Modelling the Sublimation-Desublimation Processes for Production of Ultrafine Powders

The purpose of this work is to establish the theoretical foundations for calculating and designing the sublimationcondensation processes in chemical apparatuses which are intended for production of ultrafine powders of crystalline and amorphous materials with controlled fractional composition. Theoretic analysis of the primary processes of nucleation and growth kinetics of the clusters according to the degree of super-saturation and the homogeneous or heterogeneous nature of nucleation has been carried out. The engineering design procedures of desublimation processes have been offered and tested for modification of the Claus process.

Stages of Changes for Physical Activity among Iranian Adolescent Girls

Background: Regular physical activity contributes positively to physical and psychological health. In the present study, the stages of change of physical activity and the total physical Aims: The aim of this study was to investigate the proportion of adolescent girls in each stages of change and the causative factors associated with physical activity such as the related social support and self efficacy in a sample of the high school students. Methods: In this study, Social Cognitive Theory (SCT) and the Transtheorical Model (TTM) guided instrument development. The data regarding the demographics, psychosocial determinants of physical activity, stage of change and physical activity was gathered by questionnaires. Several measures of psychosocial determinants of physical activity were translated from English into Persian using the back-translation technique. These translated measures were administered to 512 ninth and tenth-grade Iranian high school students for factor analysis. Results: The distribution of the stage of change for physical activity was as follow: 18/5% in precontemplation, 23.4% in contemplation, 38.2% in preparation, 4.6% in action and 15.3% in maintenance. They were in 80.1% pre-adoption stages (precontemplation stage, contemplation stage and preparation stage) and 19.9% post-adoption stages (action stage and maintenance stage) of physical activity. There was a significant relate between age and physical activity in adolescent girls (age-related decline of physical activity) p

Interpreting the Out-of-Control Signals of Multivariate Control Charts Employing Neural Networks

Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages. The main problem is how to interpret the out-ofcontrol signal of a multivariate chart. For example, in the case of control charts designed to monitor the mean vector, the chart signals showing that it must be accepted that there is a shift in the vector, but no indication is given about the variables that have produced this shift. The MEWMA quality control chart is a very powerful scheme to detect small shifts in the mean vector. There are no previous specific works about the interpretation of the out-of-control signal of this chart. In this paper neural networks are designed to interpret the out-of-control signal of the MEWMA chart, and the percentage of correct classifications is studied for different cases.

Machine Scoring Model Using Data Mining Techniques

this article proposed a methodology for computer numerical control (CNC) machine scoring. The case study company is a manufacturer of hard disk drive parts in Thailand. In this company, sample of parts manufactured from CNC machine are usually taken randomly for quality inspection. These inspection data were used to make a decision to shut down the machine if it has tendency to produce parts that are out of specification. Large amount of data are produced in this process and data mining could be very useful technique in analyzing them. In this research, data mining techniques were used to construct a machine scoring model called 'machine priority assessment model (MPAM)'. This model helps to ensure that the machine with higher risk of producing defective parts be inspected before those with lower risk. If the defective prone machine is identified sooner, defective part and rework could be reduced hence improving the overall productivity. The results showed that the proposed method can be successfully implemented and approximately 351,000 baht of opportunity cost could have saved in the case study company.

Strategies for Developing e-LMS for Tanzania Secondary Schools

Tanzania secondary schools in rural areas are geographically and socially isolated, hence face a number of problems in getting learning materials resulting in poor performance in National examinations. E-learning as defined to be the use of information and communication technology (ICT) for supporting the educational processes has motivated Tanzania to apply ICT in its education system. There has been effort to improve secondary school education using ICT through several projects. ICT for e-learning to Tanzania rural secondary school is one of the research projects conceived by the University of Dar-es-Salaam through its College of Engineering and Technology. The main objective of the project is to develop a tool to enable ICT support rural secondary school. The project is comprehensive with a number of components, one being development of e-learning management system (e-LMS) for Tanzania secondary schools. This paper presents strategies of developing e-LMS. It shows the importance of integrating action research methodology with the modeling methods as presented by model driven architecture (MDA) and the usefulness of Unified Modeling Language (UML) on the issue of modeling. The benefit of MDA will go along with the development based on software development life cycle (SDLC) process, from analysis and requirement phase through design and implementation stages as employed by object oriented system analysis and design approach. The paper also explains the employment of open source code reuse from open source learning platforms for the context sensitive development of the e-LMS for Tanzania secondary schools.

The Pixel Value Data Approach for Rainfall Forecasting Based on GOES-9 Satellite Image Sequence Analysis

To develop a process of extracting pixel values over the using of satellite remote sensing image data in Thailand. It is a very important and effective method of forecasting rainfall. This paper presents an approach for forecasting a possible rainfall area based on pixel values from remote sensing satellite images. First, a method uses an automatic extraction process of the pixel value data from the satellite image sequence. Then, a data process is designed to enable the inference of correlations between pixel value and possible rainfall occurrences. The result, when we have a high averaged pixel value of daily water vapor data, we will also have a high amount of daily rainfall. This suggests that the amount of averaged pixel values can be used as an indicator of raining events. There are some positive associations between pixel values of daily water vapor images and the amount of daily rainfall at each rain-gauge station throughout Thailand. The proposed approach was proven to be a helpful manual for rainfall forecasting from meteorologists by which using automated analyzing and interpreting process of meteorological remote sensing data.

Novel Anti-leukemia Calanone Compounds by Quantitative Structure-Activity Relationship AM1 Semiempirical Method

Quantitative Structure-Activity Relationship (QSAR) approach for discovering novel more active Calanone derivative as anti-leukemia compound has been conducted. There are 6 experimental activities of Calanone compounds against leukemia cell L1210 that are used as material of the research. Calculation of theoretical predictors (independent variables) was performed by AM1 semiempirical method. The QSAR equation is determined by Principle Component Regression (PCR) analysis, with Log IC50 as dependent variable and the independent variables are atomic net charges, dipole moment (μ), and coefficient partition of noctanol/ water (Log P). Three novel Calanone derivatives that obtained by this research have higher activity against leukemia cell L1210 than pure Calanone.

A New Approach to Annotate the Text's of the Websites and Documents with a Quite Comprehensive Knowledge Base

Machine-understandable data when strongly interlinked constitutes the basis for the SemanticWeb. Annotating web documents is one of the major techniques for creating metadata on the Web. Annotating websites defines the containing data in a form which is suitable for interpretation by machines. In this paper, we present a new approach to annotate websites and documents by promoting the abstraction level of the annotation process to a conceptual level. By this means, we hope to solve some of the problems of the current annotation solutions.

Minimal Residual Method for Adaptive Filtering with Finite Termination

We present a discussion of three adaptive filtering algorithms well known for their one-step termination property, in terms of their relationship with the minimal residual method. These algorithms are the normalized least mean square (NLMS), Affine Projection algorithm (APA) and the recursive least squares algorithm (RLS). The NLMS is shown to be a result of the orthogonality condition imposed on the instantaneous approximation of the Wiener equation, while APA and RLS algorithm result from orthogonality condition in multi-dimensional minimal residual formulation. Further analysis of the minimal residual formulation for the RLS leads to a triangular system which also possesses the one-step termination property (in exact arithmetic)

Multimedia E-Books for Digital Mechanism and Gear Library

This paper presents a digital engineering library – the Digital Mechanism and Gear Library, DMG-Lib – providing a multimedia collection of e-books, pictures, videos and animations in the domain of mechanisms and machines. The specific characteristic about DMG-Lib is the enrichment and cross-linking of the different sources. DMG-Lib e-books not only present pages as pixel images but also selected figures augmented with interactive animations. The presentation of animations in e-books increases the clearness of the information. To present the multimedia e-books and make them available in the DMG-Lib internet portal a special e-book reader called StreamBook was developed for optimal presentation of digitized books and to enable reading the e-books as well as working efficiently and individually with the enriched information. The objective is to support different user tasks ranging from information retrieval to development and design of mechanisms.

Intelligent ABS Fuzzy Controller for Diverse RoadSurfaces

Fuzzy controllers are potential candidates for the control of nonlinear, time variant and also complicated systems. Anti lock brake system (ABS) which is a nonlinear system, may not be easily controlled by classical control methods. An intelligent Fuzzy control method is very useful for this kind of nonlinear system. A typical antilock brake system (ABS) by sensing the wheel lockup, releases the brakes for a short period of time, and then reapplies again the brakes when the wheel spins up. In this paper, an intelligent fuzzy ABS controller is designed to adjust slipping performance for variety of roads. There are tow major sections in the proposing control system. First section consists of tow Fuzzy-Logic Controllers (FLC) providing optimal brake torque for both front and rear wheels. Second section which is also a FLC provides required amount of slip and torque references properties for different kind of roads. Simulation results of our proposed intelligent ABS for three different kinds of road show more reliable and better performance in compare with two other break systems.

Simulation of the Performance of Novel Nonlinear Optimal Control Technique on Two Cart-inverted Pendulum System

The two cart inverted pendulum system is a good bench mark for testing the performance of system dynamics and control engineering principles. Devasia introduced this system to study the asymptotic tracking problem for nonlinear systems. In this paper the problem of asymptotic tracking of the two-cart with an inverted-pendulum system to a sinusoidal reference inputs via introducing a novel method for solving finite-horizon nonlinear optimal control problems is presented. In this method, an iterative method applied to state dependent Riccati equation (SDRE) to obtain a reliable algorithm. The superiority of this technique has been shown by simulation and comparison with the nonlinear approach.

Design Considerations of PV Water Pumping and Rural Electricity System (2011) in Lower Myanmar

Photovoltaic (PV) systems provides a viable means of power generation for applications like powering residential appliances, electrification of villages in rural areas, refrigeration and water pumping. Photovoltaic-power generation is reliable. The operation and maintenance costs are very low. Since Myanmar is a land of plentiful sunshine, especially in central and southern regions of the country, the solar energy could hopefully become the final solution to its energy supply problem in rural area.

Utilization of Agro-Industrial Waste in Metal Matrix Composites: Towards Sustainability

The application of agro-industrial waste in Aluminum Metal Matrix Composites has been getting more attention as they can reinforce particles in metal matrix which enhance the strength properties of the composites. In addition, by applying these agroindustrial wastes in useful way not only save the manufacturing cost of products but also reduce the pollutions on environment. This paper represents a literature review on a range of industrial wastes and their utilization in metal matrix composites. The paper describes the synthesis methods of agro-industrial waste filled metal matrix composite materials and their mechanical, wear, corrosion, and physical properties. It also highlights the current application and future potential of agro-industrial waste reinforced composites in aerospace, automotive and other construction industries.

Limitations of the Analytic Hierarchy Process Technique with Respect to Geographically Distributed Stakeholders

The selection of appropriate requirements for product releases can make a big difference in a product success. The selection of requirements is done by different requirements prioritization techniques. These techniques are based on pre-defined and systematic steps to calculate the requirements relative weight. Prioritization is complicated by new development settings, shifting from traditional co-located development to geographically distributed development. Stakeholders, connected to a project, are distributed all over the world. These geographically distributions of stakeholders make it hard to prioritize requirements as each stakeholder have their own perception and expectations of the requirements in a software project. This paper discusses limitations of the Analytical Hierarchy Process with respect to geographically distributed stakeholders- (GDS) prioritization of requirements. This paper also provides a solution, in the form of a modified AHP, in order to prioritize requirements for GDS. We will conduct two experiments in this paper and will analyze the results in order to discuss AHP limitations with respect to GDS. The modified AHP variant is also validated in this paper.

Political Finance in Africa: Ethiopia as a Case Study

Since 1991 Ethiopia has officially adopted multi-party democracy. At present, there are 89 registered political parties in the country. Though political parties play an important role in the functioning of a democratic government, how to fund them is an issue of major concern. Political parties and individual candidates running for political office have to raise funds for election campaigns, and to survive as political candidates. The aim of this paper is to examine party funding problems in Africa by taking the case of Ethiopia as an example. The paper also evaluates the motives of local and international donors in giving financial and material support to political parties in emerging democracies and assesses the merits and de-merits of their donations.

A Logic Approach to Database Dynamic Updating

We introduce a logic-based framework for database updating under constraints. In our framework, the constraints are represented as an instantiated extended logic program. When performing an update, database consistency may be violated. We provide an approach of maintaining database consistency, and study the conditions under which the maintenance process is deterministic. We show that the complexity of the computations and decision problems presented in our framework is in each case polynomial time.

Non-Isolated Direct AC-DC Converter Design with BCM-PFC Circuit

This paper proposes two types of non-isolated direct AC-DC converters. First, it shows a buck-boost converter with an H-bridge, which requires few components (three switches, two diodes, one inductor and one capacitor) to convert AC input to DC output directly. This circuit can handle a wide range of output voltage. Second, a direct AC-DC buck converter is proposed for lower output voltage applications. This circuit is analyzed with output voltage of 12V. We describe circuit topologies, operation principles and simulation results for both circuits.

Alternative Convergence Analysis for a Kind of Singularly Perturbed Boundary Value Problems

A kind of singularly perturbed boundary value problems is under consideration. In order to obtain its approximation, simple upwind difference discretization is applied. We use a moving mesh iterative algorithm based on equi-distributing of the arc-length function of the current computed piecewise linear solution. First, a maximum norm a posteriori error estimate on an arbitrary mesh is derived using a different method from the one carried out by Chen [Advances in Computational Mathematics, 24(1-4) (2006), 197-212.]. Then, basing on the properties of discrete Green-s function and the presented posteriori error estimate, we theoretically prove that the discrete solutions computed by the algorithm are first-order uniformly convergent with respect to the perturbation parameter ε.

Prediction of Slump in Concrete using Artificial Neural Networks

High Strength Concrete (HSC) is defined as concrete that meets special combination of performance and uniformity requirements that cannot be achieved routinely using conventional constituents and normal mixing, placing, and curing procedures. It is a highly complex material, which makes modeling its behavior a very difficult task. This paper aimed to show possible applicability of Neural Networks (NN) to predict the slump in High Strength Concrete (HSC). Neural Network models is constructed, trained and tested using the available test data of 349 different concrete mix designs of High Strength Concrete (HSC) gathered from a particular Ready Mix Concrete (RMC) batching plant. The most versatile Neural Network model is selected to predict the slump in concrete. The data used in the Neural Network models are arranged in a format of eight input parameters that cover the Cement, Fly Ash, Sand, Coarse Aggregate (10 mm), Coarse Aggregate (20 mm), Water, Super-Plasticizer and Water/Binder ratio. Furthermore, to test the accuracy for predicting slump in concrete, the final selected model is further used to test the data of 40 different concrete mix designs of High Strength Concrete (HSC) taken from the other batching plant. The results are compared on the basis of error function (or performance function).