Septic B-Spline Collocation Method for Numerical Solution of the Kuramoto-Sivashinsky Equation

In this paper the Kuramoto-Sivashinsky equation is solved numerically by collocation method. The solution is approximated as a linear combination of septic B-spline functions. Applying the Von-Neumann stability analysis technique, we show that the method is unconditionally stable. The method is applied on some test examples, and the numerical results have been compared with the exact solutions. The global relative error and L∞ in the solutions show the efficiency of the method computationally.

A Content-Based Optimization of Data Stream Television Multiplex

The television multiplex has reserved capacity and therefore we can use only limited number of videos for propagation of it. Appropriate composition of the multiplex has a major impact on how many videos is spread by multiplex. Therefore in this paper is designed a simple algorithm to optimize capacity utilization multiplex. Significant impact on the number of programs in the multiplex has also the fact from which programs is composed. Content of multiplex can be movies, news, sport, animated stories, documentaries, etc. These types have their own specific characteristics that affect their resulting data stream. In this paper is also done an impact analysis of the composition of the multiplex to use its capacity by video content. 

Experimental Testing of Statistical Size Effect in Civil Engineering Structures

The presented paper copes with an experimental evaluation of a model based on modified Weibull size effect theory. Classical statistical Weibull theory was modified by introducing a new parameter (correlation length lp) representing the spatial autocorrelation of a random mechanical properties of material. This size effect modification was observed on two different materials used in civil engineering: unreinforced (plain) concrete and multi-filament yarns made of alkaliresistant (AR) glass which are used for textile-reinforced concrete. The behavior under flexural, resp. tensile loading was investigated by laboratory experiments. A high number of specimens of different sizes was tested to obtain statistically significant data which were subsequently corrected and statistically processed. Due to a distortion of the measured displacements caused by the unstiff experiment device, only the maximal load values were statistically evaluated. Results of the experiments showed a decreasing strength with an increasing sample length. Size effect curves were obtained and the correlation length was fitted according to measured data. Results did not exclude the existence of the proposed new parameter lp.

Enhanced Gram-Schmidt Process for Improving the Stability in Signal and Image Processing

The Gram-Schmidt Process (GSP) is used to convert a non-orthogonal basis (a set of linearly independent vectors) into an orthonormal basis (a set of orthogonal, unit-length vectors). The process consists of taking each vector and then subtracting the elements in common with the previous vectors. This paper introduces an Enhanced version of the Gram-Schmidt Process (EGSP) with inverse, which is useful for signal and image processing applications.

Remote Control Software for Rohde and Schwarz Instruments

The paper describes software for remote control and measuring with new Graphical User Interface for Rohde & Schwarz instruments. Software allows remote control through Ethernet and supports basic and advanced functions for control various type of instruments like network and spectrum analyzers, power meters, signal generators and oscilloscopes. Standard Commands for Programmable Instruments (SCPI) and Virtual Instrument Software Architecture (VISA) are used for remote control and setup of instruments. Developed software is modular with user friendly graphic user interface for each instrument with automatic identification of instruments.

An Improved Performance of the SRM Drives Using Z-Source Inverter with the Simplified Fuzzy Logic Rule Base

This paper is based on the performance of the Switched Reluctance Motor (SRM) drives using Z-Source Inverter with the simplified rule base of Fuzzy Logic Controller (FLC) with the output scaling factor (SF) self-tuning mechanism are proposed. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the membership functions (MFs) without losing the system performance and stability via the adjustable controller gain. ZSI exhibits both voltage-buck and voltage-boost capability. It reduces line harmonics, improves reliability, and extends output voltage range. The output SF of the controller can be tuned continuously by a gain updating factor, whose value is derived from fuzzy logic, with the plant error and error change ratio as input variables. Then the results, carried out on a four-phase 6/8 pole SRM based on the dSPACEDS1104 platform, to show the feasibility and effectiveness of the devised methods and also performance of the proposed controllers will be compared with conventional counterpart.

Pricing Strategy Selection Using Fuzzy Linear Programming

Marketing establishes a communication network between producers and consumers. Nowadays, marketing approach is customer-focused and products are directly oriented to meet customer needs. Marketing, which is a long process, needs organization and management. Therefore strategic marketing planning becomes more and more important in today’s competitive conditions. Main focus of this paper is to evaluate pricing strategies and select the best pricing strategy solution while considering internal and external factors influencing the company’s pricing decisions associated with new product development. To reflect the decision maker’s subjective preference information and to determine the weight vector of factors (attributes), the fuzzy linear programming technique for multidimensional analysis of preference (LINMAP) under intuitionistic fuzzy (IF) environments is used.

K-best Night Vision Devices by Multi-Criteria Mixed-Integer Optimization Modeling

The paper describes an approach for defining of k-best night vision devices based on multi-criteria mixed-integer optimization modeling. The parameters of night vision devices are considered as criteria that have to be optimized. Using different user preferences for the relative importance between parameters different choice of k-best devices can be defined. An ideal device with all of its parameters at their optimum is used to determine how far the particular device from the ideal one is. A procedure for evaluation of deviation between ideal solution and k-best solutions is presented. The applicability of the proposed approach is numerically illustrated using real night vision devices data. The proposed approach contributes to quality of decisions about choice of night vision devices by making the decision making process more certain, rational and efficient. 

Jacobi-Based Methods in Solving Fuzzy Linear Systems

Linear systems are widely used in many fields of science and engineering. In many applications, at least some of the parameters of the system are represented by fuzzy rather than crisp numbers. Therefore it is important to perform numerical algorithms or procedures that would treat general fuzzy linear systems and solve them using iterative methods. This paper aims are to solve fuzzy linear systems using four types of Jacobi based iterative methods. Four iterative methods based on Jacobi are used for solving a general n × n fuzzy system of linear equations of the form Ax = b , where A is a crisp matrix and b an arbitrary fuzzy vector. The Jacobi, Jacobi Over-Relaxation, Refinement of Jacobi and Refinement of Jacobi Over-Relaxation methods was tested to a five by five fuzzy linear system. It is found that all the tested methods were iterated differently. Due to the effect of extrapolation parameters and the refinement, the Refinement of Jacobi Over-Relaxation method was outperformed the other three methods.

TanSSe-L System PIM Manual Transformation to Moodle as a TanSSe-L System Specific PIM

Tanzania Secondary Schools e-Learning (TanSSe-L) system is a customized learning management system (LMS) developed to enable ICT support in teaching and learning functions. Methodologies involved in the development of TanSSe-L system are Object oriented system analysis and design with UML to create and model TanSSe-L system database structure in the form of a design class diagram, Model Driven Architecture (MDA) to provide a well defined process in TanSSe-L system development, where MDA conceptual layers were integrated with system development life cycle and customization of open source learning management system which was used during implementation stage to create a timely functional TanSSe-L system. Before customization, a base for customization was prepared. This was the manual transformation from TanSSe-L system platform independent models (PIM) to TanSSe-L system specific PIM. This paper presents how Moodle open source LMS was analyzed and prepared to be the TanSSe-L system specific PIM as applied by MDA.

Robust Coherent Noise Suppression by Point Estimation of the Cauchy Location Parameter

This paper introduces a new point estimation algorithm, with particular focus on coherent noise suppression, given several measurements of the device under test where it is assumed that 1) the noise is first-order stationery and 2) the device under test is linear and time-invariant. The algorithm exploits the robustness of the Pitman estimator of the Cauchy location parameter through the initial scaling of the test signal by a centred Gaussian variable of predetermined variance. It is illustrated through mathematical derivations and simulation results that the proposed algorithm is more accurate and consistently robust to outliers for different tailed density functions than the conventional methods of sample mean (coherent averaging technique) and sample median search.

A Visualized Framework for Representing Uncertain and Incomplete Temporal Knowledge

This paper presents a visualized computer aided case tool for non-expert, called Visual Time, for representing and reasoning about incomplete and uncertain temporal information. It is both expressive and versatile, allowing logical conjunctions and disjunctions of both absolute and relative temporal relations, such as “Before”, “Meets”, “Overlaps”, “Starts”, “During”, and “Finishes”, etc. In terms of a visualized framework, Visual Time provides a user-friendly environment for describing scenarios with rich temporal structure in natural language, which can be formatted as structured temporal phrases and modeled in terms of Temporal Relationship Diagrams (TRD). A TRD can be automatically and visually transformed into a corresponding Time Graph, supported by automatic consistency checker that derives a verdict to confirm if a given scenario is temporally consistent or inconsistent.

Periodic Orbits in a Delayed Nicholson's Blowflies Model

In this paper, a delayed Nicholson,s blowflies model with a linear harvesting term is investigated. Regarding the delay as a bifurcation parameter, we show that Hopf bifurcation will occur when the delay crosses a critical value. Numerical simulations supporting the theoretical findings are carried out.

Coordinated Design of PSS and STATCOM for Power System Stability Improvement Using Bacteria Foraging Algorithm

This paper presents the coordinated controller design of static synchronous compensator (STATCOM) and power system stabilizers (PSSs) for power system stability improvement. Coordinated design problem of STATCOM-based controller with multiple PSSs is formulated as an optimization problem and optimal controller parameters are obtained using bacteria foraging optimization algorithm. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. The nonlinear simulation results show that coordinated design of STATCOM-based controller and PSSs improve greatly the system damping oscillations and consequently stability improvement.

Green-Reduction of Covalently Functionalized Graphene Oxide with Varying Stoichiometry

Graphene-based materials were prepared by chemical reduction of covalently functionalized graphene oxide with environmentally friendly agents. Two varying stoichiometry of graphene oxide (GO) induced by using different chemical preparation conditions, further covalent functionalization of the GO materials with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride / N-hydroxysuccinimide and ascorbic acid and sodium bisulfite as reducing agents were exploited in order to obtain controllable properties of the final solution-based graphene materials. The obtained materials were characterized by thermo-gravimetric analysis, Fourier transform infrared and Raman spectroscopy and X-ray diffraction. The results showed successful functionalization of the GO materials, while a comparison of the deoxygenation efficiency of the two-type functionalized graphene oxide suspensions by the different reducing agents has been made, revealing the strong dependence of their properties on the GO structure and reducing agents.

An Empirical Model of Correlated Traffics in LTE-Advanced System through an Innovative Simulation Tool

Long Term Evolution Advanced (LTE-Advanced) LTE-Advanced is not new as a radio access technology, but it is an evolution of LTE to enhance the performance. This generation is the continuation of 3GPP-LTE (3GPP: 3rd Generation Partnership Project) and it is targeted for advanced development of the requirements of LTE in terms of throughput and coverage. The performance evaluation process of any network should be based on many models and simulations to investigate the network layers and functions and monitor the employment of the new technologies especially when this network includes large-bandwidth and low-latency links such as LTE and LTE-Advanced networks. Therefore, it’s necessary to enhance the proposed models of high-speed and high-congested link networks to make these links and traffics fulfill the needs of the huge data which transferred over the congested links. This article offered an innovative model of the most correlated links of LTE-Advanced system using the Network Simulator 2 (NS-2) with investigation of the link parameters.

An Educational Data Mining System for Advising Higher Education Students

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems. In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

An Analysis of New Service Interchange Designs

An efficient freeway system will be essential to the development of Africa, and interchanges are a key to that efficiency. Around the world, many interchanges between freeways and surface streets, called service interchanges, are of the diamond configuration, and interchanges using roundabouts or loop ramps are also popular. However, many diamond interchanges have serious operational problems, interchanges with roundabouts fail at high demand levels, and loops use lots of expensive land. Newer service interchange designs provide other options. The most popular new interchange design in the US at the moment is the double crossover diamond (DCD), also known as the diverging diamond. The DCD has enormous potential, but also has several significant limitations. The objectives of this paper are to review new service interchange options and to highlight some of the main features of those alternatives. The paper tests four conventional and seven unconventional designs using seven measures related to efficiency, cost, and safety. The results show that there is no superior design in all measures investigated. The DCD is better than most designs tested on most measures examined. However, the DCD was only superior to all other designs for bridge width. The DCD performed relatively poorly for capacity and for serving pedestrians. Based on the results, African freeway designers are encouraged to investigate the full range of alternatives that could work at the spot of interest. Diamonds and DCDs have their niches, but some of the other designs investigated could be optimum at some spots.

Changes in EEG and HRV during Event-Related Attention

Determination of attentional status is important because working performance and an unexpected accident is highly related with the attention. The autonomic nervous and the central nervous systems can reflect the changes in person’s attentional status. Reduced number of suitable pysiological parameters among autonomic and central nervous systems related signal parameters will be critical in optimum design of attentional devices. In this paper, we analyze the EEG (Electroencephalography) and HRV (Heart Rate Variability) signals to demonstrate the effective relation with brain signal and cardiovascular signal during event-related attention, which will be later used in selecting the minimum set of attentional parameters. Time and frequency domain parameters from HRV signal and frequency domain parameters from EEG signal are used as input to the optimum feature parameters selector.

Supplier Selection Criteria and Methods in Supply Chains: A Review

An effective supplier selection process is very important to the success of any manufacturing organization. The main objective of supplier selection process is to reduce purchase risk, maximize overall value to the purchaser, and develop closeness and long-term relationships between buyers and suppliers in today’s competitive industrial scenario. The literature on supplier selection criteria and methods is full of various analytical and heuristic approaches. Some researchers have developed hybrid models by combining more than one type of selection methods. It is felt that supplier selection criteria and method is still a critical issue for the manufacturing industries therefore in the present paper the literature has been thoroughly reviewed and critically analyzed to address the issue.