17 papers · ranked by Valyu relevance
Zhixuan Shao, Mustafa Kumral
Mining machinery constitutes essential assets for a mining corporation. Due to economies of scale, technological innovations and stringent quality and safety requirements, the size, complexity, functionality and diversity of industrial machinery have expanded markedly over the last two decades. This growth has…
Huazhou Chen, Hanli Qiao, Quanxi Feng, Lili Xu + 2 more
'Ken Cai'] Pomelo is an important agricultural product in southern China. Near-infrared hyperspectral imaging (NIRHI) technology is applied to the rapid detection of pomelo fruit quality. Advanced chemometric methods have been investigated for the optimization of the NIRHI spectral calibration model. The partial least…
Shaokang Li, Zheng Li, Peijian Zhang, Aili Qu + 2 more
'Jesús Vicente de Julián-Ortiz'] Cathepsin L (CatL) is a critical protease involved in cleaving the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), facilitating viral entry into host cells. Inhibition of CatL is essential for preventing SARS-CoV-2 cell entry, making it a potential…
Haohan Xue, Ruixuan Zhang, Xudong Yan, Ruihan Wang + 1 more
PARP1 is one of six enzymes required for the highly error-prone DNA repair pathway microhomology-mediated end joining (MMEJ) and needs to be inhibited when over-expressed. In order to study the PARP1 inhibitory effect of fused tetracyclic or pentacyclic dihydrodiazepinoindolone derivatives (FTPDDs) by quantitative…
Bohan Xu, Rayus Kuplicki, Sandip Sen, Martin P. Paulus + 1 more
'Chi-Hua Chen'] Normative modeling, a group of methods used to quantify an individual’s deviation from some expected trajectory relative to observed variability around that trajectory, has been used to characterize subject heterogeneity. Gaussian Processes Regression includes an estimate of variable uncertainty across…
Mahmood Ahmad, Ramez A. Al-Mansob, Irfan Jamil, Mohammad A. Al-Zubi + 3 more
'Mohanad Muayad Sabri Sabri' 'Arnold C. Alguno' 'Prabir K. Sarker'] The mechanical behavior of the rockfill materials (RFMs) used in a dam’s shell must be evaluated for the safe and cost-effective design of embankment dams. However, the characterization of RFMs with specific reference to shear strength is challenging…
Junrong Du, Jian Zhang, Laishun Yang, Xuzhi Li + 8 more
'Yangquan Chen' 'Subhas Mukhopadhyay' 'Nunzio Cennamo' 'M. Jamal Deen' 'Junseop Lee' 'Simone Morais'] Despite hard sensors can be easily used in various condition monitoring of energy production process, soft sensors are confined to some specific scenarios due to difficulty installation requirements and complex work…
R. Romero, E. L. Iglesias, L. Borrajo
Support vector machine (SVM) is a powerful technique for classification. However, SVM is not suitable for classification of large datasets or text corpora, because the training complexity of SVMs is highly dependent on the input size. Recent developments in the literature on the SVM and other kernel methods emphasize…
Patchanok Srisuradetchai, Korn Suksrikran
The k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big data contexts. However, this method is susceptible to overfitting and fit discontinuity, which present significant…
Shengbing Ren, Fa Liu, Weijia Zhou, Xian Feng + 2 more
'Chaudry Naeem Siddique' 'Robertas Damasevicius'] The deep multiple kernel Learning (DMKL) method has attracted wide attention due to its better classification performance than shallow multiple kernel learning. However, the existing DMKL methods are hard to find suitable global model parameters to improve…
Hui Wen, Weixin Xie, Jihong Pei, Xia Li
This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the…
Sutao Song, Zhichao Zhan, Zhiying Long, Jiacai Zhang + 2 more
Background Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis…
Xingheng Yu, Xinqi Gong, Hao Jiang
Background Breast cancer is one of the common kinds of cancer among women, and it ranks second among all cancers in terms of incidence, after lung cancer. Therefore, it is of great necessity to study the detection methods of breast cancer. Recent research has focused on using gene expression data to predict outcomes…
Giorgos Mountrakis, Wei Zhuang, Alex J. Cannon
Background This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the proposed MSRBF network relies on the integration of both local and global error…
Nora C Toussaint, Christian Widmer, Oliver Kohlbacher, Gunnar Rätsch
Background String kernels are commonly used for the classification of biological sequences, nucleotide as well as amino acid sequences. Although string kernels are already very powerful, when it comes to amino acids they have a major short coming. They ignore an important piece of information when comparing amino…
Hui Liu, Guo Zhou, Yongquan Zhou, Huajuan Huang + 1 more
Introduction Regression and classification are two of the most fundamental and significant areas of machine learning. Methods In this paper, a radial basis function neural network (RBFNN) based on an improved black widow optimization algorithm (IBWO) has been developed, which is called the IBWO-RBF model. In order to…
Abelardo Montesinos-López, Osval Antonio Montesinos-López, José Cricelio Montesinos-López, Carlos Alberto Flores-Cortes + 2 more
'José Cricelio Montesinos-López' 'Carlos Alberto Flores-Cortes' 'Roberto de la Rosa' 'José Crossa'] The primary objective of this paper is to provide a guide on implementing Bayesian generalized kernel regression methods for genomic prediction in the statistical software R. Such methods are quite efficient for…