Prioritizing the Relative Dominance of Drivers for Intellectual Entrepreneuring Through the Tertiary Knowledge Industry.

The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development.The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development.The knowledge industry is becoming the dominant contributor to sustainable growth. It is causing a paradigm drift towards knowledge capitalization for improvement of productivity-driven competition to attain better economic performance, wealth generation, and development. Research has identified an “intellectual entrepreneurial capacity gap” as the constraint to attaining equity between developed and developing economies. The gap is fuelling the growing technological innovation divide – the widening boundary between developed and developing economies. As a contribution to reducing the gap, this paper presents a conceptual framework of drivers for intellectual entrepreneurial capacity in knowledge capitalization for technological and economic leapfrogging in development

Modelling and experimental analysis of aerospace composites in fire

The aim of this Master of Engineering (MEng) - Aerospace thesis is to study the structural response and failure of aerospace grade composites during exposure to fire. Key aspects of the research are to analyse the thermal and mechanical responses of laminates and sandwich composites in high temperature and fire environments, which result in softening and structural failure. The research is concentrated on carbon/epoxy laminates and sandwich composites, which are the most common composite materials used in aerospace structures. To achieve the general aim of this research project, the thermal response of aerospace composites will be validated using existing thermal models for fibreglass composites. In addition, the modification of existing models to ensure the applicability to aerospace composites is an aim of this research. Another key aim is the validation of a modelling approach through the generation of experimental data. By achieving these aims it is envisaged to have a validated modelling approach that can be used by the aerospace industry for fire assessment of structural composites. The research work presented in this MEng thesis falls into three main categories: literature review; development of thermal and mechanical modelling approach for aerospace laminates and sandwich composites; and validation through experimental fire structural testing. A critical review of the scientific literature regarding the fire response of composite materials is presented in the thesis. The existing thermal modelling approach applied to composites is reviewed with identification of the fundamental factors such as heat conduction, resin decomposition and gas flow. A review of structural models is presented that can analyse changes to the mechanical properties of composites in fire, such as strength reduction, buckling effects and creep resistance. The thermal and mechanical response of various composite systems in different heating conditions and fire environments is assessed in the literature review. Based on the literature review, it is apparent that there is a lack of analysis and data on laminates and sandwich composites used in aerospace structures, and this provides the rationale for the MEng work. The thermal modelling presented in this thesis is based on existing models for composite laminates and sandwich materials that analyse the response of the composite in fire including heat flow, decomposition of the polymer matrix, flow of volatile gases into fire, reactions between fibres and char, pressure rise etc. The thermal modelling approach applied to fibreglass composites has been extensively validated, as published in literature, and can be adapted for carbon fibre reinforced composites. The accuracy of the models to predict the thermal response has been validated through experimental fire testing. Carbon/epoxy laminates, of varying thickness (4, 10 and 20 mm), and sandwich composites have been exposed to various heat fluxes (temperatures) to generate data for the temperature-time response. This data is used to validate the approach undertaken to yield thermal predictions. The good agreement obtained between experimental measurements and model predictions is presented in this thesis. The approach taken to modelling the structural response of aerospace composites is established by defining the mechanisms applied in existing models and the reasoning behind the analysis. As the failure mechanisms experienced by different composite systems (and in various loading conditions) will not be identical, the correct selection of structural effects is made. The high heat fluxes (>10kW/m²) analysed in this research eliminate any effects of creep behaviour, while strength and stiffness reduction are significant factors. The reduction of strength and stiffness is determined through experimental testing at increasing temperatures for composite laminates and sandwich structures. The work performed in this research forms part of a two-step modelling approach which comprises of a thermal analysis stage coupled to a mechanical analysis stage. The mechanical analysis combines with the thermal analysis to produce a thermomechanical model that has the ability to make predictions of the load-time response of carbon fibre composites. This is validated through fire structural testing performed on composites under one-sided heating and applied load. The extensive experimental validation is performed on composite laminates of varying thickness and heat flux, and sandwich composites at varying heat fluxes. The accurate prediction of failure times and comparison to theoretical models is presented in this thesis

Neuro-fuzzy systems approach to infill missing rainfall data for Klang River Catchment, Malaysia

Rainfall data can be regarded as the most essential input for various applications in hydrological sciences. Continuous rainfall data with adequate length is the main requirement to solve complex hydrological problems. Mostly in developing countries hydrologists are still facing problems of missing rainfall data with inadequate length. Researchers have been applying a number of statistical and data driven approaches to overcome this insufficiency. This study is an application of neuro-fuzzy system to infill the missing rainfall data for Klang River catchment. Pettitt test, standard normal homogeneity test (SNHT) and Von Neumann Ratio (VNR) tests were performed to check the homogeneity of rainfall data. The neuro-fuzzy model performances were assessed both in calibration and validation stages based on statistical measures such as coefficient of determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). To evaluate the performance of the neuro-fuzzy system model, it was compared with a traditional modeling technique known as autoregressive model with exogenous inputs (ARX). The neuro-fuzzy system model gave better performances in both stages for the best input combinations. The missing rainfall data was predicted using the input combination with best performances. The results of this study showed the effectiveness of the neuro-fuzzy systems and it is recommended as a prominent tool for filling the missing data

Throughput Enhancement of Restricted Access Window for Uniform Grouping Scheme in IEEE 802.11ah

IEEE 802.11ah has recently emerged as a promising standard for enabling massive machine-to-machine (M2M) communication. In order to support uplink data transmission from dense machine type clients (such as smart meters, IoT end nodes etc.), 802.11ah relies upon the restricted access window (RAW) based Medium Access Control (MAC) protocol. The underlying motivation behind this protocol is to reduce the contention for spectrum access among a large number of devices. The nodes contend with each other in their assigned RAW slot using Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). In each RAW slot, the throughput depends upon the number of nodes. Current studies have suggested that the duration of each RAW slot should be the same in the entire RAW frame. However in this paper, we argue that the duration of each RAW slot should be chosen according to the size of the group. We present a model where a RAW frame is divided into two sub-frames and the duration of RAW slots in each sub-frame is chosen according to the size of the group. With the help of an analytical framework, we demonstrate that the throughput under our proposed scheme can be significantly enhanced when compared to a conventional implementation

Prediction of Viral Loads for Diagnosis of Hepatitis C Infection in Human Plasma Samples Using Raman Spectroscopy Coupled with Partial Least Squares Regression Analysis

Raman spectroscopy has been used to identify the biochemical changes associated with the presence of the Hepatitis C virus (HCV) in infected human blood plasma samples as compared with healthy samples, as control. The aim of the study was to establish the Raman spectral markers of hepatitis infection, which could be used for diagnostic purposes. Moreover, multivariate data analysis techniques, including Principal Component Analysis (PCA), coupled with Linear Discriminant Analysis (LDA), and Partial Least Square Regression (PLSR) are employed to further demonstrate the diagnostic capability of the technique. The PLSR model is developed to predict the viral loads of the HCV infected plasma on the basis of the biochemical changes caused by the viral infection. Specific Raman spectral features are observed in the mean spectra of HCV plasma samples which are not observed in the control mean spectra. PCA differentiated the ‘normal’ and ‘HCV’ groups of the Raman spectra and PCA-LDA was employed to increase the efficiency of prediction of the presence of HCV infection, resulting in a sensitivity and specificity 98.8% and 98.6%, with corresponding Positive Predictive Value of 99.2%, and Negative Predictive Value of 98%. PLSR modelling was found to be 99% accurate in predicting the actual viral loads of the HCV samples, as determined clinically using the Polymerase Chain Reaction (PCR) technique, on the basis of the Raman spectral changes caused by the virus during the process of the development of Hepatitis C. Copyright © 2017 John Wiley & Sons, Ltd

Strengthen user authentication on mobile devices by using user’s touch dynamics pattern

Mobile devices, particularly the touch screen mobile devices, are increasingly used to store and access private and sensitive data or services, and this has led to an increased demand for more secure and usable security services, one of which is user authentication. Currently, mobile device authentication services mainly use a knowledge-based method, e.g. a PIN-based authentication method, and, in some cases, a fingerprint-based authentication method is also supported. The knowledge-based method is vulnerable to impersonation attacks, while the fingerprint-based method can be unreliable sometimes. To overcome these limitations and to make the authentication service more secure and reliable for touch screen mobile device users, we have investigated the use of touch dynamics biometrics as a mobile device authentication solution by designing, implementing and evaluating a touch dynamics authentication method. This paper describes the design, implementation, and evaluation of this method, the acquisition of raw touch dynamics data, the use of the raw data to obtain touch dynamics features, and the training of the features to build an authentication model for user identity verification. The evaluation results show that by integrating the touch dynamics authentication method into the PIN-based authentication method, the protection levels against impersonation attacks is greatly enhanced. For example, if a PIN is compromised, the success rate of an impersonation attempt is drastically reduced from 100% (if only a 4-digit PIN is used) to 9.9% (if both the PIN and the touch dynamics are used). © 2019, The Author(s)

Dilemma and Quantum Battle of Sexes

We analysed quantum version of the game battle of sexes using a general initial quantum state. For a particular choice of initial entangled quantum state it is shown that the classical dilemma of the battle of sexes can be resolved and a unique solution of the game can be obtained.Comment: Revised, Latex, 9 pages, no figure, corresponding author's email: [email protected]

Idiopathic multicentric Castleman disease: a mysterious case of generalized lymphadenopathy

Castleman disease is a syndrome with significant clinico-pathological overlap between malignancy, autoimmune causes and infectious etiologies. It is a spectrum and can vary in extent from unicentric to multicentric disease with generalized lymphadenopathy, organ involvement, constitutional symptoms and cytopenias, and in severity from non-severe to severe disease with TAFRO symptoms. Idiopathic multicentric Castleman disease (iMCD) is a diagnosis of exclusion after multiple causes as per diagnostic criteria are excluded. Treatment varies between the disease severity types with anti-IL 6 antibodies for non-severe disease to cytotoxic chemotherapy agents for severe disease with TAFRO symptoms. We hereby report a case of a non-severe type of iMCD with a prolonged course and delayed arrival at the diagnosis, owing to the rarity of this condition, which stresses the need for a reduced threshold to consider MCD, early in the differential diagnosis. Interestingly there were positive auto-antibodies and elevated IgG4 levels in this patient, but applying strict criteria helps to distinguish the diagnosis