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Articles 541 - 570 of 677
Full-Text Articles in Computer Sciences
A Survey On Sentiment Analysis In Urdu: A Resource-Poor Language, Asad Khattak, Muhammad Zubair Asghar, Anam Saeed, Ibrahim A. Hameed, Syed Asif Hassan, Shakeel Ahmad
A Survey On Sentiment Analysis In Urdu: A Resource-Poor Language, Asad Khattak, Muhammad Zubair Asghar, Anam Saeed, Ibrahim A. Hameed, Syed Asif Hassan, Shakeel Ahmad
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© 2020 Background/introduction: The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions. While the volume of studies conducted on sentiment analysis is rapidly expanding, these studies mostly address English language concerns. The primary goal of this study is to present state-of-art survey for identifying the progress and shortcomings saddling Urdu sentiment analysis and propose rectifications. Methods: We described the advancements made thus far in this area by categorising the studies along three dimensions, namely: text pre-processing lexical resources and sentiment classification. These …
Machine Learning Techniques For Quantification Of Knee Segmentation From Mri, Sujeet More, Jimmy Singla, Ahed Abugabah, Ahmad Ali Alzubi
Machine Learning Techniques For Quantification Of Knee Segmentation From Mri, Sujeet More, Jimmy Singla, Ahed Abugabah, Ahmad Ali Alzubi
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© 2020 Sujeet More et al. Magnetic resonance imaging (MRI) is precise and efficient for interpreting the soft and hard tissues. Moreover, for the detailed diagnosis of varied diseases such as knee rheumatoid arthritis (RA), segmentation of the knee magnetic resonance image is a challenging and complex task that has been explored broadly. However, the accuracy and reproducibility of segmentation approaches may require prior extraction of tissues from MR images. The advances in computational methods for segmentation are reliant on several parameters such as the complexity of the tissue, quality, and acquisition process involved. This review paper focuses and briefly …
On The Validation Of Web X.509 Certificates By Tls Interception Products, Ahmad Samer Wazan, Romain Laborde, David Chadwick, Remi Venant, Abdelmalek Benzekri, Eddie Billoir, Omar Alfandi
On The Validation Of Web X.509 Certificates By Tls Interception Products, Ahmad Samer Wazan, Romain Laborde, David Chadwick, Remi Venant, Abdelmalek Benzekri, Eddie Billoir, Omar Alfandi
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The Transport Layer Security (TLS) protocol aims to provide confidentiality and integrity of data. It is based on X.509 Certificates. Our previous research showed that popular Web Browsers exhibit non-standardized behaviour with respect to the certificate validation process [1]. This paper extends that work by examining their handling of OCSP Stapling. We also examine several popular HTTPS interception products, including proxies and anti-virus tools, regarding their certificate validation processes. We analyse and compare their behaviour to that described in the relative standards. Finally, we propose a system that allows the automation of certificate validation tests.
Computer Aided Autism Diagnosis Using Diffusion Tensor Imaging, Yaser A. Elnakieb, Mohamed T. Ali, Ahmed Soliman, Ali H. Mahmoud, Ahmed M. Shalaby, Norah Saleh Alghamdi, Mohammed Ghazal, Ashraf Khalil, Andrew Switala, Robert S. Keynton, Gregory Neal Barnes, Ayman El-Baz
Computer Aided Autism Diagnosis Using Diffusion Tensor Imaging, Yaser A. Elnakieb, Mohamed T. Ali, Ahmed Soliman, Ali H. Mahmoud, Ahmed M. Shalaby, Norah Saleh Alghamdi, Mohammed Ghazal, Ashraf Khalil, Andrew Switala, Robert S. Keynton, Gregory Neal Barnes, Ayman El-Baz
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© 2013 IEEE. Autism Spectrum Disorder (ASD), commonly known as autism, is a lifelong developmental disorder associated with a broad range of symptoms including difficulties in social interaction, communication skills, and restricted and repetitive behaviors. In autism spectrum disorder, numerous studies suggest abnormal development of neural networks that manifest itself as abnormalities of brain shape, functionality, and/ or connectivity. The aim of this work is to present our automated computer aided diagnostic (CAD) system for accurate identification of autism spectrum disorder based on the connectivity of the white matter (WM) tracts. To achieve this goal, two levels of analysis are …
Decentralized Telemedicine Framework For A Smart Healthcare Ecosystem, Ahed Abugabah, Nishara Nizamuddin, Ahmad Ali Alzubi
Decentralized Telemedicine Framework For A Smart Healthcare Ecosystem, Ahed Abugabah, Nishara Nizamuddin, Ahmad Ali Alzubi
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The healthcare sector is one of the most rapidly growing sectors globally. With the ever-growing technology, patient care, regulatory compliance, and digital transformation, there is an increased need for healthcare sectors to collaborate with all stakeholders – both within the healthcare ecosystem and in concurring industries. In recent times, telemedicine has proven to provide high quality, affordable, and predominantly adapted healthcare services. However, telemedicine suffers from several risks in implementation, such as data breach, restricted access across medical fraternity, incorrect diagnosis and prescription, fraud, and abuse. In this work, introduce blockchain-based framework that would unlock the future of the healthcare …
Accurate Segmentation Of Cerebrovasculature From Tof-Mra Images Using Appearance Descriptors, Fatma Taher, Ahmed Soliman, Heba Kandil, Ali Mahmoud, Ahmed Shalaby, Georgy Gimel'farb, Ayman El-Baz
Accurate Segmentation Of Cerebrovasculature From Tof-Mra Images Using Appearance Descriptors, Fatma Taher, Ahmed Soliman, Heba Kandil, Ali Mahmoud, Ahmed Shalaby, Georgy Gimel'farb, Ayman El-Baz
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© 2013 IEEE. Analyzing cerebrovascular changes can significantly lead to not only detecting the presence of serious diseases e.g., hypertension and dementia, but also tracking their progress. Such analysis could be better performed using Time-of-Flight Magnetic Resonance Angiography (ToF-MRA) images, but this requires accurate segmentation of the cerebral vasculature from the surroundings. To achieve this goal, we propose a fully automated cerebral vasculature segmentation approach based on extracting both prior and current appearance features that have the ability to capture the appearance of macro and micro-vessels in ToF-MRA. The appearance prior is modeled with a novel translation and rotation invariant …
Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily
Ai Techniques For Covid-19, Adedoyin Ahmed Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily
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© 2013 IEEE. Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the …
Fine-Grained Sentiment Analysis For Measuring Customer Satisfaction Using An Extended Set Of Fuzzy Linguistic Hedges, Asad Khattak, Waqas Tariq Paracha, Muhammad Zubair Asghar, Nosheen Jillani, Umair Younis, Furqan Khan Saddozai, Ibrahim A. Hameed
Fine-Grained Sentiment Analysis For Measuring Customer Satisfaction Using An Extended Set Of Fuzzy Linguistic Hedges, Asad Khattak, Waqas Tariq Paracha, Muhammad Zubair Asghar, Nosheen Jillani, Umair Younis, Furqan Khan Saddozai, Ibrahim A. Hameed
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© 2020 The Authors. Published by Atlantis Press SARL. In recent years, the boom in social media sites such as Facebook and Twitter has brought people together for the sharing of opinions, sentiments, emotions, and experiences about products, events, politics, and other topics. In particular, sentiment-based applications are growing in popularity among individuals and businesses for the making of purchase decisions. Fuzzy-based sentiment analysis aims at classifying customer sentiment at a fine-grained level. This study deals with the development of a fuzzy-based sentiment analysis by extending fuzzy hedges and rule-sets for a more efficient classification of customer sentiment and satisfaction. …
Improving M-Learners' Performance Through Deep Learning Techniques By Leveraging Features Weights, Muhammad Adnan, Asad Habib, Jawad Ashraf, Babar Shah, Gohar Ali
Improving M-Learners' Performance Through Deep Learning Techniques By Leveraging Features Weights, Muhammad Adnan, Asad Habib, Jawad Ashraf, Babar Shah, Gohar Ali
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© 2013 IEEE. Mobile learning (M-learning) has gained tremendous attention in the educational environment in the past decade. For effective M-learning, it is important to create an efficient M-learning model that can identify the exact requirements of mobile learners (M-learners). M-learning model is composed of features that are generated during M-learners' interaction with mobile devices. For an adaptive M-learning model, not only learning features are required, but it is also important to determine how they differ for various M-learners, their weights, and interrelationship. This study proposes a robust and adaptive M-learning model that is based on machine learning and deep …
Personalized Computer-Aided Diagnosis For Mild Cognitive Impairment In Alzheimer's Disease Based On Smri And C Pib-Pet Analysis, Fatma El Zahraa A. El-Gamal, Mohammed M. Elmogy, Ashraf Khalil, Mohammed Ghazal, Jawad Yousaf, Xiaolu Qiu, Hassan H. Soliman, Ahmed Atwan, Hermann B. Frieboes, Gregory Neal Barnes, Ayman S. El-Baz
Personalized Computer-Aided Diagnosis For Mild Cognitive Impairment In Alzheimer's Disease Based On Smri And C Pib-Pet Analysis, Fatma El Zahraa A. El-Gamal, Mohammed M. Elmogy, Ashraf Khalil, Mohammed Ghazal, Jawad Yousaf, Xiaolu Qiu, Hassan H. Soliman, Ahmed Atwan, Hermann B. Frieboes, Gregory Neal Barnes, Ayman S. El-Baz
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© 2013 IEEE. Alzheimer's disease (AD) is a neurodegenerative condition that affects the central nervous system and represents 60% to 70% of all dementia cases. Due to an increased aging population, the number of patients diagnosed with AD is expected to exceed 131 million worldwide by 2050. The disease is characterized by various clinical symptoms and pathological features that define three main sequential decline stages, namely, early/mild, intermediate/moderate and late/severe stages. Although it is considered irreversible, early diagnosis of AD is highly desirable to help preserve cognitive function. However, early diagnosis is difficult due to different factors, including the patient-specific …
Thwarting Icmp Low-Rate Attacks Against Firewalls While Minimizing Legitimate Traffic Loss, Kadhim Hayawi, Zouheir Trabelsi, Safaa Zeidan, Mohammad Mehedy Masud
Thwarting Icmp Low-Rate Attacks Against Firewalls While Minimizing Legitimate Traffic Loss, Kadhim Hayawi, Zouheir Trabelsi, Safaa Zeidan, Mohammad Mehedy Masud
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© 2013 IEEE. Low-rate distributed denial of service (LDDoS) attacks pose more challenging threats that disrupt network security devices and services. Such type of attacks is difficult to detect and mitigate. In LDDoS attacks, attacker uses low-volume of malicious traffic that looks alike legitimate traffic. Thus, it can enter the network in silence without any notice. However, it may have severe effect on disrupting network services, depleting system resources, and degrading network speed to a point considering them as one of the most damaging attack types. There are many types of LDDoS such as application server and ICMP error messages …
Iot-Enabled Flood Severity Prediction Via Ensemble Machine Learning Models, Mohammed Khalaf, Haya Alaskar, Abir Jaafar Hussain, Thar Baker, Zakaria Maamar, Rajkumar Buyya, Panos Liatsis, Wasiq Khan, Hissam Tawfik, Dhiya Al-Jumeily
Iot-Enabled Flood Severity Prediction Via Ensemble Machine Learning Models, Mohammed Khalaf, Haya Alaskar, Abir Jaafar Hussain, Thar Baker, Zakaria Maamar, Rajkumar Buyya, Panos Liatsis, Wasiq Khan, Hissam Tawfik, Dhiya Al-Jumeily
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© 2013 IEEE. River flooding is a natural phenomenon that can have a devastating effect on human life and economic losses. There have been various approaches in studying river flooding; however, insufficient understanding and limited knowledge about flooding conditions hinder the development of prevention and control measures for this natural phenomenon. This paper entails a new approach for the prediction of water level in association with flood severity using the ensemble model. Our approach leverages the latest developments in the Internet of Things (IoT) and machine learning for the automated analysis of flood data that might be useful to prevent …
Security Techniques For Intelligent Spam Sensing And Anomaly Detection In Online Social Platforms, Monther Aldwairi, Lo'ai Tawalbeh
Security Techniques For Intelligent Spam Sensing And Anomaly Detection In Online Social Platforms, Monther Aldwairi, Lo'ai Tawalbeh
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Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. The recent advances in communication and mobile technologies made it easier to access and share information for most people worldwide. Among the most powerful information spreading platforms are the Online Social Networks (OSN)s that allow Internet-connected users to share different information such as instant messages, tweets, photos, and videos. Adding to that many governmental and private institutions use the OSNs such as Twitter for official announcements. Consequently, there is a tremendous need to provide the required level of security for OSN users. However, there are many challenges due …
Selective Subtraction For Handheld Cameras, Adeel A. Bhutta, Imran Nazir Junejo, Hassan Foroosh
Selective Subtraction For Handheld Cameras, Adeel A. Bhutta, Imran Nazir Junejo, Hassan Foroosh
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© 2013 IEEE. Background subtraction techniques model the background of the scene using the stationarity property and classify the scene into two classes namely foreground and background. In doing so, most moving objects become foreground indiscriminately, except in dynamic scenes (such as those with some waving tree leaves, water ripples, or a water fountain), which are typically 'learned' as part of the background using a large training set of video data. We introduce a novel concept of background as the objects other than the foreground, which may include moving objects in the scene that cannot be learned from a training …
Intelligent Traffic Engineering In Software-Defined Vehicular Networking Based On Multi-Path Routing, Ahed Abugabah, Ahmad Ali Alzubi, Osama Alfarraj, Mohammed Al-Maitah, Waleed S. Alnumay
Intelligent Traffic Engineering In Software-Defined Vehicular Networking Based On Multi-Path Routing, Ahed Abugabah, Ahmad Ali Alzubi, Osama Alfarraj, Mohammed Al-Maitah, Waleed S. Alnumay
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© 2013 IEEE. This paper addresses traffic engineering (TE) issues in software-defined vehicular networking (SDVN). A brief analysis of the features of SDVN, which improves the efficiency of TE in SDVN, is presented. The feasibility of using multi-path routing with TE is substantiated. A procedure and an example of the formation of multiple routes based on a modified wave routing algorithm are given. Considering the features of the SDVN technology, a modified TE method is proposed, which reduces both the time complexity of forming multiple paths and the path reconfiguration time. The dynamic path reconfiguration algorithm is presented.
Contextual Healing: Privacy Through Interpretation Management, Fatma Outay, Rula Sayaf
Contextual Healing: Privacy Through Interpretation Management, Fatma Outay, Rula Sayaf
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Contextual privacy is an essential concept in social software communication. Managing privacy of data disclosed in social software dependence strongly on the context the data is disclosed in. The sheer amount of posts and audiences may lead to context ambiguity. Ambiguity can affect contextual privacy management and effective communication. Current contextual privacy management approaches can be either too complex to use, or too simple to offer fine-grained control. In many cases, it is challenging to strike a balance between effective control and ease-of-use. In this article, we analyse contextual privacy by in relation to context and communication. We examine a …
Uvis: A Formula-Based End-User Tool For Data Visualization, Mohammad Amin Amin Kuhail, Soren Lauesen
Uvis: A Formula-Based End-User Tool For Data Visualization, Mohammad Amin Amin Kuhail, Soren Lauesen
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© 2013 IEEE. Existing approaches to data visualization are one of these two: accessible to end-user developers but limited in customizability, or inaccessible and expressive. For instance, commercial charting tools are easy to use, but support only predefined visualizations, while programmatic visualization tools support custom visualizations, but require advanced programming skills. We show that it is possible to combine the learnability of charting tools and the expressiveness of visualization tools. Uvis is an interactive visualization and user interface design tool that targets end-user developers with skills comparable to spreadsheet formulas. With Uvis, designers drag and drop visual objects, set visual …
Enhanced Label Noise Filtering With Multiple Voting, Donghai Guan, Maqbool Hussain, Weiwei Yuan, Asad Masood Khattak, Muhammad Fahim, Wajahat Ali Khan
Enhanced Label Noise Filtering With Multiple Voting, Donghai Guan, Maqbool Hussain, Weiwei Yuan, Asad Masood Khattak, Muhammad Fahim, Wajahat Ali Khan
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© 2019 by the authors. Label noises exist in many applications, and their presence can degrade learning performance. Researchers usually use filters to identify and eliminate them prior to training. The ensemble learning based filter (EnFilter) is the most widely used filter. According to the voting mechanism, EnFilter is mainly divided into two types: single-voting based (SVFilter) and multiple-voting based (MVFilter). In general, MVFilter is more often preferred because multiple-voting could address the intrinsic limitations of single-voting. However, the most important unsolved issue in MVFilter is how to determine the optimal decision point (ODP). Conceptually, the decision point is a …
Fog Computing Enabling Industrial Internet Of Things: State-Of-The-Art And Research Challenges, Rabeea Basir, Saad Qaisar, Mudassar Ali, Monther Aldwairi, Muhammad Ikram Ashraf, Aamir Mahmood, Mikael Gidlund
Fog Computing Enabling Industrial Internet Of Things: State-Of-The-Art And Research Challenges, Rabeea Basir, Saad Qaisar, Mudassar Ali, Monther Aldwairi, Muhammad Ikram Ashraf, Aamir Mahmood, Mikael Gidlund
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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Industry is going through a transformation phase, enabling automation and data exchange in manufacturing technologies and processes, and this transformation is called Industry 4.0. Industrial Internet-of-Things (IIoT) applications require real-time processing, near-by storage, ultra-low latency, reliability and high data rate, all of which can be satisfied by fog computing architecture. With smart devices expected to grow exponentially, the need for an optimized fog computing architecture and protocols is crucial. Therein, efficient, intelligent and decentralized solutions are required to ensure real-time connectivity, reliability and green communication. In this paper, we provide a …
Follow-Up Decision Support Tool For Public Healthcare: A Design Research Perspective, Shah J. Miah, Najmul Hasan, John Gammack
Follow-Up Decision Support Tool For Public Healthcare: A Design Research Perspective, Shah J. Miah, Najmul Hasan, John Gammack
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© 2019, Korean Society of Medical Informatics. All rights reserved. Objectives: Mobile health (m-Health) technologies may provide an appropriate follow-up support service for patient groups with post-treatment conditions. While previous studies have introduced m-Health methods for patient care, a smart system that may provide follow-up communication and decision support remains limited to the management of a few specific types of diseases. This paper introduces an m-Health solution in the current climate of increased demand for electronic information exchange. Methods: Adopting a novel design science research approach, we developed an innovative solution model for post-treatment follow-up decision support interaction for use …
Dimensions Of 'Socio' Vulnerabilities Of Advanced Persistent Threats, Mathew Nicho, Christopher D. Mcdermott
Dimensions Of 'Socio' Vulnerabilities Of Advanced Persistent Threats, Mathew Nicho, Christopher D. Mcdermott
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© 2019 University of Split, FESB. Advanced Persistent Threats (APT) are highly targeted and sophisticated multi-stage attacks, utilizing zero day or near zero-day malware. Directed at internetworked computer users in the workplace, their growth and prevalence can be attributed to both socio (human) and technical (system weaknesses and inadequate cyber defenses) vulnerabilities. While many APT attacks incorporate a blend of socio-technical vulnerabilities, academic research and reported incidents largely depict the user as the prominent contributing factor that can weaken the layers of technical security in an organization. In this paper, our objective is to explore multiple dimensions of socio factors …
Cross-Company Customer Churn Prediction In Telecommunication: A Comparison Of Data Transformation Methods, Adnan Amin, Babar Shah, Asad Masood Khattak, Fernando Joaquim Lopes Moreira, Gohar Ali, Alvaro Rocha, Sajid Anwar
Cross-Company Customer Churn Prediction In Telecommunication: A Comparison Of Data Transformation Methods, Adnan Amin, Babar Shah, Asad Masood Khattak, Fernando Joaquim Lopes Moreira, Gohar Ali, Alvaro Rocha, Sajid Anwar
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© 2018 Elsevier Ltd Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, …
Triplet Loss Network For Unsupervised Domain Adaptation, Imad Eddine Ibrahim Bekkouch, Youssef Youssry, Rustam Gafarov, Adil Khan, Asad Masood Khattak
Triplet Loss Network For Unsupervised Domain Adaptation, Imad Eddine Ibrahim Bekkouch, Youssef Youssry, Rustam Gafarov, Adil Khan, Asad Masood Khattak
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© 2019 by the authors. Domain adaptation is a sub-field of transfer learning that aims at bridging the dissimilarity gap between different domains by transferring and re-using the knowledge obtained in the source domain to the target domain. Many methods have been proposed to resolve this problem, using techniques such as generative adversarial networks (GAN), but the complexity of such methods makes it hard to use them in different problems, as fine-tuning such networks is usually a time-consuming task. In this paper, we propose a method for unsupervised domain adaptation that is both simple and effective. Our model (referred to …
A Fina Világbajnokság (2017) Önkénteseinek Szerepe Budapest Sportturizmusában, Viktória Szenyéri, Gábor Michalkó, Anestis Fotiadis
A Fina Világbajnokság (2017) Önkénteseinek Szerepe Budapest Sportturizmusában, Viktória Szenyéri, Gábor Michalkó, Anestis Fotiadis
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Volunteers are indispensable in the organization of international mega sport events. Their activity is really important not only during these world-level meetings, but also after the competition has ended, as they play an important role in furthering the life of the events and in maintaining interest in the host location. Although the practice of volunteering in Hungary is still in its infancy, its social status and popularity are developing dynamically. The 2017 FINA Championships in Budapest is considered to be a milestone in the evolution of Hungarian volunteer work. The volunteers took part in a variety of roles in order …
The Security Of Big Data In Fog-Enabled Iot Applications Including Blockchain: A Survey, Noshina Tariq, Muhammad Asim, Feras Al-Obeidat, Muhammad Zubair Farooqi, Thar Baker, Mohammad Hammoudeh, Ibrahim Ghafir
The Security Of Big Data In Fog-Enabled Iot Applications Including Blockchain: A Survey, Noshina Tariq, Muhammad Asim, Feras Al-Obeidat, Muhammad Zubair Farooqi, Thar Baker, Mohammad Hammoudeh, Ibrahim Ghafir
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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The proliferation of inter-connected devices in critical industries, such as healthcare and power grid, is changing the perception of what constitutes critical infrastructure. The rising interconnectedness of new critical industries is driven by the growing demand for seamless access to information as the world becomes more mobile and connected and as the Internet of Things (IoT) grows. Critical industries are essential to the foundation of today’s society, and interruption of service in any of these sectors can reverberate through other sectors and even around the globe. In today’s hyper-connected world, the …
Compromised User Credentials Detection In A Digital Enterprise Using Behavioral Analytics, Saleh Shah, Babar Shah, Adnan Amin, Feras Al-Obeidat, Francis Chow, Fernando Joaquim Lopes Moreira, Sajid Anwar
Compromised User Credentials Detection In A Digital Enterprise Using Behavioral Analytics, Saleh Shah, Babar Shah, Adnan Amin, Feras Al-Obeidat, Francis Chow, Fernando Joaquim Lopes Moreira, Sajid Anwar
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© 2018 In today's digital age, the digital transformation is necessary for almost every competitive enterprise in terms of having access to the best resources and ensuring customer satisfaction. However, due to such rewards, these enterprises are facing key concerns around the risk of next-generation data security or cybercrime which is continually increasing issue due to the digital transformation four essential pillars—cloud computing, big data analytics, social and mobile computing. Data transformation-driven enterprises should ready to handle this next-generation data security problem, in particular, the compromised user credential (CUC). When an intruder or cybercriminal develops trust relationships as a legitimate …
Wireless Sensor Networks For Big Data Systems, Beom Su Kim, Ki Il Kim, Babar Shah, Francis Chow, Kyong Hoon Kim
Wireless Sensor Networks For Big Data Systems, Beom Su Kim, Ki Il Kim, Babar Shah, Francis Chow, Kyong Hoon Kim
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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Before discovering meaningful knowledge from big data systems, it is first necessary to build a data-gathering infrastructure. Among many feasible data sources, wireless sensor networks (WSNs) are rich big data sources: a large amount of data is generated by various sensor nodes in large-scale networks. However, unlike typical wireless networks, WSNs have serious deficiencies in terms of data reliability and communication owing to the limited capabilities of the nodes. Moreover, a considerable amount of sensed data are of no interest, meaningless, and redundant when a large number of sensor nodes is …
Enhancing The Teaching And Learning Process Using Video Streaming Servers And Forecasting Techniques, Raza Hasan, Sellappan Palaniappan, Salman Mahmood, Babar Shah, Ali Abbas, Kamal Uddin Sarker
Enhancing The Teaching And Learning Process Using Video Streaming Servers And Forecasting Techniques, Raza Hasan, Sellappan Palaniappan, Salman Mahmood, Babar Shah, Ali Abbas, Kamal Uddin Sarker
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© 2019 by the authors. Higher educational institutes (HEI) are adopting ubiquitous and smart equipment such as mobile devices or digital gadgets to deliver educational content in a more effective manner than the traditional approaches. In present works, a lot of smart classroom approaches have been developed, however, the student learning experience is not yet fully explored. Moreover, module historical data over time is not considered which could provide insight into the possible outcomes in the future, leading new improvements and working as an early detection method for the future results within the module. This paper proposes a framework by …
Emerging Insights Of Health Informatics Research: A Literature Analysis For Outlining New Themes, Shah Miah, Jun Shen, John W Lamp, Don Kerr, John Gammack
Emerging Insights Of Health Informatics Research: A Literature Analysis For Outlining New Themes, Shah Miah, Jun Shen, John W Lamp, Don Kerr, John Gammack
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This paper presents a contemporary literature review to provide insights into the current health informatics literature. The objective of this study is to identify emerging directions of current health informatics research from the latest and existing studies in the health informatics domain. We analyse existing health informatics studies using a thematic analysis, so that justified sets of research agenda can be outlined on the basis of these findings. We selected articles that are published in the science direct online database. The selected 73 sample articles (published from 2014 to 2018 in premier health informatics journals) are considered as representative samples …
Effective Evaluation Of The Non-Technical Skills In The Computing Discipline, Maurice Danaher, Kevin Schoepp, Ashley Ater Kranov
Effective Evaluation Of The Non-Technical Skills In The Computing Discipline, Maurice Danaher, Kevin Schoepp, Ashley Ater Kranov
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© 2019, Journal of Information Technology Eucation Research. Aim/Purpose Assessing non-technical skills is very difficult and current approaches typically assess the skills separately. There is a need for better quality assessment of these skills at undergraduate and postgraduate levels. Background A method has been developed for the computing discipline that assesses all six non-technical skills prescribed by ABET (Accreditation Board for Engineering and Technology), the accreditation board for engineering and technology. It has been shown to be a valid and reliable method for undergraduate students Methodology The method is based upon performance-based assessment where a team of students discuss and …