Papers by Ramez Alkhatib
Future Internet
The rapid expansion of social media platforms has resulted in an unprecedented surge of short tex... more The rapid expansion of social media platforms has resulted in an unprecedented surge of short text content being generated on a daily basis. Extracting valuable insights and patterns from this vast volume of textual data necessitates specialized techniques that can effectively condense information while preserving its core essence. In response to this challenge, automatic short text summarization (ASTS) techniques have emerged as a compelling solution, gaining significant importance in their development. This paper delves into the domain of summarizing short text on social media, exploring various types of short text and the associated challenges they present. It also investigates the approaches employed to generate concise and meaningful summaries. By providing a survey of the latest methods and potential avenues for future research, this paper contributes to the advancement of ASTS in the ever-evolving landscape of social media communication.
Diagnostics
Cancer is an incurable disease based on unregulated cell division. Breast cancer is the most prev... more Cancer is an incurable disease based on unregulated cell division. Breast cancer is the most prevalent cancer in women worldwide, and early detection can lower death rates. Medical images can be used to find important information for locating and diagnosing breast cancer. The best information for identifying and diagnosing breast cancer comes from medical pictures. This paper reviews the history of the discipline and examines how deep learning and machine learning are applied to detect breast cancer. The classification of breast cancer, using several medical imaging modalities, is covered in this paper. Numerous medical imaging modalities’ classification systems for tumors, non-tumors, and dense masses are thoroughly explained. The differences between various medical image types are initially examined using a variety of study datasets. Following that, numerous machine learning and deep learning methods exist for diagnosing and classifying breast cancer. Finally, this review addresse...
Applied Sciences
Due to the harm forest fires cause to the environment and the economy as they occur more frequent... more Due to the harm forest fires cause to the environment and the economy as they occur more frequently around the world, early fire prediction and detection are necessary. To anticipate and discover forest fires, several technologies and techniques were put forth. To forecast the likelihood of forest fires and evaluate the risk of forest fire-induced damage, artificial intelligence techniques are a crucial enabling technology. In current times, there has been a lot of interest in machine learning techniques. The machine learning methods that are used to identify and forecast forest fires are reviewed in this article. Selecting the best forecasting model is a constant gamble because each ML algorithm has advantages and disadvantages. Our main goal is to discover the research gaps and recent studies that use machine learning techniques to study forest fires. By choosing the best ML techniques based on particular forest characteristics, the current research results boost prediction power.
arXiv (Cornell University), Dec 12, 2022
Both unmanned aerial vehicles (UAVs) and intelligent reflecting surfaces (IRS) are gaining tracti... more Both unmanned aerial vehicles (UAVs) and intelligent reflecting surfaces (IRS) are gaining traction as transformative technologies for upcoming wireless networks. The IRS-aided UAV communication, which introduces IRSs into UAV communications, has emerged in an effort to improve the system performance while also overcoming UAV communication constraints and issues. The purpose of this paper is to provide a comprehensive overview of IRSassisted UAV communications. First, we provide five examples of how IRSs and UAVs can be combined to achieve unrivaled potential in difficult situations. The technological features of the most recent relevant researches on IRS-aided UAV communications from the perspective of the main performance criteria, i.e., energy efficiency, security, spectral efficiency, etc. Additionally, previous research studies on technology adoption as machine learning algorithms. Lastly, some promising research directions and open challenges for IRS-aided UAV communication are presented. Keywords-Intelligent reflective surface, unmanned aerial vehicle, 6G, Internet of Things, wireless power transfer. Software-Defined Surface (SDS) [16], [17], encouraged through the definition of software-defined radio regard interaction among the surface and received waves to have a software-controlled metasurface. Reconfigurable Intelligent Surface (RIS) [18], [19], [20], [8], and [21], where "reconfigurable" relates to the control of reflection angle (by software) irrespective of the angle of incidence. The designs of IRS from several teams are diverse, but they all follow several characteristics as follows:
Computer Science & Information Technology (CS & IT), 2017
Since Extensible Markup Language abbreviated as XML, became an official World Wide Web Consortium... more Since Extensible Markup Language abbreviated as XML, became an official World Wide Web Consortium recommendation in 1998, XML has emerged as the predominant mechanism for data storage and exchange, in particular over the World Web. Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of application areas and new information is increasingly being encoded as XML documents. Because of the widespread use of XML and the large amounts of data that are represented in XML, it is therefore important to provide a repository for XML documents, which supports efficient management and storage of XML data. Since the logical structure of an XML document is an ordered tree consisting of tree nodes, establishing a relationship between nodes is essential for processing the structural part of the queries. Therefore, tree navigation is essential to answer XML queries. For this purpose, many proposals have been made, the most common ones are node labeling schemes. On the other hand, XML repeatedly uses tags to describe the data itself. This self-describing nature of XML makes it verbose with the result that the storage requirements of XML are often expanded and can be excessive. In addition, the increased size leads to increased costs for data manipulation. Therefore, it also seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In our previous works, we aimed at combining the advantages of both areas (labeling and compaction technologies), Specially, we took advantage of XML structural peculiarities for attempting to reduce storage space requirements and to improve the efficiency of XML query processing using labeling schemes. In this paper, we continue our investigations on variations of binary string encoding forms to decrease the label size. Also We report the experimental results to examine the impact of binary string encoding on reducing the storage size needed to store the compacted XML documents.
International Journal of Database Management Systems, 2017
Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of ap... more Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of application areas and new information is increasingly being encoded as XML documents. Therefore, it is important to provide a repository for XML documents, which supports efficient management and storage of XML data. For this purpose, many proposals have been made, the most common ones are node labeling schemes. On the other hand, XML repeatedly uses tags to describe the data itself. This self-describing nature of XML makes it verbose with the result that the storage requirements of XML are often expanded and can be excessive. In addition, the increased size leads to increased costs for data manipulation. Therefore, it also seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In our previous works, we aimed at combining the advantages of both areas (labeling and compaction technologies), Specially, we took advantage of XML structural peculiarities for attempting to reduce storage space requirements and to improve the efficiency of XML query processing using labeling schemes. In this paper, we continue our investigations on variations of binary string encoding forms to decrease the label size. Also We report the experimental results to examine the impact of binary string encoding on the query performance and the storage size needed to store the compacted XML documents.
Journal of Big Data, Apr 23, 2020
The telecom sector is witnessing a massive increase in data, and by analyzing this massive data, ... more The telecom sector is witnessing a massive increase in data, and by analyzing this massive data, telecom operators can manage and retain customers. It is also important for companies to be able to predict the amount of income they may receive from their active customers. For this purpose, they need models able to determine customer loyalty. The cost associated with customer gain is usually higher than the cost associated
This has generated an increasing need for robust, high performance XML database systems, which ar... more This has generated an increasing need for robust, high performance XML database systems, which are able to not only query and update XML data efficiently, but also store it in a compact representation. There have been many proposals to manage XML documents. However, two common strategies are available to provide robust storage and efficient query processing. The first is based on numbering schemes for gathering structural information from XML documents and storing it in such a way that allows quick identification of structural relationships between nodes. This identification plays a crucial role in efficient XML query processing. The second strategy tries to reduce the size of XML documents through compaction techniques. While a naive representation of XML documents leads to excessive redundancy, the compaction of XML documents not only reduces the amount of disk space occupied by the data, but also enhances query processing speed. The thesis presents different solutions for the eff...
Lecture Notes in Computer Science, 2009
Due to the growing popularity of XML as a data exchange and storage format, the need to develop e... more Due to the growing popularity of XML as a data exchange and storage format, the need to develop efficient techniques for storing and querying XML documents has emerged. A common approach to achieve this is to use labeling techniques. However, their main problem is that they either do not support updating XML data dynamically or impose huge storage requirements. On the other hand, with the verbosity and redundancy problem of XML, which can lead to increased cost for processing XML documents, compaction of XML documents has become an increasingly important research issue. In this paper, we propose an approach called CXDLS combining the strengths of both, labeling and compaction techniques. Our approach exploits repetitive consecutive subtrees and tags for compacting the structure of XML documents by taking advantage of the ORDPATH labeling scheme. In addition it stores the compacted structure and the data values separately. Using our proposed approach, it is possible to support efficient query and update processing on compacted XML documents and to reduce storage space dramatically. Results of a comprehensive performance study are provided to show the advantages of CXDLS.
CXQU: A compact XML storage for efficient query and update processing
2008 Third International Conference on Digital Information Management, 2008
The volume of XML data is increasing rapidly. This poses challenges to the database community to ... more The volume of XML data is increasing rapidly. This poses challenges to the database community to find efficient XML data management solutions. Because XML is by nature verbose, compression is an important issue for XML. In this paper, we propose a new approach (CXQU) which not only supports efficient queries and updates but also compresses the structure of an XML
2008 19th International Conference on Database and Expert Systems Applications, 2008
With the rapidly increasing popularity of XML as a data format, there is a large demand for effic... more With the rapidly increasing popularity of XML as a data format, there is a large demand for efficient techniques in storing and querying XML documents. However XML is by nature verbose, due to repeatedly used tags that describe data. For this reason the storage requirements of XML can be excessive and lead to increased costs for data manipulation. Therefore, it seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In this paper, we propose a new approach called SCQX for Storing, Compressing and Querying XML documents. This approach compresses the structure of an XML document based on exploiting repetitive consecutive tags in the structure, and then SCQX stores the compressed XML structure and the data separately in a robust storage structure that includes a set of access support structures to guarantee fast query performance. Moreover, SCQX supports querying of the compressed XML structure directly and efficiently without requiring decompression. An experimental evaluation on sets of XML data shows the effectiveness of our approach.
Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of ap... more Due to the flexibility and the easy use of XML, it is nowadays widely used in a vast number of application areas and new information is increasingly being encoded as XML documents. Therefore, it is important to provide a repository for XML documents, which supports efficient management and storage of XML data. For this purpose, many proposals have been made, the most common ones are node labeling schemes. On the other hand, XML repeatedly uses tags to describe the data itself. This self-describing nature of XML makes it verbose with the result that the storage requirements of XML are often expanded and can be excessive. In addition, the increased size leads to increased costs for data manipulation. Therefore, it also seems natural to use compression techniques to increase the efficiency of storing and querying XML data. In our previous works, we aimed at combining the advantages of both areas (labeling and compaction technologies), Specially, we took advantage of XML structural peculiarities for attempting to reduce storage space requirements and to improve the efficiency of XML query processing using labeling schemes. In this paper, we continue our investigations on variations of binary string encoding forms to decrease the label size. Also We report the experimental results to examine the impact of binary string encoding on the query performance and the storage size needed to store the compacted XML documents.
inproceedings by Ramez Alkhatib
Elevating the Precision of Summarization for Short Text in Social Media using Preprocessing Techniques
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Papers by Ramez Alkhatib
inproceedings by Ramez Alkhatib