Hoda Baraka

Machine Translation of English Noun Phrases into Arabic

The present work reports our attempt in automating the translation of English noun phrase (NP) into Arabic. Translating NP is a very important task toward sentence translation since NPs form the majority of textual content of the scientific and technical documents. The system is implemented in Prolog and the parser is written in DCG formalism. The paper also describes our experience with the developed MT system and reports results of its application on real titles of theses from the computer science domain.

Generating Arabic text in multilingual speech-to-speech machine translation framework

The interlingual approach to machine translation (MT) is used successfully in multilingual translation. It aims to achieve the translation task in two independent steps. First, meanings of the source-language sentences are represented in an intermediate language-independent (Interlingua) representation. Then, sentences of the target language are generated from those meaning representations. Arabic natural language processing in general is still underdeveloped and Arabic natural language generation (NLG) is even less developed. In particular, Arabic NLG from Interlinguas was only investigated using template-based approaches. Moreover, tools used for other languages are not easily adaptable to Arabic due to the language complexity at both the morphological and syntactic levels. In this paper, we describe a rule-based generation approach for task-oriented Interlingua-based spoken dialogue that transforms a relatively shallow semantic interlingual representation, called interchange format (IF), into Arabic text that corresponds to the intentions underlying the speaker’s utterances. This approach addresses the handling of the problems of Arabic syntactic structure determination, and Arabic morphological and syntactic generation within the Interlingual MT approach. The generation approach is developed primarily within the framework of the NESPOLE! (NEgotiating through SPOken Language in E-commerce) multilingual speech-to-speech MT project. The IF-to-Arabic generator is implemented in SICStus Prolog. We conducted evaluation experiments using the input and output from the English analyzer that was developed by the NESPOLE! team at Carnegie Mellon University. The results of these experiments were promising and confirmed the ability of the rule-based approach in generating Arabic translation from the Interlingua taken from the travel and tourism domain.

Solving graph partitioning problem using genetic algorithms

The graph partitioning problem (GPP) is one of the fundamental multimodal, combinatorial problems that has many applications in computer science. Many deterministic algorithms have been devised to obtain a good solution for the GPP. This paper presents new techniques for discovering more than one solution to this problem using genetic algorithms. The techniques used are based upon applying niching methods to obtain multiple good solutions instead of only one solution. The paper also presents in detail a comparison between the results of a traditional method, simple genetic algorithm (SGA), and two niching methods, fitness sharing and deterministic crowding when applied to the graph partitioning problem.

A Structured Testing Methodology for Knowledge-Based Systems

In recent years, knowledge-based software technology has proven itself to be a valuable tool for solving hitherto intractable problems. Developers of knowledge-based systems must ensure that the system will give its users accurate advice or correct solutions to their problems. Thus, knowledge-based systems must be debugged and validated just like any other piece of software. It has been found that one of the most important problems in developing knowledge-based systems is the lack of methods to verify and validate its KB. The aim of this article is to define a methodology and its supporting tool set that are used together in order to completely test knowledge-based systems. The suggested testing methodology couples different verification and validation activities that are collectively valuable in raising the level of system correctness.

Genetic algorithms in solving graph partitioning problem

The Graph Partitioning Problem (GPP) is one of the fundamental multimodal combinatorial problems that has many applications in computer science. Many algorithms have been devised to obtain a reasonable approximate solution for the GP problem. This paper applies different Genetic Algorithms in solving GP problem. In addition to using the Simple Genetic Algorithm (SGA), it introduces a new genetic algorithm named the Adaptive Population Genetic Algorithm (APGA) that overcomes the premature convergence of SGA. The paper also presents a new approach using niching methods for solving GPP as a multimodal optimization problem. The paper also presents a comparison between the four genetic algorithms; Simple Genetic Algorithm (SGA), Adaptive Population Genetic Algorithm (APGA) and the two niching methods; Sharing and Deterministic Crowding. when applied to the graph partitioning problem. Results proved the superiority of APGA over SGA and the ability of niching methods in obtaining a set of multiple good solutions.

DRKH: dynamic re-keying with key hopping

In this paper, we present Dynamic Re-keying with Key Hopping (DRKH) encryption protocol that uses RC4 encryption technique to ensure a strong security level with the advantage of low execution cost compared to other IEEE 802.11 security schemes.

DRKH: A Power Efficient Encryption Protocol forWireless Devices

In this paper, we present dynamic rekeying with key hopping (DRKH) encryption protocol that uses RC4 encryption technique to ensure a strong security level with the advantage of low execution cost compared to other IEEE 802.11 security schemes. Low computational complexity makes DRKH suitable for solar- and battery-powered handheld devices such as nodes in Solar ESS (extended service set) and wireless sensor networks. Our design goal is to eventually integrate DRKH with different emerging wireless technologies. However, in this paper, we focus on the integration of DRKH with 802.11 standard since it is the most widely deployed wireless technology. The results and analysis show that DRKH overcomes all the security threats with wired equivalent privacy (WEP) protocol while consuming a much lower power than WEP, Wi-Fi Protected Access (WPA) 1.0 and WPA 2.0

DRKH: A Power Efficient Encryption Protocol for Wireless Devices

In this paper, we present Dynamic Re‐keying with Key Hopping (DRKH) encryption protocol that uses RC4 encryption technique to ensure a strong security level with the advantage of low execution cost compared to other IEEE 802.11 security schemes. Low computational complexity makes DRKH suitable for solar‐ and battery‐powered handheld devices such as nodes in Solar ESS (Extended Service Set) and wireless sensor networks. Our design goal is to eventually integrate DRKH with different emerging wireless technologies. However, in this paper, we will focus on the integration of DRKH with 802.11 standard since it is the most widely deployed wireless technology. The results and analysis show that DRKH overcomes all the security threats with Wired Equivalent Privacy (WEP) protocol while consuming a much lower power than WEP, Wi‐Fi Protected Access (WPA) 1.0 and WPA 2.0.

Unified chromosome representation for large scale problems

Genetic Algorithms have been successfully applied to the function optimization problem. However, the main disadvantage of this technique is its large chromosome length and hence long conversion time specially when applied to functions with a large number of parameters. In this paper, a new chromosome representation scheme that reduces the chromosome length is proposed. The scheme is also domain independent and may be used with any function. Results and a comparison between the conventional chromosome representation and the proposed one are presented.