The World of Computer Science and Information Technology Journal

6

Authors: Rachid HADDADI, Elhassane ABDELMOUNIM, Mustapha EL HANINE, Abdelaziz BELAGUID

this paper proposes the application of Discrete Wavelet Transform (DWT) to detect the QRS (ECG is characterized by a recurrent wave sequence of P, QRS and T-wave) of an electrocardiogram (ECG) signal. Wavelet Transform provides localization in both time and frequency. In preprocessing stage, DWT is used to remove the baseline wander in the ECG signal. The performance of the algorithm of QRS detection is evaluated against the standard MIT BIH (Massachusetts Institute of Technology, Beth Israel Hospital) Arrhythmia database. The average QRS complexes detection rate of 98.1 % is achieved.

5

Authors: Mohamed Nour I. Ismail, Mohamed El-Hafiz Mustafa Muse

modeling data heterogeneity by a mixture of local models and exploiting the correlation in the localized data subsets to reduce their subspace dimensionalities has been realized in many mixture models; like PCA mixture and FA mixture models. Determining the number of local models as well as the proper dimensionality for each subspace (local model space) are the most difficult questions of these models. Instead of using fixed ad-hoc dimensionality for all local models, this paper proposes using a global preserved variance percentage value to estimate the dimensionality that retains the given variability percentage in each subspace. We test the proposed method on classifying handwritten digit by a mixture of Probabilistic PCA model, the result shows that the proposed method outperforms fixed dimensionality probabilistic PCA mixture model.

4

Authors: Eman Al-Thwaib

Text classification (TC) or text categorization task is assigning a document to one or more predefined classes or categories. A common problem in TC is the high number of terms or features in document(s) to be classified (the curse of dimensionality). This problem can be solved by selecting the most important terms. In this study, an automatic text summarization is used for feature selection. Since text summarization is based on identifying the set of sentences that are most important for the overall understanding of document(s). We address the effectiveness of using summarization techniques on text classification. Another feature selection technique is used, which is Term Frequency (TF) on the same but full-text data set, i.e., before summarization. Support Vector Machine is used to classify our Arabic data set. The classifier performance is evaluated in terms of classification accuracy, precision, recall, and the execution time. Finally, a comparison is held between the results of classifying full documents and summarized documents.

11

Authors: Ghassan Samara, Tareq Alhmiedat

The new type of Mobile Ad hoc Network which is called Vehicular Ad hoc Networks (VANET) created a fertile environment for research. In this research, a protocol Particle Swarm Optimization Contention Based Broadcast (PCBB) is proposed, for fast and effective dissemination of emergency messages within a geographical area to distribute the emergency message and achieve the safety system, this research will help the VANET system to achieve its safety goals in intelligent and efficient way.

6

Authors: Adeoye Temitope Onaolamipo

Examination is one of the ways to assess the receptiveness of student to various class teachings in various schools or institutions from primary to post - primary and tertiary institutions. But this is not without problem like impersonation, student class absenteeism and debtor student sitting for examination especially in private institutions. The proposed system developed with the aim of solving stated problems. The system did not only has the ability to take student class attendance and screening before and after examination but it can also be used to verify whether such student is in debit to the institution or whether the student has paid required percentage of the tuition before being allowed to sit for the examination thereby reducing number of student in debit before examination started, it will also eliminate impersonation during examination and stress of manual class attendance taking and record keeping, also avoid writing of name of absent student unlike in manual process of class attendance. The system will also make it easier to calculate required percentage of class attendance before any student is allowed to sit for an examination in any institution. The system adopted biometric access control techniques, which is designed with extended graphical user interface by using Microsoft visual studio 2010 and integrated with Microsoft fingerprint reader. The student information is stored by MySQL which serve as database located in the user's computer or server.