Papers by Amer Al-Badarneh
Bulletin of Electrical Engineering and Informatics
This paper presents a review of the most recently published works of the use of data envelopment ... more This paper presents a review of the most recently published works of the use of data envelopment analysis (DEA) in the evaluation of websites of different fields such as healthcare, e-business, e-commerce, and e-government. The evaluation of websites is performed using web diagnostic tools (WDTs). Some studies have evaluated e-government websites using WDTs only, while others integrate them with data envelopment analysis. We summarize each study including the country that was conducted in, the size of data set, inputs to DEA, outputs from DEA, the approach used, the tools used, and the results obtained. It also covers whether there is a use of combination between DEA and data mining or machine learning approaches to classify the efficiency of these websites.
An analysis of two-way equi-join algorithms under MapReduce
Journal of King Saud University - Computer and Information Sciences
EURASIA Journal of Mathematics, Science and Technology Education
The service sector is the uppermost growing stake of the developed economies. The reliance of thi... more The service sector is the uppermost growing stake of the developed economies. The reliance of this sector on information technology (IT) deserves revision of IT curricula. As the field of computing continues to grow and diversify, and new computing-related disciplines emerge, existing curriculum programs must be updated regularly and new computing disciplines will be drafted. The primary aims of this paper, therefore, are firstly, to introduce the emerging academic discipline known as Service Science, Management, and Engineering (SSME), in response to the growing dominance of the service sector in emerging economies. Secondly, we present a feasibility study of establishing a new undergraduate academic program that offers a Bachelor's degree in SSME. The study was based on analyzing the results of a study conducted to evaluate the workforce in Jordanian information and communications industry. The results of the study concluded that the demand for hybrid IT graduates in the knowledge-based service economy is rapidly growing.
An Adaptive Role-Based Access Control Approach for Cloud E-Health Systems
LIFE: International Journal of Health and Life-Sciences, 2017
LIFE: International Journal of Health and Life-Sciences, 2016
Due to the increasing demand on Hospital Information System (HIS) resources and the high cost of ... more Due to the increasing demand on Hospital Information System (HIS) resources and the high cost of constructing independent information platform especially for medium to small hospitals, large scale clusters which are based on cloud computing technologies have been very popular to use in order to have a quality information platform that best suits the hospital budget. In this paper, we propose an enhanced model that provides a solution for hospital information systems. This model provides new features that will enhance the efficiency of data retrieval of medical images and the costs of processing these images in the cloud.
Survey of Similarity Join Algorithms Based on Mapreduce
MATTER: International Journal of Science and Technology, 2016
MATTER: International Journal of Science and Technology, 2016
Map Reduce stays an important method that deals with semi-structured or unstructured big data fil... more Map Reduce stays an important method that deals with semi-structured or unstructured big data files, however, querying data mostly needs a Join procedure to accumulate the desired result from multiple huge files. Indexing in other hand, remains the best way to ease the access to a specific record(s) in a timely manner. In this paper the authors are investigating the performance gain by implementing Map File indexing and Join algorithms together.
Phoenix: A MapReduce implementation with new enhancements
2016 7th International Conference on Computer Science and Information Technology (CSIT), 2016
Lately, the large increasing in data amount results in compound and large data-sets that caused t... more Lately, the large increasing in data amount results in compound and large data-sets that caused the appearance of "Big Data" concept which gained the attention of industrial organizations as well as academic communities. Big data APIs that need large memory can benefit from Phoenix MapReduce implementation for shared-memory machines, instead of large, distributed clusters of computers. This paper evaluates the design and the prototype of Phoenix, Phoenix performance, as well as Phoenix limitations. This paper also suggests some new approaches to get over of some Phoenix limitation and enhance its performance on large-scale shared memory. The major contribution of this work is finding new approaches that get over the <key, value> pairs limitation in phoenix framework using hash tables with B+Trees and get over the collisions problem of hash tables.
A topological-based spatial data clustering
Optical Pattern Recognition XXVII, 2016
Multi Small Index (MSI): A spatial indexing structure
Journal of Information Science, 2013
ABSTRACT Most of the existing spatial indices are constructed using a single hierarchal index str... more ABSTRACT Most of the existing spatial indices are constructed using a single hierarchal index structure; hence a large number of index pages (nodes) are most likely to be inspected during spatial query execution. Since spatial queries usually fetch spatial objects based on their spatial position in the space, it is significant that spatial objects are clustered in such a way that pertinent objects to a query are fetched quickly. This paper presents a method for partitioning the whole space into set of small subspaces. Then, an index structure for each subspace (called the Multi Small Index) is built. This makes it is easy to quickly retrieve spatial objects that are relevant to the query in question using their corresponding small spatial index structures and ignoring other irrelevant indices. To evaluate our new approach, we conducted a set of experimental studies using a collection of real-life spatial datasets (TIGER data files) with diverse sizes and different object sizes, densities and distributions, as well as various query sizes. The results show that (using small query sizes) our proposed structure (Multi Small Index) outperforms the original R-tree (Single Big Index) structure, achieving nearly 50% saving in disk access.
A Survey on MapReduce Implementations
International Journal of Cloud Applications and Computing, 2016
Performance Impact of Texture Features on MRI Image Classification
Proceedings of the The International Conference on Engineering & MIS 2015 - ICEMIS '15, 2015
Magnetic Resonance Imaging (MRI) is a medical imaging technique used to visualize and distinguish... more Magnetic Resonance Imaging (MRI) is a medical imaging technique used to visualize and distinguish the internal structure of different tissues of the body. The classification of Magnetic Resonance Imaging (MRI) brain images is important to prune the normal patient and to consider only those who have the possibility of having abnormalities. The traditional method for detecting the diseases of human brain in MRI images is done manually by physicians. The manual method faces many problems that can lead to increase the prevalence of more serious diseases. The accurate diagnosis of the brain MRI is not always easy, and takes long time. Thus, address these problems by creating automatic techniques that helps the physicians to make the right decision.
MSL: An Efficient Adaptive In-Place Radix Sort Algorithm
Lecture Notes in Computer Science, 2004
M. Bubak et al. (Eds.): ICCS 2004, LNCS 3037, pp. 606–609, 2004. © Springer-Verlag Berlin Heidelb... more M. Bubak et al. (Eds.): ICCS 2004, LNCS 3037, pp. 606–609, 2004. © Springer-Verlag Berlin Heidelberg 2004 ... MSL: An Efficient Adaptive In-Place Radix Sort Algorithm ... Fouad El-Aker1 and Amer Al-Badarneh2 ... 1 Computer Science Department, New York Institute of ...
2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2012
The traditional method for detecting the tumor diseases in the human MRI brain images is done man... more The traditional method for detecting the tumor diseases in the human MRI brain images is done manually by physicians. Automatic classification of tumors of MRI images requires high accuracy, since the non-accurate diagnosis and postponing delivery of the precise diagnosis would lead to increase the prevalence of more serious diseases. To avoid that, an automatic classification system is proposed for tumor classification of MRI images. This work shows the effect of neural network (NN) and K-Nearest Neighbor (K-NN) algorithms on tumor classification. We used a benchmark dataset MRI brain images. The experimental results show that our approach achieves 100% classification accuracy using K-NN and 98.92% using NN.
A Model Curriculum for Undergraduate Program in IT SSME
International Journal of Service Science, Management, Engineering, and Technology, 2013
Motif Finding Using Ant Colony Optimization
Lecture Notes in Computer Science, 2010
Abstract. A challenging problem in molecular biology is the identifica-tion of the specific bindi... more Abstract. A challenging problem in molecular biology is the identifica-tion of the specific binding sites of transcription factors in the promoter regions of genes referred to as motifs. This paper presents an Ant Colony Optimization approach that can be used to provide the motif ...
A spatial index structure using dynamic recursive space partitioning
2011 International Conference on Innovations in Information Technology, 2011
Abstract Generally, one spatial index structure (called Single Big Index SBI) is built for the wh... more Abstract Generally, one spatial index structure (called Single Big Index SBI) is built for the whole data space; therefore most of the index nodes are prone to be checked during query execution. In this paper, we proposed a technique to partition the space into groups and ...
International Journal of Computers and Applications, 2009
The problem of finding an optimal splitting of overflowed nodes has a major influence on query pe... more The problem of finding an optimal splitting of overflowed nodes has a major influence on query performance of the R-tree spatial index structure. Most of the previous split heuristics of R-tree-based index structures have quadratic time and face the problem of increasing overlap of the resulting minimum bounding rectangles (MBRs). In this paper, we propose an efficient heuristic method for handling R-tree node splits. The proposed method is an enhancement of the Linear R-tree method proposed in C. Ang & T. Tan, New linear node splitting algorithm for R-trees, Proc. 5th Int. Symposium on Advances in Spatial Databases, 1997, 339-349. However, it provides a solution to resolve the distance tie problem to prevent the splitting algorithm from halting. From a practical point of view, the new splitting method is very attractive because it has linear time complexity, acceptable space utilization, as well as better query performance. Results from several experiments conducted using real-life as well as synthetic datasets show that the proposed splitting method outperforms the quadratic version of the original R-tree in terms of query performance and construction time.
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Papers by Amer Al-Badarneh