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Advancing the modeling of evaporation and salt precipitation is essential in CO2 storage processes in aquifers. OpenFOAM provides a platform for computational fluid dynamics (CFD) modeling with its open-source C++ object-oriented architecture that can especially be used in the development of fluid flow models in porous media. Some OpenFOAM packages have been developed in this area, and their codes are available for use. Despite this, the existing OpenFOAM literature does not include a model that incorporates multicomponent interactions in multi-phase flow systems, referred to as compositional modeling, at the Darcy scale. This existing gap is addressed in this paper, where a new simple model in OpenFOAM is introduced that aims to model the interaction of CO2 and H2O components in CO2 storage processes in aquifers at the Darcy scale. The model, named compositionalIGFoam, incorporates a compositional solver by extending the impesFoam solver of the porousMultiphaseFoam package, while assuming some simplifications, to account for CO2/water mutual dissolution, relevant to carbon capture and storage (CCS) processes in aquifers. The functionality of the compositionalIGFoam solver was assessed by showcasing its ability to reproduce the outcomes of existing examples. In addition to that, the process of gas injection into a water-saturated core sample was simulated using the developed model to mimic CO2 injection into aquifers. The CMG-GEM commercial compositional simulator was used to compare its results with the coreflood model of this study. Phenomenal agreement was achieved with the GEM model, showing only 1.8% and 0.4% error for both components. This confirms the accuracy and reliability of the developed model. In conclusion, this study enhances the state of the art in porous media modeling using OpenFOAM 10, providing a valuable tool for examining fluid interactions in subsurface environments, especially within the context of CCS processes. [ABSTRACT FROM AUTHOR]

The ability to predict gas emissions accurately is pivotal in managing gas control and ensuring safe mining operations. Existing internationally acknowledged gas control and prediction software does not cater to the specific conditions in Chinese coal mines. Hence, this paper introduces an object-oriented programming method to design a software tool for calculating the total gas emission quantity using the MATLAB application program designer runtime environment. The software incorporates an algorithm, data structure, framework, and module functions, all of which enable seamless integration and visualization of gas emission calculation software. This software tool mitigates the inefficiencies and inaccuracies associated with manual, different-source forecast methods. Based on the field data of the Hulonggou Coal Mine in Shanxi province, this technical software was used to predict the gas emission of the mine. The research results show that the predicted value of the technical software is close to the actual measured value. The differing estimates of the working face and coal mine output primarily account for the deviation between the tool's predicted gas emission value and the field-measured value. The underlying design logic of this technical software determines that it has good adaptability to mines with clear mining technology parameters and gas geological parameters. This study provides a valuable method for researchers and engineers seeking to improve gas emission calculation efficiency. [ABSTRACT FROM AUTHOR]

The accurate representation of objects holds pivotal significance in the realm of panoptic segmentation. Presently, prevalent object representation methodologies, including box-based, keypoint-based and query-based techniques, encounter a challenge known as the 'representation confusion' issue in specific scenarios, often resulting in the mislabeling of instances. In response, this paper introduces Convex Object Representation (COR), a straightforward yet highly effective approach to address this problem. COR leverages a CNN-based Euclidean Distance Transform to convert the target instance into a convex heatmap. Simultaneously, it offers a parallel embedding method for encoding the object. Subsequently, COR characterizes objects based on the distinctive embedding vectors of their convex vertices. This paper seamlessly integrates COR into a state-of-the-art query-based panoptic segmentation framework. Experimental findings validate that COR successfully mitigates the representation confusion predicament, enhancing segmentation accuracy. The COR-augmented methods exhibit notable improvements of +1.3 and +0.7 points in PQ on the Cityscapes validation and MS COCO panoptic 2017 validation datasets, respectively. [ABSTRACT FROM AUTHOR]

The object of this research is the process of compiler optimization, as it is essential in modern software development, particularly in functional programming languages like Lambda Calculus. Optimization strategies directly impact interpreter and compiler performance, influencing resource efficiency and program execution. While functional programming compilers have garnered less attention regarding optimization efforts than their object-oriented counterparts, Lambda Calculus’s complexity poses unique challenges. Bridging this gap requires innovative approaches like leveraging machine learning techniques to enhance optimization strategies. This study focuses on leveraging machine learning to bridge the optimization gap in functional programming, particularly within the context of Lambda Calculus. This study delves into the extraction features from Lambda terms related to reduction strategies by applying machine learning. Previous research has explored various approaches, including analyzing reduction step complexities and using sequence analysis Artificial Neural Networks (ANNs) with simplified term representation. This research aims to develop a methodology for extracting comprehensive term data and providing insights into optimal reduction priorities by employing Large Language Models (LLMs). Tasks were set to generate embeddings from Lambda terms using LLMs, train ANN models to predict reduction steps, and compare results with simplified term representations. This study employs a sophisticated blend of machine learning algorithms and deep learning models as a method of analyzing and predicting optimal reduction paths in Lambda Calculus terms. The result of this study is a method that showed improvement in determining the number of reduction steps by using embeddings. Conclusions: The findings of this research offer significant implications for further advancements in compiler and interpreter optimization. This study paves the way for future research to enhance compiler efficiency by demonstrating the efficacy of employing LLMs to prioritize normalization strategies. Using machine learning in functional programming optimization opens avenues for dynamic optimization strategies and comprehensive analysis of program features. [ABSTRACT FROM AUTHOR]

Obtaining geo-data and attributes of spatial units from heterogeneous database systems with different data formats for the same land properties is still one of the main problems. The emerging technologies, such as decentralized databases, distributed networks and big data powered by blockchain, can potentially improve land registration processes. In this article, I developed a data model for a geospatially enabled blockchain infrastructure, using an object-oriented architecture model. Such a model can better find spatio-temporal patterns of land transactions and better query time-varying locations of land properties. Additionally, it will make the land registry system secure and protect privacy. [ABSTRACT FROM AUTHOR]

This paper focuses on embedded system modeling, proposing a solution to obtain a refined net via the refinement operation of an extended Petri net. Object-oriented technology and Petri net with inhibitor-arcs-based representation for embedded systems (PIRES+) are combined to obtain an object-oriented PIRES+ (OOPIRES+). A gateway refinement method of OOPIRES+ is proposed, and the preservation of the liveness, boundedness, reachability, functionality, and timing of the refined net system is investigated. The modeling analysis of a smart home system is taken as an example to verify the effectiveness of the refinement method. The results can provide an effective way for the investigation of the refined properties of a Petri net system and a favorable means for large-scale complex embedded system modeling, which has broad application prospects. [ABSTRACT FROM AUTHOR]

Copyright of Scientific Bulletin of National Mining University is the property of National Mining University, State Higher Educational Institution and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The investigation presented in this text is the study of object detection algorithms in the task of analyzing images of baggage and hand luggage. A modified version of the YOLOv5 convolutional neural network with additional rechecking based on the VGG-19 network is proposed. The modification is based on transfer learning from the available images. A comparison is made with other known algorithms. The article shows that the application of the proposed model made it possible to achieve the value of the mean average recall (mAR) at the level of 87% for dangerous objects of five classes. [ABSTRACT FROM AUTHOR]

Embedded systems are widely used in automotive electronics, smart home, smart medical, aerospace and other fields. Aiming at the problem of formal modeling and verification analysis of embedded systems, a solution is proposed using extended Petri net reduction operations. Petri net based representation for embedded system (PRES+) and the object-oriented technology are combined to obtain the object-oriented PRES+ (OOPRES+). Two kinds of subnet reduction rules of OOPRES+ are presented. The preservation of boundedness and liveness of the reduction net system has been investigated to alleviate the problem of state space explosion of OOPRES+. The modeling and analysis of the embedded control system of a smart restaurant is used as an example to verify the effectiveness of the subnet reduction rules. Results obtained can provide an effective way to examine the reduction property of Petri net systems, and present a powerful means to model and verify the large-scale complex embedded systems. [ABSTRACT FROM AUTHOR]

Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces a major redesign of SimOpt, a testbed of simulation-optimization (SO) problems and solvers. The testbed promotes the empirical evaluation and comparison of solvers and aims to accelerate their development. Relative to previous versions of SimOpt, the redesign ports the code to an object-oriented architecture in Python; uses an implementation of the MRG32k3a random number generator that supports streams, substreams, and subsubstreams; supports the automated use of common random numbers for ease and efficiency; includes a powerful suite of plotting tools for visualizing experiment results; uses bootstrapping to obtain error estimates; accommodates the use of data farming to explore simulation models and optimization solvers as their input parameters vary; and provides a graphical user interface. The SimOpt source code is available on a GitHub repository under a permissive open-source license and as a Python package. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Funding: This work was supported by the National Science Foundation [Grant CMMI-2035086]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1273) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2022.0011) at (http://dx.doi.org/10.5281/zenodo.7468744). [ABSTRACT FROM AUTHOR]

This work aims to study and develop methods and tools for analyzing video-EEG monitoring of delayed cerebral ischemia after subarachnoid haemorrhage. A study was made of methods and algorithms for processing video images, which are supposed to be used to recognize life events and medical care for a patient, which can lead to artefacts in the patient's EEG records. An approach to video monitoring of the patient was proposed and tested on real video monitoring data using object-oriented logic programming methods in combination with neural network methods for image analysis. [ABSTRACT FROM AUTHOR]

This paper reports the development of an architecture and software implementation of the library of classes for the finite-element analysis of problems in the theory of elasticity with an open-source code. The practical necessity of such systems is due to the fact that in modern equipment there are new types of materials whose structural elements' calculation has certain features. As a result, it is necessary to update the relevant scientific software or even devise a new one. A flexible software architecture is designed to reduce the time and complexity of such updates. Existing implementations of the method of finite elements with open source have been analyzed: it was revealed that there are no systems aimed at the most flexible and user-friendly architecture. The system of abstract classes proposed in the current work corresponds to known SOLID principles of object-oriented design and makes it possible to scale the already developed analysis program for new tasks in an easy and understandable way. To test the quality of the developed system from the point of view of software engineering, the maintainability index and cyclomatic complexity code metrics were used. The values of these metrics for the modules of the PyFEM system core vary in the following ranges: from 1 to 18 for the maintainability index, and from 22 to 100 for cyclomatic complexity. PyFEM testing was performed on the task of determining the stressed-strained state of the turbine rotor blade. Due to the ease of implementation, it was possible to build a set of effective and intuitive classes that make it possible to solve numerically the static and dynamic problems in the theory of elasticity. The developed class library can be used in the development of both universal and specialized software designed to analyze multiphysics problems. [ABSTRACT FROM AUTHOR]

Diabetes is among the socially significant diseases, which leads to high costs for the diagnosis and treatment of diabetes. Diagnosis and treatment of diabetes is currently one of the important tasks in medicine at the present stage of development of medical services. An important direction in the development of medical services for the population is the development and implementation of various problem-oriented information systems. Similar systems developed earlier did not cover the entire amount of heterogeneous information that is collected when diagnosing and prescribing the course of diabetes treatment, nor did they use technologies and cloud services as tools for Big Data. In this article, let’s make use of the predictive analytic to forecast and categorize the type of diabetes which offers an effective method for treating and curing patients at a reduced cost, with improved results such as affordability and availability. An information system platform has been developed and configured to manage the Hadoop cluster, as well as a non-relational database that uses and processes unstructured data in various formats. All experimental research, development of methods and algorithms, as well as solving computational problems were implemented using software languages for application development. The novelty lies in the research of distributed computing models that provide efficient execution of developed algorithms using the conceptual model of the processes of search, extraction and analysis of unstructured data in large data sets. The practical implementation of algorithms was carried out on the basis of methods of objectoriented programming and object-oriented databases. [ABSTRACT FROM AUTHOR]

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Managers have a deeper understanding of computer technology, network technology, and communication technology, which is also a necessary condition for the implementation of project management information. It plays an important role in improving the performance of regional resource-based industry and high-tech service industry. By analyzing the current situation of the company's project management, the project management and management processes are standardized and the management of project quality, progress, contract, and cost through the design system is completed, so that the various resources of the project can be effectively and rationally allocated and utilized. Information communication inside and outside the project is more convenient, smooth, and fast, and more standardized operating procedures can be carried out. This paper also improves the level of local government governance, shapes the cultural connotation of innovation, openness, and cooperation, and strengthens the cultivation and flow of social elements. A series of policy suggestions are put forward in building the capacity system of both sides of industrial integration, thus greatly improving the overall project management level and the company's decision-making and analysis ability, so as to achieve fine and precise management objectives. [ABSTRACT FROM AUTHOR]

One of the key tools in an organization's performance management is the goal tree, which is used for solving both direct and inverse problems. This research deals with goal setting based on a model of the future by presenting the goal and subgoal in the form of concrete quantitative and qualitative characteristics and stepwise formation of factors. A stepwise solution to a factor generation problem is considered on the basis of mathematical symmetry. This paper displays an algorithm for solving hierarchical inverse problems with constraints, which is based on recursively traversing the vertices that constitute the separate characteristics. Iterative methods, modified for the case of nonlinear models and the calculation of constraints, were used to generate solutions to the subproblems. To realize the algorithm, the object-oriented architecture, which simplifies the creation and modification of software, was elaborated. Computational experiments with five types of models were conducted, and the solution to a problem related to fast-food restaurant profit generation was reviewed. The metrics of remoteness from set values and t-statistics were calculated for the purpose of testing the received results, and solutions to the subproblems, with the help of a mathematical package using optimization models and a method of inverse calculations, were also provided. The results of computational experiments speak to the compliance of the received results with set constraints and the solution of separate subproblems with the usage of the mathematical package. The cases with the highest solution accuracy reached are specified. [ABSTRACT FROM AUTHOR]

In order to further promote the standardization of seismic performance design of bridge structures, one must ensure the quality of bridge design and improve design efficiency. First, based on the basic principle of the probabilistic pushover method, the randomness of the structural pushover curve is attributed to the randomness of plastic hinges. Second, the visualization of seismic performance of bridge structures based on the object-oriented technology is adopted. So that the randomness of seismic action can be considered in the analysis of seismic performance. Finally, the limit state equation of the seismic performance of the structure is used to evaluate the reliability of the seismic performance of the bridge in each limit state conveniently. The results show that the failure probability of the structure in each limit state is less than 0.5 under different basic accelerations from 0 to 0.4 g. The software method is simple in calculation and has a strong adaptability, avoiding the difficulty of seismic reliability analysis caused by large-scale simulation and large amount of calculation of traditional structures. Therefore, this method can be easily applied to the probabilistic analysis of seismic behavior of bridge structures under large earthquakes without evaporative deformation failure criterion. [ABSTRACT FROM AUTHOR]

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the agricultural ecosystem, it is necessary to grasp the differences of soil fertility and crop growth in time and space. With the rapid development of remote sensing and its popularization and application in social production practice, remote sensing has become a new way to obtain farmland information. At present, remote sensing means in the field of agroecosystem monitoring mainly include satellite remote sensing and unmanned aerial remote sensing. It can monitor and manage the agro-ecosystem environment in real time by acquiring remote sensing images. It can monitor the growth and identification of crops, pests, and diseases, and water supply, analysis timely, and effectivity for the spatial information provided by a feedback processing. But its performance needs to be improved. In this paper, the imaging methods and main features of remote sensing images are introduced in order to analyze the characteristics of agricultural ecosystem targets in remote sensing images. Then, based on object-oriented classification technology, a series of farmland images are preprocessed, segmented, and sparsely represented. Processing operations are used to study how to transform crop observation into crop and noncrop discrimination in remote sensing data. The research shows that the effective acquisition of crop image area and the remote sensing monitoring of crop farmland area can be achieved by processing the crop field map image obtained by remote sensing. [ABSTRACT FROM AUTHOR]

FEM solver is designed for shared memory architectures using an object-oriented paradigm. The FEM solver is divided into five major sections; these are a collection of mesh data, creating an object for each finite element, application of boundary conditions, assembly of a linear system of equations, and lastly a solver to calculate the solution for the system of linear equations. This work has focused on the study of multiple parallel implementations for each stage of the FEM solver. All the stages are implemented in C++ while each stage parallel regions are implemented using OpenMP. The data structures used in this work are also C++ objects implemented using STL containers, like sparse matrix used is constructed as two-layer nested binary trees where each internal tree represents a sparse row in a global matrix. These structures are used in every stage and have never been converted into more conventional matrix structures like CSR, etc. Finally, this work has shown the contribution of time for each stage and the amount of speedup achieved for them. Using 16 threads, the solver has attained a speedup of 5.21 for mesh having 2099201 unknowns and Poisson's equation. Two linear solvers Jacobi and CG are used which were consuming 95% of total solver time. The novelty of our work lies in the fact that this work focused on the implementation of Finite Element Application (FEA) using object-oriented programming for a shared memory architecture using OpenMP without considering conventional techniques of application speedup and specialized data structures like CSR, etc. [ABSTRACT FROM AUTHOR]

As such, the workshop has always been located in Italy, with the workshop Steering Committee constantly committed to involve every major Italian research group working on agents and multi-agent systems. The first Workshop "From Objects to Agents" (WOA) was held in Parma in May 2000. The OASIS ontology - An Ontology for Agent, Systems, and Integration of Services, presented in 2019 - pursues the behaviouristic approach to deliver a higher-level, semantic representation system as well as a communication protocol for agents and their commitments. [Extracted from the article]

Monitoring and analyzing land cover changes help to provide relevant information for the establishment of diagnostics and the preparation of environmental forecasts. The objective of this work is to apply an "object-oriented" classification method to three satellite images for monitoring and detecting land cover changes in the North of Ivory Coast. The landscape complexity of this environment and the low resolution of the images (30 m and 20 m) constitute an important limitation for conventional classification methods using the "pixel by pixel" approach. Two Land sat images TM/ETM + (1986; 2002) and a Sentinel-2 image (2019) were used in this study. The method developed for monitoring and detecting changes in land cover is carried out through 1) a classification of land cover using the «object-oriented» method based on fuzzy logic and 2) detecting changes of land cover by the post-classification method followed by the integration within a GIS of the three land cover maps obtained. The Kappa coefficients of the classified land cover maps were 86, 88, and 84.55% at the level of the 1986 images; 2002 and 2019, respectively. For the period of interest (33 years), we mapped and quantified land-use changes in this complex environmental context. Our study shows that the study area is undergoing major changes in land cover. The modifications identified in the study area concern all the topics of interest. [ABSTRACT FROM AUTHOR]

In this article, a 1-D electrostatic particle-in-cell (PIC) code is developed in an object-oriented paradigm with a computationally improved Poisson Solver. The performance of a Poisson solver plays a vital role in the computational cost of an electrostatic PIC. Therefore, to reduce the overall cost of the system, the Gauss–Seidel with a modified Chebyshev acceleration scheme is implemented as a Poisson solver. This method is designed by altering the standard Chebyshev acceleration scheme and executed with the optimal spectral radius. A separate program is written to optimize the spectral radius and to investigate its impact on the rate of convergence. Subsequently, a comparative analysis of this solver with the Gauss–Seidel, Gauss–Seidel with successive over-relaxation, and Gauss–Seidel with the Chebyshev acceleration factor is carried out, which implies that the modified solver converges fast. This article also provides the object-oriented architecture, including some key features of C++. The developed code is benchmarked with the two-stream instability, which evolved self-consistently. The performance of the overall code is evaluated by considering up to two million particles on two different CPUs and it is observed that the standard CPU is capable to solve the 1-D PIC problem. This code is implemented to study various characteristics of a finite-size photoplasma like plasma sheath formation, ion phase response, and electron dynamics when it is subjected to a uniform electric field. [ABSTRACT FROM AUTHOR]

The architecture of object-oriented information systems determines the use of modern and high-performance design methods, through which they can be properly modeled, based on the most appropriate modeling principles. Thus, Unified Modeling Language ensures the understanding of the semantics of the system by materializing the decisions taken in specifying its objective components. It also allows the development and use of visual modeling, as it ensures the approach to the development of complex information systems through attached diagrams (models) in the context of real world ideas. These models ensure the understanding of the semantics of these types of systems, the communication between the actors involved or analysts. In this context, this paper highlights the processes and activities specific to the design and implementation of object-oriented information systems through the Unified Modeling Language. [ABSTRACT FROM AUTHOR]

Stereo parking equipment has become an important means to solve the problem of parking difficulties, so it is necessary to study the planning of stereo parking equipment. This paper proposes an evaluation model for parking equipment planning and design, and verifies the feasibility of the model through an example. First, obtain the surface information of the planned area through object-oriented technology, and then complete the design layout of the area that can accommodate the most parking spaces according to the plan information map of the study area. Next, calculate the number of parking spaces required for each building in the area, and the number of available parking spaces within the maximum acceptable time for each building. Finally, compare the two to design the number and location of parking equipment. This method can quickly and accurately obtain the ground plane information map of the study area, while ensuring the capacity of parking spaces to meet the needs of users, it also improves the rationality and suitability of the planning and layout of stereo parking equipment, which can effectively guide the planning and construction of urban parking equipment. [ABSTRACT FROM AUTHOR]

This paper presents a quantitative pollutant discharge model for a typical molybdenum roasting plant, which combines the best available technology and object-oriented Petri net concepts. The proposed model was used to verify whether the best available technology in a molybdenum roasting process meeting the current pollutant emission limits by comparing the results of multiple simulations with online monitoring data records. Theoretical SO2 emission values were obtained via multiple simulations and compared with the online monitoring data of a typical molybdenum roasting plant to verify the authenticity of the online monitoring data. The relationship between the different operating parameters and desulfurization efficiency is established through analyzing the historical operation parameters of the enterprise and response surface method. It was found that the optimal operating parameters for the flue gas desulfurization system of this plant could be characterized by a flue gas temperature of 90–93 °C, a pH range of 6.20–6.30, and a liquid-gas ratio of 23–25 L/m3. [ABSTRACT FROM AUTHOR]

In order to improve the effect of human motion rehabilitation, a design model of human motion rehabilitation based on object-oriented technology is proposed. The entire model design process includes the following steps. First, a visual dynamic tracking model for human motion rehabilitation is established, and then a fuzzy PID (Proportion Integration Differentiation) superheterodyne control method is used to design the bone training control for human motion rehabilitation. The bone tracking control and adaptive training are under the control of object-oriented technology; it is analyzed by collecting human activity data during training. The 6-DOF kinematics problem of human movement rehabilitation is decomposed into the bone training control problem in the subspace. Combining object-oriented technology, visual blur recognition of human sports rehabilitation training, and adopting an adaptive kinematics model to design sports rehabilitation can improve the control convergence and global stability of the human sports rehabilitation process. The simulation results show that the method has a good overall steady state and the sports rehabilitation training effect is obvious. [ABSTRACT FROM AUTHOR]

On the premise of ensuring the animation effect and real-time performance, it is of great significance and value for large-scale group character animation synthesis how to reduce the disaster coincidence degree among various models of fast adaptive character animation synthesis. The realization method of object-oriented finite state machine is studied in detail. Finite state machine (FSM) is an efficient behavior modeling method, which can describe the behavioral decisions of fast adaptive character animation synthesis in a complex virtual environment. Based on the implementation defects of the finite state machine in the traditional structure, using object-oriented thinking, combined with the state design mode, we further studied a finite state machine implementation method based on object-oriented technology. This achieves code reuse and simple program maintenance. The effect is extensible and effectively overcomes the shortcomings of traditional character animation synthesis. Secondly, the multipath matching tracking algorithm of the greedy algorithm is studied to generate multiple candidate sets through multiple paths, and finally, the candidate set with the minimum residual error is selected as the estimated support set, so as to improve the reconstruction performance. Further, based on the idea of multipath, using the regularization method of the ROMP algorithm, the regularized multipath matching tracking RMSP algorithm is proposed. It uses the regularized subset method to generate multiple paths and chooses the path with the fastest residual reduction as the support set of this iteration. The simulation results show that the RMSP algorithm has better reconstruction performance than the SP algorithm. [ABSTRACT FROM AUTHOR]