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Full-Text Articles in Computer Sciences

Speech Enhancement Algorithm Based On Super-Gaussian Modeling And Orthogonal Polynomials, Basheera M. Mahmmod, Abd Rahman Ramli, Thar Baker, Feras Al-Obeidat, Sadiq H. Abdulhussain, Wissam A. Jassim Jan 2019

Speech Enhancement Algorithm Based On Super-Gaussian Modeling And Orthogonal Polynomials, Basheera M. Mahmmod, Abd Rahman Ramli, Thar Baker, Feras Al-Obeidat, Sadiq H. Abdulhussain, Wissam A. Jassim

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© 2020 Lippincott Williams and Wilkins. All rights reserved. Different types of noise from the surrounding always interfere with speech and produce annoying signals for the human auditory system. To exchange speech information in a noisy environment, speech quality and intelligibility must be maintained, which is a challenging task. In most speech enhancement algorithms, the speech signal is characterized by Gaussian or super-Gaussian models, and noise is characterized by a Gaussian prior. However, these assumptions do not always hold in real-life situations, thereby negatively affecting the estimation, and eventually, the performance of the enhancement algorithm. Accordingly, this paper focuses on …

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A Novel Quality And Reliability-Based Approach For Participants' Selection In Mobile Crowdsensing, May El Barachi, Assane Lo, Sujith Samuel Mathew, Kiyan Afsari Jan 2019

A Novel Quality And Reliability-Based Approach For Participants' Selection In Mobile Crowdsensing, May El Barachi, Assane Lo, Sujith Samuel Mathew, Kiyan Afsari

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© 2013 IEEE. With the advent of mobile crowdsensing, we now have the possibility of tapping into the sensing capabilities of smartphones carried by citizens every day for the collection of information and intelligence about cities and events. Finding the best group of crowdsensing participants that can satisfy a sensing task in terms of data types required, while satisfying the quality, time, and budget constraints is a complex problem. Indeed, the time-constrained and location-based nature of crowdsensing tasks, combined with participants' mobility, render the task of participants' selection, a difficult task. In this paper, we propose a comprehensive and practical …

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Dynamic Adaptation For Wpans Collision Prevention In Ehealth Environments, Youssef Iraqi, Loubna Mekouar Jan 2019

Dynamic Adaptation For Wpans Collision Prevention In Ehealth Environments, Youssef Iraqi, Loubna Mekouar

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© 2013 IEEE. This paper presents several adaptive mechanisms to dynamically update the wireless personal area networks (WPANs) parameters that are essential in wearable devices, especially in healthcare environments. Instead of collision detection and recovery, collision prevention is achieved using the proposed algorithms to guarantee a collision-free environment. We present a binary integer programming model for the optimal solution. To avoid the increased complexity, we introduce six suboptimal algorithms. The presented algorithms try to minimize network disruption by updating the parameters of a minimal number of the WPANs. The simulation results show how the algorithms trade off minimal disruption and …

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Forecasting Temperature In A Smart Home With Segmented Linear Regression, Bruce Spencer, Omar Alfandi, Feras Al-Obeidat Jan 2019

Forecasting Temperature In A Smart Home With Segmented Linear Regression, Bruce Spencer, Omar Alfandi, Feras Al-Obeidat

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© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Conference Program Chairs. The efficiency of heating, ventilation and cooling operations in a home are improved when they are controlled by a system that takes into account an accurate forecast of temperature in the house. Temperature forecasts are informed by data from sensors that report on activities and conditions in and around the home. Using publicly available data, we apply linear models based on LASSO regression and our recently developled MIDFEL LASSO regression. These models …

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V2v And V2i Communications For Traffic Safety And Co2 Emission Reduction: A Performance Evaluation, Fatma Outay, Faouzi Kamoun, Florent Kaisser, Doaa Alterri, Ansar Yasar Jan 2019

V2v And V2i Communications For Traffic Safety And Co2 Emission Reduction: A Performance Evaluation, Fatma Outay, Faouzi Kamoun, Florent Kaisser, Doaa Alterri, Ansar Yasar

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© 2019 The Authors. Published by Elsevier B.V. In this paper, we consider a special scenario where connected (V2V and V2I) vehicular technologies are used to alert motorists when they approach a hazardous zone, such as a low visibility area, and recommend proper speeds. We present the principles of the proposed safety driving system and compare the performance of V2V and V2I communications in terms of road safety effectiveness and network communication efficiency. This performance analysis is based on extensive computer simulation experiments by adapting the iTetris platform under various scenarios. We also explore, via simulations, whether CHAA systems, based …

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Virtual Environments Testing As A Cloud Service: A Methodology For Protecting And Securing Virtual Infrastructures, Elhadj Benkhelifa, Anoud Bani Hani, Thomas Welsh, Siyakha Mthunzi, Chirine Ghedira Guegan Jan 2019

Virtual Environments Testing As A Cloud Service: A Methodology For Protecting And Securing Virtual Infrastructures, Elhadj Benkhelifa, Anoud Bani Hani, Thomas Welsh, Siyakha Mthunzi, Chirine Ghedira Guegan

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© 2013 IEEE. Testing is a vital component of the system development life cycle. As information systems infrastructure move from native computing to cloud-based and virtualized platforms, it becomes necessary to evaluate their effectiveness to ensure completion of organizational goals. However, the complexity and scale of virtualized environments make this process difficult. Additionally, inherited and novel issues further complicate this process, while relatively high costs can be constraining. Enabling service-driven environments to provide this evaluation is therefore beneficial for both providers and users. No such complete service offering currently exists. This paper is therefore aimed to benefit industry and academia …

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Wordnet-Based Criminal Networks Mining For Cybercrime Investigation, Farkhund Iqbal, Benjamin C.M. Fung, Mourad Debbabi, Rabia Batool, Andrew Marrington Jan 2019

Wordnet-Based Criminal Networks Mining For Cybercrime Investigation, Farkhund Iqbal, Benjamin C.M. Fung, Mourad Debbabi, Rabia Batool, Andrew Marrington

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© 2019 IEEE. Cybercriminals exploit the opportunities provided by the information revolution and social media to communicate and conduct underground illicit activities, such as online fraudulence, cyber predation, cyberbullying, hacking, blackmailing, and drug smuggling. To combat the increasing number of criminal activities, structure and content analysis of criminal communities can provide insight and facilitate cybercrime forensics. In this paper, we propose a framework to analyze chat logs for crime investigation using data mining and natural language processing techniques. The proposed framework extracts the social network from chat logs and summarizes conversation into topics. The crime investigator can use information visualizer …

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Methodologies For Designing Healthcare Analytics Solutions: A Literature Analysis, Shah J. Miah, John Gammack, Najmul Hasan Jan 2019

Methodologies For Designing Healthcare Analytics Solutions: A Literature Analysis, Shah J. Miah, John Gammack, Najmul Hasan

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© The Author(s) 2019. Healthcare analytics has been a rapidly emerging research domain in recent years. In general, healthcare solution design studies focus on developing analytic solutions that enhance product, process and practice values for clinical and non-clinical decision support. The objective of this study is to explore the scope of healthcare analytics research and in particular its utilisation of design and development methodologies. Using six prominent electronic databases, qualifying articles between 2010 and mid-2018 were sourced and categorised. A total of 52 articles on healthcare analytics solutions were selected for relevant content on public healthcare. The research team scrutinised …

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Non-Orthogonal Radio Resource Management For Rf Energy Harvested 5g Networks, Mehak Basharat, Muhammad Naeem, Waleed Ejaz, Asad Masood Khattak, Alagan Anpalagan, Omar Alfandi, Hyung Seok Kim Jan 2019

Non-Orthogonal Radio Resource Management For Rf Energy Harvested 5g Networks, Mehak Basharat, Muhammad Naeem, Waleed Ejaz, Asad Masood Khattak, Alagan Anpalagan, Omar Alfandi, Hyung Seok Kim

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© 2013 IEEE. Fifth generation (5G) networks are expected to support a large number of devices, provide spectral efficiency and energy efficiency. Non-orthogonal multiple access (NOMA) has been recently investigated to accommodate a large number of devices as well as spectral efficiency. On the other hand, energy efficiency in 5G networks can be addressed using energy harvesting. In this paper, we investigate NOMA in 5G networks with RF energy harvesting to maximize the number of admitted users as well as system throughput. We model a mathematical framework to optimize user grouping, power allocation, and time allocation for information transfer and …

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Online Authentication Methods Used In Banks And Attacks Against These Methods, Anoud Bani-Hani, Munir Majdalweieh, Aisha Alshamsi Jan 2019

Online Authentication Methods Used In Banks And Attacks Against These Methods, Anoud Bani-Hani, Munir Majdalweieh, Aisha Alshamsi

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© 2019 The Authors. Published by Elsevier B.V. Growing threats and attacks to online banking security (e.g. phishing, identity theft) motivates most banks to look for and use stronger authentication methods instead of using a normal username and password authentication. The main objective of the research is to identify the most common online authentication methods used widely in international banks and compare it with the methods used in six banks operating in UAE. In addition, this research will cover the current authentication threats and attacks against these methods. Two well-defined comparison matrices [15], one based on characteristics and second one …

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Combining Machine Learning And Metaheuristics Algorithms For Classification Method Proaftn, Feras Al-Obeidat, Nabil Belacel, Bruce Spencer Jan 2019

Combining Machine Learning And Metaheuristics Algorithms For Classification Method Proaftn, Feras Al-Obeidat, Nabil Belacel, Bruce Spencer

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© Crown 2019. The supervised learning classification algorithms are one of the most well known successful techniques for ambient assisted living environments. However the usual supervised learning classification approaches face issues that limit their application especially in dealing with the knowledge interpretation and with very large unbalanced labeled data set. To address these issues fuzzy classification method PROAFTN was proposed. PROAFTN is part of learning algorithms and enables to determine the fuzzy resemblance measures by generalizing the concordance and discordance indexes used in outranking methods. The main goal of this chapter is to show how the combined meta-heuristics with inductive …

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Effect Of Consumer Innovativeness On New Product Purchase Intentions Through Learning Process And Perceived Value, Salem A. Al-Jundi, Ahmed Shuhaiber, Reshmi Augustine Jan 2019

Effect Of Consumer Innovativeness On New Product Purchase Intentions Through Learning Process And Perceived Value, Salem A. Al-Jundi, Ahmed Shuhaiber, Reshmi Augustine

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© 2019, © 2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Prior research on the impact of consumer innovativeness on new product purchase intentions experienced confusion about the definition of innovativeness and the interest in a specific domain. To fill the gaps, this study builds a new model to examine the multivariate effects of different variables on new product purchase intentions in general and the interplay between all latent variables. We tested a sample of 438 responses that reflect the perspectives of the public in the Emirate of Abu Dhabi, United …

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A Hybrid Framework For Sentiment Analysis Using Genetic Algorithm Based Feature Reduction, Farkhund Iqbal, Jahanzeb Maqbool Hashmi, Benjamin C.M. Fung, Rabia Batool, Asad Masood Khattak, Saiqa Aleem, Patrick C.K. Hung Jan 2019

A Hybrid Framework For Sentiment Analysis Using Genetic Algorithm Based Feature Reduction, Farkhund Iqbal, Jahanzeb Maqbool Hashmi, Benjamin C.M. Fung, Rabia Batool, Asad Masood Khattak, Saiqa Aleem, Patrick C.K. Hung

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© 2019 IEEE. Due to the rapid development of Internet technologies and social media, sentiment analysis has become an important opinion mining technique. Recent research work has described the effectiveness of different sentiment classification techniques ranging from simple rule-based and lexicon-based approaches to more complex machine learning algorithms. While lexicon-based approaches have suffered from the lack of dictionaries and labeled data, machine learning approaches have fallen short in terms of accuracy. This paper proposes an integrated framework which bridges the gap between lexicon-based and machine learning approaches to achieve better accuracy and scalability. To solve the scalability issue that arises …

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Hicss - Modeling Privacy Preservation In Smart Connected Toys By Petri-Nets, Benjamin Yankson, Farkhund Iqbal, Zhihui Lu, Xiaoling Wang, Patrick Hung Jan 2019

Hicss - Modeling Privacy Preservation In Smart Connected Toys By Petri-Nets, Benjamin Yankson, Farkhund Iqbal, Zhihui Lu, Xiaoling Wang, Patrick Hung

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No abstract provided.

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Towards An Efficient Data Fragmentation, Allocation, And Clustering Approach In A Distributed Environment, Hassan Abdalla, Abdel Monim Artoli Jan 2019

Towards An Efficient Data Fragmentation, Allocation, And Clustering Approach In A Distributed Environment, Hassan Abdalla, Abdel Monim Artoli

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© 2019 by the authors. Data fragmentation and allocation has for long proven to be an efficient technique for improving the performance of distributed database systems' (DDBSs). A crucial feature of any successful DDBS design revolves around placing an intrinsic emphasis on minimizing transmission costs (TC). This work; therefore, focuses on improving distribution performance based on transmission cost minimization. To do so, data fragmentation and allocation techniques are utilized in this work along with investigating several data replication scenarios. Moreover, site clustering is leveraged with the aim of producing a minimum possible number of highly balanced clusters. By doing so, …

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The Covcrav Project: Architecture And Design Of A Cooperative V2v Crash Avoidance System, Fatma Outay, Hichem Bargaoui, Anouar Chemek, Faouzi Kamoun, Ansar Yasar Jan 2019

The Covcrav Project: Architecture And Design Of A Cooperative V2v Crash Avoidance System, Fatma Outay, Hichem Bargaoui, Anouar Chemek, Faouzi Kamoun, Ansar Yasar

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© 2019 The Authors. Published by Elsevier B.V. Systems capable of warning motorists against hazardous driving conditions are extremely useful for next-generation cooperative situational awareness and collision avoidance systems. In this paper, we present some preliminary results related to the COVCRAV project which aims to develop an on-board Road Hazard Signaling (RHS) system based on a crowd-apprising model. Unlike other approaches that rely on the automatic detection of dangerous situations via onboard sensors or warning messages received from roadside units, our approach enables drivers to interact directly with a touchscreen Driver Vehicle Interface (DVI) to notify nearby vehicles about the …

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Role Assigning And Taking In Cloud Computing, Shafaq Naheed Khan, Mathew Nicho, Haifa Takruri, Zakaria Maamar, Faouzi Kamoun Jan 2019

Role Assigning And Taking In Cloud Computing, Shafaq Naheed Khan, Mathew Nicho, Haifa Takruri, Zakaria Maamar, Faouzi Kamoun

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© 2019 - IOS Press and the authors. All rights reserved. The widespread use of cloud computing (CC) has brought to the forefront information technology (IT) governance issues, rendering the lack of expertise in handling CC-based IT controls a major challenge for business enterprises and other societal organizations. In the cloud-computing context, this study identifies and ranks the determinants of role assigning and taking by IT people. The study's integrative research links CC and IT governance to humane arrangements, as it validates and ranks role assigning and taking components through in-depth interviews with twelve IT decision-makers and forty-four Information Systems …

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Intensive Pre-Processing Of Kdd Cup 99 For Network Intrusion Classification Using Machine Learning Techniques, Ibrahim M. Obeidat, Nabhan Hamadneh, Mouhammd Alkasassbeh, Mohammad Almseidin, Mazen Ibrahim Alzubi Jan 2019

Intensive Pre-Processing Of Kdd Cup 99 For Network Intrusion Classification Using Machine Learning Techniques, Ibrahim M. Obeidat, Nabhan Hamadneh, Mouhammd Alkasassbeh, Mohammad Almseidin, Mazen Ibrahim Alzubi

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© 2019, International Association of Online Engineering. Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanism that used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity and availability of the services. The speed of the IDS is very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very …

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Neuroprotective Effects Of Melatonin And Celecoxib Against Ethanol-Induced Neurodegeneration: A Computational And Pharmacological Approach, Lina T. Al Kury, Alam Zeb, Zain Ul Abidin, Nadeem Irshad, Imran Malik, Arooj Mohsin Alvi, Atif Ali Khan Khalil, Sareer Ahmad, Muhammad Faheem, Arif Ullah Khan, Fawad Ali Shah, Shupeng Li Jan 2019

Neuroprotective Effects Of Melatonin And Celecoxib Against Ethanol-Induced Neurodegeneration: A Computational And Pharmacological Approach, Lina T. Al Kury, Alam Zeb, Zain Ul Abidin, Nadeem Irshad, Imran Malik, Arooj Mohsin Alvi, Atif Ali Khan Khalil, Sareer Ahmad, Muhammad Faheem, Arif Ullah Khan, Fawad Ali Shah, Shupeng Li

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© 2019 Al Kury et al. This work is published and licensed by Dove Medical Press Limited. Purpose: Melatonin and celecoxib are antioxidants and anti-inflammatory agents that exert protective effects in different experimental models. In this study, the neuroprotective effects of melatonin and celecoxib were demonstrated against ethanol-induced neuronal injury by in silico, morphological, and biochemical approaches. Methods: For the in silico study, 3-D structures were constructed and docking analysis performed. For in vivo studies, rats were treated with ethanol, melatonin, and celecoxib. Brain samples were collected for biochemical and morphological analysis. Results: Homology modeling was performed to build 3-D …

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Cognitive Computing Meets The Internet Of Things, Zakaria Maamar, Thar Baker, Noura Faci, Emir Ugljanin, Yacine Atif, Mohammed Al-Khafajiy, Mohamed Sellami Jan 2019

Cognitive Computing Meets The Internet Of Things, Zakaria Maamar, Thar Baker, Noura Faci, Emir Ugljanin, Yacine Atif, Mohammed Al-Khafajiy, Mohamed Sellami

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This paper discusses the blend of cognitive computing with the Internet-of-Things that should result into developing cognitive things. Today's things are confined into a data-supplier role, which d ...

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Using Mobile Learning Tools In Higher Education: A Uae Case, Jenny Eppard, Zeina Hojeij, Pinar Ozdemir-Ayber, Marlieke Rodjan-Helder, Sandra Baroudi Jan 2019

Using Mobile Learning Tools In Higher Education: A Uae Case, Jenny Eppard, Zeina Hojeij, Pinar Ozdemir-Ayber, Marlieke Rodjan-Helder, Sandra Baroudi

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© International Association of Online Engineering. Research indicates that mobile learning (ML), has the potential to transform teaching and learning. Despite its benefits, mobile learning adoption is a challenging process which requires support to facilitate its integration. The focus of this article is to investigate the factors that could affect ML acceptance. The quantitative and qualitative data collected from the surveys revealed additional information regarding the pedagogical benefits of and obstacles to mobile learning integration. Even though participants in this study reported to be late adopters of technology, they maintained that ML is useful for learning, specifically ubiquitous learning. Teachers …

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An Enhanced Mobility And Temperature Aware Routing Protocol Through Multi-Criteria Decision Making Method In Wireless Body Area Networks, Beom Su Kim, Babar Shah, Feras Al-Obediat, Sana Ullah, Kyong Hoon Kim, Ki Il Kim Nov 2018

An Enhanced Mobility And Temperature Aware Routing Protocol Through Multi-Criteria Decision Making Method In Wireless Body Area Networks, Beom Su Kim, Babar Shah, Feras Al-Obediat, Sana Ullah, Kyong Hoon Kim, Ki Il Kim

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© 2018 by the authors. In wireless body area networks, temperature-aware routing plays an important role in preventing damage of surrounding body tissues caused by the temperature rise of the nodes. However, existing temperature-aware routing protocols tend to choose the next hop according to the temperature metric without considering transmission delay and data loss caused by human posture. To address this problem, multiple research efforts exploit different metrics such as temperature, hop count and link quality. Because their approaches are fundamentally based on simple computation through weighted factor for each metric, it is rarely feasible to obtain reasonable weight value …

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Extracting Semantic Relations From The Quranic Arabic Based On Arabic Conjunctive Patterns, Rahima Bentrcia, Samir Zidat, Farhi Marir Jul 2018

Extracting Semantic Relations From The Quranic Arabic Based On Arabic Conjunctive Patterns, Rahima Bentrcia, Samir Zidat, Farhi Marir

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© 2017 The Authors There is an immense need for information systems that rely on Arabic Quranic ontologies to provide a precise and comprehensive knowledge to the world. Since semantic relations are a vital component in any ontology and many applications in Natural Language Processing strongly depend on them, this motivates the development of our approach to extract semantic relations from the Quranic Arabic Corpus, written in Arabic script, and enrich the automatic construction of Quran ontology. We focus on semantic relations resulting from proposed conjunctive patterns which include two terms with the conjunctive AND enclosed in between. The strength …

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Context Mining Of Sedentary Behaviour For Promoting Self-Awareness Using A Smartphone, Muhammad Fahim, Thar Baker, Asad Masood Khattak, Babar Shah, Saiqa Aleem, Francis Chow Mar 2018

Context Mining Of Sedentary Behaviour For Promoting Self-Awareness Using A Smartphone, Muhammad Fahim, Thar Baker, Asad Masood Khattak, Babar Shah, Saiqa Aleem, Francis Chow

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© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Sedentary behaviour is increasing due to societal changes and is related to prolonged periods of sitting. There is sufficient evidence proving that sedentary behaviour has a negative impact on people’s health and wellness. This paper presents our research findings on how to mine the temporal contexts of sedentary behaviour by utilizing the on-board sensors of a smartphone. We use the accelerometer sensor of the smartphone to recognize user situations (i.e., still or active). If our model confirms that the user context is still, then there is a high probability of being …

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A Process Model For Implementing Information Systems Security Governance, Mathew Nicho Mar 2018

A Process Model For Implementing Information Systems Security Governance, Mathew Nicho

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Purpose; ; ; ; ; The frequent and increasingly potent cyber-attacks because of lack of an optimal mix of technical as well as non-technical IT controls has led to increased adoption of security governance controls by organizations. The purpose of this paper, thus, is to construct and empirically validate an information security governance (ISG) process model through the plan"“do"“check"“act (PDCA) cycle model of Deming.; ; ; ; ; Design/methodology/approach; ; ; ; ; This descriptive research using an interpretive paradigm follows a qualitative methodology using expert interviews of five respondents working in the ISG domain in United Arab Emirates (UAE) …

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Re-Engineering Of Smart City's Business Processes Based On Social Networks And Internet Of Things, Emir Ugljanin, Dragan Stojanović, Ejub Kajan, Zakaria Maamar Jan 2018

Re-Engineering Of Smart City's Business Processes Based On Social Networks And Internet Of Things, Emir Ugljanin, Dragan Stojanović, Ejub Kajan, Zakaria Maamar

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This paper reports our experience with developing a Business-2-Social (B2S) platform that provides necessary support to all this platform's constituents, namely business processes, social media (e.g., social network), and Internet of Things (IoT). This platform is exemplified with smart cities whose successful management requires a complete integration of IoT and social media capabilities into the business processes implementing user services. To ensure a successful integration, social actions, that a smart city would allow citizens execute, are analyzed in terms of impact of these smart city's business processes. Reactions to these actions are tracked and then analyzed to improve user services.

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A Cloud-Based Architecture For Multimedia Conferencing Service Provisioning, Abbas Soltanian, Fatna Belqasmi, Sami Yangui, Mohammad A. Salahuddin, Roch Glitho, Halima Elbiaze Jan 2018

A Cloud-Based Architecture For Multimedia Conferencing Service Provisioning, Abbas Soltanian, Fatna Belqasmi, Sami Yangui, Mohammad A. Salahuddin, Roch Glitho, Halima Elbiaze

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Multimedia conferencing is the real-time exchange of multimedia content between multiple parties. It is the basis of several interactive multiuser applications, such as distance learning and multimedia multiplayer online games. The cloud-based provisioning of the conferencing services on which these applications rely on can have several benefits, including the easy provisioning of new applications, efficient use of resources, and elastic scalability. This paper proposes a holistic cloud-based architecture for conferencing service provisioning, which covers both the infrastructure and platform layers of the cloud. The proposed infrastructure layer offers conferencing substrates-as-a-service (e.g., dial-in signaling, video mixing, and audio mixing), instead of …

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Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi Jan 2018

Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi

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© 2018 The Authors. Published by Elsevier Ltd. Fake news and hoaxes have been there since before the advent of the Internet. The widely accepted definition of Internet fake news is: fictitious articles deliberately fabricated to deceive readers'. Social media and news outlets publish fake news to increase readership or as part of psychological warfare. Ingeneral, the goal is profiting through clickbaits. Clickbaits lure users and entice curiosity with flashy headlines or designs to click links to increase advertisements revenues. This exposition analyzes the prevalence of fake news in light of the advances in communication made possible by the emergence …

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A Generalized Deep Learning-Based Diagnostic System For Early Diagnosis Of Various Types Of Pulmonary Nodules, Ahmed Shaffie, Ahmed Soliman, Luay Fraiwan, Mohammed Ghazal, Fatma Taher, Neal Dunlap, Brian Wang, Victor Van Berkel, Robert Keynton, Adel Elmaghraby, Ayman El-Baz Jan 2018

A Generalized Deep Learning-Based Diagnostic System For Early Diagnosis Of Various Types Of Pulmonary Nodules, Ahmed Shaffie, Ahmed Soliman, Luay Fraiwan, Mohammed Ghazal, Fatma Taher, Neal Dunlap, Brian Wang, Victor Van Berkel, Robert Keynton, Adel Elmaghraby, Ayman El-Baz

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© The Author(s) 2018. A novel framework for the classification of lung nodules using computed tomography scans is proposed in this article. To get an accurate diagnosis of the detected lung nodules, the proposed framework integrates the following 2 groups of features: (1) appearance features modeled using the higher order Markov Gibbs random field model that has the ability to describe the spatial inhomogeneities inside the lung nodule and (2) geometric features that describe the shape geometry of the lung nodules. The novelty of this article is to accurately model the appearance of the detected lung nodules using a new …

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A Refinement Of Lasso Regression Applied To Temperature Forecasting, Bruce Spencer, Omar Alfandi, Feras Al-Obeidat Jan 2018

A Refinement Of Lasso Regression Applied To Temperature Forecasting, Bruce Spencer, Omar Alfandi, Feras Al-Obeidat

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© 2018 The Authors. Published by Elsevier B.V. Model predictive controllers use accurate temperature forecasts to save energy by optimally controlling heating, ventilation and air conditioning equipment while achieving comfort for occupants. In a "smart" building, i.e. one that is outfitted with sensors, temperature forecasts are computed from data gathered by these sensors. Recently, accurate temperature forecasts have been generated using relatively few observations from each sensor. However, long sensor histories are available in smart houses. In this paper we consider improving forecast accuracy by using up to 24 hours of quarter-hourly readings. In particular, we overcome forecast inaccuracy that …

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