3DARModeler: a 3D Modeling System in Augmented Reality Environment

This paper describes a 3D modeling system in Augmented Reality environment, named 3DARModeler. It can be considered a simple version of 3D Studio Max with necessary functions for a modeling system such as creating objects, applying texture, adding animation, estimating real light sources and casting shadows. The 3DARModeler introduces convenient, and effective human-computer interaction to build 3D models by combining both the traditional input method (mouse/keyboard) and the tangible input method (markers). It has the ability to align a new virtual object with the existing parts of a model. The 3DARModeler targets nontechnical users. As such, they do not need much knowledge of computer graphics and modeling techniques. All they have to do is select basic objects, customize their attributes, and put them together to build a 3D model in a simple and intuitive way as if they were doing in the real world. Using the hierarchical modeling technique, the users are able to group several basic objects to manage them as a unified, complex object. The system can also connect with other 3D systems by importing and exporting VRML/3Ds Max files. A module of speech recognition is included in the system to provide flexible user interfaces.

Corporate Governance Practices and Audit Quality: An Empirical Study of the Listed Companies in Egypt

Recent financial international scandals around the world have led to a number of investigations into the effectiveness of corporate governance practices and audit quality. Although evidence of corporate governance practices and audit quality exists from developed economies, very scanty studies have been conducted in Egypt where corporate governance is just evolving. Therefore, this study provides evidence on the effectiveness of corporate governance practices and audit quality from a developing country. The data for analysis are gathered from the top 50 most active companies in the Egyptian Stock Exchange, covering the three year period 2007-2009. Logistic regression was used in investigating the questions that were raised in the study. Findings from the study show that board independence; CEO duality and audit committees significantly have relationship with audit quality. The results also, indicate that institutional investor and managerial ownership have no significantly relationship with audit quality. Evidence also exist that size of the company; complexity and business leverage are important factors in audit quality for companies quoted on the Egypt Stock Exchange.

Dynamic Anonymity

Encryption protects communication partners from disclosure of their secret messages but cannot prevent traffic analysis and the leakage of information about “who communicates with whom". In the presence of collaborating adversaries, this linkability of actions can danger anonymity. However, reliably providing anonymity is crucial in many applications. Especially in contextaware mobile business, where mobile users equipped with PDAs request and receive services from service providers, providing anonymous communication is mission-critical and challenging at the same time. Firstly, the limited performance of mobile devices does not allow for heavy use of expensive public-key operations which are commonly used in anonymity protocols. Moreover, the demands for security depend on the application (e.g., mobile dating vs. pizza delivery service), but different users (e.g., a celebrity vs. a normal person) may even require different security levels for the same application. Considering both hardware limitations of mobile devices and different sensitivity of users, we propose an anonymity framework that is dynamically configurable according to user and application preferences. Our framework is based on Chaum-s mixnet. We explain the proposed framework, its configuration parameters for the dynamic behavior and the algorithm to enforce dynamic anonymity.

Developing a Sustainable Educational Portal for the D-Grid Community

Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.

A Simplified Approach for Load Flow Analysis of Radial Distribution Network

This paper presents a simple approach for load flow analysis of a radial distribution network. The proposed approach utilizes forward and backward sweep algorithm based on Kirchoff-s current law (KCL) and Kirchoff-s voltage law (KVL) for evaluating the node voltages iteratively. In this approach, computation of branch current depends only on the current injected at the neighbouring node and the current in the adjacent branch. This approach starts from the end nodes of sub lateral line, lateral line and main line and moves towards the root node during branch current computation. The node voltage evaluation begins from the root node and moves towards the nodes located at the far end of the main, lateral and sub lateral lines. The proposed approach has been tested using four radial distribution systems of different size and configuration and found to be computationally efficient.

Effect of Butachlor on the Microbial Population of Direct Sown Rice

Field experiments were conducted at Annamalai University Experimental Farm, Department of Agronomy; to device suitable weed control measures for direct seeded puddled rice and to study the effect of the weed control measures on the soil microbial population. The treatments comprised of incorporation of pressmud @ 6.25 t ha-1 and application of herbicide butachlor @1.5 kg a. i. ha- 1 with and without safener 4 days after sowing (DAS), 8 DAS alone and also in conjunction with hand weeding at 30 DAS. Hand weeding twice and a weedy check were also maintained. At maximum tillering stage, the population of bacteria was significantly reduced by butachlor application. The injury to microbes caused by herbicide disappeared with the advancement of crop's age and at flowering stage of crop, there was no significant difference among the treatments. The fungal and actinomycetes population remained unaltered by weed control treatments at both the stages of observation.

Using Neural Network for Execution of Programmed Pulse Width Modulation (PPWM) Method

Application of neural networks in execution of programmed pulse width modulation (PPWM) of a voltage source inverter (VSI) is studied in this paper. Using the proposed method it is possible to cancel out the desired harmonics in output of VSI in addition to control the magnitude of fundamental harmonic, contineously. By checking the non-trained values and a performance index, the most appropriate neural network is proposed. It is shown that neural networks may solve the custom difficulties of practical utilization of PPWM such as large size of memory, complex digital circuits and controlling the magnitude of output voltage in a discrete manner.

Capacity of Overloaded DS-CDMA System on Rayleigh Fading Channel with Timing Error

The number of users supported in a DS-CDMA cellular system is typically less than spreading factor (N), and the system is said to be underloaded. Overloading is a technique to accommodate more number of users than the spreading factor N. In O/O overloading scheme, the first set is assigned to the N synchronous users and the second set is assigned to the additional synchronous users. An iterative multistage soft decision interference cancellation (SDIC) receiver is used to remove high level of interference between the two sets. Performance is evaluated in terms of the maximum number acceptable users so that the system performance is degraded slightly compared to the single user performance at a specified BER. In this paper, the capacity of CDMA based O/O overloading scheme is evaluated with SDIC receiver. It is observed that O/O scheme using orthogonal Gold codes provides 25% channel overloading (N=64) for synchronous DS-CDMA system on an AWGN channel in the uplink at a BER of 1e-5.For a Rayleigh faded channel, the critical capacity is 40% at a BER of 5e-5 assuming synchronous users. But in practical systems, perfect chip timing is very difficult to maintain in the uplink.. We have shown that the overloading performance reduces to 11% for a timing synchronization error of 0.02Tc for a BER of 1e-5.

Alignment of MG-63 Osteoblasts on Fibronectin-Coated Phosphorous Doping Lattices in Silicon

A major challenge in biomaterials research is the regulation of protein adsorption which is a key factor for controlling the subsequent cell adhesion at implant surfaces. The aim of the present study was to control the adsorption of fibronectin (FN) and the attachment of MG-63 osteoblasts with an electronic nanostructure. Shallow doping line lattices with a period of 260 nm were produced for this purpose by implantation of phosphorous in silicon wafers. Protein coverage was determined after incubating the substrate with FN by means of an immunostaining procedure and the measurement of the fluorescence intensity with a TECAN analyzer. We observed an increased amount of adsorbed FN on the nanostructure compared to control substrates. MG-63 osteoblasts were cultivated for 24h on FN-incubated substrates and their morphology was assessed by SEM. Preferred orientation and elongation of the cells in direction of the doping lattice lines was observed on FN-coated nanostructures.

An Effective Approach for Distribution System Power Flow Solution

An effective approach for unbalanced three-phase distribution power flow solutions is proposed in this paper. The special topological characteristics of distribution networks have been fully utilized to make the direct solution possible. Two matrices–the bus-injection to branch-current matrix and the branch-current to busvoltage matrix– and a simple matrix multiplication are used to obtain power flow solutions. Due to the distinctive solution techniques of the proposed method, the time-consuming LU decomposition and forward/backward substitution of the Jacobian matrix or admittance matrix required in the traditional power flow methods are no longer necessary. Therefore, the proposed method is robust and time-efficient. Test results demonstrate the validity of the proposed method. The proposed method shows great potential to be used in distribution automation applications.

Adjusted Ratio and Regression Type Estimators for Estimation of Population Mean when some Observations are missing

Ratio and regression type estimators have been used by previous authors to estimate a population mean for the principal variable from samples in which both auxiliary x and principal y variable data are available. However, missing data are a common problem in statistical analyses with real data. Ratio and regression type estimators have also been used for imputing values of missing y data. In this paper, six new ratio and regression type estimators are proposed for imputing values for any missing y data and estimating a population mean for y from samples with missing x and/or y data. A simulation study has been conducted to compare the six ratio and regression type estimators with a previous estimator of Rueda. Two population sizes N = 1,000 and 5,000 have been considered with sample sizes of 10% and 30% and with correlation coefficients between population variables X and Y of 0.5 and 0.8. In the simulations, 10 and 40 percent of sample y values and 10 and 40 percent of sample x values were randomly designated as missing. The new ratio and regression type estimators give similar mean absolute percentage errors that are smaller than the Rueda estimator for all cases. The new estimators give a large reduction in errors for the case of 40% missing y values and sampling fraction of 30%.

Feature Weighting and Selection - A Novel Genetic Evolutionary Approach

A feature weighting and selection method is proposed which uses the structure of a weightless neuron and exploits the principles that govern the operation of Genetic Algorithms and Evolution. Features are coded onto chromosomes in a novel way which allows weighting information regarding the features to be directly inferred from the gene values. The proposed method is significant in that it addresses several problems concerned with algorithms for feature selection and weighting as well as providing significant advantages such as speed, simplicity and suitability for real-time systems.

Problems and Obstacles to Value Creation of Thai Monk-s Bowls: The Case Study of Ban-Baat Village, Bangkok

This research aims to study value-creation process of producing monk-s bowls, Thai traditional handicrafts, which is facing problems in adapting to the changing society. It also aims to identify problems and obstacles to value creation. This research is based on a case study of monk-s bowl manufactures from Ban-Baat Village, Bangkok. The conceptual framework is based on the model of value chain to analyze the process. The research methodology is qualitative. This research found that the value-creation process of monk-s bowls consists of eight activities contributing to adding value to the products and increasing profits to the producers in return. Five major problems and obstacles are found. The research suggests that these problems and obstacles limit the manufacturers- potential for creating more valued product and lead to business stagnation. These problems should be addressed and solved with collaboration among the government, the private sector and the manufacturers.

Influence of Reaction Temperature and Water Content on Wheat Straw Pyrolysis

The aim of this study was to investigate the influence of reaction temperature and wheat straw moisture content on the pyrolysis product yields, in the temperature range of 475-575 °C. Samples of straw with moisture contents from 1.5 wt % to 15.0 wt % were fed to a bench scale Pyrolysis Centrifuge Reactor (PCR). The experimental results show that the changes in straw moisture content have no significant effect on the distribution of pyrolysis product yields. The maximum bio-oil yields approximately 60 (wt %, on dry ash free feedstock basis) was observed around 525 °C - 550 °C for all straw moisture levels. The water content in the wet straw bio-oil was the highest. The heating value of bio-oil and solid char were measured and the percentages of its energy distribution were calculated. The energy distributions of bio-oil, char and gas were 56- 69 % 24-33 %, and 2-19 %, respectively.

Investigating Ultra Violet (UV) Strength against Different Level of Altitude using New Environmental Data Management System

This paper presents the investigation results of UV measurement at different level of altitudes and the development of a new portable instrument for measuring UV. The rapid growth of industrial sectors in developing countries including Malaysia, brings not only income to the nation, but also causes pollution in various forms. Air pollution is one of the significant contributors to global warming by depleting the Ozone layer, which would reduce the filtration of UV rays. Long duration of exposure to high to UV rays has many devastating health effects to mankind directly or indirectly through destruction of the natural resources. This study aimed to show correlation between UV and altitudes which indirectly can help predict Ozone depletion. An instrument had been designed to measure and monitors the level of UV. The instrument comprises of two main blocks namely data logger and Graphic User Interface (GUI). Three sensors were used in the data logger to detect changes in the temperature, humidity and ultraviolet. The system has undergone experimental measurement to capture data at two different conditions; industrial area and high attitude area. The performance of the instrument showed consistency in the data captured and the results of the experiment drew a significantly high reading of UV at high altitudes.

Effects of Tillage and Oil Palm Bunch Ash Plus Poultry Manure on Soil Chemical Properties, Growth and Ginger Yield

Field experiments were carried out at Owo, southwest Nigeria to evaluate the effect of different tillage practices (zero tillage with mulch (ZTM), row tillage (RT) and conventional tillage (CT), and with or without oil palm bunch ash plus poultry manure (OBA+PM) on soil chemical properties, growth and yield of ginger. The experiment was laid out in a randomized complete plot design with three replications. Soil chemical properties, growth and fresh rhizome yield reduced with frequency/intensity of tillage imposed while application of OBA+PM increased them. Among the tillage practices, the highest fresh rhizome yield (15.0t ha-1) was produced by ZTM which was significantly different from other tillage practices. Among the tillage – OBA+PM combinations, the  most satisfactorily yield (20.1t ha-1) was produced by ZTM+OBA+PM while the lowest yield (15.7t ha-1) was in CT+OBA+PM.

VaR Forecasting in Times of Increased Volatility

The paper evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the ARMA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting accuracy is evaluated on the out-of-sample data, which are more volatile. The main aim of the paper is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index separately. The primary result of the paper is that the volatility is best modelled using a GARCH process and that an ARMA process pattern cannot be found in analyzed time series.

A Stochastic Approach of Mitochondrial Dynamics

Mitochondria are dynamic organelles, capable to interact with each other. While the number of mitochondria in a cell varies, their quality and functionality depends on the operation of fusion, fission, motility and mitophagy. Nowadays, several researches declare as an important factor in neurogenerative diseases the disruptions in the regulation of mitochondrial dynamics. In this paper a stochastic model in BioAmbients calculus is presented, concerning mitochondrial fusion and its distribution in the renewal of mitochondrial population in a cell. This model describes the successive and dependent stages of protein synthesis, protein-s activation and merging of two independent mitochondria.

A Strategy for Scaling-Up Vitamin A Supplementation in a Remote Rural Setting

Vitamin A deficiency is a public health problem in Zimbabwe. Addressing vitamin A deficiency has the potential of enhancing resistance to disease and reducing mortality especially in children less than 5 years. We implemented and adapted vitamin A outreach supplementation strategy within the National Immunization Days and Extended Programme of Immunization in a rural district in Zimbabwe. Despite usual operational challenges faced this approach enabled the district to increase delivery of supplementation coverage. This paper describes the outreach strategy that was implemented in the remote rural district. The strategy covered 63 outreach sites with 2 sites being covered per day and visited once per month for the whole year. Coverage reached 71% in an area of previous coverage rates of around less than 50%. We recommend further exploration of this strategy by others working in similar circumstances. This strategy can be a potential way for use by Scaling-Up-Nutrition member states.

Improved Tropical Wood Species Recognition System based on Multi-feature Extractor and Classifier

An automated wood recognition system is designed to classify tropical wood species.The wood features are extracted based on two feature extractors: Basic Grey Level Aura Matrix (BGLAM) technique and statistical properties of pores distribution (SPPD) technique. Due to the nonlinearity of the tropical wood species separation boundaries, a pre classification stage is proposed which consists ofKmeans clusteringand kernel discriminant analysis (KDA). Finally, Linear Discriminant Analysis (LDA) classifier and KNearest Neighbour (KNN) are implemented for comparison purposes. The study involves comparison of the system with and without pre classification using KNN classifier and LDA classifier.The results show that the inclusion of the pre classification stage has improved the accuracy of both the LDA and KNN classifiers by more than 12%.