Journal of Applied Mathematics最新文献_第3页

Nonclassical Parametric Variational Technique to Manipulability Control of a Serial-Link Robot That Is Used in Treatment of Femoral Shaft Fractures 非经典参数变分技术在治疗股骨干骨折的串联机器人可操作性控制中的应用

Journal of Applied Mathematics Pub Date : 2023-10-28 DOI: 10.1155/2023/5575131

Ghazwa F. Abd

{"title":"Nonclassical Parametric Variational Technique to Manipulability Control of a Serial-Link Robot That Is Used in Treatment of Femoral Shaft Fractures","authors":"Ghazwa F. Abd","doi":"10.1155/2023/5575131","DOIUrl":"https://doi.org/10.1155/2023/5575131","url":null,"abstract":"Robot-assisted intramedullary nailing is a minimally invasive surgical procedure commonly used to treat femur fractures. Despite its benefits, there are several disadvantages associated with this technique, such as frequent malalignment, physical fatigue, and excessive radiation exposure for medical personnel. Therefore, it is crucial to ensure that robotic surgery for fracture reduction is precise and safe. Precise calculation and regulation of the robot’s reduction force are of utmost importance. In this study, we propose a manipulator that utilises robot assistance and indirect contact with the femur to effectively reduce fractures in the shaft. The dynamics of the reduction robot are analysed using the implicit function theorem, which allows us to address the reduced problem. A parametric approach is presented to tackle the initial algebraic constraints, enabling the approximation of the state-space solution while simultaneously controlling the class of constraints in a multiway manner. This approach simplifies the problem from an infinite-dimensional one to a finite-dimensional one, leading to an approximate solution obtained by solving a set of control linear algebraic equations. The proposed robotic-assisted system enhances fracture repositioning while reducing radiation exposure for both the patient and the medical staff. Through numerical results and their practical application, we have developed an efficient method that yields positive outcomes.","PeriodicalId":49251,"journal":{"name":"Journal of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136158332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring the Benefits of Representing Multiplayer Game Data in a Coordinate System 探讨用坐标系统表示多人游戏数据的好处

Journal of Applied Mathematics Pub Date : 2023-10-28 DOI: 10.1155/2023/9999615

Mekdad Slime, Mohammed El Kamli, Abdellah Ould Khal

{"title":"Exploring the Benefits of Representing Multiplayer Game Data in a Coordinate System","authors":"Mekdad Slime, Mohammed El Kamli, Abdellah Ould Khal","doi":"10.1155/2023/9999615","DOIUrl":"https://doi.org/10.1155/2023/9999615","url":null,"abstract":"In the realm of game theory, a range of mathematical approaches exists for the representation of game data, with the extensive form (depicted as a game tree) and the normal form (illustrated as a payoff matrix) standing out as the most prevalent. However, a significant drawback associated with these approaches is their limited scalability. As the number of players or their strategic options increases, these techniques progressively lose their feasibility and become less practical for meaningful analysis. The present work proposes an alternative approach that significantly enhances the representation of data in two- or three-player games. Within this framework, the conventional payoff matrix is substituted with a payoff coordinate system, employing a coordinate plane for two-player games and a coordinate space for three-player games. This approach offers numerous advantages when compared to other methods. For instance, the Nash equilibrium can be readily identified within a game without requiring an extensive duration to exhaustively examine all strategies for its determination. By employing this approach, the representation of game data becomes more convenient and efficient, making it easier to analyze and comprehend the underlying strategies employed by players.","PeriodicalId":49251,"journal":{"name":"Journal of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136159324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study of Deep Learning Neural Network Algorithms and Genetic Algorithms for FJSP FJSP的深度学习神经网络算法和遗传算法研究

Journal of Applied Mathematics Pub Date : 2023-10-25 DOI: 10.1155/2023/4573352

Xiaofeng Shang

{"title":"A Study of Deep Learning Neural Network Algorithms and Genetic Algorithms for FJSP","authors":"Xiaofeng Shang","doi":"10.1155/2023/4573352","DOIUrl":"https://doi.org/10.1155/2023/4573352","url":null,"abstract":"Flexible job-shop scheduling problem (FJSP) is a new research hotspot in the field of production scheduling. To solve the multiobjective FJSP problem, the production of flexible job shop can run normally and quickly. This research takes into account various characteristics of FJSP problems, such as the need to ensure the continuity and stability of processing, the existence of multiple objectives in the whole process, and the constant complexity of changes. It starts with deep learning neural networks and genetic algorithms. Long short-term memory (LSTM) and convolutional neural networks (CNN) are combined in deep learning neural networks. The new improved algorithm is based on the combination of deep learning neural networks LSTM and CNN with genetic algorithm (GA), namely, CNN-LSTM-GA algorithm. Simulation results showed that the accuracy of the CNN-LSTM-GA algorithm was between 85.2% and 95.3% in the test set. In the verification set, the minimum accuracy of the CNN-LSTM-GA algorithm was 84.6%, both of which were higher than the maximum accuracy of the other two algorithms. In the FJSP simulation experiment, the AUC value of the CNN-LSTM-GA algorithm was 0.92. After 40 iterations, the F1 value of the CNN-LSTM-GA algorithm remained above 0.8, which was significantly higher than the other two algorithms. CNN-LSTM-GA is superior to the other two algorithms in terms of prediction accuracy and overall performance of FJSP. It is more suitable for solving the discrete manufacturing job scheduling problem with FJSP characteristics. This study significantly raises the utilisation rate of the assembly shop’s equipment, optimises the scheduling of FJSP, and fully utilises each processing device’s versatile characteristics, which are quite useful for the production processes of domestic vehicle manufacturing companies.","PeriodicalId":49251,"journal":{"name":"Journal of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134973616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modified

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-Parameterized Differential Transform Method for Solving Nonlinear Generalized Gardner Equation 求解非线性广义Gardner方程的改进α参数化微分变换方法

Journal of Applied Mathematics Pub Date : 2023-10-23 DOI: 10.1155/2023/3339655

Abdulghafor M. Al-Rozbayani, Ahmed Farooq Qasim

{"title":"Modified <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M1\"> <mi>α</mi> </math>-Parameterized Differential Transform Method for Solving Nonlinear Generalized Gardner Equation","authors":"Abdulghafor M. Al-Rozbayani, Ahmed Farooq Qasim","doi":"10.1155/2023/3339655","DOIUrl":"https://doi.org/10.1155/2023/3339655","url":null,"abstract":"In this article, we present a novel enhancement to the <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M2\"> <mi>α</mi> </math> -parameterized differential transform method (PDTM) for solving nonlinear boundary value problems. The proposed method is applied to solve the generalized Gardner equation by utilizing genetic algorithms to obtain optimal parameter values. Our proposed approach extends the general differential transformation method, allowing for the use of various values for the coefficient <math xmlns=\"http://www.w3.org/1998/Math/MathML\" id=\"M3\"> <mi>α</mi> </math> . Our solution procedure offers a distinct advantage by allowing the original differential transformation method to be divided into multiple steps, thereby illustrating specific solution properties for nonlinear boundary value problems. Additionally, possible alternative solutions based on varying parameter values are also explored and discussed. The results with those obtained through the DTM method and exact solutions are compared to confirm the accuracy of our method and its efficiency in reaching the exact solution quickly.","PeriodicalId":49251,"journal":{"name":"Journal of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135366256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of the Prox Penalty and Bregman Algorithms for Image Denoising Prox罚算法与Bregman算法在图像去噪中的比较分析

Journal of Applied Mathematics Pub Date : 2023-10-20 DOI: 10.1155/2023/6689311

Soulef Bougueroua, Nourreddine Daili

引用次数: 0

Detection of COVID-19 Using Protein Sequence Data via Machine Learning Classification Approach 基于机器学习分类方法的蛋白质序列数据检测COVID-19

Journal of Applied Mathematics Pub Date : 2023-09-28 DOI: 10.1155/2023/9991095

Siti Aminah, Gianinna Ardaneswari, Mufarrido Husnah, Ghani Deori, Handi Bagus Prasetyo

{"title":"Detection of COVID-19 Using Protein Sequence Data via Machine Learning Classification Approach","authors":"Siti Aminah, Gianinna Ardaneswari, Mufarrido Husnah, Ghani Deori, Handi Bagus Prasetyo","doi":"10.1155/2023/9991095","DOIUrl":"https://doi.org/10.1155/2023/9991095","url":null,"abstract":"The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019 resulted in the COVID-19 pandemic, necessitating rapid and accurate detection of pathogens through protein sequence data. This study is aimed at developing an efficient classification model for coronavirus protein sequences using machine learning algorithms and feature selection techniques to aid in the early detection and prediction of novel viruses. We utilized a dataset comprising 2000 protein sequences, including 1000 SARS-CoV-2 sequences and 1000 non-SARS-CoV-2 sequences. Feature extraction provided 27 essential features representing the primary structural data, achieved through the Discere package. To optimize performance, we employed machine learning classification algorithms such as K-nearest neighbor (KNN), XGBoost, and Naïve Bayes, along with feature selection techniques like genetic algorithm (GA), LASSO, and support vector machine recursive feature elimination (SVM-RFE). The SVM-RFE+KNN model exhibited exceptional performance, achieving a classification accuracy of 99.30%, specificity of 99.52%, and sensitivity of 99.55%. These results demonstrate the model’s efficacy in accurately classifying coronavirus protein sequences. Our research successfully developed a robust classification model capable of early detection and prediction of protein sequences in SARS-CoV-2 and other coronaviruses. This advancement holds great promise in facilitating the development of targeted treatments and preventive strategies for combating future viral outbreaks.","PeriodicalId":49251,"journal":{"name":"Journal of Applied Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135385837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Mathematical Model of the Dynamics of Coffee Berry Disease 咖啡浆果病动态的数学模型

Journal of Applied Mathematics Pub Date : 2023-09-27 DOI: 10.1155/2023/9320795

H. O. Nyaberi, W. N. Mutuku, D. M. Malonza, G. W. Gachigua

引用次数: 0

Subspace-Based Anomaly Detection for Large-Scale Campus Network Traffic 基于子空间的大规模校园网流量异常检测

Journal of Applied Mathematics Pub Date : 2023-09-16 DOI: 10.1155/2023/8489644

Xiaofeng Zhao, Qiubing Wu

引用次数: 0

Mathematical Modeling for Optimal Management of Human Resources in Banking Sector of Bangladesh 孟加拉银行业人力资源优化管理的数学模型

Journal of Applied Mathematics Pub Date : 2023-09-13 DOI: 10.1155/2023/1321365

Uzzwal Kumar Mallick, Md. Haider Ali Biswas

引用次数: 0

Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm 基于AHP-KNN算法的农业人才培养模型构建与应用

Journal of Applied Mathematics Pub Date : 2023-09-11 DOI: 10.1155/2023/5745955

Shubing Qiu, Yong Liu, Xiaohong Zhou

引用次数: 0