This paper compares between testing performance methods of classifier algorithm on a standard database of mammogram images. Mammographic interchange society dataset (MIAS) is used in this work. For classifying these images tumors a multiclass support vector machine (SVM) classifier is used. Evaluating this classifier accuracy for classifying the mammogram tumors into the malignant, benign or normal case is done using two evaluating classifier methods that are a hold-out method and one of the cross-validation methods. Then selecting the better test method depending on the obtained classifier accuracy and the running time consumed with each method. The classifier accuracy, training time and the classification time are considered for comparison purpose.

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Due to the occurred increasing in information sharing, internet popularization, E-commerce transactions, and data transferring, security and authenticity become an important and necessary subject. In this paper an automated schema was proposed to generate a strong and complex password which is based on entering initial data such as text (meaningful and simple information or not), with the concept of encoding it, then employing the Genetic Algorithm by using its operations crossover and mutation to generated different data from the entered one. The generated password is non-guessable and can be used in many and different applications and internet services like social networks, secured system, distributed systems, and online services. The proposed password generator achieved diffusion, randomness, and confusions, which are very necessary, required and targeted in the resulted password, in addition to the notice that the length of the generated password differs from the length of initial data, and any simple changing and modification in the initial data produces more and clear modification in the generated password. The proposed work was done using visual basic programing language.

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Face to face interviews are considered as a type of genre in spoken discourse and they include various linguistic strategies that worth investigating. Within these interviews, there is context sensitivity, since the interaction is active and direct between participants. Thus, there should be a use of certain expressions to perform a number of functions such as: topic shift, introducing a new topic, producing personal comment by participants, expressing politeness, etc. Those expressions are called discourse markers (henceforth DMs); they are of different categories and they convey textual functions (expressing coherence and cohesion) and pragmatic functions (expressing the speaker's attitude and other communicative purposes). DMs act as connectors ( connect clauses, sentences, and paragraphs) , indicators (indicate relations in discourse), and instructors (direct participants to the accurate interpretation of an utterance). This study is a discourse study that concerns with the functions of different types of DMs in spoken interaction (social interviews). This study aims at:(i) presenting a general theoretical survey of discourse           markers and their relation to other types of markers in an attempt to get a unified framework to analyse the data of this study,                                                                      (ii) investigating the effect and role of context, specifically social context in determining the meanings and functions of DMs, (iii) explaining the various functions that different types of DMs convey in spoken interaction particularly social interviews.             To achieve these aims , the study hypothesizes that: (i) It is hypothesized that context is the major factor that affects the choice of meanings and functions of        DM , (ii)Certain types of DMs are used frequently in active spoken interaction, and                             (iii) DMs convey particular types of functions in social interviews.      The model  adopted in this study is: Fraser's classification of Pragmatic Markers 1996. It is applied to 2 selected TV interviews within one context , involving both genders, and from one program. The interviews are analyzed  according to the adopted model.             The main conclusions of the current study are: (i) Context is represented as a main independent factor, that  determines the choice of DMs types and the type of functions DMs convey, rather than working with other factors such as  gender and social distance, (ii) Considering the variation of DMs, there are different types of DMs in the analyzed data, such as: SDMs and parallel markers, and (iii) DMs mainly convey textual and interpersonal functions in social interviews .