The World of Computer Science and Information Technology Journal

4

Authors: Fatima T. AL-Khawaldeh

Negation and speculation are two common linguistic concepts in natural language processing field, need more semantic understanding of texts. They are used to definite factuality of text. Negation is used to express the opposite of the text and the Speculation is used to determine the degree of certainty. Biomedical text mining is the main natural language processing application concerns with negation and speculation to distinguish between facts and uncertain or negated information in biomedical text. To our knowledge, there is no previous research on annotating Arabic biomedical text to identify the negative or speculative expression and no publicly available standard corpora of suitable size that are practical for evaluating the automatic detection of negation and speculation tools and scope determination. This paper presents produced corpus handling negation and speculative in Arabic biomedical texts with the main annotation (we call this corpus the BioArabic corpus). The goal of building BioArabic corpus is to help biologists and computational linguistics, who develop tools for identifying the negation and speculation, to train and evaluate these tools since in biomedical texts language, assumptions, experimental results and negative results are used extensively. We will report our statistics on corpus size and the consistency of annotations. Keywords-Arabic NLP; negation; speculation; biomedical (medical and biological); cues; certainty.

4

Authors: Mohammed Ashraf Zoghoul, Ashraf Abu-Ain, Jihad Nader Abdeljalil

Segmentation is a vital step in image processing, especially when image has to be transferred over a network. This paper presents an image segmentation algorithm via four different splitting and merging techniques, namely, Rectangle Technique, Matrix Technique, Line Technique and Free Hand Technique. Keywords-Image Segmentation; Image Merge; Image Splitting; Image Processing.

6

Authors: Khaled Batiha, Mohammed O. Alshroqee

According to the information technology and regarding to the revolutions of the computer worlds, this world has got important information and files that have to be secured from different types of attacks that corrupt and distort them. Thus, many algorithms have turned up to increase the level of security and to detect all types of such attacks. Furthermore, many algorithms such as Message Digest algorithm 5 (MD5) and Secure Hash Algorithm 1 (SHA-1) tend to detect whether the file is attacked, corrupt and distorted or not. In addition, there should be more algorithms to detect the range of harm which the files are exposed to in order to make sure we can use these files after they have been affected by such attacks. To be clear, MD5 and SHA-1 consider the file corrupt once it is attacked; regardless the rate of change. Therefore, the aim of this paper is to use an algorithm that allows certain rate of change according to the user, which is SSdeep algorithm. Meanwhile, it gives the rates of change depending on the importance of each file. Moreover, each rate of change determines whether we can make use of the file or not. I made assumption in creating four folders, each contains multiple files with minimum predefined allowed of similarity. Then graphical user interface is created to utilize the SSdeep algorithm and to permit user to define the allowed similarity on each folder or file depending on impotency of it. After applying the algorithm, I got results showing the benefits of such algorithm to make use of these attacked or modified files. Keywords-Intrusion Detection System; false alarm; fuzzy logic; computer security.

9

Authors: Siniša Vlajić, Vojislav Stanojević, Dušan Savić, Miloš Milić, Ilija Antović, Saša Lazarević

In this paper, we present a general form of GoF Design Patterns as a process that transforms the BDPSP (the Basic Design Pattern Structure of the Problem) to the BDPSS (the Basic Design Pattern Structure of the Solution), i.e. transforms the unstable structure of the program to the stable structure. The stability of the BDPSP and BDPSS is explained by using Robert C. Martin’s Stability metric. The BDPSP and BDPSS are described by three elements: Client, Abstract Server and Concrete Server. The Client is an element of the pattern structure that uses the functionalities of the abstract server and concrete servers in order to carry out its own functionality. The Abstract Server is an element of the pattern structure that provides the client with an abstract functionalities that can be implemented with various specific functionalities. The Concrete Server is an element of the pattern structure that provide the client with concrete functionalities that realise abstract functionalities of the abstract server. In this sense, the Design Pattern is a process that relationship Client has Concrete Server, transform to relationships: a) Client has Abstract Server and b) Concrete server is Abstract Server. We believe the BDPSS is the key mechanism or essence of the GoF design patterns, which allow easy maintenance and upgrade of the program. We have showed that in 20 of 23 GoF design patterns the BDPSS completely describes a pattern or a particular part of the pattern. We are using the general form of GoF design patterns in the teaching process, as the first step in the overall understanding of the GoF design patterns, before a detailed explanation of the specific characteristics of GoF design patterns. We think that this paper can greatly help the students and developers to quickly and clearly understand the essence of GoF design patterns. Keywords- Software design; Design patterns; Stability metric; Software stability; Software maintenance.

4

Authors: Fatima T. AL-Khawaldeh

Negation and speculation are two common linguistic concepts in natural language processing field, need more semantic understanding of texts. They are used to definite factuality of text. Negation is used to express the opposite of the text and the Speculation is used to determine the degree of certainty. Biomedical text mining is the main natural language processing application concerns with negation and speculation to distinguish between facts and uncertain or negated information in biomedical text. To our knowledge, there is no previous research on annotating Arabic biomedical text to identify the negative or speculative expression and no publicly available standard corpora of suitable size that are practical for evaluating the automatic detection of negation and speculation tools and scope determination. This paper presents produced corpus handling negation and speculative in Arabic biomedical texts with the main annotation (we call this corpus the BioArabic corpus). The goal of building BioArabic corpus is to help biologists and computational linguistics, who develop tools for identifying the negation and speculation, to train and evaluate these tools since in biomedical texts language, assumptions, experimental results and negative results are used extensively. We will report our statistics on corpus size and the consistency of annotations.