Adsorption Kinetics of Alcohols over MCM-41 Materials

Adsorption of methanol and ethanol over mesoporous siliceous material are studied in the current paper. The pure mesoporous silica is prepared using tetraethylorthosilicate (TEOS) as silica source and dodecylamine as template at low pH. The prepared material was characterized using nitrogen adsorption,nX-ray diffraction (XRD) and scanning electron microscopy (SEM). The adsorption kinetics of methanol and ethanol from aqueous solution were studied over the prepared mesoporous silica material. The percent removal of alcohol was calculated per unit mass of adsorbent used. The 1st order model is found to be in agreement with both adsorbates while the 2nd order model fit the adsorption of methanol only.

Assessment of the Environmental Destructive Effects of Building Dams

From the beginning of creation, human being has ever fought against the ecosystem by changes has made in environment. The most environmental changes on the nature have been done after starting the concentrated life in the same region. Dams are one of the most important buildings in water resources and transferring. These buildings have been made from old times without access to hydrological, hydraulically, hydro mechanical information. Dams have positive and negative effects on environment. Constructing a dam relatively causes equal ecological consequences. According to different criteria, environmental effects of dams can lead short term and long term damages. These effects may influence on the situation and treatment of meteorology, biology, culture, ancient works, etc and severely causes to change and complicate it. So considering importance of positive effects of dam construction, it is necessary to minimize negative environmental effects of dams to achieve a stable development. In this article the considered effects and their solutions in influencing on assessment of destructive environmental effects of dams construction have been surveyed and presented.

Numerical Solution of the Equations of Salt Diffusion into the Potato Tissues

Fick's second law equations for unsteady state diffusion of salt into the potato tissues were solved numerically. The set of equations resulted from implicit modeling were solved using Thomas method to find the salt concentration profiles in solid phase. The needed effective diffusivity and equilibrium distribution coefficient were determined experimentally. Cylindrical samples of potato were infused with aqueous NaCl solutions of 1-3% concentrations, and variations in salt concentrations of brine were determined over time. Solute concentrations profiles of samples were determined by measuring salt uptake of potato slices. For the studied conditions, equilibrium distribution coefficients were found to be dependent on salt concentrations, whereas the effective diffusivity was slightly affected by brine concentration.

Two-dimensional Differential Transform Method for Solving Linear and Non-linear Goursat Problem

A method for solving linear and non-linear Goursat problem is given by using the two-dimensional differential transform method. The approximate solution of this problem is calculated in the form of a series with easily computable terms and also the exact solutions can be achieved by the known forms of the series solutions. The method can easily be applied to many linear and non-linear problems and is capable of reducing the size of computational work. Several examples are given to demonstrate the reliability and the performance of the presented method.

A New Divide and Conquer Software Process Model

The software system goes through a number of stages during its life and a software process model gives a standard format for planning, organizing and running a project. The article presents a new software development process model named as “Divide and Conquer Process Model", based on the idea first it divides the things to make them simple and then gathered them to get the whole work done. The article begins with the backgrounds of different software process models and problems in these models. This is followed by a new divide and conquer process model, explanation of its different stages and at the end edge over other models is shown.

Finite Element Investigation of Transmission Conditions for Non-Monotonic Temperature Interphases

Imperfect transmission conditions modeling a thin reactive 2D interphases layer between two dissimilar bonded strips have been extracted. In this paper, the soundness of these transmission conditions for heat conduction problems are examined by the finite element method for a strong temperature-dependent source or sink and non-monotonic temperature distributions around the faces..

Emergency Health Management at a South African University

Response to the public health-related emergencies is analysed here for a rural university in South Africa. The structure of the designated emergency plan covers all the phases of the disaster management cycle. The plan contains elements of the vulnerability model and the technocratic model of emergency management. The response structures are vertically and horizontally integrated, while the planning contains elements of scenario-based and functional planning. The available number of medical professionals at the Rhodes University, along with the medical insurance rates, makes the staff and students potentially more medically vulnerable than the South African population. The main improvements of the emergency management are required in the tornado response and the information dissemination during health emergencies. The latter should involve the increased use of social media and e-mails, following the Taylor model of communication. Infrastructure must be improved in the telecommunication sector in the face of unpredictable electricity outages.

Analysis and Simulation of Automotive Interleaved Buck Converter

This paper will focus on modeling, analysis and simulation of a 42V/14V dc/dc converter based architecture. This architecture is considered to be technically a viable solution for automotive dual-voltage power system for passenger car in the near further. An interleaved dc/dc converter system is chosen for the automotive converter topology due to its advantages regarding filter reduction, dynamic response, and power management. Presented herein, is a model based on one kilowatt interleaved six-phase buck converter designed to operate in a Discontinuous Conduction Mode (DCM). The control strategy of the converter is based on a voltagemode- controlled Pulse Width Modulation (PWM) with a Proportional-Integral-Derivative (PID). The effectiveness of the interleaved step-down converter is verified through simulation results using control-oriented simulator, MatLab/Simulink.

Semantic Modeling of Management Information: Enabling Automatic Reasoning on DMTF-CIM

CIM is the standard formalism for modeling management information developed by the Distributed Management Task Force (DMTF) in the context of its WBEM proposal, designed to provide a conceptual view of the managed environment. In this paper, we propose the inclusion of formal knowledge representation techniques, based on Description Logics (DLs) and the Web Ontology Language (OWL), in CIM-based conceptual modeling, and then we examine the benefits of such a decision. The proposal is specified as a CIM metamodel level mapping to a highly expressive subset of DLs capable of capturing all the semantics of the models. The paper shows how the proposed mapping can be used for automatic reasoning about the management information models, as a design aid, by means of new-generation CASE tools, thanks to the use of state-of-the-art automatic reasoning systems that support the proposed logic and use algorithms that are sound and complete with respect to the semantics. Such a CASE tool framework has been developed by the authors and its architecture is also introduced. The proposed formalization is not only useful at design time, but also at run time through the use of rational autonomous agents, in response to a need recently recognized by the DMTF.

Combining Fuzzy Logic and Neural Networks in Modeling Landfill Gas Production

Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Unsteady Transonic Aerodynamic Analysis for Oscillatory Airfoils using Time Spectral Method

This research proposes an algorithm for the simulation of time-periodic unsteady problems via the solution unsteady Euler and Navier-Stokes equations. This algorithm which is called Time Spectral method uses a Fourier representation in time and hence solve for the periodic state directly without resolving transients (which consume most of the resources in a time-accurate scheme). Mathematical tools used here are discrete Fourier transformations. It has shown tremendous potential for reducing the computational cost compared to conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy. The accuracy and efficiency of this technique is verified by Euler and Navier-Stokes calculations for pitching airfoils. Because of flow turbulence nature, Baldwin-Lomax turbulence model has been used at viscous flow analysis. The results presented by the Time Spectral method are compared with experimental data. It has shown tremendous potential for reducing the computational cost compared to the conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy, because results verify the small number of time intervals per pitching cycle required to capture the flow physics.

Designing a Football Team of Robots from Beginning to End

The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.

Implementing a Visual Servoing System for Robot Controlling

Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

LMS in Higher Education: Analysis of the Effect of a Critical Factor ‘Faculty Training’

The purpose of this research is the analysis of the impact of ICT-related training in the adoption of a learning management systems (LMS) for teaching practicesby faculties in a higher education institution. Based on comparative analyses the impact will be obtained by the number of LMS courses created and managed by participants in ICT for teaching workshops and those who have not attended to any workshops. Involving near 1320 LMS courses and 265 faculties, the results evidence that(i) faculties who have not attend any workshop present a larger distribution of empty courses and (ii) faculties who have attended three or more workshops managed a higher distribution of courses with a considerable level of use intensity, when compared to the others groups. These findings supportthe idea that faculty training is a crucial factor in the process of LMS integration in higher education institutions and that faculties who have been enrolled in three or more workshops develop a higher level of technical and pedagogical proficiency in LMS.

Influence of Dilution and Lean-premixed on Mild Combustion in an Industrial Burner

Understanding of how and where NOx formation occurs in industrial burner is very important for efficient and clean operation of utility burners. Also the importance of this problem is mainly due to its relation to the pollutants produced by more burners used widely of gas turbine in thermal power plants and glass and steel industry. In this article, a numerical model of an industrial burner operating in MILD combustion is validated with experimental data.. Then influence of air flow rate and air temperature on combustor temperature profiles and NOX product are investigated. In order to modification this study reports on the effects of fuel and air dilution (with inert gases H2O, CO2, N2), and also influence of lean-premixed of fuel, on the temperature profiles and NOX emission. Conservation equations of mass, momentum and energy, and transport equations of species concentrations, turbulence, combustion and radiation modeling in addition to NO modeling equations were solved together to present temperature and NO distribution inside the burner. The results shows that dilution, cause to a reduction in value of temperature and NOX emission, and suppresses any flame propagation inside the furnace and made the flame inside the furnace invisible. Dilution with H2O rather than N2 and CO2 decreases further the value of the NOX. Also with raise of lean-premix level, local temperature of burner and the value of NOX product are decreases because of premixing prevents local “hot spots" within the combustor volume that can lead to significant NOx formation. Also leanpremixing of fuel with air cause to amount of air in reaction zone is reach more than amount that supplied as is actually needed to burn the fuel and this act lead to limiting NOx formation

A Novel Pareto-Based Meta-Heuristic Algorithm to Optimize Multi-Facility Location-Allocation Problem

This article proposes a novel Pareto-based multiobjective meta-heuristic algorithm named non-dominated ranking genetic algorithm (NRGA) to solve multi-facility location-allocation problem. In NRGA, a fitness value representing rank is assigned to each individual of the population. Moreover, two features ranked based roulette wheel selection including select the fronts and choose solutions from the fronts, are utilized. The proposed solving methodology is validated using several examples taken from the specialized literature. The performance of our approach shows that NRGA algorithm is able to generate true and well distributed Pareto optimal solutions.

An Adaptive Fuzzy Clustering Approach for the Network Management

The Chiu-s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering principle to estimate both the number of clusters and the initial locations of a cluster centers. Each obtained cluster corresponds to a Mamdani fuzzy rule. Then, it optimizes the fuzzy model parameters by applying a genetic algorithm. This method is illustrated on a traffic network management application. We suggest also a Mamdani fuzzy rules generation method, where the expert wants to classify the output variables in some fuzzy predefined classes.

Survey of Curriculum Quality of Postgraduate Studies of Insurance Management Field Case: University of Allameh Taba Tabaee

Curriculum is one of the most important inputs in higher education system and for knowing the strong and weak spots of it we need evaluation. The main purpose of this study was to survey of the curriculum quality of Insurance Management field. Case: University of Allameh Taba Tabaee(according to view point of students,alumni,employer and faculty members).Descriptive statistics (mean, tables, percentages, frequency distribution) and inferential statistics (CHI SQUARE) were used to analyze the data. Six criterions considered for the Quality of curriculum: objectives, content, teaching and learning methods, space and facilities, Time, assessment of learning. objectives, teaching and learning methods criterions was desirable level, content criteria was undesirable level, space and facilities, time and assessment of learning were rather desirable level. The quality of curriculum of insurance management field was relatively desirable level.

Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR

Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it-s not possible to apply other languages algorithms to Farsi directly. In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.

A CTL Specification of Serializability for Transactions Accessing Uniform Data

Existing work in temporal logic on representing the execution of infinitely many transactions, uses linear-time temporal logic (LTL) and only models two-step transactions. In this paper, we use the comparatively efficient branching-time computational tree logic CTL and extend the transaction model to a class of multistep transactions, by introducing distinguished propositional variables to represent the read and write steps of n multi-step transactions accessing m data items infinitely many times. We prove that the well known correspondence between acyclicity of conflict graphs and serializability for finite schedules, extends to infinite schedules. Furthermore, in the case of transactions accessing the same set of data items in (possibly) different orders, serializability corresponds to the absence of cycles of length two. This result is used to give an efficient encoding of the serializability condition into CTL.