**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**6346

# Search results for: BER

##### 46 Iterative Joint Power Control and Partial Crosstalk Cancellation in Upstream VDSL

**Authors:**
H. Bagheri,
H. Emami,
M. R. Pakravan

**Abstract:**

Crosstalk is the major limiting issue in very high bit-rate digital subscriber line (VDSL) systems in terms of bit-rate or service coverage. At the central office side, joint signal processing accompanied by appropriate power allocation enables complex multiuser processors to provide near capacity rates. Unfortunately complexity grows with the square of the number of lines within a binder, so by taking into account that there are only a few dominant crosstalkers who contribute to main part of crosstalk power, the canceller structure can be simplified which resulted in a much lower run-time complexity. In this paper, a multiuser power control scheme, namely iterative waterfilling, is combined with previously proposed partial crosstalk cancellation approaches to demonstrate the best ever achieved performance which is verified by simulation results.

**Keywords:**
iterative waterfilling,
partial crosstalk cancellation,
run-time complexity,
VDSL.

##### 45 Performance Enhancement of Cellular OFDM Based Wireless LANs by Exploiting Spatial Diversity Techniques

**Authors:**
S. Ali. Tajer,
Babak H. Khalaj

**Abstract:**

This paper represents an investigation on how exploiting multiple transmit antennas by OFDM based wireless LAN subscribers can mitigate physical layer error rate. Then by comparing the Wireless LANs that utilize spatial diversity techniques with the conventional ones it will reveal how PHY and TCP throughputs behaviors are ameliorated. In the next step it will assess the same issues based on a cellular context operation which is mainly introduced as an innovated solution that beside a multi cell operation scenario benefits spatio-temporal signaling schemes as well. Presented simulations will shed light on the improved performance of the wide range and high quality wireless LAN services provided by the proposed approach.

**Keywords:**
Multiple Input Multiple Output (MIMO),
Orthogonal Frequency Division Multiplexing (OFDM),
and WirelessLocal Area Network (WLAN).

##### 44 Grey Prediction Based Handoff Algorithm

**Authors:**
Seyed Saeed Changiz Rezaei,
Babak Hossein Khalaj

**Abstract:**

As the demand for higher capacity in a cellular environment increases, the cell size decreases. This fact makes the role of suitable handoff algorithms to reduce both number of handoffs and handoff delay more important. In this paper we show that applying the grey prediction technique for handoff leads to considerable decrease in handoff delay with using a small number of handoffs, compared with traditional hystersis based handoff algorithms.

**Keywords:**
Cellular network,
Grey prediction,
Handoff.

##### 43 Generalized Morphological 3D Shape Decomposition Grayscale Interframe Interpolation Method

**Authors:**
Dragos Nicolae VIZIREANU

**Abstract:**

One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.

**Keywords:**
3D shape decomposition representation,
mathematical morphology,
gray scale interframe interpolation

##### 42 A New Current-mode Multifunction Filter with High Impedance Outputs Using Minimum Number of Passive Elements

**Authors:**
Mehmet Sagbas,
Kemal Fidanboylu,
Mehmet C. Bayram

**Abstract:**

A new current-mode multifunction filter using minimum number of passive elements is proposed. The proposed filter has single-input and four high-impedance outputs. It uses four passive elements (two capacitors and two resistors) and four dual output second generation current conveyors. Each output provides a different filter response, namely, low-pass, high-pass, band-pass and band-reject. The sensitivity analysis is also carried out on both ideal and non-ideal filter configurations. The validity of the proposed filter is verified through PSPICE simulations.

**Keywords:**
Active filter,
Universal filter,
Currentconveyors.

##### 41 Acoustic Detection of the Red Date Palm Weevil

**Authors:**
Mohammed A. Al-Manie,
Mohammed I. Alkanhal

**Abstract:**

In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.

**Keywords:**
Acoustic emissions,
acoustic sensors,
nondestructivetests,
Red Date Palm Weevil,
signal processing..

##### 40 A New Approach to Signal Processing for DC-Electromagnetic Flowmeters

**Authors:**
Michael Schukat

**Abstract:**

Electromagnetic flowmeters with DC excitation are used for a wide range of fluid measurement tasks, but are rarely found in dosing applications with short measurement cycles due to the achievable accuracy. This paper will identify a number of factors that influence the accuracy of this sensor type when used for short-term measurements. Based on these results a new signal-processing algorithm will be described that overcomes the identified problems to some extend. This new method allows principally a higher accuracy of electromagnetic flowmeters with DC excitation than traditional methods.

**Keywords:**
Electromagnetic Flowmeter,
Kalman Filter,
ShortMeasurement Cycles,
Signal Estimation

##### 39 Multiple Regression based Graphical Modeling for Images

**Authors:**
Pavan S.,
Sridhar G.,
Sridhar V.

**Abstract:**

Super resolution is one of the commonly referred inference problems in computer vision. In the case of images, this problem is generally addressed using a graphical model framework wherein each node represents a portion of the image and the edges between the nodes represent the statistical dependencies. However, the large dimensionality of images along with the large number of possible states for a node makes the inference problem computationally intractable. In this paper, we propose a representation wherein each node can be represented as acombination of multiple regression functions. The proposed approach achieves a tradeoff between the computational complexity and inference accuracy by varying the number of regression functions for a node.

**Keywords:**
Belief propagation,
Graphical model,
Regression,
Super resolution.

##### 38 An Implementation of Data Reusable MPEG Video Coding Scheme

**Authors:**
Vasily G. Moshnyaga

**Abstract:**

This paper presents an optimized MPEG2 video codec implementation, which drastically reduces the number of computations and memory accesses required for video compression. Unlike traditional scheme, we reuse data stored in frame memory to omit unnecessary coding operations and memory read/writes for unchanged macroblocks. Due to dynamic memory sharing among reference frames, data-driven macroblock characterization and selective macroblock processing, we perform less than 15% of the total operations required by a conventional coder while maintaining high picture quality.

**Keywords:**
Data reuse,
adaptive processing,
video coding,
MPEG

##### 37 Extracting Tongue Shape Dynamics from Magnetic Resonance Image Sequences

**Authors:**
María S. Avila-García,
John N. Carter,
Robert I. Damper

**Abstract:**

An important problem in speech research is the automatic extraction of information about the shape and dimensions of the vocal tract during real-time speech production. We have previously developed Southampton dynamic magnetic resonance imaging (SDMRI) as an approach to the solution of this problem.However, the SDMRI images are very noisy so that shape extraction is a major challenge. In this paper, we address the problem of tongue shape extraction, which poses difficulties because this is a highly deforming non-parametric shape. We show that combining active shape models with the dynamic Hough transform allows the tongue shape to be reliably tracked in the image sequence.

**Keywords:**
Vocal tract imaging,
speech production,
active shapemodels,
dynamic Hough transform,
object tracking.

##### 36 Quantitative Analysis of Weld Defect Images in Industrial Radiography Based Invariant Attributes

**Authors:**
N. Nacereddine,
M. Tridi,
S. S. Belaïfa,
M. Zelmat

**Abstract:**

For the characterization of the weld defect region in the radiographic image, looking for features which are invariant regarding the geometrical transformations (rotation, translation and scaling) proves to be necessary because the same defect can be seen from several angles according to the orientation and the distance from the welded framework to the radiation source. Thus, panoply of geometrical attributes satisfying the above conditions is proposed and which result from the calculation of the geometrical parameters (surface, perimeter, etc.) on the one hand and the calculation of the different order moments, on the other hand. Because the large range in values of the raw features and taking into account other considerations imposed by some classifiers, the scaling of these values to lie between 0 and 1 is indispensable. The principal component analysis technique is used in order to reduce the number of the attribute variables in the aim to give better performance to the further defect classification.

**Keywords:**
Geometric parameters,
invariant attributes,
principal component analysis,
weld defect image.

##### 35 Microarrays Denoising via Smoothing of Coefficients in Wavelet Domain

**Authors:**
Mario Mastriani,
Alberto E. Giraldez

**Abstract:**

We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on a smoothing of the coefficients of the highest subbands. Specifically, we decompose the noisy microarray into wavelet subbands, apply smoothing within each highest subband, and reconstruct a microarray from the modified wavelet coefficients. This process is applied a single time, and exclusively to the first level of decomposition, i.e., in most of the cases, it is not necessary a multirresoltuion analysis. Denoising results compare favorably to the most of methods in use at the moment.

**Keywords:**
Directional smoothing,
denoising,
edge preservation,
microarrays,
thresholding,
wavelets

##### 34 Bridging the Mental Gap between Convolution Approach and Compartmental Modeling in Functional Imaging: Typical Embedding of an Open Two-Compartment Model into the Systems Theory Approach of Indicator Dilution Theory

**Authors:**
Gesine Hellwig

**Abstract:**

Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

**Keywords:**
Functional imaging,
Tracer kinetic modeling,
LTIsystem,
Indicator dilution theory / convolution approach,
Two-Compartment model.

##### 33 Statistics over Lyapunov Exponents for Feature Extraction: Electroencephalographic Changes Detection Case

**Authors:**
Elif Derya UBEYLI,
Inan GULER

**Abstract:**

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

**Keywords:**
Chaotic signal,
Electroencephalogram (EEG) signals,
Feature extraction/selection,
Lyapunov exponents

##### 32 Towards Automatic Recognition and Grading of Ganoderma Infection Pattern Using Fuzzy Systems

**Authors:**
Mazliham Mohd Su'ud,
Pierre Loonis,
Idris Abu Seman

**Abstract:**

This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

**Keywords:**
Fuzzy Inference Systems,
Tomography analysis,
Modelizationof expert's information,
Ganoderma Infection pattern recognition

##### 31 Analysis of Investment in Knowledge inside OECD Countries

**Authors:**
JunSeok Hwang,
Mohsen Gerami

**Abstract:**

**Keywords:**
Knowledge,
GDP,
Multifactor productivity,
Investment,
efficiency.

##### 30 String Matching using Inverted Lists

**Authors:**
Chouvalit Khancome,
Veera Boonjing

**Abstract:**

This paper proposes a new solution to string matching problem. This solution constructs an inverted list representing a string pattern to be searched for. It then uses a new algorithm to process an input string in a single pass. The preprocessing phase takes 1) time complexity O(m) 2) space complexity O(1) where m is the length of pattern. The searching phase time complexity takes 1) O(m+α ) in average case 2) O(n/m) in the best case and 3) O(n) in the worst case, where α is the number of comparing leading to mismatch and n is the length of input text.

**Keywords:**
String matching,
inverted list,
inverted index,
pattern,
algorithm.

##### 29 Mapping of C* Elements in Finite Element Method using Transformation Matrix

**Authors:**
G. H. Majzoob,
B. Sharifi Hamadani

**Abstract:**

**Keywords:**
Mapping,
Finite element method,
C* elements,
Convergence,
C0 elements.

##### 28 A Comparison between Heuristic and Meta-Heuristic Methods for Solving the Multiple Traveling Salesman Problem

**Authors:**
San Nah Sze,
Wei King Tiong

**Abstract:**

**Keywords:**
Multiple Traveling Salesman Problem,
GeneticAlgorithm,
Nearest Neighbor Algorithm,
k-Means Clustering.

##### 27 Mathematical Modeling of SISO based Timoshenko Structures – A Case Study

**Authors:**
T.C. Manjunath,
Student Member,
B. Bandyopadhyay

**Abstract:**

This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.

**Keywords:**
Smart structure,
Timoshenko beam theory,
Discretesliding mode control,
Bartoszewicz law,
Finite Element Method,
State space model,
Vibration control,
Mathematical model,
SISO.

##### 26 On Some Properties of Interval Matrices

**Authors:**
K. Ganesan

**Abstract:**

**Keywords:**
Interval arithmetic,
Interval matrix,
linear equations.

##### 25 On Submaximality in Intuitionistic Topological Spaces

**Authors:**
Ahmet Z. Ozcelik,
Serkan Narli

**Abstract:**

**Keywords:**
Intuitionistic set; intuitionistic topology;intuitionistic submaximality and mega-connectedness.

##### 24 The Number of Rational Points on Conics Cp,k : x2 − ky2 = 1 over Finite Fields Fp

**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.

##### 23 The Elliptic Curves y2 = x3 - t2x over Fp

**Authors:**
Ahmet Tekcan

**Abstract:**

Let p be a prime number, Fp be a finite field and t ∈ F*p= Fp- {0}. In this paper we obtain some properties of ellipticcurves Ep,t: y2= y2= x3- t2x over Fp. In the first sectionwe give some notations and preliminaries from elliptic curves. In the second section we consider the rational points (x, y) on Ep,t. Wegive a formula for the number of rational points on Ep,t over Fnp for an integer n ≥ 1. We also give some formulas for the sum of x?andy?coordinates of the points (x, y) on Ep,t. In the third section weconsider the rank of Et: y2= x3- t2x and its 2-isogenous curve Et over Q. We proved that the rank of Etand Etis 2 over Q. In the last section we obtain some formulas for the sums Σt∈F?panp,t for an integer n ≥ 1, where ap,t denote the trace of Frobenius.

**Keywords:**
Elliptic curves over finite fields,
rational points onelliptic curves,
rank,
trace of Frobenius.

##### 22 The Number of Rational Points on Elliptic Curves y2 = x3 + b2 Over Finite Fields

**Authors:**
Betül Gezer,
Hacer Özden,
Ahmet Tekcan,
Osman Bizim

**Abstract:**

Let p be a prime number, Fpbe a finite field and let Qpdenote the set of quadratic residues in Fp. In the first section we givesome notations and preliminaries from elliptic curves. In the secondsection, we consider some properties of rational points on ellipticcurves Ep,b: y2= x3+ b2 over Fp, where b ∈ F*p. Recall that theorder of Ep,bover Fpis p + 1 if p ≡ 5(mod 6). We generalize thisresult to any field Fnp for an integer n≥ 2. Further we obtain someresults concerning the sum Σ[x]Ep,b(Fp) and Σ[y]Ep,b(Fp), thesum of x- and y- coordinates of all points (x, y) on Ep,b, and alsothe the sum Σ(x,0)Ep,b(Fp), the sum of points (x, 0) on Ep,b.

**Keywords:**
Elliptic curves over finite fields,
rational points on elliptic curves.

##### 21 Optimization of a Triangular Fin with Variable Fin Base Thickness

**Authors:**
Hyung Suk Kang

**Abstract:**

**Keywords:**
A triangular fin,
Convection characteristic number,
Heat loss,
Fin base thickness.

##### 20 Rational Points on Elliptic Curves 2 3 3y = x + a inF , where p 5(mod 6) is Prime

**Authors:**
Gokhan Soydan,
Musa Demirci,
Nazli Yildiz Ikikardes,
Ismail Naci Cangul

**Abstract:**

In this work, we consider the rational points on elliptic curves over finite fields Fp where p ≡ 5 (mod 6). We obtain results on the number of points on an elliptic curve y2 ≡ x3 + a3(mod p), where p ≡ 5 (mod 6) is prime. We give some results concerning the sum of the abscissae of these points. A similar case where p ≡ 1 (mod 6) is considered in [5]. The main difference between two cases is that when p ≡ 5 (mod 6), all elements of Fp are cubic residues.

**Keywords:**
Elliptic curves over finite fields,
rational points.

##### 19 A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks

**Authors:**
Syed Muhammad Aqil Burney,
Tahseen Ahmed Jilani,
C. Ardil

**Abstract:**

**Keywords:**
Backpropagation algorithm,
conjugacy condition,
line search,
matrix perturbation

##### 18 Learning of Class Membership Values by Ellipsoidal Decision Regions

**Authors:**
Leehter Yao,
Chin-Chin Lin

**Abstract:**

A novel method of learning complex fuzzy decision regions in the n-dimensional feature space is proposed. Through the fuzzy decision regions, a given pattern's class membership value of every class is determined instead of the conventional crisp class the pattern belongs to. The n-dimensional fuzzy decision region is approximated by union of hyperellipsoids. By explicitly parameterizing these hyperellipsoids, the decision regions are determined by estimating the parameters of each hyperellipsoid.Genetic Algorithm is applied to estimate the parameters of each region component. With the global optimization ability of GA, the learned decision region can be arbitrarily complex.

**Keywords:**
Ellipsoid,
genetic algorithm,
decision regions,
classification.

##### 17 Computing Entropy for Ortholog Detection

**Authors:**
Hsing-Kuo Pao,
John Case

**Abstract:**

Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.

**Keywords:**
compression,
decision tree,
entropy,
ortholog,
ROC.