Time Series Forecasting Using a Hybrid RBF Neural Network and AR Model Based On Binomial Smoothing

ANNARIMA that combines both autoregressive integrated moving average (ARIMA) model and artificial neural network (ANN) model is a valuable tool for modeling and forecasting nonlinear time series, yet the over-fitting problem is more likely to occur in neural network models. This paper provides a hybrid methodology that combines both radial basis function (RBF) neural network and auto regression (AR) model based on binomial smoothing (BS) technique which is efficient in data processing, which is called BSRBFAR. This method is examined by using the data of Canadian Lynx data. Empirical results indicate that the over-fitting problem can be eased using RBF neural network based on binomial smoothing which is called BS-RBF, and the hybrid model–BS-RBFAR can be an effective way to improve forecasting accuracy achieved by BSRBF used separately.

Perturbation in the Fractional Fourier Span due to Erroneous Transform Order and Window Function

Fractional Fourier Transform is a generalization of the classical Fourier Transform. The Fractional Fourier span in general depends on the amplitude and phase functions of the signal and varies with the transform order. However, with the development of the Fractional Fourier filter banks, it is advantageous in some cases to have different transform orders for different filter banks to achieve better decorrelation of the windowed and overlapped time signal. We present an expression that is useful for finding the perturbation in the Fractional Fourier span due to the erroneous transform order and the possible variation in the window shape and length. The expression is based on the dependency of the time-Fractional Fourier span Uncertainty on the amplitude and phase function of the signal. We also show with the help of the developed expression that the perturbation of span has a varying degree of sensitivity for varying degree of transform order and the window coefficients.

Implementing Authentication Protocol for Exchanging Encrypted Messages via an Authentication Server Based on Elliptic Curve Cryptography with the ElGamal-s Algorithm

In this paper the authors propose a protocol, which uses Elliptic Curve Cryptography (ECC) based on the ElGamal-s algorithm, for sending small amounts of data via an authentication server. The innovation of this approach is that there is no need for a symmetric algorithm or a safe communication channel such as SSL. The reason that ECC has been chosen instead of RSA is that it provides a methodology for obtaining high-speed implementations of authentication protocols and encrypted mail techniques while using fewer bits for the keys. This means that ECC systems require smaller chip size and less power consumption. The proposed protocol has been implemented in Java to analyse its features and vulnerabilities in the real world.

Discovering Complex Regularities: from Tree to Semi-Lattice Classifications

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries- import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.

Comparison of Hough Transform and Mean Shift Algorithm for Estimation of the Orientation Angle of Industrial Data Matrix Codes

In automatic manufacturing and assembling of mechanical, electrical and electronic parts one needs to reliably identify the position of components and to extract the information of these components. Data Matrix Codes (DMC) are established by these days in many areas of industrial manufacturing thanks to their concentration of information on small spaces. In today’s usually order-related industry, where increased tracing requirements prevail, they offer further advantages over other identification systems. This underlines in an impressive way the necessity of a robust code reading system for detecting DMC on the components in factories. This paper compares two methods for estimating the angle of orientation of Data Matrix Codes: one method based on the Hough Transform and the other based on the Mean Shift Algorithm. We concentrate on Data Matrix Codes in industrial environment, punched, milled, lasered or etched on different materials in arbitrary orientation.

Study of Damage in Beams with Different Boundary Conditions

–In this paper the damage in clamped-free, clampedclamped and free-free beam are analyzed considering samples without and with structural modifications. The damage location is investigated by the use of the bispectrum and wavelet analysis. The mathematical models are obtained using 2D elasticity theory and the Finite Element Method (FEM). The numerical and experimental data are approximated using the Particle Swarm Optimizer (PSO) method and this way is possible to adjust the localization and the severity of the damage. The experimental data are obtained through accelerometers placed along the sample. The system is excited using impact hammer.

Swedish: Being or Becoming? Immigration, National Identity and the Democratic State

This article discusses superordinate national identity as a means for immigrants integration into democratic polities. It is suggested that a superordinate national identity perceived as inclusive, by immigrants and by the native population, would be conducive to such integration. Command of the dominant language of society is seen as most important of the inclusive criteria. Other such criteria are respect of the country's political institutions and feelings of belonging to the country where you live. The argument is supported by data, showing a majority in favour of inclusive criteria for 'Swedishness', from a recent study among 1000 secondary school students of 'Swedish' and non-'Swedish' backgrounds.

Reservoir Operating by Ant Colony Optimization for Continuous Domains (ACOR) Case Study: Dez Reservoir

A direct search approach to determine optimal reservoir operating is proposed with ant colony optimization for continuous domains (ACOR). The model is applied to a system of single reservoir to determine the optimum releases during 42 years of monthly steps. A disadvantage of ant colony based methods and the ACOR in particular, refers to great amount of computer run time consumption. In this study a highly effective procedure for decreasing run time has been developed. The results are compared to those of a GA based model.

Solar Cell Parameters Estimation Using Simulated Annealing Algorithm

This paper presents Simulated Annealing based approach to estimate solar cell model parameters. Single diode solar cell model is used in this study to validate the proposed approach outcomes. The developed technique is used to estimate different model parameters such as generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor that govern the current-voltage relationship of a solar cell. A practical case study is used to test and verify the consistency of accurately estimating various parameters of single diode solar cell model. Comparative study among different parameter estimation techniques is presented to show the effectiveness of the developed approach.

An Empirical Formula for Seismic Test of Telecommunication Equipments

Antiseismic property of telecommunication equipment is very important for the grasp of the damage and the restoration after earthquake. Telecommunication business operators are regulating seismic standard for their equipments. These standards are organized to simulate the real seismic situations and usually define the minimum value of first natural frequency of the equipments or the allowable maximum displacement of top of the equipments relative to bottom. Using the finite element analysis, natural frequency can be obtained with high accuracy but the relative displacement of top of the equipments is difficult to predict accurately using the analysis. Furthermore, in the case of simulating the equipments with access floor, predicting the relative displacement of top of the equipments become more difficult. In this study, using enormous experimental datum, an empirical formula is suggested to forecast the relative displacement of top of the equipments. Also it can be known that which physical quantities are related with the relative displacement.

Outcomes of Teenage Mothers at Dankhunthot Hospital, Nakhon Ratchasima

The aim of this study was to investigate the pregnancy outcomes of teenage mothers at DanKhunThot hospital, Nakhon Ratchasima, Thailand. A retrospective descriptive study was conducted in 573 of teenage pregnant from charts reviewed from 1st October 2010-31st March, 2012. Data were analyzed by frequency distribution, mean and Standard Deviation. The results shown several problems and negatives outcomes of pregnancy in teenager such as not attended prenatal care, Low birth weight infants, death fetus in utero and other complications. The results of this study can be utilized in the development of prenatal, perinatal and post natal care services, especially in DanKhunthot Hospital contexts. Moreover, the results were present to the District Health Care committees in order to enhance health care service system for teenage pregnancy of DanKhunthot District in further.

Extracting Multiword Expressions in Machine Translation from English to Urdu using Relational Data Approach

Machine Translation, (hereafter in this document referred to as the "MT") faces a lot of complex problems from its origination. Extracting multiword expressions is also one of the complex problems in MT. Finding multiword expressions during translating a sentence from English into Urdu, through existing solutions, takes a lot of time and occupies system resources. We have designed a simple relational data approach, in which we simply set a bit in dictionary (database) for multiword, to find and handle multiword expression. This approach handles multiword efficiently.

Aspects to Motivate users of a Design Engineering Wiki to Share their Knowledge

Industrial design engineering is an information and knowledge intensive job. Although Wikipedia offers a lot of this information, design engineers are better served with a wiki tailored to their job, offering information in a compact manner and functioning as a design tool. For that reason WikID has been developed. However for the viability of a wiki, an active user community is essential. The main subject of this paper is a study to the influence of the communication and the contents of WikID on the user-s willingness to contribute. At first the theory about a website-s first impression, general usability guidelines and user motivation in an online community is studied. Using this theory, the aspects of the current site are analyzed on their suitability. These results have been verified with a questionnaire amongst 66 industrial design engineers (or students industrial design engineering). The main conclusion is that design engineers are enchanted with the existence of WikID and its knowledge structure (taxonomy) but this structure has not become clear without any guidance. In other words, the knowledge structure is very helpful for inspiring and guiding design engineers through their tailored knowledge domain in WikID but this taxonomy has to be better communicated on the main page. Thereby the main page needs to be fitted more to the target group preferences.

Thermal Management of Space Power Electronics using TLM-3D

When designing satellites, one of the major issues aside for designing its primary subsystems is to devise its thermal. The thermal management of satellites requires solving different sets of issues with regards to modelling. If the satellite is well conditioned all other parts of the satellite will have higher temperature no matter what. The main issue of thermal modelling for satellite design is really making sure that all the other points of the satellite will be within the temperature limits they are designed. The insertion of power electronics in aerospace technologies is becoming widespread and the modern electronic systems used in space must be reliable and efficient with thermal management unaffected by outer space constraints. Many advanced thermal management techniques have been developed in recent years that have application in high power electronic systems. This paper presents a Three-Dimensional Modal Transmission Line Matrix (3D-TLM) implementation of transient heat flow in space power electronics. In such kind of components heat dissipation and good thermal management are essential. Simulation provides the cheapest tool to investigate all aspects of power handling. The 3DTLM has been successful in modeling heat diffusion problems and has proven to be efficient in terms of stability and complex geometry. The results show a three-dimensional visualisation of self-heating phenomena in the device affected by outer space constraints, and will presents possible approaches for increasing the heat dissipation capability of the power modules.

Testing the Accuracy of ML-ANN for Harmonic Estimation in Balanced Industrial Distribution Power System

In this paper, we analyze and test a scheme for the estimation of electrical fundamental frequency signals from the harmonic load current and voltage signals. The scheme was based on using two different Multi Layer Artificial Neural Networks (ML-ANN) one for the current and the other for the voltage. This study also analyzes and tests the effect of choosing the optimum artificial neural networks- sizes which determine the quality and accuracy of the estimation of electrical fundamental frequency signals. The simulink tool box of the Matlab program for the simulation of the test system and the test of the neural networks has been used.

Applications of Support Vector Machines on Smart Phone Systems for Emotional Speech Recognition

An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Characterization of Electrohydrodynamic Force on Dielectric-Barrier-Discharge Plasma Actuator Using Fluid Simulation

Wall-surface jet induced by the dielectric barrier discharge (DBD) has been proposed as an actuator for active flow control in aerodynamic applications. Discharge plasma evolution of the DBD plasma actuator was simulated based on a simple fluid model, in which the electron, one type of positive ion and negative ion were taken into account. Two-dimensional simulation was conducted, and the results are in agreement with the insights obtained from experimental studies. The simulation results indicate that the discharge mode changes depending on applied voltage slope; when the applied voltage is positive-going with high applied voltage slope, the corona-type discharge mode turns into the streamer-type discharge mode and the threshold voltage slope is around 300 kV/ms in this simulation. The characteristics of the electrohydrodynamic (EHD) force, which is the source of the wall-surface jet, also change depending on the discharge mode; the tentative peak value of the EHD force during the positive-going voltage phase is saturated by the periodical formation of the streamer-type discharge.

A Recommender Agent to Support Virtual Learning Activities

This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the input information for the agent. By using the attribute-based recommender technique, the information can be processed and resource recommendations can be obtained. These serve as support for pending activity development in the course. To integrate this technique, we used an ontology. This served as support for the semantic annotation of attributes and recommended files recovery.

A Genetic-Algorithm-Based Approach for Audio Steganography

In this paper, we present a novel, principled approach to resolve the remained problems of substitution technique of audio steganography. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.