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Personal Information  
Name :Essam Al Daoud
Academic Rank :Professor
Office No :1512
Phone :
Department :Cyber Security
Email :Essamdz@zu.edu.jo
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Qualifications
Bachelor : Mu'tah Date :
Master : Al al-bayt Date :
Ph.D. : University Putra Malaysia Date :
Research - Journals
Essam Al Daoud , A New Addition Formula For Elliptic Curves Over GF(2n), IEEE Transactions on Computers , Vol. 51, No. 8, pp: 972-975
08/01/2002
In this paper we propose a new addition formula in projective coordinates for elliptic curves over GF(2n). The new formula speeds up the elliptic curve scalar multiplication by reducing the number of field multiplications. This was achieved by rewriting the elliptic curve addition formula. The complexity analysis shows that the new addition formula speeds up the addition in projective coordinates by about 10 -12 percent, which leads to enhanced scalar multiplication methods for random and
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Essam Al Daoud , Quantum Computing for Solving a System of Nonlinear Equations, International Arab Journal of Information Technolo , Vol. 4, No. 3, pp. 201-205
06/01/2007
Grover’s quantum search algorithm is one of the most widely studied and has produced results in some search applications faster than their classical counterpart by a square-root. This paper modifies Grover’s algorithm to solve nonlinear equations over Galois Finite field GF(q) in O(2nm) iteration, while the best classical general solution takes O(2nm) iteration. The modification is done by using a register for each variable and represent it by n qubits. The paper also introduces the imple
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Essam Al Daoud , Identifying DNA Splice Sites using Patterns Statistical Properties and Fuzzy Neural Networks, . EXCLI Experimental and Clinical Sciences Journal , Vol 8, 2009, pp: 195-202
08/01/2009
This study introduces a new approach to recognize the boundaries between the parts of the DNA sequence retained after splicing and the parts of the DNA that are spliced out. The basic idea is to derive a new dataset from the original data to enhance the accuracy of the well-known classification algorithms. The most accurate results are obtained by using a derived dataset that consists from the highest correlated features and the interesting statistical properties of the DNA sequences. On
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Essam Al Daoud , A Framework to Automate the Parsing of Arabic Language Sentences, International Arab Journal of Information Technolo , Vol. 6, No. 2, pp:191-195
04/01/2009
Abstract: This paper proposes a framework to automate the parsing of Arabic language sentences in general, although it focuses on the simple verbal sentences but it can be extended to any Arabic language sentence. The proposed system is divided into two separated phases which are lexical analysis and syntax analysis. Lexical phase analyses the words, finds its originals and roots, separates it from prefixes and suffixes, and assigns the filtered words to special tokens. Syntax analysis recei
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Essam Al Daoud , Fast Protein Classification by Using the Most Significant Pairs, EXCLI Experimental and Clinical Sciences Journal, , Vol. 9, pp: 133-140
09/01/2010
This study introduces a new approach to speed up the protein classification process. The basic idea is rewriting the sequences of each family by using the most significant pairs, where the total number of the pairs that can be appeared in the protein sequences is 400 different pairs. The sequence length could be reduced to 0.86, 0.91 and 0.95 by using the most 100, 200 and 300 significant pairs, respectively. The average time reduction is 0.53 %, 0.33 % and 0.22 % for 100, 200, and 300 pair
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Essam Al Daoud , A new iris localization method based on the competitive chords, Signal, Image and Video Processing Journal. , Vol. 6, No. 4, pp: 547-555
07/01/2012
Abstract This study introduces a novel iris localization method based on the competitive chords. The new method can be used to detect pupil–iris and iris sclera boundaries. The basic idea is to construct a set of chords from the left edges and the right edges of the pupil (or iris), and then find the winner chords with aligned centers. The winner chords can be used to vote to the correct pupil’s (or iris’s) center and radius. To verify the effectiveness of the proposed method, it is compared wit
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7. Al Daoud, E. and Turabieh , New Empirical Nonparametric Kernels for Support Vector Machine Classification, Applied Soft Computing , Vol. 13 No. 4 , pp:1759-1765
04/01/2013
Despite the excellent applicability of kernel methods, there seems to be no systematic way of choosing appropriate kernel functions or the optimum parameters. Therefore, the performance of support vector machines (SVMs) cannot be easily optimized. To address this problem, a general procedure is suggested to produce nonparametric and efficient kernels. This is achieved by finding an empirical and theoretical connection between positive semidefinite matrices and certain metric space properties. Th
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Essam Al Daoud, Noura Al-Fayoumi , Enhanced Metaheuristic Algorithms for the Identification of Cancer MDPs, International Journal of Intelligent Systems and A , Vol. 6, No. 2, pp: 14-21
02/01/2014
Abstract— Cancer research revolves around the study of diseases that involve unregulated cell growth. This direction facilitated the development of a wide range of cancer genomics projects that are designed to support the identification of mutated driver pathways in several cancer types. In this research, a maximum weight submatrix problem is used to identify the driver pathway in a specific type of cancer. To solve this problem, we propose two new metaheuristic algorithms. The first is an impro
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Essam Al Daoud , An Efficient Algorithm for Finding a Fuzzy Rough Set Reduct Using an Improved Harmony Search, International Journal of Modern Education and Comp , Vol. 7, No. 2, pp:16-23
02/01/2015
Abstract—To increase learning accuracy, it is important to remove misleading, redundant, and irrelevant features. Fuzzy rough set offers formal mathematical tools to reduce the number of attributes and determine the minimal subset. Unfortunately, using the formal approach is time consuming, particularly if a large dataset is used. In this paper, an efficient algorithm for finding a reduct is introduced. Several techniques are proposed and combined with the harmony search, such as using a balance
10. Feras Hanandeh, Mohammed Akour, Essam Al Daoud, Rafat Alshorman, Izzat Alsmadi , Essam Al Daoud, Rafat Alshorman, Izzat Alsmadi,KP-Trie Algorithm for Update and Search Operations , The International Arab Journal of Information Tech , Vol. 13, No. 6
11/01/2016
Abstract: Radix-Tree is a space optimized data structure that performs data compression by means of cluster nodes that share the same branch. Each node with only one child is merged with its child and is considered as space optimized. Nevertheless, it can't be considered as speed optimized because the root is associated with the empty string . Moreover, values are not normally associated with every node; they are associated only with leaves and some inner nodes that correspond to keys of interes
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Essam Al Daoud , A Modified Optimization Algorithm Inspired by Wild Dog Packs, International Journal of Science and Advanced Tech , Vol. 4, No. 9, pp: 25-28
09/01/2014
Abstract—The difficulties associated with using mathematical optimization problems have contributed to the development of alternative solution1s. The formal methods often fail in solving NP-hard applications of the large size. To overcome this problem, several metaheuristic algorithm have been suggested. In this paper a modified optimization algorithm inspired by wild dog packs is suggested, the new approach solved the drawback of the wild dog packs optimization by using a set of harmony search
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31. Al Daoud, E., Alshorman, R., and Hanandeh, F. , A New Efficient Meta-Heuristic Optimization Algorithm Inspired by Wild Dog Packs, International Journal of Hybrid Information Techno , Vol. 7, No. 6, pp: 83-100
06/01/2014
Although meta-heuristic optimization algorithms have been used to solve many optimization problems, they still suffer from two main difficulties: What are the best parameters for a particular problem? How do we escape from the local optima? In this paper, a new, efficient meta-heuristic optimization algorithm inspired by wild dog packs is proposed. The main idea involves using three self-competitive parameters that are similar to the smell strength. The parameters are used to control the movemen
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Essam Al Daoud , Quantum Meta-Heuristic Algorithm Based on Harmony, International Journal of Engineering Science , Vol.4, No. 10, pp:13-18.
10/01/2015
ABSTRACT: Harmony search is meta-heuristic optimization algorithm. It was inspired by the observation that the aim of music is to search for a perfect state of harmony. A drawback of the harmony search algorithm cannot find the global minimum easily and becomes very slow near the minimum points, moreover an exhaustive search method should be implemented around the minimum points to get high accuracy. Therefore a modified quantum search algorithm is suggested to handle the candidates points.
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Ala'a Abu-Srhan and Essam Al Daoud, , Power Aware Ant Colony Routing Algorithm for Mobile Ad-hoc Networks, International Journal of Software Engineering and , Vol. 9, No. 12 (2015), pp. 197-212
12/01/2015
Due to the limited lifetime of nodes in ad hoc and sensor network, energy efficiency needs to be an important design consideration in any routing algorithm. Most of the existing Ant colony based routing algorithms grantee the packet delivery. However, they suffer from the high power consumption due to the huge number of control messages to establish and maintain a route from a source to a destination. This paper introduces two new power-aware ant colony routing algorithms for mobile ad hoc
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Essam Al Daoud , International Journal of Engineering Science Invention, A new algorithm for Predicting Metabolic Pathways , Vol. 5, No. 8,PP. 20-24
08/01/2016
The reconstruction of the metabolic network of an organism based on its genome sequence is a key challenge in systems biology. The aim of the work described here is to develop a new algorithm to predict pathway classes and individual pathways for a previously unknown query molecule. The main idea is
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Feras Hanandeh, Essam Al Daoud , Simplified approach for generating integrity tests in distributed database systems, Int. J. Innovation and Learning , Vol.13 /No.4 /pp.375 - 387
06/01/2013
Distributed database systems (DDBS) usually contain massive collections of data that rapidly evolve over time. It is extremely time consuming to make a perfect checking at each database update operation. This paper introduces a new algorithm to generate simplified integrity tests which could be used to automatically verify that database updates does not introduce any violation of integrity. The main attractive features of this approach are simplicity, flexibility in generating sufficient a
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Essam Al-Daoud , Feras Al-Hanandeh, Emad E. Abdallah and Alaa E. Abdallah , Texture Recognition by using a Non-Linear Kernel , Int. J. of Computer Applications in Technology , Vol. 48/No. 3/ pp. 235-240
06/01/2013
This study proposes the use of features combination and a non-linear kernel to improve the classification rate of texture recognition. The feature vector concatenates three different sets of feature: the first set is extracted using grey-level cooccurrence matrix, the second set is collected from three different radii of local binary patterns, and the third set is generated using Gabor wavelet features. Gabor features are the mean, the standard deviation, and the skew of each scaling and or
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Essam Al Daoud , Efficient DNA Motifs Discovery using Modified Genetic Algorithm, International Journal of Computational Intelligenc , Vol. 12/No. 3/ pp. 1- 15.
06/01/2013
In this study, a new genetic algorithm was developed to discover the best motifs in a set of DNA sequences. The main steps were: ¯nding the potential positions in each sequence by using few voters (15 sequences), constructing the chromosomes from the potential positions, evaluating the ¯tness for each gene (position) and for each chromosome, calculating the new random distribution, and using the new distribution to generate the next generation. To verify the e®ectiveness of the proposed al
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Emad E. Abdallah*, Alaa E. Abdallah, Mohammad Bsoul and Essam Al Douad , Simplified Features for Email Authorship Identification,, International Journal of Security and Networks , Vol.8/ No.2 /pp.72 – 81
08/01/2013
We present an investigation analysis approach for mining anonymous email content. The core idea behind our approach is concentrated on collecting various effective features from previous emails for all the possible suspects. The extracted features are then used with several machine learning algorithms to extract a unique writing style for each suspect. A sophisticated comparison between the investigated anonymous email and the suspects writing styles is employed to extract evidence of the p
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Ala'a Abu-Srhan and Essam Al Daoud , A Hybrid Algorithm Using a Genetic Algorithm and Cuckoo Search Algorithm to Solve the Traveling Salesman Problem and its Application to Multiple Sequence Alignment., International Journal of Advanced Science and Tech , Vol.61 / pp.29-38
12/01/2013
The traveling salesman problem (TSP) is one of the most studied in operations research and computer science. Research has led to a large number of techniques to solve this problem; in particular, genetic algorithms (GA) produce good results compared to other techniques. A disadvantage of GA, though, is that they easily become trapped in the local minima. In this paper, a cuckoo search optimizer (CS) is used along with a GA in order to avoid the local minima problem and to benefit from the advant
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Essam Al Daoud, Noura Al-Fayoumi , Enhanced Metaheuristic Algorithms for the Identification of Cancer MDPs , International Journal of Intelligent Systems and A , Vol. 6/No. 2/pp: 14-21
02/01/2014
Cancer research revolves around the study of diseases that involve unregulated cell growth. This direction facilitated the development of a wide range of cancer genomics projects that are designed to support the identification of mutated driver pathways in several cancer types. In this research, a maximum weight submatrix problem is used to identify the driver pathway in a specific type of cancer. To solve this problem, we propose two new metaheuristic algorithms. The first is an improved harmon
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Essam Al Daoud , A new algorithm for Predicting Metabolic Pathways, International Journal of Engineering Science Inven , Vol. 5/No. 8/PP. 20-24
08/01/2016
The reconstruction of the metabolic network of an organism based on its genome sequence is a key challenge in systems biology. The aim of the work described here is to develop a new algorithm to predict pathway classes and individual pathways for a previously unknown query molecule. The main idea is to use a dense graph, where the compounds are represented as vertices and the enzymes are represented as edges, the weights are assigned to the edges according to the previous known pathways. The sho
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Essam Al DAoud , Minimal Walking Technicolor Simulation using Generative Adversarial Networks (GANs), International Journal of Emerging Trends in Engine , 8/3
04/01/2020
The Minimal Walking Technicolor (MWT) has been studied extensively and it was an excellent candidate for breaking the electroweak symmetry. However, to verify the correctness of the Lagrangian of the minimal walking Technicolor, the theoretical simulation of the Feynman rules that are extracted from Lagrangian of MWT must be identical to the data accumulated from practical experiments that are done by the large hadron collider (LHC). In this paper we amplified the rare events by generating sampl
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Conferences
Face Recognition Using Fuzzy Clustering and Kernelized Lest Square
4th International Conference on Signal and Image Processing CSIP 2015
Suzhou, China
2015.03.18
Over the last fifteen years, face recognition has become a popular area of research in image analysis and one of the most successful applications of machine learning and understanding. To enhance the classification rate of the image recognition, several techniques are introduced, modified and combined. The suggested model extracts the features using Fourier-Gabor filter, selects the best features using signal to noise ratio, deletes or modifies anomalous images using fuzzy c-mean clustering, use
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An Improved Ant Colony Algorithm for Genome Rearrangements
ICBBBCB 2014: International Conference on Bioinformatics, Biomedicine, Biotechnology and Computation
London, United Kingdom
2014.05.26
Abstract—Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed per
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Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines
ICCCISE 2013 : International Conference on Computer,Communication and Information Sciences, and Engi
Lucerne, Switzerland
2013.05.07
Abstract—Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by ap
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Improving Protein-Protein Interaction Prediction by Using Encoding Strategies and Random Indices
ICCVISP: International Conference on Computer Vision, Image and Signal Processing,
Franch, Paris
2011.11.14
Abstract—A New features are extracted and compared to improve the prediction of protein-protein interactions. The basic idea is to select and use the best set of features from the Tensor matrices that are produced by the frequency vectors of the protein sequences. Three set of features are compared, the first set is based on the indices that are the most common in the interacting proteins, the second set is based on the indices that tend to be common in the interacting and non-interacting protei
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Integration of Support Vector Machine and Bayesian Neural Network for Data Mining and Classification
ICDMKE 2010, International Conference on Data Mining and Knowledge Engineering,
Rome, Italy
2010.04.28
Abstract—Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied
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Essam Al Daoud
ICBBBCB 2016 : 18th International Conference on Bioinformatics, Biomedicine, Biotechnology and Compu
Boston, USA
2016.04.25
This study solves a phylogeny problem by using modified wild dog pack optimization. Theleast squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, ne
File Research
Large Scale and Real Time Classifiers for Social Media Text
IASTEM - 704TH INTERNATIONAL CONFERENCE ON RECENT
USA
2020.04.29
Abstract - Social media text has received attention of researchers and decision makers due to the valuable information that can be extracted from the text such as people behavior and their opinions. Classification is very important step to convert the raw text to information or knowledge. However, social media text has some serious problems such as, repeated characters, new words, a lot of unwanted symbols and informal structure. Therefore, to standardized the text, regular expression, prepr
File Research
Experiences