Search

This paper involves a determination of paracetamol using less environment harmful reagent; the hydroxy analog of the pharmaceutical naproxen replaced a chemical reagent in which it is used as a coupling agent for the diazotized p-aminophenol (the hydrolysis product of paracetamol), the paper offers a determination of an analgesic paracetamol in the presence of high content of another analgesic. Paracetamol azo-dye exhibits maximum absorption at 500 nm. Beer's law is obeyed over the concentration range from 10 to 650 µg/20ml, (i.e. 0.5-32.5 ppm) with a good sensitivity (molar absorptivity 1.2x104 l.mol-1.cm-1), good precision (RSD better than ±0.275%) and high accuracy (relative error less than + 0.77%), Sandell's sensitivity index is 0.0124µg.cm-2, the limit of detection (LOD) is 0.0030 µg/ml and the limit of quantitation (LOQ) is 0.0101 µg/ml. The method has been successfully applied for determination for paracetamol in dosage forms and its already applicable for the determination of paracetamol in presence of naproxen.

Natural language means a language that is used for communication by human. Natural Language Processing (NLP) helps machines to understand the natural language. The natural language for the web pages consists of many semantic relations between entities. Discovering significant types of relations from the web is challenging because of its open nature. In this paper we survey several important types of semantic relations. This paper also covers the relation extraction (RE) approaches which are divided into: supervised approach, which contains Feature base and Kernel base, and the unsupervised approach. Three relation extraction algorithms are discussed: Support Vector Machine (SVM), Genetic algorithm and Naive Bayes classifier This survey would be useful for three kinds of readers First the Newcomers in the field who want to quickly learn about relation extraction. Second the researchers who want to know how the various relation extraction techniques developed over time. Third the trainers who just need to know which RE technique works best in different settings

All areas of business and governmental organizations are currently dependent on information technology (IT) to meet business objectives of improving network service and maximizing limited resources. In this paper the main problems that’s represented by using the information network to transfer information such as text, image and video files, conversations or direct video lectures, periods of use that can cause bottlenecks and network downtime, in addition to the large number of users of the network and the causes of these problems. The main objective of this paper is to find out what methods or means to overcome the problems that guide us in terms of optimal use of resources and components even if it is limited, and to determine which technologies are best depending on the typically, quality, importance and confidentiality of the information and the periods of arrival of the information to be transferred. The information is based on the type of networks adopted if they are localized on a given building or the scope of a city or a wide range to include a country or continent and so on.

The objective of this paper is to develop a parallel Pole numerical integration method suitable for renaming in MIMD computing systems. In this paper we improve the Pole Method for numerical integration by partitioning and parallel processing .we compared the developed methods with initial methods the comparison showed the supervise the developed Method for the initial method. The developed methods are suitable fof running on MIMD computing systems.

Patients at healthcare facilities require a long-term continuous healthcare monitoring system to keep track of their vital signs. Because it deals with human life, this system must be safe, trustworthy, and ensure that it does not interfere with available radio frequencies or sensitive electronic devices such as MRI (magnetic resonance imaging). This paper introduces a patient monitoring system in intensive care that used Li-Fi technology, designed to help enhance patient care and boost doctor’s clinical results. This robust approach timely collects patient data and integrates securely within the hospital IT framework feeding information to physicians, allowing them to make informed clinical decisions. The system used real-time software which displays the data from different locations for assessment. It was successfully tested in the laboratory. Some measurements are discussed, which compare the received pulses to the modules line of sight (LOS) output channel to correlate the transmitted channels. In this work, experimental analysis and measurements are performed to check the efficiency of the proposed concept.

A chatbot is a computer program which is designed to interact with users and answer questions. Nowadays, chatbots are one of the most common systems that are used in many fields and by different companies to achieve different tasks. Cloud computing is gaining increasing interest. A myriad of fields and applications have been developed based on cloud computing. In this paper, a college chatbot was developed and implemented to assist students to interact with their college and ask questions related to faculty, activities, exams, admission, amongst other tasks. Text similarity algorithms were adopted to achieve the proposed system. More specifically, cosine similarity and jaccard similarity algorithms were used to find the closest question in the dataset. Firebase real-time database, which is one of the Google cloud services, was used as a connector channel between users and the chatbot server. Experiments were conducted to evaluate the performance of cosine similarity and jaccard similarity methods, and to compare the results of both. In addition, real-time database was also evaluated as a chatbot connecter channel.

This paper investigates the field of Video image analysis depending on texture for detecting a goal and tracing its movement in a video series. Analysing images depending on texture is better than depending on colour or shape , for the goal sometimes depends on different features . The aim of this study is to propose a method for tracing a goal within a video series after detecting it in each video frame. This study exhibits one of the techniques of extracting the image features depending on the signal frequency through using Gabor filter and in different trends for each frame. Then the histogram is taken for each frame and the frame given the best description for the goal is selected , in which case the threshold is depended . Then it is transformed into the binary form of the video frame ,to decrease time consumed short in detecting the object target . The algorithm is applied to part of the video frame . The location of the object target is determined through calculating the centre for part of the frame and the operation is applied to the series of the frames of the video film . Two films have been adopted as a research sample ,The first is a person„s movement by the traffic lights in al-Nabi Yunus area and the other are the students movement at the university of Mosul in the College of Education.

A Genetic Algorithm is defined as a smart algorithm which can be used to solve the complex matters and improve them, which are used in many fields. Also, Genetic Algorithm is considered as one of the efficient search methods which depends on the natural test and genetics. In this research, the Genetic Algorithm features were used to determined and find the encrypted key which was used to encrypt a plain-text by firstly using many selected random generated keys, then apply the Genetic Algorithm with its different features such as: selection, crossover and mutation, leading to the most efficient key to attack the cipher-text and return it to its plain-text with very small or non error ratio. Thus the user will be able to use this key to attack other coming texts for the same destination. The GA which is used in this paper were applied on a different English texts. Results showed the importance of Genetic Algorithm through its potentiality in wide space intelligent search of keys to find the right key, from the other hand, these results showed the accuracy of Genetic Algorithm during its approach.

In this paper, a three (four) dimensional autonomous Finance chaotic (hyperchaotic) system is considered, and we obtained the stability of this systems. We show that the chaotic (three dimensional) system is asymptotically stable at the critical points when , and unstable otherways. While the hyperchaotic (four dimensional) system is asymptotically stable if the variables has the form . Finally, illustrative examples are given.

In this paper we suggested a new learning rate , which improves the classical Backpropagation algorithm (BP). The derivatation of are based on approximating the error function to the quadratic one in sufficiently small neighborhood for the optimal weight vector. The suggested algorithm (Spectral Backpropagation SBP say) is tested and the experimental results show that the SBP learning strategy improves the considered methods.

In this paper, a modified globally convergent self-scaling BFGS algorithm for solving convex unconstrained optimization problems was investigated in which it employs exact line search strategy and the inverse Hessian matrix approximations were positive definite. Experimental results indicate that the new proposed algorithm was more efficient than the standard BFGS- algorithm.

The aim of this paper is to provide a representation of a standard lipschitzian functions by mean of a microscope. More precisely, under certain conditions, the following results have been obtained. Let be a standard function, and be the shadow of its graph : (i) If is s-continuous and limited, then is the graph of a continuous function on . (ii) If is continuous and if is the graph of a function defined on , then is a continuous function. The standard function is lipschitzian at a neighbourhood of a standard point if and only if is limited under every microscope of power centered at a point or at a point infinitely close to it. If the standard function is lipschitzian at a neighbourhood of a standard point ,then it's representation under a microscopic of power centered at the point or at a point infinitely close to it, is a graph of a lipschitzian function.

In this paper, two models are presented for Multiprocessor Stochastic Systems (MSS). The first one is the Generalized Semi-Markov Process (GSMP), the second is the Generalized Stochastic Petri Net (GSPN). These models are used to study performance arbitrary parameters of (MSS). Our main result is by constructing an isomorphism mapping between (MSS) model and (GSPN) model. This isomorphism captures the essential dynamical structure of (MSS).

Morphological filtering is a useful technique for processing and analyzing binary and grayscale images. These filters are effective in impulsive noise filtering, feature extracting, and images enhancing. So it is important to find out method for applying morphological technique on color image and keep the colors unchanged at the same time. This paper deals with the use of morphological filters for suppression "salt & pepper" noise in color images. We have used "component-wise approach", in which grayscale morphological operations are applied to each of the three colors image components independently. We present experimental results of applying this approach for the application of noise suppression in color images.

In an electronic color-imaging device, such as a digital camera, using a single CCD (Charge Coupled Device) sensor, the color information is usually acquired in sub-sampled patterns of Red (R), Green (G) and Blue (B) pixels. The methodology to recover or interpolate the missing color components is known as color demosaicing, a type of image interpolation. This paper introduces and compares some of the most popularly demosaicing algorithms of adaptive type applied on true color images. Another comparison is done between these methods and the non-adaptive traditional methods. Also, a new method is invented, which depends on both types. The used images are of Bitmap type. Signal to noise ratio measure is used as an objective quality metric. The results of comparison are presented with some sampled images. Programming has been applied using Visual C++ 6.0 programming language.

This paper proposes a new algorithm for recognizing text object images by using fractal geometry. The fractal dimension was used as a main feature for recognizing text objects within images. Box-counting method was used to estimate the fractal dimension for image contents. In order to determine a threshold value for the textual objects within image, the fractal dimension was computed for a number of gray scale textual images. The fractal number of each pixel was calculated, then the mean value of all these fractal values were computed. The threshold value was used in recognizing and retrieving the textual objects within image. This algorithm was applied on 75 image samples, 25 image samples were used in training phase, the threshold value was determined throughout this phase; whereas 50 image samples were used in testing the algorithm. The proposed algorithm has performed extremely well with recognition rates 91.5% which is considered good performance. It is a promising technique for optical character recognition system.

In this paper, we have developed a new formula which is more suitable to the Barrier function and we have also investigated a new hybrid algorithm of SD and VM formulas with exact line search in the field of non-linear constrained optimization.

It may be possible to find the Wiener polynomial with respect to a generalized distance of a compound graph constructed from two graphs having some kind of regularity. In this paper, we obtain the Wiener polynomials for a generalized distance of compound graphs constructed from a complete graph with some other special graph, such as a complete bipartite graph, a star, and a wheel, using binary operations defined by Gutman [4]. The Wiener index with respect to such generalized distance for each such compound graph is also obtained.الملخصإن وضع صیغة لمتعددة حدود وینر لتعمیم المسافة فی البیانات المرکبة یتطلب ان تکون البیانات المرکبة لها درجة من الانتظام, وهذا ینطبق على تراکیب بعض البیانات الخاصة التی لها انتظام معین, لذلک وجدنا من المناسب إیجاد حدودیات وینر لتعمیم المسافة للبیان المرکب من البیان التام مع بعض البیانات الخاصة مثلا البیان الثنائی التجزئة التام, وبیان النجمة, وبیان العجلة بإحدى العملیات الثنائیة المعرفة لـ[4] Gutman. وکذلک أوجدنا دلیل وینر لمتعددات الحدود لتعمیم المسافة لکل من البیانات المرکبة المذکورة سابقا.

In This paper, An efficient architecture for the implementation of two dimensional discrete wavelet transform based on lifting scheme for two types of JPEG2000 filters (5/3 and 9/7 filter) are proposed. The pipelining method is applied in the proposed architecture to design multilevel (three-level) architecture for both direction (forward and inverse) transform. After that, the proposed architecture is used to study the effect of clearing the detail coefficients HH, HL and LH sub-band images into the quality of reconstruction image, the proposed one-level two dimensional discrete wavelet transform architecture (one-level 2-D DWT) is built by using the one dimensional discrete wavelet transform (1-D DWT) only,then by using the 1-D DWT as basic element, the architecture are developed to built the three-level two dimensional discrete wavelet transform module (three-level 2-D DWT). The Matlab was used to simulate the proposed architectures and measure the quality of image by using the signal to Noise Ratio (SNR).

The last decade witnessed a great evolution on the fields of computer science, artificial intelligence, communication and data transmission. This evolution draw the attention of specialists to design a modern cryptosystem for data encryption based on neural networks methodologies that are very hard, if not impossible, to be broken. This paper employs cryptography scheme utilizes the neural networks in block cipher algorithms. Taking into consideration different plaintexts block size. The block frequency test has been show the successful of ciphertexts with difficulty to break the cipher process. The application of the neural network in cryptography provides fast and high security system in block ciphering in comparison with traditional methods. The C++ language is used for designing the programs of neural network to encryption and decryption algorithms.

In this paper, a new adapted optimal step-size is designed to improve the efficiency of pair conjugate method. At each linear search an acceptable step- size is estimated during quadratic interpolation and this estimate is used as an initial trial step-size. The technique needs only additional gradient evaluation at each search direction. Also we have improved Armijo line search technique to be used together with the new optimal stepsize. The numerical results are more efficient than the results of the same method using the classical scheme for the linear search technique.

This paper discusses a suggested approach for new kind of Speech Signal Compression Algorithm based on KL transform (Karhunen-Loève transform) which normally used with digital image. Speech signal (which is single sequence) rearranged in form of two dimension square matrix to be suitable for KL transformation. Then to be compressed using different no. of eigen values and eigenvectors. Measuring the performance of applied KL transformation (by evaluating the PSNR and SNR factors) with different numbers of eigen values and vectors studied. High rate of compression with high SNR, PSNR got with so closed speech signal to the original one measured using correlation factor which gives values near to 1. In addition to short time needed for compression operation.

Voice compression is one of the important subject today specially in field of communication and application so in this paper, speech compression was adopted based on hybrid technique between wavelet and Huffman code. Wavelet in single dimension can reduce the signal size to half of the original in each level, then using Huffman code to store output the file. Hybrid between the above two techniques give high rate of compression ratio, and closed returned signal from the original one, because of the coding technique from the lossless classification but the idea of sample down was achieved with the wavelet which produce little loss in the retrieved data, while the effected of the wavelet is positive effect due to the reduction of the high frequencies, which effect as noise in most application[specially in speech],in addition to that it give high redundancy in the component of the speech signal [in low-low components]. The practical application of the proposed algorithm give (30%) compression ratio plus stability when the file size growth up. SNR&MSE show that retrieved speech quality is good.