Burning Rates of Turbulent Gaseous and Aerosol Flames

Combustion of sprays is of technological importance, but its flame behavior is not fully understood. Furthermore, the multiplicity of dependent variables such as pressure, temperature, equivalence ratio, and droplet sizes complicates the study of spray combustion. Fundamental study on the influence of the presence of liquid droplets has revealed that laminar flames within aerosol mixtures more readily become unstable than for gaseous ones and this increases the practical burning rate. However, fundamental studies on turbulent flames of aerosol mixtures are limited particularly those under near mono-dispersed droplet conditions. In the present work, centrally ignited expanding flames at near atmospheric pressures are employed to quantify the burning rates in gaseous and aerosol flames. Iso-octane-air aerosols are generated by expansion of the gaseous pre-mixture to produce a homogeneously distributed suspension of fuel droplets. The effects of the presence of droplets and turbulence velocity in relation to the burning rates of the flame are also investigated.

A Soft Systems Methodology Perspective on Data Warehousing Education Improvement

This paper demonstrates how the soft systems methodology can be used to improve the delivery of a module in data warehousing for fourth year information technology students. Graduates in information technology needs to have academic skills but also needs to have good practical skills to meet the skills requirements of the information technology industry. In developing and improving current data warehousing education modules one has to find a balance in meeting the expectations of various role players such as the students themselves, industry and academia. The soft systems methodology, developed by Peter Checkland, provides a methodology for facilitating problem understanding from different world views. In this paper it is demonstrated how the soft systems methodology can be used to plan the improvement of data warehousing education for fourth year information technology students.

Feature Point Reduction for Video Stabilization

Corner detection and optical flow are common techniques for feature-based video stabilization. However, these algorithms are computationally expensive and should be performed at a reasonable rate. This paper presents an algorithm for discarding irrelevant feature points and maintaining them for future use so as to improve the computational cost. The algorithm starts by initializing a maintained set. The feature points in the maintained set are examined against its accuracy for modeling. Corner detection is required only when the feature points are insufficiently accurate for future modeling. Then, optical flows are computed from the maintained feature points toward the consecutive frame. After that, a motion model is estimated based on the simplified affine motion model and least square method, with outliers belonging to moving objects presented. Studentized residuals are used to eliminate such outliers. The model estimation and elimination processes repeat until no more outliers are identified. Finally, the entire algorithm repeats along the video sequence with the points remaining from the previous iteration used as the maintained set. As a practical application, an efficient video stabilization can be achieved by exploiting the computed motion models. Our study shows that the number of times corner detection needs to perform is greatly reduced, thus significantly improving the computational cost. Moreover, optical flow vectors are computed for only the maintained feature points, not for outliers, thus also reducing the computational cost. In addition, the feature points after reduction can sufficiently be used for background objects tracking as demonstrated in the simple video stabilizer based on our proposed algorithm.

Learning Objects: A New Paradigm for ELearning Resource Development for Secondary Schools in Tanzania

The Information and Communication Technologies (ICTs), and the Wide World Web (WWW) have fundamentally altered the practice of teaching and learning world wide. Many universities, organizations, colleges and schools are trying to apply the benefits of the emerging ICT. In the early nineties the term learning object was introduced into the instructional technology vernacular; the idea being that educational resources could be broken into modular components for later combination by instructors, learners, and eventually computes into larger structures that would support learning [1]. However in many developing countries, the use of ICT is still in its infancy stage and the concept of learning object is quite new. This paper outlines the learning object design considerations for developing countries depending on learning environment.

Wetting Behavior of Reactive and Non–Reactive Wetting of Liquids on Metallic Substrates

Wetting characteristics of reactive (Sn–0.7Cu solder) and non– reactive (castor oil) wetting of liquids on Cu and Ag plated Al substrates have been investigated. Solder spreading exhibited capillary, gravity and viscous regimes. Oils did not exhibit noticeable spreading regimes. Solder alloy showed better wettability on Ag coated Al substrate compared to Cu plating. In the case of castor oil, Cu coated Al substrate exhibited good wettability as compared to Ag coated Al substrates. The difference in wettability during reactive wetting of solder and non–reactive wetting of oils is attributed to the change in the surface energies of Al substrates brought about by the formation of intermetallic compounds (IMCs).

A Digitally Programmable Voltage-mode Multifunction Biquad Filter with Single-Output

This article proposes a voltage-mode multifunction filter using differential voltage current controllable current conveyor transconductance amplifier (DV-CCCCTA). The features of the circuit are that: the quality factor and pole frequency can be tuned independently via the values of capacitors: the circuit description is very simple, consisting of merely 1 DV-CCCCTA, and 2 capacitors. Without any component matching conditions, the proposed circuit is very appropriate to further develop into an integrated circuit. Additionally, each function response can be selected by suitably selecting input signals with digital method. The PSpice simulation results are depicted. The given results agree well with the theoretical anticipation.

New Explicit Group Newton's Iterative Methods for the Solutions of Burger's Equation

In this article, we aim to discuss the formulation of two explicit group iterative finite difference methods for time-dependent two dimensional Burger-s problem on a variable mesh. For the non-linear problems, the discretization leads to a non-linear system whose Jacobian is a tridiagonal matrix. We discuss the Newton-s explicit group iterative methods for a general Burger-s equation. The proposed explicit group methods are derived from the standard point and rotated point Crank-Nicolson finite difference schemes. Their computational complexity analysis is discussed. Numerical results are given to justify the feasibility of these two proposed iterative methods.

Capacity Optimization for Local and Cooperative Spectrum Sensing in Cognitive Radio Networks

The dynamic spectrum allocation solutions such as cognitive radio networks have been proposed as a key technology to exploit the frequency segments that are spectrally underutilized. Cognitive radio users work as secondary users who need to constantly and rapidly sense the presence of primary users or licensees to utilize their frequency bands if they are inactive. Short sensing cycles should be run by the secondary users to achieve higher throughput rates as well as to provide low level of interference to the primary users by immediately vacating their channels once they have been detected. In this paper, the throughput-sensing time relationship in local and cooperative spectrum sensing has been investigated under two distinct scenarios, namely, constant primary user protection (CPUP) and constant secondary user spectrum usability (CSUSU) scenarios. The simulation results show that the design of sensing slot duration is very critical and depends on the number of cooperating users under CPUP scenario whereas under CSUSU, cooperating more users has no effect if the sensing time used exceeds 5% of the total frame duration.

Optimization of Conditions for Xanthan Gum Production from Waste Date in Submerged Fermantation

Xanthan gum is one of the major commercial biopolymers. Due to its excellent rheological properties xanthan gum is used in many applications, mainly in food industry. Commercial production of xanthan gum uses glucose as the carbon substrate; consequently the price of xanthan production is high. One of the ways to decrease xanthan price, is using cheaper substrate like agricultural wastes. Iran is one of the biggest date producer countries. However approximately 50% of date production is wasted annually. The goal of this study is to produce xanthan gum from waste date using Xanthomonas campestris PTCC1473 by submerged fermentation. In this study the effect of three variables including phosphor and nitrogen amount and agitation rate in three levels using response surface methodology (RSM) has been studied. Results achieved from statistical analysis Design Expert 7.0.0 software showed that xanthan increased with increasing level of phosphor. Low level of nitrogen leaded to higher xanthan production. Xanthan amount, increasing agitation had positive influence. The statistical model identified the optimum conditions nitrogen amount=3.15g/l, phosphor amount=5.03 g/l and agitation=394.8 rpm for xanthan. To model validation, experiments in optimum conditions for xanthan gum were carried out. The mean of result for xanthan was 6.72±0.26. The result was closed to the predicted value by using RSM.

Spectroscopic and SEM Investigation of TCPP in Titanium Matrix

Titanium gels doped with water-soluble cationic porphyrin were synthesized by the sol–gel polymerization of Ti (OC4H9)4. In this work we investigate the spectroscopic properties along with SEM images of tetra carboxyl phenyl porphyrin when incorporated into porous matrix produced by the sol–gel technique.

Structural Integrity Management for Fixed Offshore Platforms in Malaysia

Structural Integrity Management (SIM) is important for the protection of offshore crew, environment, business assets and company and industry reputation. API RP 2A contained guidelines for assessment of existing platforms mostly for the Gulf of Mexico (GOM). ISO 19902 SIM framework also does not specifically cater for Malaysia. There are about 200 platforms in Malaysia with 90 exceeding their design life. The Petronas Carigali Sdn Bhd (PCSB) uses the Asset Integrity Management System and the very subjective Risk based Inspection Program for these platforms. Petronas currently doesn-t have a standalone Petronas Technical Standard PTS-SIM. This study proposes a recommended practice for the SIM process for offshore structures in Malaysia, including studies by API and ISO and local elements such as the number of platforms, types of facilities, age and risk ranking. Case study on SMG-A platform in Sabah shows missing or scattered platform data and a gap in inspection history. It is to undergo a level 3 underwater inspection in year 2015.

Process-Oriented Learning Requirements for Employees and for Organizations

Using activity theory, organisational theory and didactics as theoretical foundations, a comprehensive model of the organisational dimensions relevant for learning and knowledge transfer will be developed. In a second step, a Learning Assessment Guideline will be elaborated. This guideline will be designed to permit a targeted analysis of organisations to identify the status quo in those areas crucial to the implementation of learning and knowledge transfer. In addition, this self-analysis tool will enable learning managers to select adequate didactic models for e- and blended learning. As part of the European Integrated Project "Process-oriented Learning and Information Exchange" (PROLIX), this model of organisational prerequisites for learning and knowledge transfer will be empirically tested in four profit and non-profit organisations in Great Britain, Germany and France (to be finalized in autumn 2006). The findings concern not only the capability of the model of organisational dimensions, but also the predominant perceptions of and obstacles to learning in organisations.

Study of Heat Transfer in the Poly Ethylene Fluidized Bed Reactor Numerically and Experimentally

In this research, heat transfer of a poly Ethylene fluidized bed reactor without reaction were studied experimentally and computationally at different superficial gas velocities. A multifluid Eulerian computational model incorporating the kinetic theory for solid particles was developed and used to simulate the heat conducting gas–solid flows in a fluidized bed configuration. Momentum exchange coefficients were evaluated using the Syamlal– O-Brien drag functions. Temperature distributions of different phases in the reactor were also computed. Good agreement was found between the model predictions and the experimentally obtained data for the bed expansion ratio as well as the qualitative gas–solid flow patterns. The simulation and experimental results showed that the gas temperature decreases as it moves upward in the reactor, while the solid particle temperature increases. Pressure drop and temperature distribution predicted by the simulations were in good agreement with the experimental measurements at superficial gas velocities higher than the minimum fluidization velocity. Also, the predicted time-average local voidage profiles were in reasonable agreement with the experimental results. The study showed that the computational model was capable of predicting the heat transfer and the hydrodynamic behavior of gas-solid fluidized bed flows with reasonable accuracy.

The Flashbulb Memory of the Positive and Negative Events: Wenchuan Earthquake and Acceptance to College

53 college students answered questions regarding the circumstances in which they first heard about the news of Wenchuan earthquake or the news of their acceptance to college which took place approximately one year ago, and answered again two years later. The number of details recalled about their circumstances for both events was high and didn-t decline two years later. However, consistency in reported details over two years was low. Participants were more likely to construct central (e.g., Where were you?) than peripheral information (What were you wearing?), and the confidence of the central information was higher than peripheral information, which indicated that they constructed more when they were more confident.

Optimization of Acid Treatments by Assessing Diversion Strategies in Carbonate and Sandstone Formations

When acid is pumped into damaged reservoirs for damage removal/stimulation, distorted inflow of acid into the formation occurs caused by acid preferentially traveling into highly permeable regions over low permeable regions, or (in general) into the path of least resistance. This can lead to poor zonal coverage and hence warrants diversion to carry out an effective placement of acid. Diversion is desirably a reversible technique of temporarily reducing the permeability of high perm zones, thereby forcing the acid into lower perm zones. The uniqueness of each reservoir can pose several challenges to engineers attempting to devise optimum and effective diversion strategies. Diversion techniques include mechanical placement and/or chemical diversion of treatment fluids, further sub-classified into ball sealers, bridge plugs, packers, particulate diverters, viscous gels, crosslinked gels, relative permeability modifiers (RPMs), foams, and/or the use of placement techniques, such as coiled tubing (CT) and the maximum pressure difference and injection rate (MAPDIR) methodology. It is not always realized that the effectiveness of diverters greatly depends on reservoir properties, such as formation type, temperature, reservoir permeability, heterogeneity, and physical well characteristics (e.g., completion type, well deviation, length of treatment interval, multiple intervals, etc.). This paper reviews the mechanisms by which each variety of diverter functions and discusses the effect of various reservoir properties on the efficiency of diversion techniques. Guidelines are recommended to help enhance productivity from zones of interest by choosing the best methods of diversion while pumping an optimized amount of treatment fluid. The success of an overall acid treatment often depends on the effectiveness of the diverting agents.

Simulation of the Temperature and Heat Gain by Solar Parabolic Trough Collector in Algeria

The objectif of the present work is to determinate the potential of the solar parabolic trough collector (PTC) for use in the design of a solar thermal power plant in Algeria. The study is based on a mathematical modeling of the PTC. Heat balance has been established respectively on the heat transfer fluid (HTF), the absorber tube and the glass envelop using the principle of energy conservation at each surface of the HCE cross-sectionn. The modified Euler method is used to solve the obtained differential equations. At first the results for typical days of two seasons the thermal behavior of the HTF, the absorber and the envelope are obtained. Then to determine the thermal performances of the heat transfer fluid, different oils are considered and their temperature and heat gain evolutions compared.

The Influencing Factors and the Approach to Enhance the Standard of E-Commerce for Small and Medium Enterprises in Bangkok

The objectives of this research paper were to study the influencing factors that contributed to the success of electronic commerce (e-commerce) and to study the approach to enhance the standard of e-commerce for small and medium enterprises (SME). The research paper focused the study on only sole proprietorship SMEs in Bangkok, Thailand. The factors contributed to the success of SME included business management, learning in the organization, business collaboration, and the quality of website. A quantitative and qualitative mixed research methodology was used. In terms of quantitative method, a questionnaire was used to collect data from 251 sole proprietorships. The System Equation Model (SEM) was utilized as the tool for data analysis. In terms of qualitative method, an in-depth interview, a dialogue with experts in the field of ecommerce for SMEs, and content analysis were used. By using the adjusted causal relationship structure model, it was revealed that the factors affecting the success of e-commerce for SMEs were found to be congruent with the empirical data. The hypothesis testing indicated that business management influenced the learning in the organization, the learning in the organization influenced business collaboration and the quality of the website, and these factors, in turn, influenced the success of SMEs. Moreover, the approach to enhance the standard of SMEs revealed that the majority of respondents wanted to enhance the standard of SMEs to a high level in the category of safety of e-commerce system, basic structure of e-commerce, development of staff potentials, assistance of budget and tax reduction, and law improvement regarding the e-commerce respectively.

Low Resolution Single Neural Network Based Face Recognition

This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

An Adaptive Mammographic Image Enhancement in Orthogonal Polynomials Domain

X-ray mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are of low-contrast and noisy. In this paper, a new algorithm for image denoising and enhancement in Orthogonal Polynomials Transformation (OPT) is proposed for radiologists to screen mammograms. In this method, a set of OPT edge coefficients are scaled to a new set by a scale factor called OPT scale factor. The new set of coefficients is then inverse transformed resulting in contrast improved image. Applications of the proposed method to mammograms with subtle lesions are shown. To validate the effectiveness of the proposed method, we compare the results to those obtained by the Histogram Equalization (HE) and the Unsharp Masking (UM) methods. Our preliminary results strongly suggest that the proposed method offers considerably improved enhancement capability over the HE and UM methods.

Diagnosis of Hate Schemas in Prisoners with Antisocial Personality Disorder (ASPD)

The aim of this study is to show innovative techniques that describe the effectiveness of individuals diagnosed with antisocial personality disorders (ASPD). The author presents information about hate schemas regarding persons with ASPD and their understanding of the role of hate. The data of 60 prisoners with ASPD, 40 prisoners without ASPD, and 60 men without antisocial tendencies, has been analyzed. The participants were asked to describe their hate inspired by a photograph. The narrative discourse was analyzed, the three groups were compared. The results show the differences between the inmates with ASPD, those without ASPD, and the controls. The antisocial individuals describe hate as an ambivalent feeling with low emotional intensity, i.e., actors (in stories) are presented more as positives than as partners. They use different mechanisms to keep them from understanding the meaning of the emotional situation. The schema's characteristics were expressed in narratives attributed to high Psychopathy.