International Journal of Applied Mathematics and Computer Science最新文献

A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers 从解释者集合产生的反事实集合中选择解释的多标准方法

International Journal of Applied Mathematics and Computer Science Pub Date : 2024-03-20 DOI: 10.61822/amcs-2024-0009

Ignacy Stkepka, Mateusz Lango, Jerzy Stefanowski

引用次数: 0

Assessment Measures of an Ensemble Classifier Based on the Distributivity Equation to Predict the Presence of Severe Coronary Artery Disease 基于分布方程的集合分类器预测严重冠状动脉疾病的评估措施

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0026

Ewa Rak, A. Szczur, Jan G. Bazan, S. Bazan-Socha

{"title":"Assessment Measures of an Ensemble Classifier Based on the Distributivity Equation to Predict the Presence of Severe Coronary Artery Disease","authors":"Ewa Rak, A. Szczur, Jan G. Bazan, S. Bazan-Socha","doi":"10.34768/amcs-2023-0026","DOIUrl":"https://doi.org/10.34768/amcs-2023-0026","url":null,"abstract":"Abstract The aim of this study is to apply and evaluate the usefulness of the hybrid classifier to predict the presence of serious coronary artery disease based on clinical data and 24-hour Holter ECG monitoring. Our approach relies on an ensemble classifier applying the distributivity equation aggregating base classifiers accordingly. Such a method may be helpful for physicians in the management of patients with coronary artery disease, in particular in the face of limited access to invasive diagnostic tests, i.e., coronary angiography, or in the case of contraindications to its performance. The paper includes results of experiments performed on medical data obtained from the Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland. The data set contains clinical data, data from Holter ECG (24-hour ECG monitoring), and coronary angiography. A leave-one-out cross-validation technique is used for the performance evaluation of the classifiers on a data set using the WEKA (Waikato Environment for Knowledge Analysis) tool. We present the results of comparing our hybrid algorithm created from aggregation with the distributive equation of selected classification algorithms (multilayer perceptron network, support vector machine, k-nearest neighbors, naïve Bayes, and random forests) with themselves on raw data.","PeriodicalId":502322,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"23 1","pages":"361 - 377"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139345513","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

Constant Q–Transform–Based Deep Learning Architecture for Detection of Obstructive Sleep Apnea 用于检测阻塞性睡眠呼吸暂停的基于恒定 Q 变换的深度学习架构

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0036

Usha Rani Kandukuri, A. J. Prakash, Kiran Kumar Patro, B. Neelapu, R. Tadeusiewicz, Paweł Pławiak

{"title":"Constant Q–Transform–Based Deep Learning Architecture for Detection of Obstructive Sleep Apnea","authors":"Usha Rani Kandukuri, A. J. Prakash, Kiran Kumar Patro, B. Neelapu, R. Tadeusiewicz, Paweł Pławiak","doi":"10.34768/amcs-2023-0036","DOIUrl":"https://doi.org/10.34768/amcs-2023-0036","url":null,"abstract":"Abstract Obstructive sleep apnea (OSA) is a long-term sleep disorder that causes temporary disruption in breathing while sleeping. Polysomnography (PSG) is the technique for monitoring different signals during the patient’s sleep cycle, including electroencephalogram (EEG), electromyography (EMG), electrocardiogram (ECG), and oxygen saturation (SpO2). Due to the high cost and inconvenience of polysomnography, the usefulness of ECG signals in detecting OSA is explored in this work, which proposes a two-dimensional convolutional neural network (2D-CNN) model for detecting OSA using ECG signals. A publicly available apnea ECG database from PhysioNet is used for experimentation. Further, a constant Q-transform (CQT) is applied for segmentation, filtering, and conversion of ECG beats into images. The proposed CNN model demonstrates an average accuracy, sensitivity and specificity of 91.34%, 90.68% and 90.70%, respectively. The findings obtained using the proposed approach are comparable to those of many other existing methods for automatic detection of OSA.","PeriodicalId":502322,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"46 1","pages":"493 - 506"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139343702","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

Computing a Mechanism for a Bayesian and Partially Observable Markov Approach 计算贝叶斯和部分可观测马尔可夫方法的机制

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0034

J. Clempner, A. Poznyak

引用次数: 0

Applications of the Fractional Sturm–Liouville Difference Problem to the Fractional Diffusion Difference Equation 分数斯特姆-利乌维尔差分问题在分数扩散差分方程中的应用

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0025

A. Malinowska, T. Odzijewicz, A. Poskrobko

引用次数: 0

Spike Patterns and Chaos in a Map–Based Neuron Model 基于图谱的神经元模型中的尖峰模式与混沌

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0028

Piotr Bartłomiejczyk, Frank Llovera Trujillo, Justyna Signerska-Rynkowska

引用次数: 0

On the Analysis of a Mathematical Model of CAR–T Cell Therapy for Glioblastoma: Insights from a Mathematical Model 关于胶质母细胞瘤 CAR-T 细胞疗法数学模型的分析：数学模型的启示

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0027

M. Bodnar, U. Foryś, M. Piotrowska, Mariusz Bodzioch, J. A. Romero-Rosales, J. Belmonte-Beitia

{"title":"On the Analysis of a Mathematical Model of CAR–T Cell Therapy for Glioblastoma: Insights from a Mathematical Model","authors":"M. Bodnar, U. Foryś, M. Piotrowska, Mariusz Bodzioch, J. A. Romero-Rosales, J. Belmonte-Beitia","doi":"10.34768/amcs-2023-0027","DOIUrl":"https://doi.org/10.34768/amcs-2023-0027","url":null,"abstract":"Abstract Chimeric antigen receptor T (CAR-T) cell therapy has been proven to be successful against different leukaemias and lymphomas. Its success has led, in recent years, to its use being tested for different solid tumours, including glioblastoma, a type of primary brain tumour, characterised by aggressiveness and recurrence. This paper presents an analytical study of a mathematical model describing the competition of CAR-T and glioblastoma tumour cells, taking into account their immunosuppressive capacity. The model is formulated in a general way, and its basic properties are investigated. However, most of the analysis considers the model with exponential tumour growth, assuming this growth type for simplicity. The existence and stability of steady states are studied, and the subsequent focus is on two different types of treatment: constant and periodic. Finally, protocols for CAR-T cell therapy of glioblastoma are numerically derived; these are aimed at preventing the tumour from reaching a critical size and at prolonging the patients’ survival time as much as possible. The analytical and numerical results provide theoretical support for the treatment of glioblastoma using CAR-T cells.","PeriodicalId":502322,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"4 1","pages":"379 - 394"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139344841","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

Investigation of the Lombard Effect Based on a Machine Learning Approach 基于机器学习方法的伦巴第效应研究

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0035

G. Korvel, P. Treigys, Krzysztof Kakol, Bożena Kostek

{"title":"Investigation of the Lombard Effect Based on a Machine Learning Approach","authors":"G. Korvel, P. Treigys, Krzysztof Kakol, Bożena Kostek","doi":"10.34768/amcs-2023-0035","DOIUrl":"https://doi.org/10.34768/amcs-2023-0035","url":null,"abstract":"Abstract The Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters related to speech changes produced by the Lombard effect are extracted. Mid-term statistics are built upon the parameters and used for the self-similarity matrix construction. They constitute input data for a convolutional neural network (CNN). The self-similarity-based approach is then compared with two other methods, i.e., spectrograms used as input to the CNN and speech acoustic parameters combined with the k-nearest neighbors algorithm. The experimental investigations show the superiority of the self-similarity approach applied to Lombard effect detection over the other two methods utilized. Moreover, small standard deviation values for the self-similarity approach prove the resulting high accuracies.","PeriodicalId":502322,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"113 1","pages":"479 - 492"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139344077","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 Method of Lower and Upper Solutions for Control Problems and Application to a Model of Bone Marrow Transplantation 控制问题的上下解法及在骨髓移植模型中的应用

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0029

L. Parajdi, Radu Precup, Ioan Ştefan Haplea

引用次数: 0

Nonsmooth Optimization Control Based on a Sandwich Model with Hysteresis for Piezo–Positioning Systems 基于带滞后的三明治模型的压电定位系统非平滑优化控制

International Journal of Applied Mathematics and Computer Science Pub Date : 2023-09-01 DOI: 10.34768/amcs-2023-0033

Sen Yang, Yonghong Tan, Ruili Dong, Qingyuan Tan

{"title":"Nonsmooth Optimization Control Based on a Sandwich Model with Hysteresis for Piezo–Positioning Systems","authors":"Sen Yang, Yonghong Tan, Ruili Dong, Qingyuan Tan","doi":"10.34768/amcs-2023-0033","DOIUrl":"https://doi.org/10.34768/amcs-2023-0033","url":null,"abstract":"Abstract A nonsmooth optimization control (NOC) based on a sandwich model with hysteresis is proposed to control a micropositioning system (MPS) with a piezoelectric actuator (PEA). In this control scheme, the hysteresis phenomenon inherent in the PEA is described by a Duhem submodel embedded between two linear dynamic submodels that describe the behavior of the drive amplifier and the flexible hinge with load, respectively, thus constituting a sandwich model with hysteresis. Based on this model, a nonsmooth predictor for sandwich systems with hysteresis is constructed. To avoid the complicated online search for the optimal value of the generalized gradient at a nonsmooth point, the method of the so-called weighted estimation of generalized gradient is proposed. In order to compensate for the model error caused by model uncertainty, a model error compensator (MEC) is integrated into the online optimization control strategy. Afterwards, the stability of the control system is analyzed based on Lyapunov’s theory. Finally, the proposed NOC-MEC method is verified on an MPS with a PEA, and the corresponding experimental results are presented.","PeriodicalId":502322,"journal":{"name":"International Journal of Applied Mathematics and Computer Science","volume":"22 1","pages":"449 - 461"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139345067","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