اسراء حسين عبد الامير الزبيدي

ABSTRACT This paper is concerned with the study and design of a fingerprint recognition system based on wavelet transformation. Fingerprints of 100- persons were taken as test data. These fingerprints were scaled, rotated and translated accordingly and compared with the original images. The system proved to be successful in the presence of these effects, where. The improve the feature extraction and recognition rate of the system, texture features were extracted from spatial domain and combined with the wavelet features. The selected texture features are well known for their capability to recognize images in general. The recognition accuracy, after the combination, was highly improved. It gives about 100% for the conditions covered in the tests. In the case of recognizing multiple instances for the same person, the results show that wavelet descriptors can be efficient representation (when compared with moment descriptors) and can provide reliable recognition in problems with large input variability.

Documents classification is from most important fields for Natural language processing and text mining. There are many algorithms can be used for this task. In this paper, focuses on improving Text Classification by feature selection. This means determine some of the original features without affecting the accuracy of the work, where our work is a new feature selection method was suggested which can be a general formulation and mathematical model of Recursive Feature Elimination (RFE). The used method was compared with other two well-known feature selection methods: Chi-square and threshold. The results proved that the new method is comparable with the other methods, The best results were 83% when 60% of features used, 82% when 40% of features used, and 82% when 20% of features used. The tests were done with the Naïve Bayes (NB) and decision tree (DT) classification algorithms , where the used dataset is a well-known English data set “20 newsgroups text” consists of approximately 18846 files. The results showed that our suggested feature selection method is comparable with standard Like Chi-square.

Cryptography is data processed in a way that becomes incomprehensible and unavailable to unauthorized persons. In this paper instructed method to encryption image by using RC6 algorithm and generated key by using hybrid chaotic map (tent and logistic map). Used some measures such as frequency test within a block, entropy, serial test (two-bit test), and frequency test (monobit test); to demonstrate the strength of the algorithm proposed in the image coding and protection. The MATLAB program was used as a work environment.

In recent years ، we have witnessed the revolution of technology in all sides of life. Therefore ، education has been used to exploit this revolution and everyone has the opportunity to b enefit from it in the learning. Education at this time has become both electronic and traditional. The educational seeks to achieve many results that keep pace with the times. This study aimed at revealing the extent of the use of technology in the learnin g for students of the Faculty of Science / Karbala University and the Faculty of Education for Girls / Kufa University in all departments (Computer ، Chemistry ، Physics ، Biology ، Mathematics ، Sports ، Geography ، History ، Arabic) by electronic questionnaire a imed to comparison between students of humanities study and scientific study in the use of the Internet ، comparison of the most sites (YouTube ، Google ، Facebook ، ...) that used by students ، know number of hours spent by learners in the use of the Internet in the learning process ، and stand on the reasons not to use the Internet in the self - learning. This article showed that the number of Internet scientific study students in learning exceeded the number of human study students who do not use the Internet in le arning

Text classification is one of the important fields in natural language processing. It has many applications in the commercial world like email spam filtering, information retrieval and many other applications. There are many algorithms were used in text classification where few of them are essential. Decision Tree, Support Vector Machine, K-Nearest Neighbors, Naïve Bayes and hidden Markov model are the most essential five classification algorithms. All these algorithms were modified, by many researchers, to obtain high precision. Our work is comprehensive study for almost all the amendments which were done on these five algorithms for text classification. Because of many researchers have been implement them on private data, the comparison for getting accurate decision is very difficult. These amendments are classified according to Learner (modification), main algorithm (modification and addition) and features (extraction and reduction). Then comparison among these modifications for each algorithm is done.

Information security has become the topic of most interest nowadays. Because of significant technological development, transferring information from one person to another has become very easy. This information may be exposed to penetration by unauthorized persons, so the security interest in encryption and steganography has increased. In this paper presents a novel approach by integrating the methodologies of steganography and encryption, resulting in an algorithm that exhibits enhanced resilience against external attacks. The key is first initialized using Grigorchuk's group, which gives an unstructured permutation of data bits. Followed by the stage of encrypting the audio file using RC4, which relies on random generation of the final key in which it is encrypted. In order to increase security and protect data from hacking, the encrypted audio file is hidden in video frames using a non-sequential method based on LSB. The proposed method proved effective results in data preservation as it provided the Peak Signal-to-Noise Ratio scale value of 88, which makes high imputation capacity

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