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The present paper proposes a strength model for unidirectional composites with Lin/Epoxy. The model assumes that, a central core of broken fibers flanked by unbroken fibers which are subject to stress concentrations from the broken fibers. The approach of the model consists of using a modified shear lag model to calculate the ineffective lengths and stress concentrations around fiber breaks. In this paper, we attempt to incorporate in the proposed model the unidirectional composite property variation with temperature and moisture in order to predict even composite strength degradation. Strength degradation is often seen as a result of changes in ineffective lengths at fiber breaks. Subsequently, damage to the material can be estimated at the micromechanical scale under the effect of temperature and humidity

This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.

Abstract Memristive devices have elicited intense research in the past decade thanks to their inherent low voltage operation, multi-bit storage and cost-effective manufacturability. Nonetheless, several outstanding performance and manufacturability challenges have prevented the widespread industry adoption of redox-based memristive matrices. Here, we discuss these challenges in terms of key metrics and propose a roadmap towards realizing competitive memristive-based neuromorphic processing systems.

The practice of self-directed learning is important to adult students as it allows them to learn effectively while juggling work, family and other commitments. This study set out to examine the self-directed learning characteristics present in the adult students' study process at the case university. The relationship between the adult students' perceived competence level in self-directed learning and their academic performance was also investigated. In this study, 1695 adult students in the case university participated in a survey that included both Likert-type and open-ended response items. Eleven indicators of self-directed learning were conceptualised and quantified. These indicators included: Goal Setting, Time Management, Procrastination Management, Assignment Preparation, Exam Preparation, Note-taking Capability, Research Capability, Seminar Class Readiness, Technical Readiness, Online Class Readiness and Stress Management. The findings showed that the adult students' perceived level of competence in the 11 self-directed learning indicators had a direct or an indirect effect on their academic performance. Based on the findings, the case university has conceptualised some new initiatives in the provision of support in terms of self-directed learning to help its adult students to do well in their studies.