Ishikawa-type Iterative Solution of m−Accretive Operator Equation and its Stability in Arbitrary Banach Spaces

Abstract Let X be a Banach space. Suppose that A : X → X is a Lipschitz accretive operator and x+Ax = f is a nonlinear equation. The objective of this note is to discuss simultaneously the existence and uniqueness of solution of the equation, its convergence, convergence rate estimate and stability of Ishikawa-type iterative procedure. If iterative parameters be selected suitably, then the iterative procedure converges strongly to unique solution and the iterative process is stable. Mathematics Subject Classification: 47H17, 47H06, 47H10 Keywords: m−accretive operator; Ishikawa-type iterative solution; convergence rate estimate; stability Throughout this note, X is assumed a real Banach space. An operator A with domain D(A) ⊂ X and range R(A) ⊂ X is said to be accretive if an

A Novel Method for Acquiring Engineering-Oriented Operational Empirical Knowledge

The operational knowledge of skilled technicians gained from years of experience is invaluable for an enterprise. Possession of such knowledge will facilitate an enterprise sharing technician’s know-how and training of new employees effectively. However, until now there is rare efficient quantitative method to obtain this kind of tacit knowledge. In this paper we propose a concept of engineering-oriented operational empirical knowledge (OEK) to describe this kind of knowledge and design a framework to acquire OEK from skilled technician’s operations. The framework integrates motion analysis, motion elicitation, and intent analysis. The modular arrangement of predetermined time standards (MODAPTS) is used to divide the technician’s operational process into basic motion elements; and the variable precision rough set (VPRS) algorithm is used to extract the technician’s OEK content, which combined with the technician’s intent elicited via interview; the completed OEK is obtained. At the end of our study, an engineering case is used to validate the feasibility of the proposed method, which shows that satisfactory results have been reached for the study

A COVID-19 Risk Score Combining Chest CT Radiomics and Clinical Characteristics to Differentiate COVID-19 Pneumonia From Other Viral Pneumonias

With the continued transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the world, identification of highly suspected COVID-19 patients remains an urgent priority. In this study, we developed and validated COVID-19 risk scores to identify patients with COVID-19. In this study, for patient-wise analysis, three signatures, including the risk score using radiomic features only, the risk score using clinical factors only, and the risk score combining radiomic features and clinical variables, show an excellent performance in differentiating COVID-19 from other viral-induced pneumonias in the validation set. For lesion-wise analysis, the risk score using three radiomic features only also achieved an excellent AUC value. In contrast, the performance of 130 radiologists based on the chest CT images alone without the clinical characteristics included was moderate as compared to the risk scores developed. The risk scores depicting the correlation of CT radiomics and clinical factors with COVID-19 could be used to accurately identify patients with COVID-19, which would have clinically translatable diagnostic and therapeutic implications from a precision medicine perspective

Value added utilization of by-product electric furnace ferronickel slag as construction materials: A review

This paper reviews the potential use of electric furnace ferronickel slag (FNS) as a fine aggregate and binder in Portland cement and geopolymer concretes. It has been reported that the use of FNS as a fine aggregate can improve the strength and durability properties of concrete. Use of some FNS aggregates containing reactive silica may potentially cause alkali-silica reaction (ASR) in Portland cement concrete. However, the inclusion of supplementary cementitious materials (SCM) such as fly ash and blast furnace slag as partial cement replacement can effectively mitigate the ASR expansion. When finely ground FNS is used with cement, it shows pozzolanic reaction, which is similar to that of other common SCMs such as fly ash. Furthermore, 20% FNS powder blended geopolymer showed greater strength and durability properties as compared to 100% fly ash based geopolymers. The utilization of raw FNS in pavement construction is reported as a useful alternative to natural aggregate. Therefore, the use of by-product FNS in the construction industry will be a valuable step to help conservation of natural resources and add sustainability to infrastructures development. This paper presents a comprehensive review of the available results on the effects of FNS in concrete as aggregate and binder, and provides some recommendations for future research in this field

Towards molecular breeding of reproductive traits in cereal crops

The transition from vegetative to reproductive phase, flowering per se, floral organ development, panicle structure and morphology, meiosis, pollination and fertilization, cytoplasmic male sterility (CMS) and fertility restoration, and grain development are the main reproductive traits. Unlocking their genetic insights will enable plant breeders to manipulate these traits in cereal germplasm enhancement. Multiple genes or quantitative trait loci (QTLs) affecting flowering (phase transition, photoperiod and vernalization, flowering per se), panicle morphology and grain development have been cloned, and gene expression research has provided new information about the nature of complex genetic networks involved in the expression of these traits. Molecular biology is also facilitating the identification of diverse CMS sources in hybrid breeding. Few Rf (fertility restorer) genes have been cloned in maize, rice and sorghum. DNA markers are now used to assess the genetic purity of hybrids and their parental lines, and to pyramid Rf or tms (thermosensitive male sterility) genes in rice. Transgene(s) can be used to create de novo CMS trait in cereals. The understanding of reproductive biology facilitated by functional genomics will allow a better manipulation of genes by crop breeders and their potential use across species through genetic transformation

Network Traffic Prediction Using Radial Basis Function Neural Network Optimized by Ant Colony Algorithm

The disadvantages of the traditional radial basis function (RBF) neural network during the network traffic prediction process, such as a slow convergence rate and easy occurrence of local optima, result in low prediction precision. In this study, the ant colony optimization (ACO) algorithm is used to optimize the parameters of the RBF neural network for network traffic prediction. ACO is used to train the width and centre of the basis function of the RBF neural network, simplify the network structure, accelerate the convergence speed, prevent the occurrence of local optima, and improve the generalist ability of the RBF neural network. The experimental results show that compared with the genetic algorithm (GA)-RBF and particle swarm optimization (PSO)-RBF traffic prediction models, the proposed model exhibits higher prediction accuracy and can describe the varying trends in the network traffic well. The model used in this study exhibits strong generalization ability and good stability and therefore has practical value in network traffic prediction