D.c. conduction studies on thermally evaporated neodymium oxide thin films

Aluminium-neodymium oxide-aluminium thin film capacitors have been prepared by thermal evaporation and the d.c. conduction properties of these films have been studied. The thicknesses of the films have been determined by a multiple beam interferometer. The current-voltage power-law dependence showed that the conduction in these films is space-charge limited. The linear dependence of the current density on the square root of the applied field confirmed the exponential trap distribution. The trap density has been found to be of the order of 10²⁶ m^–3. It has also been observed that the Schottky type of conduction is predominant in the high-field region and the height of the Schottky barrier has been determined. It is seen that the conduction mechanism is an activated process with the activation energy decreasing with increasing field.     

The MITRE E3 family of models structure and results

A family of energy/economic/environmental (E³) models is presented as a mechanism for analysing national policy issues. The family consists of discrete models which are designed to be run in an integrated manner. The outputs of certain models provide the inputs to the next. This structure allows the analyst to readily incorporate an understanding of regional factors such as local energy prices, concerns over air quality, water availability, or attitudes towards construction of new energy facilities, into national assessments of energy policies. This paper reviews the analytic framework within which energy policy issues are currently addressed. The initial family of E³ models is described with the emphasis on the data linkages and feedback which are provided when these models are run sequentially. The ongoing MITRE research programme with the E³ family of models is presented and plans and opportunities for future work are outlined.     

Finite element crack growth algorithm for dynamic fracture

A new finite element crack growth algorithm has been developed to simulate dynamic fracture. In this algorithm, pseudo elements with very high initial density are placed below the crack plane and the density is reduced to zero in a gradual manner as the crack passes the element. A number of linear elastic and elasto-viscoplastic problems have been carried out to test the new algorithm. The results are compared with some of the existing crack growth models.     

The adoption and concerns of e-finance in Malaysia

Technological advancement has brought a whole new way of delivering financial services around the world. E-finance industry in Malaysia has grown rapidly with the help of internet and conducting financial services are far easier now if compared to last time. Internet provided a new medium or channel in delivering financial services. However, there are also risks and challenges when using electronic finance. A total of 100 respondents had been targeted in completing this study. Survey method was utilized in collecting respondent’s opinion and perception to test the variables. The target was companies which used electronic finance in delivering their services. Interviews were also conducted and relevant tests conducted which provided evidence to support the hypotheses for this study. It was found that e-finance was affected by security, revenue and cost dimensions, and technology architecture with the adoption of global technology.     

A novel hybrid feature selection via Symmetrical Uncertainty ranking based local memetic search algorithm

A novel correlation based memetic framework (MA-C) which is a combination of genetic algorithm (GA) and local search (LS) using correlation based filter ranking is proposed in this paper. The local filter method used here fine-tunes the population of GA solutions by adding or deleting features based on Symmetrical Uncertainty (SU) measure. The focus here is on filter methods that are able to assess the goodness or ranking of the individual features. Empirical study of MA-C on several commonly used datasets from the large-scale Gene expression datasets indicates that it outperforms recent existing methods in the literature in terms of classification accuracy, selected feature size and efficiency. Further, we also investigate the balance between local and genetic search to maximize the search quality and efficiency of MA-C.     

DanVideo: an MPEG-7 authoring and retrieval system for dance videos

A well-annotated dance media is an essential part of a nation’s identity, transcending cultural and language barriers. Many dance video archives suffer from problems concerning authoring and access, because of the complex spatio-temporal relationships that exist between the dancers in terms of movements of their body parts and the emotions expressed by them in a dance. This paper presents a system named DanVideo for semi-automatic authoring and access to dance archives. DanVideo provides methods of annotation and authoring and retrieval tools for choreographers, dancers, and students. We demonstrate how dance media can be semantically annotated and how this information can be used for the retrieval of the dance video semantics. In particular, DanVideo offers an MPEG-7 based semi-automatic authoring tool that takes dance video annotations generated by dance experts and produces MPEG-7 metadata. DanVideo also has a search engine that takes users’ queries and retrieves dance semantics from metadata arranged using tree-embedding technique and based on spatial, temporal and spatio-temporal features of dancers. The search engine also leverages a domain-specific ontology to process knowledge-based queries. We have assessed the dance-video queries and semantic annotations in terms of precision, recall, and fidelity.     

Epitomic Location Recognition

This paper presents a novel method for location recognition, which exploits an epitomic representation to achieve both high efficiency and good generalization. A generative model based on epitomic image analysis captures the appearance and geometric structure of an environment while allowing for variations due to motion, occlusions, and non-Lambertian effects. The ability to model translation and scale invariance together with the fusion of diverse visual features yields enhanced generalization with economical training. Experiments on both existing and new labeled image databases result in recognition accuracy superior to state of the art with real-time computational performance.     

A genetic algorithm-based artificial neural network model for the optimization of machining processes

Artificial intelligent tools like genetic algorithm, artificial neural network (ANN) and fuzzy logic are found to be extremely useful in modeling reliable processes in the field of computer integrated manufacturing (for example, selecting optimal parameters during process planning, design and implementing the adaptive control systems). When knowledge about the relationship among the various parameters of manufacturing are found to be lacking, ANNs are used as process models, because they can handle strong nonlinearities, a large number of parameters and missing information. When the dependencies between parameters become noninvertible, the input and output configurations used in ANN strongly influence the accuracy. However, running of a neural network is found to be time consuming. If genetic algorithm-based ANNs are used to construct models, it can provide more accurate results in less time. This article proposes a genetic algorithm-based ANN model for the turning process in manufacturing Industry. This model is found to be a time-saving model that satisfies all the accuracy requirements.     

Curvature and entropy based wall boundary condition for the high order spectral volume Euler solver

A curvature and entropy based wall boundary condition is implemented in the high order spectral volume (SV) context. This method borrows ideas from the “curvature-corrected symmetry technique” developed by (Dadone A, Grossman B. Surface Boundary Conditions for Compressible Flows. AIAA J 1994; 32(2): 285–93), for a low order structured grid Euler solver. After numerically obtaining the curvature, the right state (by convention, the left state is inside the computational domain and the right state lies outside of the computational domain) face pressure values are obtained by solving a linearised system of equations. This is unlike that of the lower order finite volume and difference simulations, wherein the right state face values are trivial to obtain. The right state face density values are then obtained by enforcing entropy conservation. Accuracy studies show that simulations performed by employing the new boundary conditions deliver much more accurate results than the ones which employ traditional boundary conditions, while at the same time asymptotically reaching the desired order of accuracy. Numerical results for two-dimensional inviscid flows around the NACA0012 airfoil and over a bump with the new boundary condition showed dramatic improvements over those with the conventional approach. In all cases and orders, spurious entropy productions with the new boundary treatment are significantly reduced. In general, the numerical results are very promising and indicate that the approach has a great potential for 3D high order simulations.     

Application of NSGA-II Algorithm to Single-Objective Transmission Constrained Generation Expansion Planning

This paper presents an application of elitist nondominated sorting genetic algorithm version II (NSGA-II), a multiobjective algorithm to a constrained single objective optimization problem, the transmission constrained generation expansion planning (TC-GEP) problem. The TC-GEP problem is a large scale and challenging problem for the decision makers (to decide upon site, capacity, type of fuel, etc.) as there exist a large number of combinations. Normally the TC-GEP problem has an objective and a set of constraints. To use NSGA-II, the problem is treated as a two-objective problem. The first objective is the minimization of cost and the second objective is to minimize the sum of normalized soft constraints violation. The hard constraints (must satisfy constraints) are treated as constraints only. To improve the performance of the NSGA-II, two modifications are proposed. In problem formulation the modification is virtual mapping procedure (VMP), and in NSGA-II algorithm, controlled elitism is introduced. The NSGA-II is applied to solve TC-GEP problem for modified IEEE 30-bus test system for a planning horizon of six years. The results obtained by NSGA-II are compared and validated against single-objective genetic algorithm and dynamic programming. The effectiveness of each proposed approach has also been discussed in detail.