Search results for: radial basis function network.

Authors: Paul Crowther, Richard Hill

Abstract:

Much has been written about the difficulties students have with producing traditional dissertations. This includes both native English speakers (L1) and students with English as a second language (L2). The main emphasis of these papers has been on the structure of the dissertation, but in all cases, even when electronic versions are discussed, the dissertation is still in what most would regard as a traditional written form. Master of Science Degrees in computing disciplines require students to gain technical proficiency and apply their knowledge to a range of scenarios. The basis of this paper is that if a dissertation is a means of showing that such a student has met the criteria for a pass, which should be based on the learning outcomes of the dissertation module, does meeting those outcomes require a student to demonstrate their skills in a solely text based form, particularly in a highly technical research project? Could it be possible for a student to produce a series of related artifacts which form a cohesive package that meets the learning out comes of the dissertation?

Keywords: Computing, Masters dissertation, thesis, portfolio

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Authors: María Teresa García-Álvarez, Isabel Soares, Rosa María Mariz-Pérez

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Directive 2009/28/CE establishes, as obligatory objective, a share of renewable energies on energetic consumption of 20%, in European Union, in 2020 However, such European normative gives freedom to member states in the selection of the renewable promotion mechanism that allows them to obtain that objective. In this paper, we analyze the main characteristics of the promotion mechanisms of renewable energy used in the countries that shape the Electricity Iberian Market (Spain and Portugal) and the results in employment. The importance of these countries is given by the great increasing of the renewable energies which suppose a share higher than 30% of the overall generation in 2010. Therefore, this research paper can serve as the basis for the learning of other countries with regard to the main advantages that entail the use of a feed-in tariff system.

Keywords: Employment, Energy policy, Professional profiles, Renewable energies, Professional profiles.

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Authors: Zoja Raud, Valery Vodovozov

Abstract:

The paper focuses on the distance laboratory organisation for training the electrical engineering staff and students in the fields of electrical drive and power electronics. To support online knowledge acquisition and professional enhancement, new challenges in remote education based on an active learning approach with self-assessment have been emerged by the authors. Following the literature review and explanation of the improved assessment methodology, the concept and technological basis of the labs arrangement are presented. To decrease the gap between the distance study of the up-to-date equipment and other educational activities in electrical engineering, the improvements in the following-up the learners’ progress and feedback composition are introduced. An authoring methodology that helps to personalise knowledge acquisition and enlarge Web-based possibilities is described. Educational management based on self-assessment is discussed.

Keywords: Advanced training, active learning, distance learning, electrical engineering, remote laboratory, self-assessment.

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Authors: Atman Jbari, Abdellah Adib, Driss Aboutajdine

Abstract:

This paper addresses the problem of blind source separation (BSS). To recover original signals, from linear instantaneous mixtures, we propose a new contrast function based on the use of a double referenced system. Our approach assumes statistical independence sources. The reference vectors will be incrusted in the cumulant to evaluate the independence. The estimation of the separating matrix will be performed in two steps: whitening observations and joint diagonalization of a set of referenced cumulant matrices. Computer simulations are presented to demonstrate the effectiveness of the suggested approach.

Keywords: Blind source separation, Referenced Cumulant, Contrast, Joint Diagonalization.

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Authors: Zebiri Chemseddine, Benabdelaziz Fatiha

Abstract:

The effect of a chiral bianisotropic substrate on the complex resonant frequency of a rectangular microstrip resonator has been studied on the basis of the integral equation formulation. The analysis is based on numerical resolution of the integral equation using Galerkin procedure for moment method in the spectral domain. This work aim first to study the effect of the chirality of a bianisotopic substrate upon the resonant frequency and the half power bandwidth, second the effect of a magnetic anisotropy via an asymptotic approach for very weak substrate upon the resonant frequency and the half power bandwidth has been investigated. The obtained results are compared with previously published work [11-9], they were in good agreement.

Keywords: Microstrip antenna, bianisotropic media, resonant frequency, moment method.

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Authors: Pavel Y. Tabakov, Kevin Duffy

Abstract:

The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Keywords: Classification, clustering, data minig, genetic algorithms.

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Authors: Daniel Kade, Oğuzhan Özcan, Rikard Lindell

Abstract:

Motion capturing technology has been used for quite a while and several research has been done within this area. Nevertheless, we discovered open issues within current motion capturing environments. In this paper we provide a state-of-the-art overview of the addressed research areas and show issues with current motion capturing environments. Observations, interviews and questionnaires have been used to reveal the challenges actors are currently facing in a motion capturing environment. Furthermore, the idea to create a more immersive motion capturing environment to improve the acting performances and motion capturing outcomes as a potential solution is introduced. It is hereby the goal to explain the found open issues and the developed ideas which shall serve for further research as a basis. Moreover, a methodology to address the interaction and systems design issues is proposed. A future outcome could be that motion capture actors are able to perform more naturally, especially if using a non-body-worn solution.

Keywords: Immersive acting environment, Interaction in a mediated environment, Motion capturing, MoCap.

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

Abstract:

The paper discusses the main aspects involved in the development of a supply chain management system using the developed PredictionSCMS software as a basis for the discussion. The discussion is focused on three topics: the first is demand forecasting, where we present the predictive algorithms implemented and discuss related concepts such as the calculation of the safety stock, the effect of out-of-stock days etc. The second topic concerns the design of a supply chain, where the core parameters involved in the process are given, together with a methodology of incorporating these parameters in a meaningful order creation strategy. Finally, the paper discusses some critical events that can happen during the operation of a supply chain management system and how the developed software notifies the end user about their occurrence.

Keywords: Demand forecasting, machine learning, risk management, supply chain design.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.

Keywords: Robust exponential stability, delay-dependent stability, discrete-time neutral networks, time-varying delays.

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Authors: S. H. Nasseri, E. Ardil, A. Yazdani, R. Zaefarian

Abstract:

The fuzzy set theory has been applied in many fields, such as operations research, control theory, and management sciences, etc. In particular, an application of this theory in decision making problems is linear programming problems with fuzzy numbers. In this study, we present a new method for solving fuzzy number linear programming problems, by use of linear ranking function. In fact, our method is similar to simplex method that was used for solving linear programming problems in crisp environment before.

Keywords: Fuzzy number linear programming, rankingfunction, simplex method.

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Authors: Manoranjan Das, Benudhar Sahu, Urmila Bhanja

Abstract:

Co-channel interference is one of the major problems in wireless systems. The effects of co-channel interference in a Nakagami fading channel on the ABER (Average Bit Error Rate) with static nodes are well analyzed. In this paper, we derive the ABER with the presence of mobile nodes. ABER is also derived for mobile systems in the presence of co-channel interference.

Keywords: ABER, co-channel interference, Nakagami fading.

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Authors: Hamed Vahdat Nejad, Hossein Deldari

Abstract:

Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images. Image compression is one of major applications of wavelet transforms in image processing. It is considered as one of the most powerful methods that provides a high compression ratio. However, its implementation is very time-consuming. At the other hand, parallel computing technologies are an efficient method for image compression using wavelets. In this paper, we propose a parallel wavelet compression algorithm based on quadtrees. We implement the algorithm using MatlabMPI (a parallel, message passing version of Matlab), and compute its isoefficiency function, and show that it is scalable. Our experimental results confirm the efficiency of the algorithm also.

Keywords: Image compression, MPI, Parallel computing, Wavelets.

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Authors: Yeonsoo Jang, Dongweon Yoon, Ki Ho Kwon, Jaeyoon Lee, Wooju Lee

Abstract:

Phase error in communications systems degrades error performance. In this paper, we present a simple approximation for the average error probability of the binary phase shift keying (BPSK) in the presence of phase error having a uniform distribution on arbitrary intervals. For the simple approximation, we use symmetry and periodicity of a sinusoidal function. Approximate result for the average error probability is derived, and the performance is verified through comparison with simulation result.

Keywords: Average error probability, Phase shift keying, Phase error

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Authors: M. Kamel El-Sayed

Abstract:

The process of determining the degree of membership for an element to an uncertain concept has been found in many ways, using equivalence and symmetry relations in information systems. In the case of similarity, these methods did not take into account the degree of symmetry between elements. In this paper, we use a new definition for finding the membership based on the degree of symmetry. We provide an example to clarify the suggested methods and compare it with previous methods. This method opens the door to more accurate decisions in information systems.

Keywords: Information system, uncertain concept, membership function, similarity relation, degree of similarity.

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Authors: Leila Maleki, Ezatollah Ahmadi

Abstract:

Neuroplasticity or the flexibility of the neural system is the ability of the brain to adapt to the lack or deterioration of sense and the capability of the neural system to modify itself through changing shape and function. Not only have studies revealed that neuroplasticity does not end in childhood, but also they have proven that it continues till the end of life and is not limited to the neural system and covers the cognitive system as well. In the field of cognition, neuroplasticity is defined as the ability to change old thoughts according to new conditions and the individuals' differences in using various styles of cognitive regulation inducing several social, emotional and cognitive outcomes. This paper attempts to discuss and define major theories and principles of neuroplasticity and elaborate on nature or nurture.

Keywords: Neuroplasticity, Cognitive plasticity, Plasticity theories, Plasticity mechanisms.

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Authors: R. N. Rao, S. L. Tulasi Devi

Abstract:

Tribological behavior and wear regimes of ascast and heattreted Al-Cu-Mg matrix composites containing SiC particles were studied using a pin-on-disc wear testing apparatus against an EN32 steel counterface giving emphasis on wear rate as a function of applied pressures (0.2, 0.6, 1.0 and 1.4 MPa) at different sliding distances (1000, 2000, 3000, 4000 and 5000 meters) and at a fixed sliding speed of 3.35m/s. The results showed that the composite exhibited lower wear rate than that of the matrix alloy and the wear rate of the composites is noted to be invariant to the sliding distance and is reducing by heat treatment. Wear regimes such as low, mild and severe wear were observed as per the Archard-s wear calculations. It is very interesting to note that the mild wear is almost constant in all the wear regimes.

Keywords: Aluminum, matrix, regimes, wear.

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Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

Abstract:

Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

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Authors: Manpreet Singh, Parvinder Singh Sandhu, Basant Raj Singh

Abstract:

Hybridization refers to the crossing breeding of two plants. Coefficient of Parentage (COP) is used by the plant breeders to determine the genetic diversity across various varieties so as to incorporate the useful characters of the two varieties to develop a new crop variety with particular useful characters. Genetic Diversity is the prerequisite for any cultivar development program. Genetic Diversity depends upon the pedigree information of the varieties based on particular levels. Pedigree refers to the parents of a particular variety at various levels. This paper discusses the searching and analyses of different possible pairs of varieties selected on the basis of morphological characters, Climatic conditions and Nutrients so as to obtain the most optimal pair that can produce the required crossbreed variety. An algorithm was developed to determine the coefficient of parentage (COP) between the selected wheat varieties. Dummy values were used wherever actual data was not available.

Keywords: Coefficient of Parentage, Morphological characters, Pedigree, Genetic Diversity.

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Authors: Artur Matuck, Guilherme F. Nobre

Abstract:

Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: Artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art.

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Authors: Behrooz Rezaie, Zahra Rahmani Cherati, Mohammad Reza Jahed Motlagh, Mohammad Farrokhi

Abstract:

In this paper, a fuzzy controller is designed for stabilization of the Lorenz chaotic equations. A simple Mamdani inference method is used for this purpose. This method is very simple and applicable for complex chaotic systems and it can be implemented easily. The stability of close loop system is investigated by the Lyapunov stabilization criterion. A Lyapunov function is introduced and the global stability is proven. Finally, the effectiveness of this method is illustrated by simulation results and it is shown that the performance of the system is improved.

Keywords: Chaotic system, Fuzzy control, Lorenz equation.

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Authors: Chih-Cheng Kao, Hsin- Hua Chu

Abstract:

This paper mainly proposes an efficient modified particle swarm optimization (MPSO) method, to identify a slidercrank mechanism driven by a field-oriented PM synchronous motor. In system identification, we adopt the MPSO method to find parameters of the slider-crank mechanism. This new algorithm is added with “distance" term in the traditional PSO-s fitness function to avoid converging to a local optimum. It is found that the comparisons of numerical simulations and experimental results prove that the MPSO identification method for the slider-crank mechanism is feasible.

Keywords: Slider-crank mechanism, distance, systemidentification, modified particle swarm optimization.

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Authors: Young-Seok Choi

Abstract:

This paper presents a normalized subband adaptive filtering (NSAF) algorithm to cope with the sparsity condition of an underlying system in the context of compressive sensing. By regularizing a weighted l1-norm of the filter taps estimate onto the cost function of the NSAF and utilizing a subgradient analysis, the update recursion of the l1-norm constraint NSAF is derived. Considering two distinct weighted l1-norm regularization cases, two versions of the l1-norm constraint NSAF are presented. Simulation results clearly indicate the superior performance of the proposed l1-norm constraint NSAFs comparing with the classical NSAF.

Keywords: Subband adaptive filtering, sparsity constraint, weighted l1-norm.

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Authors: M.R. Safizadeh, M. Hussein, K. F. Samat, M.S. Che Kob, M.S. Yaacob, M.Z. Md Zain

Abstract:

The aim of this paper is to present the kinematic analysis and mechanism design of an assistive robotic leg for hemiplegic and hemiparetic patients. In this work, the priority is to design and develop the lightweight, effective and single driver mechanism on the basis of experimental hip and knee angles- data for walking speed of 1 km/h. A mechanism of cam-follower with three links is suggested for this purpose. The kinematic analysis is carried out and analysed using commercialized MATLAB software based on the prototype-s links sizes and kinematic relationships. In order to verify the kinematic analysis of the prototype, kinematic analysis data are compared with the experimental data. A good agreement between them proves that the anthropomorphic design of the lower extremity exoskeleton follows the human walking gait.

Keywords: Kinematic analysis, assistive robotic leg, lower extremity exoskeleton, cam-follower mechanism.

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Authors: Z. Pavlík, H. Benešová, P. Matiašovský, M. Pavlíková

Abstract:

In this paper, study on carbonation process of several types of advanced plasters on lime basis is presented. The movement of carbonation head was measured by colorimetric method using phenolphtalein. The rate of carbonation was accessed also by gravimetric method. Samples of studied materials were placed into the climatic chamber for simulation of environment with high concentration of CO2. The particular samples were on all lateral sides and on the bottom side provided by epoxy resin in order to arrange 1-D transport of CO2 into the studied samples. The carbonation rates of particular materials pointed to the time dependence of diffusion process of CO2 for all the studied plasters. From the quantitative point of view, the carbonation of advanced modified plasters was much faster than for the reference lime plaster, what is beneficial for the practical application of the tested newly developed materials.

Keywords: Carbonation, colorimetric method, gravimetric method, lime-based plasters, pozzolana admixtures.

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Authors: Sarra Ben Hariz, Zied Elouedi, Khaled Mellouli

Abstract:

The belief K-modes method (BKM) approach is a new clustering technique handling uncertainty in the attribute values of objects in both the cluster construction task and the classification one. Like the standard version of this method, the BKM results depend on the chosen initial modes. So, one selection method of initial modes is developed, in this paper, aiming at improving the performances of the BKM approach. Experiments with several sets of real data show that by considered the developed selection initial modes method, the clustering algorithm produces more accurate results.

Keywords: Clustering, Uncertainty, Belief function theory, Belief K-modes Method, Initial modes selection.

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Authors: H. Mahboubi, B. Moshiri, A. Khaki Seddigh

Abstract:

In the past decade, because of wide applications of hybrid systems, many researchers have considered modeling and control of these systems. Since switching systems constitute an important class of hybrid systems, in this paper a method for optimal control of linear switching systems is described. The method is also applied on the two-tank system which is a much appropriate system to analyze different modeling and control techniques of hybrid systems. Simulation results show that, in this method, the goals of control and also problem constraints can be satisfied by an appropriate selection of cost function.

Keywords: Hybrid systems, optimal control, switched systems, two-tank system

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Authors: Amr A. El Hanafy, Yasir Anwar, Saleh A. Mohamed, Saleh Mohamed Saleh Al-Garni, Jamal S. M. Sabir, Osama A. H. Abu Zinadah, Mohamed Morsi Ahmed

Abstract:

In the vicinity of red sea about 15 fungi species were isolated from oil contaminated sites. On the basis of aptitude to degrade the crude oil and DCPIP assay, two fungal isolates were selected amongst 15 oil degrading strains. Analysis of ITS-1, ITS-2 and amplicon pyrosequencing studies of fungal diversity revealed that these strains belong to Penicillium and Aspergillus species. Two strains that proved to be the most efficient in degrading crude oil was Aspergillus niger (54%) and Penicillium commune (48%) Subsequent to two weeks of cultivation in BHS medium the degradation rate were recorded by using spectrophotometer and GC-MS. Hence, it is cleared that these fungal strains has capability of degradation and can be utilize for cleaning the Saudi Arabian environment.

Keywords: Fungal strains, hydrocarbon contaminants, molecular identification, biodegradation, GC-MS.

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Authors: Zulfadhli Hasan Adli, Mohd Hafiz Musa, M. N. Khairul Arifin

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The objective of this paper is to study the electrical resistivity complexity between field and laboratory measurement, in order to improve the effectiveness of data interpretation for geophysical ground resistivity survey. The geological outcrop in Penang, Malaysia with an obvious layering contact was chosen as the study site. Two dimensional geoelectrical resistivity imaging were used in this study to maps the resistivity distribution of subsurface, whereas few subsurface sample were obtained for laboratory advance. In this study, resistivity of samples in original conditions is measured in laboratory by using time domain low-voltage technique, particularly for granite core sample and soil resistivity measuring set for soil sample. The experimentation results from both schemes are studied, analyzed, calibrated and verified, including basis and correlation, degree of tolerance and characteristics of substance. Consequently, the significant different between both schemes is explained comprehensively within this paper.

Keywords: Electrical Resistivity, Granite, Soil.

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: Md Fazlul Kader, Soo Young Shin

Abstract:

In this paper, we consider a cognitive relay network (CRN) in which the primary receiver (PR) is protected by peak transmit power ¯PST and/or peak interference power Q constraints. In addition, the interference effect from the primary transmitter (PT) is considered to show its impact on the performance of the CRN. We investigate the outage probability (OP) and outage capacity (OC) of the CRN by deriving closed-form expressions over Rayleigh fading channel. Results show that both the OP and OC improve by increasing the cooperative relay nodes as well as when the PT is far away from the SR.

Keywords: Cognitive relay, outage, interference limited, decode-and-forward (DF).

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