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Bio-inspired method for segmenting the optic disc and macula in retinal images 视网膜图像中视盘和黄斑分割的仿生方法
IF 1.1 Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.10058751
A. Azar
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引用次数: 0
Large-scale orthogonal integer wavelet transform features-based active support vector machine for multi-class face recognition 基于大尺度正交整数小波变换特征的多类别人脸识别主动支持向量机
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133036
Tanvi Dalal, Jyotsna Yadav
Support vector machines are widely utilised in the field of Face Recognition (FR) but it suffers from the drawback of high-computational time. In proposed work, new active set strategy is utilised for support vector machines on Integer Wavelet Transform (IWT) based large scale facial features with low-computational time. Lifting scheme-based significant localised wavelet features are extracted using IWT based on orthogonal wavelets. Large Scale Orthogonal-IWT (LSOI) features with maximum covariance are then projected into eigen space from where robust training and testing features are selected. For classification of data, Active Support Vector Machine (ASVM) based machine learning technique is utilised which generates a less complex procedure compared to traditional support vector machine. ASVM aims to solve a fixed number of linear equations for One-vs-One (OVO) and One-vs-All (OVA) multiclass FR. Extensive experiments on Yale, ORL, AR, JAFFE and Georgia-Tech databases have revealed high performance compared to existing FR techniques.
支持向量机在人脸识别领域得到了广泛的应用,但存在计算时间长等缺点。本文提出了一种基于整数小波变换(IWT)的大规模人脸特征支持向量机的主动集策略,计算时间短。利用基于正交小波的小波变换提取基于提升方案的显著局部小波特征。然后将协方差最大的大规模正交小波变换(LSOI)特征投影到特征空间中,从特征空间中选择稳健的训练和测试特征。对于数据分类,采用基于主动支持向量机(ASVM)的机器学习技术,与传统支持向量机相比,该技术生成的过程更简单。ASVM旨在解决一对一(OVO)和一对全(OVA)多类FR的固定数量的线性方程。在耶鲁、ORL、AR、JAFFE和佐治亚理工大学数据库上的大量实验表明,与现有FR技术相比,ASVM具有更高的性能。
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引用次数: 0
Ensemble-based software fault prediction with two staged data pre-processing 基于集成的两阶段数据预处理软件故障预测
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133297
Shubham P. Kulkarni, Sanjeev Patel
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引用次数: 0
A summative survey on ECG and PPG signal analysis 心电和PPG信号分析综述
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.134762
Tara Rasti, Quanmin Zhu, Keming Zhou, Aakash Soni, Shanshan Zhao, Duncan Sleeman
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引用次数: 0
Optimised reactive resource aware routing for wireless infrastructure-less networks 优化无无线基础设施网络的响应资源感知路由
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133040
Arshad Ahmad Khan Mohammad, Arif Mohammad Abdul
Wireless infrastructure-less networks comprise mobile devices disseminated in radio communication areas without any central coordinator. The nodes communicate directly if they are within the radio range; otherwise, they rely on other nodes. Thus, nodes should act as a router to forward the information to other nodes. The network permits the nodes to be mobile freely and organises arbitrarily; therefore, any node can participate or leave the network independently. Further, nodes in the network consist of constrained heterogeneous resources. Proper utilisation and management of network resources and characteristics are needed to achieve performance efficiency in communication. The paper designs an Optimised Reactive Resource Aware Routing Mechanism to utilise resources effectively and adequately control network characteristics. The proposed mechanism is validated with NS2, and performance is compared with current routing protocols. Results indicate that the proposed mechanism outperforms energy efficiency, packet delivery and resource utilisation.
无无线基础设施网络包括在无线电通信区域内传播的移动设备,没有任何中央协调器。如果节点在无线电范围内,则直接通信;否则,它们依赖于其他节点。因此,节点应该充当路由器,将信息转发给其他节点。网络允许节点自由移动和任意组织;因此,任何节点都可以独立地参与或离开网络。此外,网络中的节点由受约束的异构资源组成。为了实现通信的性能效率,需要对网络资源和网络特性进行合理的利用和管理。为了有效地利用资源,充分控制网络特性,设计了一种优化的响应式资源感知路由机制。通过NS2验证了该机制的有效性,并与现有路由协议进行了性能比较。结果表明,所提出的机制优于能源效率,数据包传输和资源利用。
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引用次数: 0
Efficient load balancing in cloud computing using HHO improved by differential perturbed velocity and TEO 差分摄动速度和TEO改进了HHO在云计算中的高效负载平衡
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133836
U.K. Jena, M.R. Kabat, P.K. Das
Load balancing is one of the primary aspects of cloud computing to avoid situations of being overloaded or underloaded in the node. The paper aims to carry out the dynamic load balancing of non-determent independent tasks in the cloud network and resolved through the hybridisation of an improved version of the Harris Hawks Optimisation Algorithm (HHO) improved by differential perturbed velocity and Thermal Exchange Optimisation (TEO). The main motivations of hybridising are to intensify the diversification ability of the device through the load balance with the VMs, optimise different matrices and enhance the convergence speed. The strength of the algorithm has been authenticated by relating the outcome gained from simulation and real platform processes with the surviving load balancing. The conclusions drawn from the simulation and comparison results illustrate that the projected procedure is outstripping its opponent in the manner of different matrices.
负载平衡是云计算的一个主要方面,它可以避免节点过载或负载不足的情况。本文旨在实现云网络中非阻止独立任务的动态负载平衡,并通过差分摄动速度和热交换优化(TEO)改进的哈里斯鹰优化算法(HHO)的改进版本的混合解决。混合的主要动机是通过与虚拟机的负载平衡来增强设备的多样化能力,优化不同的矩阵,提高收敛速度。通过将仿真和实际平台过程的结果与幸存的负载平衡相结合,验证了算法的强度。仿真和对比结果表明,该算法在不同矩阵的情况下优于对手算法。
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引用次数: 0
An automatic image retrieval system using multi-scale local ternary pattern 基于多尺度局部三元模式的图像自动检索系统
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133296
Megha Agarwal
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引用次数: 0
Hybrid machine learning approach for human activity recognition 人类活动识别的混合机器学习方法
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133307
Ahmad Taher Azar
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引用次数: 0
To predict the characteristic impedance of the microstrip transmission line using supervised machine learning regression techniques 利用监督式机器学习回归技术预测微带传输线的特性阻抗
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133037
Mohammad Ahmad Ansari, Krishnan Rajkumar, Poonam Agarwal
In this paper, supervised machine learning regression techniques: Support Vector Machine (SVM), Random Forest and Deep Neural Network (DNN) models, are demonstrated to predict the characteristic impedance of the microstrip transmission line. Here, microstrip transmission line width, substrate height and substrate dielectric constant are taken as the input and characteristics impedance as the output parameter. To train the models, the data set is created using microstrip transmission line analytical models. DNN models are developed using Feed-forward Back-propagation learning algorithm, where 'adam' is used as optimiser and 'relu' as the activation function. The regression predictive model of SVM and Random Forest model of ensemble learning using bagging technique are developed. It is found that minimum MSE of DNN model is 0.04191 with high execution time 1114.179655 sec, whereas SVM model shows low execution time of 0.8327 sec with MSE of 0.49. Random Forest model showed the MSE of 0.14 with execution time 1.4296 sec.
本文演示了监督机器学习回归技术:支持向量机(SVM)、随机森林和深度神经网络(DNN)模型,以预测微带传输线的特性阻抗。这里以微带传输线宽度、衬底高度和衬底介电常数为输入参数,特性阻抗为输出参数。为了训练模型,使用微带传输线分析模型创建数据集。DNN模型使用前馈反向传播学习算法开发,其中“adam”用作优化器,“relu”用作激活函数。提出了基于支持向量机的回归预测模型和基于bagging技术的集成学习随机森林模型。结果表明,DNN模型的最小MSE为0.04191,执行时间为1114.179655秒,而SVM模型的最小MSE为0.8327秒,执行时间为0.49。随机森林模型显示,MSE为0.14,执行时间为1.4296秒。
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引用次数: 0
A systems engineering approach for Baxter Assistant: programming platform to facilitate the configuration of CoBots through natural language 百特助手的系统工程方法:编程平台,通过自然语言促进协作机器人的配置
Q2 Engineering Pub Date : 2023-01-01 DOI: 10.1504/ijcat.2023.133038
Juan C. Tejada, Alejandro Toro Ossaba, Juan Berruecos, Santiago Rúa, Daniel Sanin Villa, Alexandro López González
Collaborative robots (cobot) are a great solution for companies that must automate processes without modifying the production line, however, these robots lose flexibility in the application when they need to be located in another point of the production line performing a different task than usual because this action involves programming changes. This paper presents the creation of a programming platform that facilitates the configuration of cobots, for the operator to reprogram the robot simply by writing the task to be performed in a web application, without any programming structure, compatible with the flexibility and adaptability of the collaborative robot. To develop this platform, a technology called Robotic Process Automation (RPA) will be used, with which a bot will be created with the ability to interpret user instructions, structure the corresponding code and program the cobot. Thus, a platform is obtained capable of implementing without the need for additional hardware.
协作机器人(cobot)对于那些必须在不修改生产线的情况下实现流程自动化的公司来说是一个很好的解决方案,然而,当这些机器人需要位于生产线的另一点执行与通常不同的任务时,这些机器人在应用程序中失去了灵活性,因为这种操作涉及编程更改。本文提出了一个编程平台的创建,方便了协作机器人的配置,操作者只需在web应用程序中编写要执行的任务即可对机器人进行重新编程,无需任何编程结构,与协作机器人的灵活性和适应性相适应。为了开发这个平台,将使用一种名为机器人过程自动化(RPA)的技术,通过这种技术,将创建一个能够解释用户指令、构建相应代码并对协作机器人进行编程的机器人。这样,就得到了一个不需要额外硬件就能实现的平台。
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引用次数: 0
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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY
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