Search results for: Singular curve

Authors: Pradya Pornnimitkul, Suwich Kunaruttanapruk, Bamrung Tau Sieskul, Somchai Jitapunkul

Abstract:

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

Keywords: Channel estimation, MC-CDMA, SVD, URV.

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Authors: A. Chillali, A. Tadmori, M. Ziane

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In this article we will study the elliptic curve defined over the ring An and we define the mathematical operations of ECC, which provides a high security and advantage for wireless applications compared to other asymmetric key cryptosystem.

Keywords: Elliptic Curves, Finite Ring, Cryptography.

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Authors: A. U. Haque, W. Asrar, A. A. Omar, E. Sulaeman, J. S. Mohamed Ali

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Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angle of attack. As a part of the validation of low fidelity tool, plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficients, the overall trend has under predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: Wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics.

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Authors: Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag

Abstract:

Term Extraction, a key data preparation step in Text Mining, extracts the terms, i.e. relevant collocation of words, attached to specific concepts (e.g. genetic-algorithms and decisiontrees are terms associated to the concept “Machine Learning" ). In this paper, the task of extracting interesting collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as interesting/not interesting. From these examples, the ROGER algorithm learns a numerical function, inducing some ranking on the collocations. This ranking is optimized using genetic algorithms, maximizing the trade-off between the false positive and true positive rates (Area Under the ROC curve). This approach uses a particular representation for the word collocations, namely the vector of values corresponding to the standard statistical interestingness measures attached to this collocation. As this representation is general (over corpora and natural languages), generality tests were performed by experimenting the ranking function learned from an English corpus in Biology, onto a French corpus of Curriculum Vitae, and vice versa, showing a good robustness of the approaches compared to the state-of-the-art Support Vector Machine (SVM).

Keywords: Text-mining, Terminology Extraction, Evolutionary algorithm, ROC Curve.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

Abstract:

Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, Pareto Optimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Osamu Igawa, Hiroshi Kouchiwa, Yuji Ito

Abstract:

In recent years, a reconstruction project for sewer  pipelines has been progressing in Japan with the aim of renewing old  sewer culverts. However, it is difficult to secure a sufficient base area  for shafts in an urban area because many streets are narrow with a  complex layout. As a result, construction in such urban areas is  generally very demanding.  In urban areas, there is a strong requirement for a safe, reliable and  economical construction method that does not disturb the public’s  daily life and urban activities. With this in mind, we developed a new  construction method called the “shield switching type micro-tunneling  method,” which integrates the micro-tunneling method and shield  method.  In this method, pipeline is constructed first for sections that are  gently curved or straight using the economical micro-tunneling  method, and then the method is switched to the shield method for  sections with a sharp curve or a series of curves without establishing  an intermediate shaft.  This paper provides the information, features and construction  examples of this newly developed method.

 

Keywords: Micro-tunneling method, Secondary lining applied RC segment, Sharp curve, Shield method, Switching type.

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Authors: Roghaieh Parvizsedghy, Seyyed Mojtaba Sadrameli

Abstract:

Biodiesel as an alternative diesel fuel is steadily gaining more attention and significance. However, there are some drawbacks while using biodiesel regarding its properties that requires it to be blended with petrol based diesel and/or additives to improve the fuel characteristics. This study analyses thermal cracking as an alternative technology to improve biodiesel characteristics in which, FAME based biodiesel produced by transesterification of castor oil is fed into a continuous thermal cracking reactor at temperatures range of 450-500°C and flowrate range of 20-40 g/hr. Experiments designed by response surface methodology and subsequent statistical studies show that temperature and feed flowrate significantly affect the products yield. Response surfaces were used to study the impact of temperature and flowrate on the product properties. After each experiment, the produced crude bio-oil was distilled and diesel cut was separated. As shorter chain molecules are produced through thermal cracking, the distillation curve of the diesel cut fitted more with petrol based diesel curve in comparison to the biodiesel. Moreover, the produced diesel cut properties adequately pose within property ranges defined by the related standard of petrol based diesel. Cold flow properties, high heating value as the main drawbacks of the biodiesel are improved by this technology. Thermal cracking decreases kinematic viscosity, Flash point and cetane number. 

Keywords: Biodiesel, castor oil, fuel properties, thermal cracking.

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Authors: Azadeh Golshan, Craig Evans, Phillip Geary, Abigail Morrow, Zoe Rogers, Marcel Maeder

Abstract:

22 physicochemical variables have been determined in water samples collected weekly from January to December in 2013 from three sampling stations located within a major drinking water reservoir. Classical Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) analysis was used to investigate the environmental factors associated with the physico-chemical variability of the water samples at each of the sampling stations. Matrix augmentation MCR-ALS (MA-MCR-ALS) was also applied, and the two sets of results were compared for interpretative clarity. Links between these factors, reservoir inflows and catchment land-uses were investigated and interpreted in relation to chemical composition of the water and their resolved geographical distribution profiles. The results suggested that the major factors affecting reservoir water quality were those associated with agricultural runoff, with evidence of influence on algal photosynthesis within the water column. Water quality variability within the reservoir was also found to be strongly linked to physical parameters such as water temperature and the occurrence of thermal stratification. The two methods applied (MCR-ALS and MA-MCR-ALS) led to similar conclusions; however, MA-MCR-ALS appeared to provide results more amenable to interpretation of temporal and geological variation than those obtained through classical MCR-ALS.

Keywords: Catchment management, drinking water reservoir, multivariate curve resolution alternating least squares, thermal stratification, water quality.

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Authors: Abdolali Basiri

Abstract:

In this paper we present an efficient method for inverting an ideal in the ideal class group of a Cab curve by extending the method which is presented in [3]. More precisely we introduce a useful generator for the inverse ideal as a K[X]-module.

Keywords: Cab Curves, Ideal Class Group

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

Abstract:

Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: Stacking, multi-layers, ensemble, multi-class.

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Authors: Youssef Khmou, Said Safi, Miloud Frikel

Abstract:

This paper treats different aspects of entropy measure in classical information theory and statistical quantum mechanics, it presents the possibility of extending the definition of Von Neumann entropy to image and array processing. In the first part, we generalize the quantum entropy using singular values of arbitrary rectangular matrices to measure the randomness and the quality of denoising operation, this new definition of entropy can be implemented to compare the performance analysis of filtering methods. In the second part, we apply the concept of pure state in quantum formalism to generalize the maximum entropy method for narrowband and farfield source localization problem. Several computer simulation results are illustrated to demonstrate the effectiveness of the proposed techniques.

Keywords: Von Neumann entropy, Filtering, array, DoA, Maximum Entropy Method.

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Authors: Yongxin Yuan, Hao Liu

Abstract:

In this paper, we first give the representation of the general solution of the following least-squares problem (LSP): Given matrices X ∈ Rn×p, B ∈ Rp×p and A0 ∈ Rr×r, find a matrix A ∈ Rn×n such that XT AX − B = min, s. t. A([1, r]) = A0, where A([1, r]) is the r×r leading principal submatrix of the matrix A. We then consider a best approximation problem: given an n × n matrix A˜ with A˜([1, r]) = A0, find Aˆ ∈ SE such that A˜ − Aˆ = minA∈SE A˜ − A, where SE is the solution set of LSP. We show that the best approximation solution Aˆ is unique and derive an explicit formula for it. Keyw

Keywords: Inverse problem, Least-squares solution, model updating, Singular value decomposition (SVD), Optimal approximation.

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Authors: M. De la Sen, O. Barambones

Abstract:

This paper presents an indirect adaptive stabilization scheme for first-order continuous-time systems under saturated input which is described by a sigmoidal function. The singularities are avoided through a modification scheme for the estimated plant parameter vector so that its associated Sylvester matrix is guaranteed to be non-singular and then the estimated plant model is controllable. The modification mechanism involves the use of a hysteresis switching function. An alternative hybrid scheme, whose estimated parameters are updated at sampling instants is also given to solve a similar adaptive stabilization problem. Such a scheme also uses hysteresis switching for modification of the parameter estimates so as to ensure the controllability of the estimated plant model.

Keywords: Hybrid dynamic systems, discrete systems, saturated input, control, stabilization.

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Authors: Naoki Yamamoto, Jun Murakami, Chiharu Okuma, Yutaro Shigeto, Satoko Saito, Takashi Izumi, Nozomi Hayashida

Abstract:

Multi-dimensional principal component analysis (PCA) is the extension of the PCA, which is used widely as the dimensionality reduction technique in multivariate data analysis, to handle multi-dimensional data. To calculate the PCA the singular value decomposition (SVD) is commonly employed by the reason of its numerical stability. The multi-dimensional PCA can be calculated by using the higher-order SVD (HOSVD), which is proposed by Lathauwer et al., similarly with the case of ordinary PCA. In this paper, we apply the multi-dimensional PCA to the multi-dimensional medical data including the functional independence measure (FIM) score, and describe the results of experimental analysis.

Keywords: multi-dimensional principal component analysis, higher-order SVD (HOSVD), functional independence measure (FIM), medical data, tensor decomposition

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Authors: H. Nouri, A. Tabbel, N. Douib, H. Aitsaid, Y. Zebboudj

Abstract:

This study and the field test comparisons were carried out on the Algerian Derguna – Setif transmission systems. The transmission line of normal voltage 225 kV is 65 km long, transported and uses twin bundle conductors protected with two shield wires of transposed galvanized steel. An iterative finite-element method is used to solve Poisons equation. Two algorithms are proposed for satisfying the current continuity condition and updating the space-charge density. A new approach to the problem of corona discharge in transmission system has been described in this paper. The effect of varying the configurations and wires number is also investigated. The analysis of this steady is important in the design of HVDC transmission lines. The potential and electric field have been calculating in locations singular points of the system.

Keywords: Corona discharge, Electric field, Finite element method, HVDC.

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Authors: M. C. Cardoso, L. P. Moreira

Abstract:

In this work, the plastic behaviour of cold-rolled zinc coated dual-phase steel sheets DP600 and DP800 grades is firstly investigated with the help of uniaxial, hydraulic bulge and Forming Limit Curve (FLC) tests. The uniaxial tensile tests were performed in three angular orientations with respect to the rolling direction to evaluate the strain-hardening and plastic anisotropy. True stressstrain curves at large strains were determined from hydraulic bulge testing and fitted to a work-hardening equation. The limit strains are defined at both localized necking and fracture conditions according to Nakajima’s hemispherical punch procedure. Also, an elasto-plastic localization model is proposed in order to predict strain and stress based forming limit curves. The investigated dual-phase sheets showed a good formability in the biaxial stretching and drawing FLC regions. For both DP600 and DP800 sheets, the corresponding numerical predictions overestimated and underestimated the experimental limit strains in the biaxial stretching and drawing FLC regions, respectively. This can be attributed to the restricted failure necking condition adopted in the numerical model, which is not suitable to describe the tensile and shear fracture mechanisms in advanced high strength steels under equibiaxial and biaxial stretching conditions.

Keywords: Advanced high strength steels, forming limit curve, numerical modeling, sheet metal forming.

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Authors: F. Sarabchi, M. E. Kalantari

Abstract:

In this paper, Optimum adaptive loading algorithms are applied to multicarrier system with Space-Time Block Coding (STBC) scheme associated with space-time processing based on singular-value decomposition (SVD) of the channel matrix over Rayleigh fading channels. SVD method has been employed in MIMO-OFDM system in order to overcome subchannel interference. Chaw-s and Compello-s algorithms have been implemented to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The adaptive loaded SVD-STBC scheme is capable of providing both full-rate and full-diversity for any number of transmit antennas. The effectiveness of these techniques has demonstrated through the simulation of an Adaptive loaded SVDSTBC system, and the comparison shown that the proposed algorithms ensure better performance in the case of MIMO.

Keywords: OFDM, MIMO, SVD, STBC, Adaptive Loading.

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

Abstract:

Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and timeconsuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: Soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil.

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Authors: E. G. Bautista, J. M. Reyes, O. Bautista, J. C. Arcos

Abstract:

In this work, we analyze the deformation of surface waves in shallow flows conditions, propagating in a channel of slowly varying cross-section. Based on a singular perturbation technique, the main purpose is to predict the motion of waves by using a dimensionless formulation of the governing equations, considering that the longitudinal variation of the transversal section obey a power-law distribution. We show that the spatial distribution of the waves in the varying cross-section is a function of a kinematic parameter,κ , and two geometrical parameters εh and w ε . The above spatial behavior of the surface elevation is modeled by an ordinary differential equation. The use of single formulas to model the varying cross sections or transitions considered in this work can be a useful approximation to natural or artificial geometrical configurations.

Keywords: Surface waves, Asymptotic solution, Power law function, Non-dispersive waves.

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Authors: Richard W. Longman

Abstract:

Iterative learning control aims to achieve zero tracking error of a specific command. This is accomplished by iteratively adjusting the command given to a feedback control system, based on the tracking error observed in the previous iteration. One would like the iterations to converge to zero tracking error in spite of any error present in the model used to design the learning law. First, this need for stability robustness is discussed, and then the need for robustness of the property that the transients are well behaved. Methods of producing the needed robustness to parameter variations and to singular perturbations are presented. Then a method involving reverse time runs is given that lets the world behavior produce the ILC gains in such a way as to eliminate the need for a mathematical model. Since the real world is producing the gains, there is no issue of model error. Provided the world behaves linearly, the approach gives an ILC law with both stability robustness and good transient robustness, without the need to generate a model.

Keywords: Iterative learning control, stability robustness, monotonic convergence.

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Authors: Ahmet Tekcan

Abstract:

Let p be a prime number, Fp be a finite field, and let k ∈ F*p. In this paper, we consider the number of rational points onconics Cp,k: x2 − ky2 = 1 over Fp. We proved that the order of Cp,k over Fp is p-1 if k is a quadratic residue mod p and is p + 1 if k is not a quadratic residue mod p. Later we derive some resultsconcerning the sums ΣC[x]p,k(Fp) and ΣC[y]p,k(Fp), the sum of x- and y-coordinates of all points (x, y) on Cp,k, respectively.

Keywords: Elliptic curve, conic, rational points.

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Authors: Tetsuki Taniguchi, Yoshio Karasawa

Abstract:

This paper describes a subarray based low computational design method of multiuser massive multiple input multiple output (MIMO) system. In our previous works, use of large array is assumed only in transmitter, but this study considers the case both of transmitter and receiver sides are equipped with large array antennas. For this aim, receive arrays are also divided into several subarrays, and the former proposed method is modified for the synthesis of a large array from subarrays in both ends. Through computer simulations, it is verified that the performance of the proposed method is degraded compared with the original approach, but it can achieve the improvement in the aspect of complexity, namely, significant reduction of the computational load to the practical level.

Keywords: Massive multiple input multiple output (MIMO), multiuser, large array, subarray, zero forcing, singular value decomposition.

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Authors: R. Leelaruji, V. Knazkins

Abstract:

This paper proposes a methodology for mitigating the occurrence of cascading failure in stressed power systems. The methodology is essentially based on predicting voltage instability in the power system using a voltage stability index and then devising a corrective action in order to increase the voltage stability margin. The paper starts with a brief description of the cascading failure mechanism which is probable root cause of severe blackouts. Then, the voltage instability indices are introduced in order to evaluate stability limit. The aim of the analysis is to assure that the coordination of protection, by adopting load shedding scheme, capable of enhancing performance of the system after the major location of instability is determined. Finally, the proposed method to generate instability prediction is introduced.

Keywords: Blackouts, cascading failure, voltage stability indices, singular value decomposition, load shedding.

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Authors: Sudipta Majumdar

Abstract:

This paper presents a method for identification of a linear time invariant (LTI) autonomous all pole system using singular value decomposition. The novelty of this paper is two fold: First, MUSIC algorithm for estimating complex frequencies from real measurements is proposed. Secondly, using the proposed algorithm, we can identify the coefficients of differential equation that determines the LTI system by switching off our input signal. For this purpose, we need only to switch off the input, apply our complex MUSIC algorithm and determine the coefficients as symmetric polynomials in the complex frequencies. This method can be applied to unstable system and has higher resolution as compared to time series solution when, noisy data are used. The classical performance bound, Cramer Rao bound (CRB), has been used as a basis for performance comparison of the proposed method for multiple poles estimation in noisy exponential signal.

Keywords: MUSIC algorithm, Cramer Rao bound, frequency estimation.

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Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

Due to the increasing penetration of wind energy, it is necessary to possess design tools that are able to simulate the impact of these installations in utility grids. In order to provide a net contribution to this issue a detailed wind park model has been developed and is briefly presented. However, the computational costs associated with the performance of such a detailed model in describing the behavior of a wind park composed by a considerable number of units may render its practical application very difficult. To overcome this problem integral manifolds theory has been applied to reduce the order of the detailed wind park model, and therefore create the conditions for the development of a dynamic equivalent which is able to retain the relevant dynamics with respect to the existing a.c. system. In this paper integral manifold method has been introduced for order reduction. Simulation results of the proposed method represents that integral manifold method results fit the detailed model results with a higher precision than singular perturbation method.

Keywords: Wind, Reduced Order, Integral Manifold.

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Authors: Anh Duc Dang, Joachim Horn

Abstract:

This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these free-robots dose not influence the general motion of their swarm and nor other robots. When one singular robot approaches the swarm then its swarm-search will finish, and it will further participate with its swarm to reach the position of the target. The connections between member-robots with their neighbors are controlled by the artificial attractive/repulsive force field between them to avoid collisions and keep the constant distances between them in ordered formation. The effectiveness of the proposed approach has been verified in simulations.

Keywords: Formation control, potential field method, obstacle avoidance, swarm intelligence, multi-agent systems.

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Authors: Seong-Bae Park, Hee-Geun Yoon

Abstract:

It is an important task in Korean-English machine translation to classify the gender of names correctly. When a sentence is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus, in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method yields the improvement in accuracy over the simple looking-up of the collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed method is more plausible for the gender classification of the Korean names.

Keywords: machine translation, natural language processing, gender of proper nouns, statistical method

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

Abstract:

This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Wudhichai Assawinchaichote, Sing Kiong Nguang

Abstract:

This paper examines the problem of designing a robust H∞ filter for a class of uncertain fuzzy descriptor systems described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain nonlinear descriptor systems to have an H∞ performance are derived. To alleviate the ill-conditioning resulting from the interaction of slow and fast dynamic modes, solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation ε, when ε is sufficiently small. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard uncertain nonlinear descriptor systems. A numerical example is provided to illustrate the design developed in this paper.

Keywords: H∞ control, Takagi-Sugeno (TS) fuzzy model, Linear Matrix Inequalities (LMIs), Descriptor systems.

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