Spectral analysis is a practical technology used for rapid of fruit maturity. Least-squares support vector regression (LSSVR) with radial basis function (RBF) kernel an effective nonlinear method the quantitative calibration in visible-near-infrared (Vis-NIR) spectral region. However, effect and high-dimensional spectrum data influence prediction accuracy complexity modeling procedures. This article presents fuzzy optimization strategy to improve performance RBF LSSVR model Vis-NIR...

IoT devices typically stream data such as sensor values to other including cloud-based services. Analyzing these streams for cyber-attacks is a challenging task. This due the infinite nature of stream-based datatypes. can require additional real-time processing and computational performance capabilities. In this article, we focus on how concept drifts affect Botnet cyber-attack detection in scenarios. To reveal result, incorporate drift analysis detect Bot-IoT dataset, which consists...

Pomelo is an important agricultural product in southern China. Near-infrared hyperspectral imaging (NIRHI) technology applied to the rapid detection of pomelo fruit quality. Advanced chemometric methods have been investigated for optimization NIRHI spectral calibration model. The partial least squares (PLS) method improved non-linear regression by combining it with kernel Gaussian radial basis function (RBF). In this study, core parameters PLS latent variables and RBF width were designed...

Industry 4.0 and Industrial Internet of Things (IIoT) are current trends in the industrial automation world. They require connections factory networks to internet. This trend increases vulnerability attacks. Here, we present an approach that monitors activities network traffic based on two linear feature extraction algorithms, i.e. LDA PCA. A Machine-Learning-based is used analyze records from UNSW-NB15 database detect report anomalies such as malicious The experimental results show...

In this paper, we propose a novel approach named by Discriminative Principal Component Analysis which is abbreviated as PCA in order to enhance separability of Linear Discriminant (LDA). The proposed method performs feature extraction determining linear projection that captures the most scattered discriminative information. innovation performing on matrix rather than original sample matrix. For calculating required under low complexity, exploit LDA converted obtain within-class and...

There are two problems need to be dealt with for Non-negative Matrix Factorization (NMF): choose a suitable rank of the factorization and provide good initialization method NMF algorithms. This paper aims solve these using Singular Value Decomposition (SVD). At first we extract number main components as rank, actually this is inspired from [1, 2]. Second, use singular value its vectors initialize algorithm. In 2008, Boutsidis Gollopoulos [3] provided titled NNDSVD enhance They extracted...

Abstract With the widespread application of smart devices, security IoT systems faces entirely new challenges. The data stream operates in a non-stationary, dynamic environment, making it prone to concept drift. This paper focuses on addressing issue drift streams, with key emphasis introducing an innovative detection method—Ensemble Multiple Non-parametric Concept Drift detectors, abbreviated as EMNCD. approach employs ensemble learning three non-parametric statistical methods:...

<abstract><p>With the widespread application of smart devices, security internet things (IoT) systems faces entirely new challenges. The IoT data stream operates in a non-stationary, dynamic environment, making it prone to concept drift. This paper focused on addressing issue drift streams, with key emphasis introducing an innovative detection method-ensemble multiple non-parametric localization detectors, abbreviated as EMNCD. EMNCD employs ensemble statistical methods,...

An ecosystem made of nutrients, plants, detritus and dissolved oxygen is presented. Its equilibria are established. Sufficient conditions for the existence coexistence equilibrium derived its feasibility discussed in every detail.

The purpose of image registration is to determine a transformation such that the transformed version source similar target one. In this paper we focus on landmark-based using radial basis functions (RBFs) transformations, in particular topology preservation compactly supported (CSRBFs) transformations. [1] performances Gneiting's and Wu's are compared with ones other well known schemes registration, as thin plate spline Wendland's functions. Several numerical experiments real-life cases...

In image registration, a proper transformation should be topology preserving. Especially for landmark-based if the displacement of one landmark is larger enough than those neighbourhood landmarks, violation will occurred. This paper aim to analyse preservation some Radial Basis Functions (RBFs) which are used model deformations in registration. Mat\'{e}rn functions quite common statistic literature (see, e.g. \cite{Matern86,Stein99}). this paper, we use them solve registration problem. We...

Due to complexity and invisibility of human organs, diagnosticians need analyze medical images determine where the lesion region is, which kind disease in order make precise diagnoses. For satisfying clinical purposes through analyzing images, registration plays an essential role. instance, Image-Guided Interventions (IGI) computer-aided surgeries, patient anatomy is registered preoperative guide surgeons complete procedures. Medical image also very useful surgical planning, monitoring...

Non-invasive techniques for rapid blood testing are gaining traction in global healthcare as they optimize medical screening, diagnosis and clinical decisions. Fourier transform infrared (FT-IR) spectroscopy is one of the most common technologies that can be used non-destructive aided detection. Typically, after acquiring spectrum, spectral data preprocessing feature extraction quantitative analysis several indicators samples accomplished, combination with chemometric method studies. At...