Influence of Thermo-fluid-dynamic Parameters on Fluidics in an Expanding Thermal Plasma Deposition Chamber

Technology of thin film deposition is of interest in many engineering fields, from electronic manufacturing to corrosion protective coating. A typical deposition process, like that developed at the University of Eindhoven, considers the deposition of a thin, amorphous film of C:H or of Si:H on the substrate, using the Expanding Thermal arc Plasma technique. In this paper a computing procedure is proposed to simulate the flow field in a deposition chamber similar to that at the University of Eindhoven and a sensitivity analysis is carried out in terms of: precursor mass flow rate, electrical power, supplied to the torch and fluid-dynamic characteristics of the plasma jet, using different nozzles. To this purpose a deposition chamber similar in shape, dimensions and operating parameters to the above mentioned chamber is considered. Furthermore, a method is proposed for a very preliminary evaluation of the film thickness distribution on the substrate. The computing procedure relies on two codes working in tandem; the output from the first code is the input to the second one. The first code simulates the flow field in the torch, where Argon is ionized according to the Saha-s equation, and in the nozzle. The second code simulates the flow field in the chamber. Due to high rarefaction level, this is a (commercial) Direct Simulation Monte Carlo code. Gas is a mixture of 21 chemical species and 24 chemical reactions from Argon plasma and Acetylene are implemented in both codes. The effects of the above mentioned operating parameters are evaluated and discussed by 2-D maps and profiles of some important thermo-fluid-dynamic parameters, as per Mach number, velocity and temperature. Intensity, position and extension of the shock wave are evaluated and the influence of the above mentioned test conditions on the film thickness and uniformity of distribution are also evaluated.

Culturally Enhanced Collaborative Filtering

We propose an enhanced collaborative filtering method using Hofstede-s cultural dimensions, calculated for 111 countries. We employ 4 of these dimensions, which are correlated to the costumers- buying behavior, in order to detect users- preferences for items. In addition, several advantages of this method demonstrated for data sparseness and cold-start users, which are important challenges in collaborative filtering. We present experiments using a real dataset, Book Crossing Dataset. Experimental results shows that the proposed algorithm provide significant advantages in terms of improving recommendation quality.

Digital Social Networks: Examining the Knowledge Characteristics

In today-s information age, numbers of organizations are still arguing on capitalizing the values of Information Technology (IT) and Knowledge Management (KM) to which individuals can benefit from and effective communication among the individuals can be established. IT exists in enabling positive improvement for communication among knowledge workers (k-workers) with a number of social network technology domains at workplace. The acceptance of digital discourse in sharing of knowledge and facilitating the knowledge and information flows at most of the organizations indeed impose the culture of knowledge sharing in Digital Social Networks (DSN). Therefore, this study examines whether the k-workers with IT background would confer an effect on the three knowledge characteristics -- conceptual, contextual, and operational. Derived from these three knowledge characteristics, five potential factors will be examined on the effects of knowledge exchange via e-mail domain as the chosen query. It is expected, that the results could provide such a parameter in exploring how DSN contributes in supporting the k-workers- virtues, performance and qualities as well as revealing the mutual point between IT and KM.

Evaluation of Drainage Conditions along Selected Roadways in Amman

Roadways in Amman city face many problems consequent upon poor drainage systems. Evaluation tools are necessary to identify those roads needing improvement in their drainage system, and those needing regular maintenance. This work aims at evaluating drainage conditions in selected roadways in Amman city with the intent of identifying the problems encountered in their drainage systems. Three sites in the vicinity of Amman city have been selected and then inspected via several field visits to determine the state of their existing drainage systems and define the major problems encountered in these systems. The evaluation tool used in this study is based on visual inspection supported by photographs that depicted the defined problems. Following the field assessment, the drainage system in each road was rated as excellent, fair, good, or poor. The study reveals that more than 60% of the roadways in the selected sites were in poor drainage conditions, which lead to tremendous environmental problems. This assessment serves as a guide for local decision makers to help plan for the maintenance of Amman city roadways drainage systems, and propose ways of managing the associated problems.

Scatterer Density in Edge and Coherence Enhancing Nonlinear Anisotropic Diffusion for Medical Ultrasound Speckle Reduction

This paper proposes new enhancement models to the methods of nonlinear anisotropic diffusion to greatly reduce speckle and preserve image features in medical ultrasound images. By incorporating local physical characteristics of the image, in this case scatterer density, in addition to the gradient, into existing tensorbased image diffusion methods, we were able to greatly improve the performance of the existing filtering methods, namely edge enhancing (EE) and coherence enhancing (CE) diffusion. The new enhancement methods were tested using various ultrasound images, including phantom and some clinical images, to determine the amount of speckle reduction, edge, and coherence enhancements. Scatterer density weighted nonlinear anisotropic diffusion (SDWNAD) for ultrasound images consistently outperformed its traditional tensor-based counterparts that use gradient only to weight the diffusivity function. SDWNAD is shown to greatly reduce speckle noise while preserving image features as edges, orientation coherence, and scatterer density. SDWNAD superior performances over nonlinear coherent diffusion (NCD), speckle reducing anisotropic diffusion (SRAD), adaptive weighted median filter (AWMF), wavelet shrinkage (WS), and wavelet shrinkage with contrast enhancement (WSCE), make these methods ideal preprocessing steps for automatic segmentation in ultrasound imaging.

Differential Protection for Power Transformer Using Wavelet Transform and PNN

A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard deviation are calculated using Parsevals theorem. These features are used as inputs to PNN (Probabilistic neural network) for fault classification. The proposed algorithm provides more accurate results even in the presence of noise inputs and accurately identifies inrush and fault currents. Overall classification accuracy of the proposed method is found to be 96.45%. Simulation of the fault (with and without noise) was done using MATLAB AND SIMULINK software taking 2 cycles of data window (40 m sec) containing 800 samples. The algorithm was evaluated by using 10 % Gaussian white noise.

Construction Of Decentralized Lifetime Maximizing Tree for Data Aggregation in Wireless Sensor Networks

To meet the demands of wireless sensor networks (WSNs) where data are usually aggregated at a single source prior to transmitting to any distant user, there is a need to establish a tree structure inside any given event region. In this paper , a novel technique to create one such tree is proposed .This tree preserves the energy and maximizes the lifetime of event sources while they are constantly transmitting for data aggregation. The term Decentralized Lifetime Maximizing Tree (DLMT) is used to denote this tree. DLMT features in nodes with higher energy tend to be chosen as data aggregating parents so that the time to detect the first broken tree link can be extended and less energy is involved in tree maintenance. By constructing the tree in such a way, the protocol is able to reduce the frequency of tree reconstruction, minimize the amount of data loss ,minimize the delay during data collection and preserves the energy.

Skin Lesion Segmentation Using Color Channel Optimization and Clustering-based Histogram Thresholding

Automatic segmentation of skin lesions is the first step towards the automated analysis of malignant melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most effective color space for melanoma application. This paper proposes an automatic segmentation algorithm based on color space analysis and clustering-based histogram thresholding, a process which is able to determine the optimal color channel for detecting the borders in dermoscopy images. The algorithm is tested on a set of 30 high resolution dermoscopy images. A comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm, applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. By performing ROC analysis and ranking the metrics, it is demonstrated that the best results are obtained with the X and XoYoR color channels, resulting in an accuracy of approximately 97%. The proposed method is also compared with two state-of-theart skin lesion segmentation methods.

Futures Trading: Design of a Strategy

The paper describes the futures trading and aims to design the speculators trading strategy. The problem is formulated as the decision making task and such as is solved. The solution of the task leads to complex mathematical problems and the approximations of the decision making is demanded. Two kind of approximation are used in the paper: Monte Carlo for the multi-step prediction and iteration spread in time for the optimization. The solution is applied to the real-market data and the results of the off-line experiments are presented.

Estimation Method for the Construction of Hydrogen Society with Various Biomass Resources in Japan-Project of Cost Reductions in Biomass Transport and Feasibility for Hydrogen Station with Biomass-

It was determined that woody biomass and livestock excreta can be utilized as hydrogen resources and hydrogen produced from such sources can be used to fill fuel cell vehicles (FCVs) at hydrogen stations. It was shown that the biomass transport costs for hydrogen production may be reduced the costs for co-generation. In the Tokyo Metropolitan Area, there are only a few sites capable of producing hydrogen from woody biomass in amounts greater than 200 m3/h-the scale required for a hydrogen station to be operationally practical. However, in the case of livestock excreta, it was shown that 15% of the municipalities in this area are capable of securing sufficient biomass to be operationally practical for hydrogen production. The differences in feasibility of practical operation depend on the type of biomass.

A Forecast Model for Projecting the Amount of Hazardous Waste

The objective of the paper is to develop the forecast model for the HW flows. The methodology of the research included 6 modules: historical data, assumptions, choose of indicators, data processing, and data analysis with STATGRAPHICS, and forecast models. The proposed methodology was validated for the case study for Latvia. Hypothesis on the changes in HW for time period of 2010-2020 have been developed and mathematically described with confidence level of 95.0% and 50.0%. Sensitivity analysis for the analyzed scenarios was done. The results show that the growth of GDP affects the total amount of HW in the country. The total amount of the HW is projected to be within the corridor of – 27.7% in the optimistic scenario up to +87.8% in the pessimistic scenario with confidence level of 50.0% for period of 2010-2020. The optimistic scenario has shown to be the least flexible to the changes in the GDP growth.

Modeling and Parametric Study for CO2/CH4 Separation Using Membrane Processes

The upgrading of low quality crude natural gas (NG) is attracting interest due to high demand of pipeline-grade gas in recent years. Membrane processes are commercially proven technology for the removal of impurities like carbon dioxide from NG. In this work, cross flow mathematical model has been suggested to be incorporated with ASPEN HYSYS as a user defined unit operation in order to design the membrane system for CO2/CH4 separation. The effect of operating conditions (such as feed composition and pressure) and membrane selectivity on the design parameters (methane recovery and total membrane area required for the separation) has been studied for different design configurations. These configurations include single stage (with and without recycle) and double stage membrane systems (with and without permeate or retentate recycle). It is shown that methane recovery can be improved by recycling permeate or retentate stream as well as by using double stage membrane systems. The ASPEN HYSYS user defined unit operation proposed in the study has potential to be applied for complex membrane system design and optimization.

Public Transport Reform in Indonesia, A Case Study in the City of Yogyakarta

The provision of urban public transport in Indonesia is not free of problems. Some of the problems include: an overall lack of capacity, lack of quality and choice, severe traffic congestions and insufficient fund to renew and repair vehicles. Generally, the comfort and quality of the city bus is poor, and many of the vehicles are dilapidated and dirty. Surveys were carried out in the city of Yogyakarta, by counting city bus vehicles and occupancies, interviewing the bus passengers, drivers and institutional staffs, who involve in public transport management. This paper will then analyze the possible plan to develop the public transport system to become more attractive and to improve the public transport management. The short, medium and long term plans are analyzed, to find the best solutions. Some constraints such as social impacts and financial impact are also taken into accounts.

Multi-Criteria Spatial Analysis for the Localization of Production Structures. Analytic Hierarchy Process and Geographical Information Systems in the Case of Expanding an Industrial Area

Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.

Preparing Entrepreneurial Women: A Challenge for Indian Education System

Education, as the most important resource in any country, has multiplying effects on all facets of development in a society. The new social realities, particularly the interplay between democratization of education; unprecedented developments in IT sector; emergence of knowledge society, liberalization of economy and globalization have greatly influenced the educational process of all nations. This turbulence entails upon education to undergo dramatic changes to keep up with the new expectations. Growth of entrepreneurship among Indian women is highly important for empowering them and this is highly essential for socio-economic development of a society. Unfortunately in India there is poor acceptance of entrepreneurship among women as unfounded myths and fears restrain them to be enterprising. To remove these inhibitions, education system needs to be re-engineered to make entrepreneurship more acceptable. This paper empirically analyses the results of a survey done on around 500 female graduates in North India to measure and evaluate various entrepreneurial traits present in them. A formative model has been devised in this context, which should improve the teaching-learning process in our education system, which can lead to sustainable growth of women entrepreneurship in India.

Critical Issues Affecting the Engagement by Staff in Professional Development for E-Learning: Findings from a Research Project within the Context of a National Tertiary Education Sector

This paper focuses on issues of engagement by staff in professional development related to the delivery of e-learning. The paper reports on findings drawn from a New Zealand research project which is producing a sector-wide framework for professional development in tertiary e-learning. The research findings indicate that staff engaged in e-learning in tertiary institutions is not making the most effective use of the professional development opportunities available to them; rather they seem to gain their knowledge and support from a variety of informal means. This is despite an emphasis on the provision of professional development opportunities by both Government Policies and Institutions themselves. The conclusion drawn from the findings is that institutional approaches to professional development for e-learning do not yet fully reflect the demands and constraints that working in a digital context impose.

Mixture Design Experiment on Flow Behaviour of O/W Emulsions as Affected by Polysaccharide Interactions

Interaction effects of xanthan gum (XG), carboxymethyl cellulose (CMC), and locust bean gum (LBG) on the flow properties of oil-in-water emulsions were investigated by a mixture design experiment. Blends of XG, CMC and LBG were prepared according to an augmented simplex-centroid mixture design (10 points) and used at 0.5% (wt/wt) in the emulsion formulations. An appropriate mathematical model was fitted to express each response as a function of the proportions of the blend components that are able to empirically predict the response to any blend of combination of the components. The synergistic interaction effect of the ternary XG:CMC:LBG blends at approximately 33-67% XG levels was shown to be much stronger than that of the binary XG:LBG blend at 50% XG level (p < 0.05). Nevertheless, an antagonistic interaction effect became significant as CMC level in blends was more than 33% (p < 0.05). Yield stress and apparent viscosity (at 10 s-1) responses were successfully fitted with a special quartic model while flow behaviour index and consistency coefficient were fitted with a full quartic model (R2 adjusted ≥ 0.90). This study found that a mixture design approach could serve as a valuable tool in better elucidating and predicting the interaction effects beyond the conventional twocomponent blends.

Loop Back Connected Component Labeling Algorithm and Its Implementation in Detecting Face

In this study, a Loop Back Algorithm for component connected labeling for detecting objects in a digital image is presented. The approach is using loop back connected component labeling algorithm that helps the system to distinguish the object detected according to their label. Deferent than whole window scanning technique, this technique reduces the searching time for locating the object by focusing on the suspected object based on certain features defined. In this study, the approach was also implemented for a face detection system. Face detection system is becoming interesting research since there are many devices or systems that require detecting the face for certain purposes. The input can be from still image or videos, therefore the sub process of this system has to be simple, efficient and accurate to give a good result.

Modified Vector Quantization Method for Image Compression

A low bit rate still image compression scheme by compressing the indices of Vector Quantization (VQ) and generating residual codebook is proposed. The indices of VQ are compressed by exploiting correlation among image blocks, which reduces the bit per index. A residual codebook similar to VQ codebook is generated that represents the distortion produced in VQ. Using this residual codebook the distortion in the reconstructed image is removed, thereby increasing the image quality. Our scheme combines these two methods. Experimental results on standard image Lena show that our scheme can give a reconstructed image with a PSNR value of 31.6 db at 0.396 bits per pixel. Our scheme is also faster than the existing VQ variants.

Differences in Students` Satisfaction with Distance Learning Studies

Rapid growth of distance learning resulted in importance to conduct research on students- satisfaction with distance learning because differences in students- satisfaction might influence educational opportunities for learning in a relevant Web-based environment. In line with this, this paper deals with satisfaction of students with distance module at Faculty of organizational sciences (FOS) in Serbia as well as some factors affecting differences in their satisfaction . We have conducted a research on a population of 68 first-year students of distance learning studies at FOS. Using statistical techniques, we have found out that there is no significant difference in students- satisfaction with distance learning module between men and women. In the same way, we also concluded that there is a difference in satisfaction with distance learning module regarding to student-s perception of opportunity to gain knowledge as the classic students.