commercial structures, as well as in making management decisions by stakeholders.

Feasibility Study of Technology Footwork Ability Test on National Disability Badminton Athletes

Technological advances in sports testing and measurement are expanding, but there is a notable gap in research focused on physical conditioning tests for athletes with disabilities. This study aims to evaluate the effectiveness of footwork ability test technology for para badminton athletes. A quantitative descriptive design was employed, involving trials with both the footwork ability test technology and conventional methods. The subjects were National Para Badminton Athletes of Malaysia, selected through purposive sampling for their relevance to the research objectives. The study utilized a footwork ability test device, whose validity and reliability were assessed in comparison to conventional tests. Data were analyzed using percentage calculation techniques to determine effectiveness and error rates. Results indicate that the footwork ability test technology achieved an effectiveness rate of 97.1%, demonstrating superior performance with a lower error rate than conventional tests. This indicates the technology's suitability for athletes with disabilities, including those categorized as lower standing, upper standing, and short stature. The findings suggest significant potential for broader application in various sports disciplines. Future research should explore the technology's adaptability to different sports and environmental conditions, contributing to more inclusive and advanced training methodologies for athletes with disabilities.