System Identification with General Dynamic Neural Networks and Network Pruning

This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.

Application of Artificial Neural Network to Forecast Actual Cost of a Project to Improve Earned Value Management System

This paper presents an application of Artificial Neural Network (ANN) to forecast actual cost of a project based on the earned value management system (EVMS). For this purpose, some projects randomly selected based on the standard data set , and it is produced necessary progress data such as actual cost ,actual percent complete , baseline cost and percent complete for five periods of project. Then an ANN with five inputs and five outputs and one hidden layer is trained to produce forecasted actual costs. The comparison between real and forecasted data show better performance based on the Mean Absolute Percentage Error (MAPE) criterion. This approach could be applicable to better forecasting the project cost and result in decreasing the risk of project cost overrun, and therefore it is beneficial for planning preventive actions.

New Multipath Node-Disjoint Routing Based on AODV Protocol

Today, node-disjoint routing becomes inessential technique in communication of packets among various nodes in networks. Meanwhile AODV (Ad Hoc On-demand Multipath Distance Vector) creates single-path route between a pair of source and destination nodes. Some researches has done so far to make multipath node-disjoint routing based on AODV protocol. But however their overhead and end-to-end delay are relatively high, while the detail of their code is not available too. This paper proposes a new approach of multipath node-disjoint routing based on AODV protocol. Then the algorithm of analytical model is presented. The extensive results of this algorithm will be presented in the next paper.

Learning Paradigms for Educating a New Generation of Computer Science Students

In this paper challenges associated with a new generation of Computer Science students are examined. The mode of education in tertiary institutes has progressed slowly while the needs of students have changed rapidly in an increasingly technological world. The major learning paradigms and learning theories within these paradigms are studied to find a suitable strategy for educating modern students. These paradigms include Behaviourism, Constructivism, Humanism and Cogntivism. Social Learning theory and Elaboration theory are two theories that are further examined and a survey is done to determine how these strategies will be received by students. The results and findings are evaluated and indicate that students are fairly receptive to a method that incorporates both Social Learning theory and Elaboration theory, but that some aspects of all paradigms need to be implemented to create a balanced and effective strategy with technology as foundation.

Comparison of Evolutionary Algorithms and their Hybrids Applied to MarioAI

Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.

Measuring Teachers- Beliefs about Mathematics: A Fuzzy Set Approach

This paper deals with the application of a fuzzy set in measuring teachers- beliefs about mathematics. The vagueness of beliefs was transformed into standard mathematical values using a fuzzy preferences model. The study employed a fuzzy approach questionnaire which consists of six attributes for measuring mathematics teachers- beliefs about mathematics. The fuzzy conjoint analysis approach based on fuzzy set theory was used to analyze the data from twenty three mathematics teachers from four secondary schools in Terengganu, Malaysia. Teachers- beliefs were recorded in form of degrees of similarity and its levels of agreement. The attribute 'Drills and practice is one of the best ways of learning mathematics' scored the highest degree of similarity at 0. 79860 with level of 'strongly agree'. The results showed that the teachers- beliefs about mathematics were varied. This is shown by different levels of agreement and degrees of similarity of the measured attributes.

Applications of High-Order Compact Finite Difference Scheme to Nonlinear Goursat Problems

Several numerical schemes utilizing central difference approximations have been developed to solve the Goursat problem. However, in a recent years compact discretization methods which leads to high-order finite difference schemes have been used since it is capable of achieving better accuracy as well as preserving certain features of the equation e.g. linearity. The basic idea of the new scheme is to find the compact approximations to the derivative terms by differentiating centrally the governing equations. Our primary interest is to study the performance of the new scheme when applied to two Goursat partial differential equations against the traditional finite difference scheme.

A Multilevel Comparative Assessment Approach to International Services Trade Competitiveness: The Case of Romania and Bulgaria

International competitiveness receives much attention nowadays, but up to now its assessment has been heavily based on manufacturing industry statistics. This paper addresses the need for competitiveness indicators that cover the service sector and sets out a multilevel framework for measuring international services trade competitiveness. The approach undertaken here aims at comparatively examining the international competitiveness of the EU-25 (the twenty-five European Union member states before the 1st of January 2007), Romanian and Bulgarian services trade, as well as the last two countries- structure of specialization on the EU-25 services market. The primary changes in the international competitiveness of three major services sectors – transportation, travel and other services - are analyzed. This research attempts to determine the ability of the two recent European Union (EU) member states to contend with the challenges that might arise from the hard competition within the enlarged EU, in the field of services trade.

Factors Influencing the Success of Mobile Phone Entrepreneurs at Central Plaza

The purpose of this research was to study the factors that influenced the success of mobile phone entrepreneurs at Central Plaza. The sample group included 187 entrepreneurs at Central Plaza. A questionnaire was utilized as a tool to collect data. Statistics used in this research included frequency, percentage, mean, and standard deviation. Independent- sample t- test, one way ANOVA, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences.The findings disclosed that the majority of respondents were male between 25-40 years old, and held an undergraduate degree. The average income of respondents was between 15,001-25,000 baht. The majority of respondents had less than 5 years of working experience. In terms of personality, the findings revealed that expression and agreement were ranked at the highest level. Whereas, emotion stability, consciousness, open to new experience were ranked at high. From the hypotheses testing, the findings revealed that different genders had different success in their mobile phone business with different income from the last 6 months. However, difference in age, income, level of education, and experience affected the success in terms of income, number of customers, and overall success of business. Moreover, the factors of personalities included expression, agreement, emotion stability, consciousness, open to new experience, and competitive strategy. From the findings, these factors were able to predict mobile phone business success at 66.9 percent.

Chemical Compositions and Physico-Chemical Properties of Malted Sorghum Flour and Characteristics of Gluten Free Bread

This study investigated the effect of germination on chemical compositions, physio-chemical properties of malted (germinated) red sorghum flours and evaluated characteristics of gluten free breads from sorghum flour. Results showed that germinated sorghum flour had higher amylase activity, swelling power and solubility at 95°C, but lower in the peak, break down, final and set back viscosities than ungerminated sample (p≤0.05). Five gluten free breads made from sorghum flour blends, with different ratios of ungerminated and germinated sorghum flour, were compared for the physical properties with those made from wheat flour. Crumb hardness, cohesiveness, gumminess and chewiness of sorghum breads were found significantly higher than those of wheat bread. With increasing of ungerminated flour proportion, the bread hardness increased while the cohesiveness declined. Sorghum breads appeared red to human eyes with a*values of 10.41-15.77.Their crust and crumb colors differed significantly from those of wheat bread.

The Biomechanical Properties of the Different Modalities of Surgically Corrected Coarctation of the Aorta in Neonates and Infants

Biomechanical properties of infantile aorta in vitro in cases of different standard anastomoses: end-to-end (ETE), extended anastomosis end-to-end (EETE) and subclavian flap aortoplasty (SFA) used for surgical correction of coarctation were analyzed to detect the influence of the method on the biomechanics of infantile aorta and possible changes in haemodinamics. 10 specimens of native aorta, 3 specimens with ETE, 4 EEET and 3 SFA were investigated. The experiments showed a non-linear relationship between stress and strain in the infantile aorta, the modulus of elasticity of the aortic wall increased with the increase of inner pressure. In the case of anastomosis end-to-end the modulus was almost constant, relevant to the modulus of elasticity of the aorta with the inner pressure 100-120 mmHg. The anastomoses EETE and SFA showed elastic properties closer to native aorta, the stiffness of ETE did not change with the changes in inner pressure.

Application of Adaptive Network-Based Fuzzy Inference System in Macroeconomic Variables Forecasting

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Histogenesis of Rabbit Vallate Papillae

The gustatory system allows animals to distinguish varieties of food and affects greatly the consumption of food, hence the health and growth of animals. In the current study, we investigated the histogenesis of vallate papillae (VLP) in the rabbit tongue using light and scanning electron microscopy. Samples were obtained from rabbit embryos at the embryonic days 16-30 (E16-30), and from newborns until maturity; 6 months. At E16, the first primordia of vallate papillae were observed as small pits on the surface epithelium of the tongue-s root. At E18, the caudal part was prominent with loose mesenchymal tissue core; meanwhile the rostral part of the papilla was remained as a thick mass of epithelial cells. At E20-24, the side epithelium formed the primitive annular groove. At E26, the primitive taste buds appeared only at the papillary surface and reached their maturity by E28. The annular groove started to appear at E26 became more defined at E28. The definitive vallate papillae with substantial number of apparently mature taste buds were observed by the end of the second week. We conclude that the vallate papillae develop early and mature during the early postnatal life.

Designing an Irregular Tensegrity as a Monumental Object

A novel and versatile numerical technique to solve a self-stress equilibrium state is adopted herein as a form-finding procedure for an irregular tensegrity structure. The numerical form-finding scheme of a tensegrity structure uses only the connectivity matrix and prototype tension coefficient vector as the initial guess solution. Any information on the symmetrical geometry or other predefined initial structural conditions is not necessary to get the solution in the form-finding process. An eight-node initial condition example is presented to demonstrate the efficiency and robustness of the proposed method in the form-finding of an irregular tensegrity structure. Based on the conception from the form-finding of an eight-node irregular tensegrity structure, a monumental object is designed by considering the real world situation such as self-weight, wind and earthquake loadings.

Optical Properties of Some A2BCl4 Type Chlorides

Efficient luminescence is reported for the first time in Eu2+ activated double Chlorides A2BCl4 (A=Alkali metal, B=Alkaline earth element). A simple wet-chemical preparation is described. Emission intensities are comparable to that of the commercial phosphor. Excitation covers near UV region. These phosphors may be useful for applications like solid state lighting, scintillation detectors and X-ray storage using photo-stimulable phosphors.

Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines

Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by applying a new formula to update the position and the velocity of a particle; the support vector machine is used as a classifier. The proposed model is tested and compared with the other methods using the KDD CUP 1999 dataset. The results indicate that this new method achieves better accuracy rates than previous methods.

Investigating Determinants of Medical User Expectations from Hospital Information System

User satisfaction is one of the most used success indicators in the research of information system (IS). Literature shows user expectations have great influence on user satisfaction. Both expectation and satisfaction of users are important for Hospital Information Systems (HIS). Education, IS experience, age, attitude towards change, business title, sex and working unit of the hospital, are examined as the potential determinant of the medical users’ expectations. Data about medical user expectations are collected by the “Expectation Questionnaire” developed for this study. Expectation data are used for calculating the Expectation Meeting Ratio (EMR) with the evaluation framework also developed for this study. The internal consistencies of the answers to the questionnaire are measured by Cronbach´s Alpha coefficient. The multivariate analysis of medical user’s EMRs of HIS is performed by forward stepwise binary logistic regression analysis. Education and business title is appeared to be the determinants of expectations from HIS.

Estimating Saturated Hydraulic Conductivity from Soil Physical Properties using Neural Networks Model

Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).

Genetic-Based Planning with Recursive Subgoals

In this paper, we introduce an effective strategy for subgoal division and ordering based upon recursive subgoals and combine this strategy with a genetic-based planning approach. This strategy can be applied to domains with conjunctive goals. The main idea is to recursively decompose a goal into a set of serializable subgoals and to specify a strict ordering among the subgoals. Empirical results show that the recursive subgoal strategy reduces the size of the search space and improves the quality of solutions to planning problems.

An EOQ Model for Non-Instantaneous Deteriorating Items with Power Demand, Time Dependent Holding Cost, Partial Backlogging and Permissible Delay in Payments

In this paper, Economic Order Quantity (EOQ) based model for non-instantaneous Weibull distribution deteriorating items with power demand pattern is presented. In this model, the holding cost per unit of the item per unit time is assumed to be an increasing linear function of time spent in storage. Here the retailer is allowed a trade-credit offer by the supplier to buy more items. Also in this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This model aids in minimizing the total inventory cost by finding the optimal time interval and finding the optimal order quantity. The optimal solution of the model is illustrated with the help of numerical examples. Finally sensitivity analysis and graphical representations are given to demonstrate the model.