Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

This experiment was conducted to study the effect of injecting hatching eggs into a flock of broiler aged mothers with different concentrations of the alcoholic extract of Moringa oleifera powder on productive performance of broilers during the period of rearing of 35 days. The study included two experiments for a period at 2/10/2021 to 28/11/2021, where eggs were injected into the Mustafa Poultry Hatchery/ Wasit Governorate- Aziziyah District. A 400 hatching eggs of 308 Ross  mothers of modern broilers used at age  of 48  week, eggs of average weight  66 ± 1 g/egg were collected in same day then stored for two days. A quarter of treatments were randomly distributed with 100 eggs for each treatment.

The aim of this work was to develop and validate a rapid and low cost method for estimation of ibuprofen in pharmaceutical suspensions using Reverse-Phase High Performance Liquid Chromatography. The proposed method was conducted and validated according to International Conference on Harmonization (ICH) requirements. The chromatographic parameters were as follows: column of octyldecylsilyl C18 with dimensions (150 × 4.6) mm, mobile phase composed of acetonitrile with phosphoric acid with a ratio of 50 to 50 each using isocratic mode, flow rate of 1.5 mL/min and injection volume of 5 μL. The detection was carried out using UV detector at 220 nm. The method was validated and showed short retention time for ibuprofen peak at 7.651 min, wit

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an

The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4