South Africa in the era of Industry 4.0: An Insightful Investigation

Scientometrics - Science and technology are one of the essential elements to ensure innovation. Innovative developments significantly contribute towards strategic growth initiatives in every...     

A study on thermophysiological comfort properties of fabrics in relation to constituent fibre fineness and cross-sectional shapes

The present study reports the effect of linear densities and profiles of polyester fibres on the physiological properties of their fabrics. Four different polyester fibre finenesses along with microdenier and four cross-sectional shapes (circular, scalloped oval, tetrakelion and trilobal) were selected to produce two sets of 2/1 twill fabrics; one composed of 100% polyester and the other 67:33 P/V blends. In studying the thermophysiological component of the clothing comfort, heat, air and moisture transmission characteristics of the fabrics were assessed. The principal thermal properties, such as thermal absorptivity, thermal resistance and thermal conductivity, were experimentally evaluated, using the Alambeta instrument. The study of the obtained results established the fabrics of non-circular cross-sections as against circular ones, and increase in the linear density results in higher thermal resistance, lower thermal conductivity and lower thermal absorptivity. Wicking behaviour of fabrics was studied under two conditions–wicking from an infinite liquid reservoir (transverse wicking) and wicking from a finite liquid reservoir (single drop wicking into the fabrics). Increase in fibre linear density enhances transplaner wicking but slows down the spreading speed of water drops. Air permeability and moisture vapour permeability are found to be positively correlated with fibre decitex. The role of fibre cross-sectional shapes in influencing mass-flow characteristics is quite considerable. Use of non-circular polyester in place of a circular one augments the wickability of liquid water along with the permeability of air and moisture vapour through the fabrics, revealing their high porosity, which assists air and moisture to propagate. Mixing viscose into polyester brings down the air permeability and moisture vapour transmission rate (MVTR) of fabrics. Results show that moisture absorption of viscose is an important factor in influencing the moisture transport characteristics including both wickability and MVTR of 100% viscose and P/V-blended fabrics.     

Exchange rate forecasting: comparison of various architectures of neural networks

This paper evaluates the predictive accuracy of neural networks in forecasting exchange rate. The multi-layer perceptron (MLP) and radial basis function (RBF) networks with different architectures are used to forecast five exchange rate time series. The results of each prediction are evaluated and compared according to the networks and architectures used. It is found that neural networks can be effectively used in forecasting exchange rate and hence in designing trading strategies. RBF networks performed better than MLP networks in our simulation experiment. This experiment suggests that it is possible to extract information hidden in the exchange rate and predict it into future.     

The Seven Flaws of Identity Management: Usability and Security Challenges

Web identity management systems are complex systems with powerful features - and many potential vulnerabilities. They aim to facilitate the management of identifiers, credentials, personal information, and the presentation of this information to other parties. In many schemes, an identity provider (IdP) issues identities or credentials to users, while a relying party (RP) depends on the IdP to check the user credentials before it allows users access to Web site services. By separating the role of and IdP from the RP, identity management systems let users leverage one identifier across multiple Web services.