Abstract- Many methods have been applied in order to reduce nitrate concentration in aqueous solutions, among them

is the adsorption onto the surface of agricultural wastes. In this study, batch experiments were carried out to investigate

the adsorption of nitrate onto olive pomace (OP), a solid by-product of olive oil industry. To achieve this, six parameters

were studied by varying only one parameter at a time. These parameters were the effect of: pH, contact time,

temperature, adsorbent weight, agitation speed and nitrate concentration. The optimum pH was found to be 5, while the

optimum time was 75 minutes. Nitrate removal percentage was found to increase with increasing adsorbent weight or

temperature, with 92.5% of nitrate removed by using 2 g of OP and 48% of nitrate was removed at 60ºC. Generally,

agitation speed increased the nitrate removal percentage, while high initial concentration of nitrate was found to decrease

its removal percentage. These findings, combined with the low cost of OP and its abundance, suggest that OP is a

potential adsorbent for nitrate removal provided that the optimum conditions are applied. Applying this method for

nitrate removal will make drinking water safer to drink and wastewater safer to discharge.

The measurement errors problem is endemic in many econometric studies, and one of the oldest known statistical problems. Instrumental variable (IV) method is one of the popular solutions adopted to deal with the mismeasured variables in statistical and econometric analyses. This paper proposes an efficient IV estimator to the parameters of the simple regression model where both variables are subject to measurement errors. The proposed IV is defined using simple mathematical transformation of the manifest independent variable (mismeasured variable). The proposed method is straightforward, and easy to implement. The theoretical superiority of the proposed estimator over the existing IV based estimators due to Wald (1940), Bartlett (1949), and Durbin (1954) is established by analytical comparison and geometric expositions. Simulation based numerical comparisons of the proposed estimator with four different existing estimators are also included.

The object of the present paper is to introduce a new subclass of p-valent starlike functions with negative coefficients in the open unit disc which is defiined by a generalized derivative operator. We obtain coefficient inequalities, growth and distortion theorems and extreme points for the subclass of p-valent functions.

Recent developments in both information and communication security have heightened interest in enhancing the embedding capacity for data handling techniques. Although many steganographic techniques, in the literature, have been developed for this purpose, most of them distort the quality of the host-signal during data embedding and the changes will be become visible to the human eye especially for those signals distributed via the Internet which must be processed by a low bit rate compression due to bandwidth limitations. Therefore, the challenge is to create a steganographic technique that is able to hide acceptable amount of data without altering the quality of the host-signal. In this paper, pixel-value differencing (PVD) steganographic scheme and its two modified versions, namely, enhanced pixel-value differencing (EPVD) and tri-way pixel-value differencing (TPVD) were implemented, analyzed and compared in terms of invisibility, fidelity and impact of data hiding on the compression efficiency. Experimental results indicate that the EPVD scheme is capable of providing better performance than other compared schemes.

Abstract Mel Frequency Cepstral Coefficients (MFCCs) are the most widely used features in the majority of the speaker and speech recognition applications. Since 1980s, remarkable efforts have been undertaken for the development of these features. Issues such as use suitable spectral estimation methods, design of effective filter banks, and the number of chosen features all play an important role in the performance and robustness of the speech recognition systems. This paper provides an overview of MFCC's enhancement techniques that are applied in speech recognition systems. The details such as accuracy, types of environments, the nature of data, and the number of features are investigated and summarized in the table combined with the corresponding key references. Benefits and drawbacks of these MFCC's enhancement techniques have been discussed. This study will hopefully contribute to raising …

Abstract— Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient’s survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the ‘Hospital Pedro Hispano’ [1] and the results of cross-validation have shown high detection accuracy.

The aim of this paper is to introduce and study a new class of Bazilevič p-valent function of order β by using the subordination concept between this function and a generalized derivative operator. Some interesting properties are also obtained

The theory of analytic functions and more specific p-valent functions, is one of the most fascinating topics in one complex variable. There are many remarkable theorems dealing with extremal problems for a class of p-valent functions on the unit disk U. Recently, many researchers have shown great interests in the study of differential operator. The objective of this paper is to define a new generalized derivative operator of p-valent analytic functions of fractional power in the open unit disk U. This operator generalized some well-known operators studied earlier, we mention some of them in the present paper. Motivation by the generalized derivative operator; we introduce and investigate two new subclasses of starlike p-valent analytic functions of fractional power with positive coefficients and starlike p-valent analytic functions of fractional power with negative coefficients, respectively. In addition, a sufficient condition will be obtained. Some corollaries are also pointed out. Moreover, we determine the extreme points of functions belong to the class.

Seed size is a key functional trait that affects plant fitness at the seedling stage and may

vary greatly with species fruit size, growth form and fecundity. Using structural equation

modelling (SEM) and correlated trait evolution analysis, we investigated the interaction network

between seed size and fecundity, postfire regeneration strategy, fruit size, plant height

and serotiny (on-plant seed storage) among 82 species of the woody shrub genus, Hakea,

with a wide spectrum of seed sizes (2–500 mg). Seed size is negatively correlated with fecundity,

while fire-killed species (nonsprouters) produce more seeds than resprouters

though they are of similar size. Seed size is unrelated to plant height and level of serotiny

while it scales allometrically with fruit size. A strong phylogenetic signal in seed size revealed

phylogenetic constraints on seed size variation in Hakea. Our analyses suggest a

causal relationship between seed size, fecundity and postfire regeneration strategy in

Hakea. These results demonstrate that fruit size, fecundity and evolutionary history have

had most control over seed size variation among Hakea species.

The aim of the article is to study a sufficient condition for the classes of starlike and convex harmonic univalent functions with respect to k- symmetric points. The necessary condition for f to be in the classes will be studied. In addition, growth bounds for functions will also be given.