Simulation Design of Separator for the Treatment of Emulsions

A prototype model of an emulsion separator was designed and manufactured. Generally, it is a cylinder filled with different fractal modules. The emulsion was fed into the reactor by a peristaltic pump through an inlet placed at the boundary between the two phases. For hydrodynamic design and sizing of the reactor the assumptions of the theory of filtration were used and methods to describe the separation process were developed. Based on this methodology and using numerical methods and software of Autodesk the process is simulated in different operating modes. The basic hydrodynamic characteristics - speed and performance for different types of fractal systems and decisions to optimize the design of the reactor were also defined.

Factors of Successful Wooden Furniture Design Process

This study systemizes processes and methods in wooden furniture design that contains uniqueness in function and aesthetics. The study was done by research and analysis for designer-s consideration factors that affect function and production. Therefore, the study result indicates that such factors are design process (planning for design, product specifications, concept design, product architecture, industrial design, production), design evaluation as well as wooden furniture design dependent factors i.e. art (art style; furniture history, form), functionality (the strength and durability, area place, using), material (appropriate to function, wood mechanical properties), joints, cost, safety, and social responsibility. Specifically, all aforementioned factors affect good design. Resulting from direct experience gained through user-s usage, the designer must design the wooden furniture systemically and effectively. As a result, this study selected dinning armchair as a case study with all involving factors and all design process stated in this study.

Structural and Optical Properties of Ce3+ Doped YPO4: Nanophosphors Synthesis by Sol Gel Method

Recently, nanomaterials are developed in the form of nano-films, nano-crystals and nano-pores. Lanthanide phosphates as a material find extensive application as laser, ceramic, sensor, phosphor, and also in optoelectronics, medical and biological labels, solar cells and light sources. Among the different kinds of rare-earth orthophosphates, yttrium orthophosphate has been shown to be an efficient host lattice for rare earth activator ions, which have become a research focus because of their important role in the field of light display systems, lasers, and optoelectronic devices. It is in this context that the 4fn- « 4fn-1 5d transitions of rare earth in insulating materials, lying in the UV and VUV, are the aim of large number of studies .Though there has been a few reports on Eu3+, Nd3+, Pr3+,Er3+, Ce3+, Tm3+ doped YPO4. The 4fn- « 4fn-1 5d transitions of the rare earth dependent to the host-matrix, several matrices ions were used to study these transitions, in this work we are suggesting to study on a very specific class of inorganic material that are orthophosphate doped with rare earth ions. This study focused on the effect of Ce3+ concentration on the structural and optical properties of Ce3+ doped YPO4 yttrium orthophosphate with powder form prepared by the Sol Gel method.

Artificial Neural Network based Web Application Firewall for SQL Injection

In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.

Comparison of Parametric and Nonparametric Techniques for Non-peak Traffic Forecasting

Accurately predicting non-peak traffic is crucial to daily traffic for all forecasting models. In the paper, least squares support vector machines (LS-SVMs) are investigated to solve such a practical problem. It is the first time to apply the approach and analyze the forecast performance in the domain. For comparison purpose, two parametric and two non-parametric techniques are selected because of their effectiveness proved in past research. Having good generalization ability and guaranteeing global minima, LS-SVMs perform better than the others. Providing sufficient improvement in stability and robustness reveals that the approach is practically promising.

Solving Facility Location Problem on Cluster Computing

Computation of facility location problem for every location in the country is not easy simultaneously. Solving the problem is described by using cluster computing. A technique is to design parallel algorithm by using local search with single swap method in order to solve that problem on clusters. Parallel implementation is done by the use of portable parallel programming, Message Passing Interface (MPI), on Microsoft Windows Compute Cluster. In this paper, it presents the algorithm that used local search with single swap method and implementation of the system of a facility to be opened by using MPI on cluster. If large datasets are considered, the process of calculating a reasonable cost for a facility becomes time consuming. The result shows parallel computation of facility location problem on cluster speedups and scales well as problem size increases.

Effects of Road Disturbance on Plant Biodiversity

Urbanization and related anthropogenic modifications cause extent of habitat fragmentation and directly lead to decline of local biodiversity. Conservation biologists advocate corridor creation as one approach to rescue biodiversity. Here we examine the utility of roads as corridors in preserving plant diversity by investigating roadside vegetation in Yellow River Delta (YRD), China. We examined the spatio-temporal distribution pattern of plant species richness, diversity and composition along roadside. The results suggest that roads, as dispersal conduits, increase occurrence probability of new settlers to a new area, meanwhile, roads accumulate the greater propagule pressure and favourable survival condition during operation phase. As a result, more species, including native and alien plants, non- halophyte and halophyte species, threatened and cosmopolitic species, were found prosperous at roadside. Roadside may be a refuge for more species, and the pattern of vegetation distribution is affected by road age and the distance from road verge.

Rarefactive and Compressive Solitons in Warm Dusty Plasma with Electrons and Nonthermal Ions

Dust acoustic solitary waves are studied in warm dusty plasma containing negatively charged dusts, nonthermal ions and Boltzmann distributed electrons. Sagdeev pseudopotential method is used in order to investigate solitary wave solutions in the plasmas. The existence of compressive and rarefractive solitons is studied.

On the Need to have an Additional Methodology for the Psychological Product Measurement and Evaluation

Cognitive Science appeared about 40 years ago, subsequent to the challenge of the Artificial Intelligence, as common territory for several scientific disciplines such as: IT, mathematics, psychology, neurology, philosophy, sociology, and linguistics. The new born science was justified by the complexity of the problems related to the human knowledge on one hand, and on the other by the fact that none of the above mentioned sciences could explain alone the mental phenomena. Based on the data supplied by the experimental sciences such as psychology or neurology, models of the human mind operation are built in the cognition science. These models are implemented in computer programs and/or electronic circuits (specific to the artificial intelligence) – cognitive systems – whose competences and performances are compared to the human ones, leading to the psychology and neurology data reinterpretation, respectively to the construction of new models. During these processes if psychology provides the experimental basis, philosophy and mathematics provides the abstraction level utterly necessary for the intermission of the mentioned sciences. The ongoing general problematic of the cognitive approach provides two important types of approach: the computational one, starting from the idea that the mental phenomenon can be reduced to 1 and 0 type calculus operations, and the connection one that considers the thinking products as being a result of the interaction between all the composing (included) systems. In the field of psychology measurements in the computational register use classical inquiries and psychometrical tests, generally based on calculus methods. Deeming things from both sides that are representing the cognitive science, we can notice a gap in psychological product measurement possibilities, regarded from the connectionist perspective, that requires the unitary understanding of the quality – quantity whole. In such approach measurement by calculus proves to be inefficient. Our researches, deployed for longer than 20 years, lead to the conclusion that measuring by forms properly fits to the connectionism laws and principles.

AJcFgraph - AspectJ Control Flow Graph Builder for Aspect-Oriented Software

The ever-growing usage of aspect-oriented development methodology in the field of software engineering requires tool support for both research environments and industry. So far, tool support for many activities in aspect-oriented software development has been proposed, to automate and facilitate their development. For instance, the AJaTS provides a transformation system to support aspect-oriented development and refactoring. In particular, it is well established that the abstract interpretation of programs, in any paradigm, pursued in static analysis is best served by a high-level programs representation, such as Control Flow Graph (CFG). This is why such analysis can more easily locate common programmatic idioms for which helpful transformation are already known as well as, association between the input program and intermediate representation can be more closely maintained. However, although the current researches define the good concepts and foundations, to some extent, for control flow analysis of aspectoriented programs but they do not provide a concrete tool that can solely construct the CFG of these programs. Furthermore, most of these works focus on addressing the other issues regarding Aspect- Oriented Software Development (AOSD) such as testing or data flow analysis rather than CFG itself. Therefore, this study is dedicated to build an aspect-oriented control flow graph construction tool called AJcFgraph Builder. The given tool can be applied in many software engineering tasks in the context of AOSD such as, software testing, software metrics, and so forth.

Grid Based and Random Based Ant Colony Algorithms for Automatic Hose Routing in 3D Space

Ant Colony Algorithms have been applied to difficult combinatorial optimization problems such as the travelling salesman problem and the quadratic assignment problem. In this paper gridbased and random-based ant colony algorithms are proposed for automatic 3D hose routing and their pros and cons are discussed. The algorithm uses the tessellated format for the obstacles and the generated hoses in order to detect collisions. The representation of obstacles and hoses in the tessellated format greatly helps the algorithm towards handling free-form objects and speeds up computation. The performance of algorithm has been tested on a number of 3D models.

Multiscale Analysis and Change Detection Based on a Contrario Approach

Automatic methods of detecting changes through satellite imaging are the object of growing interest, especially beca²use of numerous applications linked to analysis of the Earth’s surface or the environment (monitoring vegetation, updating maps, risk management, etc...). This work implemented spatial analysis techniques by using images with different spatial and spectral resolutions on different dates. The work was based on the principle of control charts in order to set the upper and lower limits beyond which a change would be noted. Later, the a contrario approach was used. This was done by testing different thresholds for which the difference calculated between two pixels was significant. Finally, labeled images were considered, giving a particularly low difference which meant that the number of “false changes” could be estimated according to a given limit.

PCR based Detection of Food Borne Pathogens

Many high-risk pathogens that cause disease in humans are transmitted through various food items. Food-borne disease constitutes a major public health problem. Assessment of the quality and safety of foods is important in human health. Rapid and easy detection of pathogenic organisms will facilitate precautionary measures to maintain healthy food. The Polymerase Chain Reaction (PCR) is a handy tool for rapid detection of low numbers of bacteria. We have designed gene specific primers for most common food borne pathogens such as Staphylococci, Salmonella and E.coli. Bacteria were isolated from food samples of various food outlets and identified using gene specific PCRs. We identified Staphylococci, Salmonella and E.coli O157 using gene specific primers by rapid and direct PCR technique in various food samples. This study helps us in getting a complete picture of the various pathogens that threaten to cause and spread food borne diseases and it would also enable establishment of a routine procedure and methodology for rapid identification of food borne bacteria using the rapid technique of direct PCR. This study will also enable us to judge the efficiency of present food safety steps taken by food manufacturers and exporters.

A Comparison Study of Inspector's Performance between Regular and Complex Tasks

This research was to study a comparison of inspector-s performance between regular and complex visual inspection task. Visual task was simulated on DVD read control circuit. Inspection task was performed by using computer. Subjects were 10 undergraduate randomly selected and test for 20/20. Then, subjects were divided into two groups, five for regular inspection (control group) and five for complex inspection (treatment group) tasks. Result was showed that performance on regular and complex inspectors was significantly difference at the level of 0.05. Inspector performance on regular inspection was showed high percentage on defects detected by using equal time to complex inspection. This would be indicated that inspector performance was affected by visual inspection task.

Dose due the Incorporation of Radionuclides Using Teeth as Bioindicators nearby Caetité Uranium Mines

Uranium mining and processing in Brazil occur in a northeastern area near to Caetité-BA. Several Non-Governmental Organizations claim that uranium mining in this region is a pollutant causing health risks to the local population,but those in charge of the complex extraction and production of“yellow cake" for generating fuel to the nuclear power plants reject these allegations. This study aimed at identifying potential problems caused by mining to the population of Caetité. In this, work,the concentrations of 238U, 232Th and 40K radioisotopes in the teeth of the Caetité population were determined by ICP-MS. Teeth are used as bioindicators of incorporated radionuclides. Cumulative radiation doses in the skeleton were also determined. The concentration values were below 0.008 ppm, and annual effective dose due to radioisotopes are below to the reference values. Therefore, it is not possible to state that the mining process in Caetité increases pollution or radiation exposure in a meaningful way.

A Model of Market Segmentation for the Customers of Mellat Bank in Iran

If organizations like Mellat Bank want to identify its customer market completely to reach its specified goals, it can segment the market to offer the product package to the right segment. Our objective is to offer a segmentation model for Iran banking market in Mellat bank view. The methodology of this project is combined by “segmentation on the basis of four part-quality variables" and “segmentation on the basis of different in means". Required data are gathered from E-Systems and researcher personal observation. Finally, the research offers the organization that at first step form a four dimensional matrix with 756 segments using four variables named value-based, behavioral, activity style, and activity level, and at the second step calculate the means of profit for every cell of matrix in two distinguished work level (levels α1:normal condition and α2: high pressure condition) and compare the segments by checking two conditions that are 1- homogeneity every segment with its sub segment and 2- heterogeneity with other segments, and so it can do the necessary segmentation process. After all, the last offer (more explained by an operational example and feedback algorithm) is to test and update the model because of dynamic environment, technology, and banking system.

EU Socioeconomic Indicators and Car Market

Since 2008 a new economic crisis is present is the entire planet. This crisis affects several domains of the economic but also of the social life. Consumption decreases due to the lack of necessary resources of households to increase their expenditures. The car manufacturing is one of the main industrial activities in European Union (EU) and the present crisis particularly affects it. The present study examines the correlations between several socio-economic indicators and car market in European Union. The target is to find out the impact of the present economic crisis on the car market in EU.

Data Mining Classification Methods Applied in Drug Design

Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

Removal of Arsenic (III) from Contaminated Waterby Synthetic Nano Size Zerovalent Iron

The present work was conducted for Arsenic (III) removal, which one of the most poisonous groundwater pollutants, by synthetic nano size zerovalent iron (nZVI). Batch experiments were performed to investigate the influence of As (III), nZVI concentration, pH of solution and contact time on the efficiency of As (III) removal. nZVI was synthesized by reduction of ferric chloride by sodium borohydrid. SEM and XRD were used to determine particle size and characterization of produced nanoparticles. Up to 99.9% removal efficiency for arsenic (III) was obtained by nZVI dosage of 1 g/L at time equal to 10 min. and pH=7. It could be concluded that the removal efficiency were enhanced with increasing of ZVI dosage and reaction time, but decreased with increasing of arsenic concentration and pH for nano sized ZVI. nZVI presented an outstanding ability to remove As (III) due to not only a high surface area and low particle size but also to high inherent activity.

A New Self-Adaptive EP Approach for ANN Weights Training

Evolutionary Programming (EP) represents a methodology of Evolutionary Algorithms (EA) in which mutation is considered as a main reproduction operator. This paper presents a novel EP approach for Artificial Neural Networks (ANN) learning. The proposed strategy consists of two components: the self-adaptive, which contains phenotype information and the dynamic, which is described by genotype. Self-adaptation is achieved by the addition of a value, called the network weight, which depends on a total number of hidden layers and an average number of neurons in hidden layers. The dynamic component changes its value depending on the fitness of a chromosome, exposed to mutation. Thus, the mutation step size is controlled by two components, encapsulated in the algorithm, which adjust it according to the characteristics of a predefined ANN architecture and the fitness of a particular chromosome. The comparative analysis of the proposed approach and the classical EP (Gaussian mutation) showed, that that the significant acceleration of the evolution process is achieved by using both phenotype and genotype information in the mutation strategy.