A Blind SLM Scheme for Reduction of PAPR in OFDM Systems

In this paper we propose a blind algorithm for peakto- average power ratio (PAPR) reduction in OFDM systems, based on selected mapping (SLM) algorithm as a distortionless method. The main drawback of the conventional SLM technique is the need for transmission of several side information bits, for each data block, which results in loss in data rate transmission. In the proposed method some special number of carriers in the OFDM frame is reserved to be rotated with one of the possible phases according to the number of phase sequence blocks in SLM algorithm. Reserving some limited number of carriers wont effect the reduction in PAPR of OFDM signal. Simulation results show using ML criteria at the receiver will lead to the same system-performance as the conventional SLM algorithm, while there is no need to send any side information to the receiver.

Iris Localization using Circle and Fuzzy Circle Detection Method

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we consider Daugman iris localization method as a standard method, propose a new method in this field and then analyze and compare the results of them on a standard set of iris images. The proposed method is based on the detection of circular edge of iris, and improved by fuzzy circles and surface energy difference contexts. Implementation of this method is so easy and compared to the other methods, have a rather high accuracy and speed. Test results show that the accuracy of our proposed method is about Daugman method and computation speed of it is 10 times faster.

Comparing Autoregressive Moving Average (ARMA) Coefficients Determination using Artificial Neural Networks with Other Techniques

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

Utilization of EAF Reducing Slag from Stainless Steelmaking Process as a Sorbent for CO2

In this study, an experimental investigation was carried out to fix CO2 into the electronic arc furnace (EAF) reducing slag from stainless steelmaking process under wet grinding. The slag was ground by the vibrating ball mill with the CO2 and pure water. The reaction behavior was monitored with constant pressure method, and the change of CO2 volume in the experimental system with grinding time was measured. It was found that the CO2 absorption occurred as soon as the grinding started. The CO2 absorption under wet grinding was significantly larger than that under dry grinding. Generally, the amount of CO2 absorption increased as the amount of water, the amount of slag, the diameter of alumina ball and the initial pressure of CO2 increased. However, the initial absorption rate was scarcely influenced by the experimental conditions except for the initial CO2 pressure. According to this research, the CO2 reacted with the CaO inside the slag to form CaCO3.

Silicone on Blending Vegetal Petrochemical Based Polyurethane

Polyurethane foam (PUF) is formed by a chemical reaction of polyol and isocyanate. The aim is to understand the impact of Silicone on synthesizing polyurethane in differentiate volume of molding. The method used was one step process, which is simultaneously caried out a blending polyol (petroleum polyol and soybean polyol), a TDI (2,4):MDI (4,4-) (80:20), a distilled water, and a silicone. The properties of the material were measured via a number of parameters, which are polymer density, compressive strength, and cellular structures. It is found that density of polyurethane using silicone with volume of molding either 250 ml or 500 ml is lower than without using silicone.

Globally Convergent Edge-preserving Reconstruction with Contour-line Smoothing

The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

Nano-Alumina Sulfuric Acid: An Efficient Catalyst for the Synthesis of α-Aminonitriles Derivatives

An efficient and green protocol for the synthesis of α- aminonitriles derivatives by one-pot reaction of different aldehydes with amines and trimethylsilyl cyanides has been developed using natural alumina, alumina sulfuric acid (ASA), nano-γ-alumina, nanoalumina sulfuric acid (nano-ASA) under microwave irradiation and solvent-free conditions. The advantages of methods are short reaction times, high yields, milder conditions and easy work up. The catalysts can be recovered for the subsequent reactions and reused without any appreciable loss of efficiency.

Effect of Band Contact on the Temperature Distribution for Dry Friction Clutch

In this study, the two dimensional heat conduction problem for the dry friction clutch disc is modeled mathematically analysis and is solved numerically using finite element method, to determine the temperature field when band contacts occurs between the rubbing surfaces during the operation of an automotive clutch. Temperature calculation have been made for contact area of different band width and the results obtained compared with these attained when complete contact occurs. Furthermore, the effects of slipping time and sliding velocity function are investigated as well. Both single and repeated engagements made at regular interval are considered.

A Fuzzy Mixed Integer Multi-Scenario Portfolio Optimization Model

In this paper, we propose a multiple objective optimization model with respect to portfolio selection problem for investors looking forward to diversify their equity investments in a number of equity markets. Based on Markowitz-s M-V model we developed a Fuzzy Mixed Integer Multi-Objective Nonlinear Programming Problem (FMIMONLP) to maximize the investors- future gains on equity markets, reach the optimal proportion of the budget to be invested in different equities. A numerical example with a comprehensive analysis on artificial data from several equity markets is presented in order to illustrate the proposed model and its solution method. The model performed well compared with the deterministic version of the model.

Induction of alpha-Amylase in Wheat Grain Cultivars as an Indicator of Resistance to Pre-harvest Sprouting

The influence of humidity and low temperature on the α- amylase activity and isoenzyme composition of grains of different wheat varieties have been studied. The identified samples of varieties have significant difference in the level of enzyme induction under the impact of high humidity and low temperature. It is proposed to use this methodological approach for testing genotypes and wheat breeding lines for resistance to pre-harvest sprouting (PHS).

Two Fourth-order Iterative Methods Based on Continued Fraction for Root-finding Problems

In this paper, we present two new one-step iterative methods based on Thiele-s continued fraction for solving nonlinear equations. By applying the truncated Thiele-s continued fraction twice, the iterative methods are obtained respectively. Analysis of convergence shows that the new methods are fourth-order convergent. Numerical tests verifying the theory are given and based on the methods, two new one-step iterations are developed.

Noise Reduction in Image Sequences using an Effective Fuzzy Algorithm

In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.

Validation on 3D Surface Roughness Algorithm for Measuring Roughness of Psoriasis Lesion

Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.

Identifying Dry Years by Using the Dependable Rainfall Index and Its Effects on the Olive Crop in Roudbar, Gilan, South Western of Caspian Sea

Drought is one of the most important natural disasters which is probable to occur in all regions with completely different climates and in addition to causing death. It results in many economic losses and social consequences. For this reason. Studying the effects and losses caused by drought which include limitation or shortage of agricultural and drinking water resources. Decreased rainfall and increased evapotranspiration. Limited plant growth and decreased agricultural products. Especially those of dry-farming. Lower levels of surface and ground waters and increased immigrations. Etc. in the country is statistical period (1988-2007) for six stations in Roudbar town were used for statistical analysis and calculating humid and dry years. The dependable rainfall index (DRI) was the main method used in this research. Results showed that during the said statistical period and also during the years 1996-1998 and 2007. more than half of the stations had faced drought. With consideration of the conducted studies. Drawing diagrams and comparing the available data with those of dry and humid years it was found that drought affected agricultural products (e.g.olive) in a way that during the year 1996 1996 drought. Olive groves of Roudbar suffered the greatest damages. Whereupon about 70% of the crops were lost.

FEA for Transient Responses of an S-Shaped Force Transducer with a Viscoelastic Absorber Using a Nonlinear Complex Spring

To compute dynamic characteristics of nonlinear viscoelastic springs with elastic structures having huge degree-of-freedom, Yamaguchi proposed a new fast numerical method using finite element method [1]-[2]. In this method, restoring forces of the springs are expressed using power series of their elongation. In the expression, nonlinear hysteresis damping is introduced. In this expression, nonlinear complex spring constants are introduced. Finite element for the nonlinear spring having complex coefficients is expressed and is connected to the elastic structures modeled by linear solid finite element. Further, to save computational time, the discrete equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. In this report, the proposed method is applied to simulation for impact responses of a viscoelastic shock absorber with an elastic structure (an S-shaped structure) by colliding with a concentrated mass. The concentrated mass has initial velocities and collides with the shock absorber. Accelerations of the elastic structure and the concentrated mass are measured using Levitation Mass Method proposed by Fujii [3]. The calculated accelerations from the proposed FEM, corresponds to the experimental ones. Moreover, using this method, we also investigate dynamic errors of the S-shaped force transducer due to elastic mode in the S-shaped structure.

Artificial Intelligence Techniques Applications for Power Disturbances Classification

Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.

Determination and Assessment of Ground Motion and Spectral Parameters for Iran

Many studies have been conducted for derivation of attenuation relationships worldwide, however few relationships have been developed to use for the seismic region of Iranian plateau and only few of these studies have been conducted for derivation of attenuation relationships for parameters such as uniform duration. Uniform duration is the total time during which the acceleration is larger than a given threshold value (default is 5% of PGA). In this study, the database was same as that used previously by Ghodrati Amiri et al. (2007) with same correction methods for earthquake records in Iran. However in this study, records from earthquakes with MS< 4.0 were excluded from this database, each record has individually filtered afterward, and therefore the dataset has been expanded. These new set of attenuation relationships for Iran are derived based on tectonic conditions with soil classification into rock and soil. Earthquake parameters were chosen to be hypocentral distance and magnitude in order to make it easier to use the relationships for seismic hazard analysis. Tehran is the capital city of Iran wit ha large number of important structures. In this study, a probabilistic approach has been utilized for seismic hazard assessment of this city. The resulting uniform duration against return period diagrams are suggested to be used in any projects in the area.

A Comparison of Inflow Generation Methods for Large-Eddy Simulation

A study of various turbulent inflow generation methods was performed to compare their relative effectiveness for LES computations of turbulent boundary layers. This study confirmed the quality of the turbulent information produced by the family of recycling and rescaling methods which take information from within the computational domain. Furthermore, more general inflow methods also proved applicable to such simulations, with a precursor-like inflow and a random inflow augmented with forcing planes showing promising results.

Dynamic Inverted Index Maintenance

The majority of today's IR systems base the IR task on two main processes: indexing and searching. There exists a special group of dynamic IR systems where both processes (indexing and searching) happen simultaneously; such a system discards obsolete information, simultaneously dealing with the insertion of new in¬formation, while still answering user queries. In these dynamic, time critical text document databases, it is often important to modify index structures quickly, as documents arrive. This paper presents a method for dynamization which may be used for this task. Experimental results show that the dynamization process is possible and that it guarantees the response time for the query operation and index actualization.

Calibration of Parallel Multi-View Cameras

This paper focuses on the calibration problem of a multi-view shooting system designed for the production of 3D content for auto-stereoscopic visualization. The considered multiview camera is characterized by coplanar and decentered image sensors regarding to the corresponding optical axis. Based on the Faugéras and Toscani-s calibration approach, a calibration method is herein proposed for the case of multi-view camera with parallel and decentered image sensors. At first, the geometrical model of the shooting system is recalled and some industrial prototypes with some shooting simulations are presented. Next, the development of the proposed calibration method is detailed. Finally, some simulation results are presented before ending with some conclusions about this work.