The Role of Gender and Age on Students- Perceptions towards Online Education Case Study: Sakarya University, Vocational High School

The aim of this study is to find out and analyze the role of gender and age on the perceptions of students to the distant online program offered by Vocational High School in Sakarya University. The research is based on a questionnaire as a mean of data collection method to find out the role of age and gender on the student-s perceptions toward online education, and the study progressed through finding relationships between the variables used in the data collection instrument. The findings of the analysis revealed that although the students registered to the online program by will, they preferred the traditional face-to-face education due to the difficulty of the nonverbal communication, their incompetence of using the technology required, and their belief in traditional face-toface learning more than online education. Regarding gender, the results showed that the female students have a better perception of the online education as opposed to the male students. Regarding age, the results showed that the older the students are the more is their preference towards attending face-toface classes.

Model to Support Synchronous and Asynchronous in the Learning Process with An Adaptive Hypermedia System

In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.

Problem Solving Techniques with Extensive Computational Network and Applying in an Educational Software

Knowledge bases are basic components of expert systems or intelligent computational programs. Knowledge bases provide knowledge, events that serve deduction activity, computation and control. Therefore, researching and developing of models for knowledge representation play an important role in computer science, especially in Artificial Intelligence Science and intelligent educational software. In this paper, the extensive deduction computational model is proposed to design knowledge bases whose attributes are able to be real values or functional values. The system can also solve problems based on knowledge bases. Moreover, the models and algorithms are applied to produce the educational software for solving alternating current problems or solving set of equations automatically.

Markov Chain Monte Carlo Model Composition Search Strategy for Quantitative Trait Loci in a Bayesian Hierarchical Model

Quantitative trait loci (QTL) experiments have yielded important biological and biochemical information necessary for understanding the relationship between genetic markers and quantitative traits. For many years, most QTL algorithms only allowed one observation per genotype. Recently, there has been an increasing demand for QTL algorithms that can accommodate more than one observation per genotypic distribution. The Bayesian hierarchical model is very flexible and can easily incorporate this information into the model. Herein a methodology is presented that uses a Bayesian hierarchical model to capture the complexity of the data. Furthermore, the Markov chain Monte Carlo model composition (MC3) algorithm is used to search and identify important markers. An extensive simulation study illustrates that the method captures the true QTL, even under nonnormal noise and up to 6 QTL.

Parameter Estimation for Viewing Rank Distribution of Video-on-Demand

Video-on-demand (VOD) is designed by using content delivery networks (CDN) to minimize the overall operational cost and to maximize scalability. Estimation of the viewing pattern (i.e., the relationship between the number of viewings and the ranking of VOD contents) plays an important role in minimizing the total operational cost and maximizing the performance of the VOD systems. In this paper, we have analyzed a large body of commercial VOD viewing data and found that the viewing rank distribution fits well with the parabolic fractal distribution. The weighted linear model fitting function is used to estimate the parameters (coefficients) of the parabolic fractal distribution. This paper presents an analytical basis for designing an optimal hierarchical VOD contents distribution system in terms of its cost and performance.

Analysis of an Electrical Transformer: A Bond Graph Approach

Bond graph models of an electrical transformer including the nonlinear saturation are presented. These models determine the relation between self and mutual inductances, and the leakage and magnetizing inductances of power transformers with two and three windings using the properties of a bond graph. The modelling and analysis using this methodology to three phase power transformers or transformers with internal incipient faults can be extended.

Interoperability in Component Based Software Development

The ability of information systems to operate in conjunction with each other encompassing communication protocols, hardware, software, application, and data compatibility layers. There has been considerable work in industry on the development of component interoperability models, such as CORBA, (D)COM and JavaBeans. These models are intended to reduce the complexity of software development and to facilitate reuse of off-the-shelf components. The focus of these models is syntactic interface specification, component packaging, inter-component communications, and bindings to a runtime environment. What these models lack is a consideration of architectural concerns – specifying systems of communicating components, explicitly representing loci of component interaction, and exploiting architectural styles that provide well-understood global design solutions. The development of complex business applications is now focused on an assembly of components available on a local area network or on the net. These components must be localized and identified in terms of available services and communication protocol before any request. The first part of the article introduces the base concepts of components and middleware while the following sections describe the different up-todate models of communication and interaction and the last section shows how different models can communicate among themselves.

The Hardware Implementation of a Novel Genetic Algorithm

This paper presents a novel genetic algorithm, termed the Optimum Individual Monogenetic Algorithm (OIMGA) and describes its hardware implementation. As the monogenetic strategy retains only the optimum individual, the memory requirement is dramatically reduced and no crossover circuitry is needed, thereby ensuring the requisite silicon area is kept to a minimum. Consequently, depending on application requirements, OIMGA allows the investigation of solutions that warrant either larger GA populations or individuals of greater length. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of existing hardware GA implementations. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space.

Using Reuse Water for Irrigation Green space of Naein City

Since water resources of desert Naein City are very limited, a approach which saves water resources and meanwhile meets the needs of the greenspace for water is to use city-s sewage wastewater. Proper treatment of Naein-s sewage up to the standards required for green space uses may solve some of the problems of green space development of the city. The present paper closely examines available statistics and information associated with city-s sewage system, and determines complementary stages of sewage treatment facilities of the city. In the present paper, population, per capita water use, and required discharge for various greenspace pieces including different plants are calculated. Moreover, in order to facilitate the application of water resources, a Crude water distribution network apart from drinking water distribution network is designed, and a plan for mixing municipal wells- water with sewage wastewater in proposed mixing tanks is suggested. Hence, following greenspace irrigation reform and complementary plan, per capita greenspace of the city will be increased from current amount of 13.2 square meters to 32 square meters.

Study of Peptide Fragment of Alpha-Fetoprotein as a Radionuclide Vehicle

Alpfa-fetoprotein and its fragments may be an important vehicle for targeted delivery of radionuclides to the tumor. We investigated the effect of conditions on the labeling of biologically active synthetic peptide based on the (F-afp) with technetium-99m. The influence of the nature of the buffer solution, pH, concentration of reductant, concentration of the peptide and the reaction temperature on the yield of labeling was examined. As a result, the following optimal conditions for labeling of (F-afp) are found: pH 8.5 (phosphate and bicarbonate buffers) and pH from 1.7 to 7.0 (citrate buffer). The reaction proceeds with sufficient yield at room temperature for 30 min at the concentration of SnCl2 and (Fafp) (F-afp) is to be less than 10 mkg/ml and 25 mkg/ml, respectively. Investigations of the test drug accumulation in the tumor cells of human breast cancer were carried out. Results can be assumed that the in vivo study of the (F-afp) in experimental tumor lesions will show concentrations sufficient for imaging these lesions by SPECT.

Spreading Dynamics of a Viral Infection in a Complex Network

We report a computational study of the spreading dynamics of a viral infection in a complex (scale-free) network. The final epidemic size distribution (FESD) was found to be unimodal or bimodal depending on the value of the basic reproductive number R0 . The FESDs occurred on time-scales long enough for intermediate-time epidemic size distributions (IESDs) to be important for control measures. The usefulness of R0 for deciding on the timeliness and intensity of control measures was found to be limited by the multimodal nature of the IESDs and by its inability to inform on the speed at which the infection spreads through the population. A reduction of the transmission probability at the hubs of the scale-free network decreased the occurrence of the larger-sized epidemic events of the multimodal distributions. For effective epidemic control, an early reduction in transmission at the index cell and its neighbors was essential.

Integrating Fast Karnough Map and Modular Neural Networks for Simplification and Realization of Complex Boolean Functions

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Adsorption of Crystal Violet onto BTEA- and CTMA-bentonite from Aqueous Solutions

CTMA-bentonite and BTEA-Bentonite prepared by Na-bentonite cation exchanged with cetyltrimethylammonium(CTMA) and benzyltriethylammonium (BTEA). Products were characterized by XRD and IR techniques.The d001 spacing value of CTMA-bentonite and BTEA-bentonite are 7.54Å and 3.50Å larger than that of Na-bentonite at 100% cation exchange capacity, respectively. The IR spectrum showed that the intensities of OH stretching and bending vibrations of the two organoclays decreased greatly comparing to untreated Na-bentonite. Batch experiments were carried out at 303 K, 318 K and 333 K to obtain the sorption isotherms of Crystal violet onto the two organoclays. The results show that the sorption isothermal data could be well described by Freundlich model. The dynamical data for the two organoclays fit well with pseudo-second-order kinetic model. The adsorption capacity of CTMA-bentonite was found higher than that of BTEA-Bentonite. Thermodynamic parameters such as changes in the free energy (ΔG°), the enthalpy (ΔH°) and the entropy (ΔS°) were also evaluated. The overall adsorption process of Crystal violet onto the two organoclays were spontaneous, endothermic physisorption. The CTMA-bentonite and BTEA-Bentonite could be employed as low-cost alternatives to activated carbon in wastewater treatment for the removal of color which comes from textile dyes.

Authentication Analysis of the 802.11i Protocol

IEEE has designed 802.11i protocol to address the security issues in wireless local area networks. Formal analysis is important to ensure that the protocols work properly without having to resort to tedious testing and debugging which can only show the presence of errors, never their absence. In this paper, we present the formal verification of an abstract protocol model of 802.11i. We translate the 802.11i protocol into the Strand Space Model and then prove the authentication property of the resulting model using the Strand Space formalism. The intruder in our model is imbued with powerful capabilities and repercussions to possible attacks are evaluated. Our analysis proves that the authentication of 802.11i is not compromised in the presented model. We further demonstrate how changes in our model will yield a successful man-in-the-middle attack.

Joint Design of MIMO Relay Networks Based on MMSE Criterion

This paper deals with wireless relay communication systems in which multiple sources transmit information to the destination node by the help of multiple relays. We consider a signal forwarding technique based on the minimum mean-square error (MMSE) approach with multiple antennas for each relay. A source-relay-destination joint design strategy is proposed with power constraints at the destination and the source nodes. Simulation results confirm that the proposed joint design method improves the average MSE performance compared with that of conventional MMSE relaying schemes.

A Fast Replica Placement Methodology for Large-scale Distributed Computing Systems

Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.

Computational Networks for Knowledge Representation

In the artificial intelligence field, knowledge representation and reasoning are important areas for intelligent systems, especially knowledge base systems and expert systems. Knowledge representation Methods has an important role in designing the systems. There have been many models for knowledge such as semantic networks, conceptual graphs, and neural networks. These models are useful tools to design intelligent systems. However, they are not suitable to represent knowledge in the domains of reality applications. In this paper, new models for knowledge representation called computational networks will be presented. They have been used in designing some knowledge base systems in education for solving problems such as the system that supports studying knowledge and solving analytic geometry problems, the program for studying and solving problems in Plane Geometry, the program for solving problems about alternating current in physics.

A Method to Predict Hemorrhage Disease of Grass Carp Tends

Hemorrhage Disease of Grass Carp (HDGC) is a kind of commonly occurring illnesses in summer, and the extremely high death rate result in colossal losses to aquaculture. As the complex connections among each factor which influences aquiculture diseases, there-s no quit reasonable mathematical model to solve the problem at present.A BP neural network which with excellent nonlinear mapping coherence was adopted to establish mathematical model; Environmental factor, which can easily detected, such as breeding density, water temperature, pH and light intensity was set as the main analyzing object. 25 groups of experimental data were used for training and test, and the accuracy of using the model to predict the trend of HDGC was above 80%. It is demonstrated that BP neural network for predicating diseases in HDGC has a particularly objectivity and practicality, thus it can be spread to other aquiculture disease.

Adaptation Learning Speed Control for a High- Performance Induction Motor using Neural Networks

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Synthesis and Analysis of Swelling and Controlled Release Behaviour of Anionic sIPN Acrylamide based Hydrogels

In modern agriculture, polymeric hydrogels are known as a component able to hold an amount of water due to their 3-dimensional network structure and their tendency to absorb water in humid environments. In addition, these hydrogels are able to controllably release the fertilisers and pesticides loaded in them. Therefore, they deliver these materials to the plants' roots and help them with growing. These hydrogels also reduce the pollution of underground water sources by preventing the active components from leaching. In this study, sIPN acrylamide based hydrogels are synthesised by using acrylamide free radical, potassium acrylate, and linear polyvinyl alcohol. Ammonium nitrate is loaded in the hydrogel as the fertiliser. The effect of various amounts of monomers and linear polymer, measured in molar ratio, on the swelling rate, equilibrium swelling, and release of ammonium nitrate is studied.