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Articles 31 - 57 of 57
Full-Text Articles in Physical Sciences and Mathematics
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 …
A Review Of Challenges And Barriers Implementing Rfid Technology In The Healthcare Sector, Ahed Abugabah, Nishara Nizamuddin, Alaa Abuqabbeh
A Review Of Challenges And Barriers Implementing Rfid Technology In The Healthcare Sector, Ahed Abugabah, Nishara Nizamuddin, Alaa Abuqabbeh
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© 2020 The Authors. Published by Elsevier B.V.All rights reserved. The healthcare industry is progressively involved in adopting new technologies to provide improved quality of care given to patients. The implementation of RFID technology has globally impacted several industries and this revolution has improved the aspects of service delivery in the healthcare industry as well. The RFID technology has the potential to track medical assets and interact with almost any of the medical devices, pharmaceutical materials, IT equipment, or individual patients, deployed in hospitals all over the world. The motivation behind this paper is to investigate the advantages and obstacles …
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 …
Scalable And Secure Big Data Iot System Based On Multifactor Authentication And Lightweight Cryptography, Saleh Atiewi, Amer Al-Rahayfeh, Muder Almiani, Salman Yussof, Omar Alfandi, Ahed Abugabah, Yaser Jararweh
Scalable And Secure Big Data Iot System Based On Multifactor Authentication And Lightweight Cryptography, Saleh Atiewi, Amer Al-Rahayfeh, Muder Almiani, Salman Yussof, Omar Alfandi, Ahed Abugabah, Yaser Jararweh
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© 2013 IEEE. Organizations share an evolving interest in adopting a cloud computing approach for Internet of Things (IoT) applications. Integrating IoT devices and cloud computing technology is considered as an effective approach to storing and managing the enormous amount of data generated by various devices. However, big data security of these organizations presents a challenge in the IoT-cloud architecture. To overcome security issues, we propose a cloud-enabled IoT environment supported by multifactor authentication and lightweight cryptography encryption schemes to protect big data system. The proposed hybrid cloud environment is aimed at protecting organizations' data in a highly secure manner. …
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 …
A Novel Computer-Aided Diagnosis System For The Early Detection Of Hypertension Based On Cerebrovascular Alterations, Heba Kandil, Ahmed Soliman, Fatma Taher, Mohammed Ghazal, Ashraf Khalil, Guruprasad Giridharan, Robert Keynton, J. Richard Jennings, Ayman El-Baz
A Novel Computer-Aided Diagnosis System For The Early Detection Of Hypertension Based On Cerebrovascular Alterations, Heba Kandil, Ahmed Soliman, Fatma Taher, Mohammed Ghazal, Ashraf Khalil, Guruprasad Giridharan, Robert Keynton, J. Richard Jennings, Ayman El-Baz
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© 2019 The Authors Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanometer are widely used to diagnose hypertension, they could not predict the disease before its onset. Clinical studies suggest that alterations in the structure of human brains’ cerebrovasculature start to develop years before the onset of hypertension. In this research, we present a novel computer-aided diagnosis (CAD) system for the early detection of hypertension. The proposed CAD system analyzes magnetic resonance angiography (MRA) data of human brains to detect and track the cerebral vascular alterations and this is achieved using …
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 …
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 …
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 …
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.
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 …
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 …
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. …
Framework For Examination Of Software Quality Characteristics In Conflict: A Security And Usability Exemplar, Bilal Naqvi, Ahmed Seffah, Alain Abran
Framework For Examination Of Software Quality Characteristics In Conflict: A Security And Usability Exemplar, Bilal Naqvi, Ahmed Seffah, Alain Abran
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© 2020, © 2020 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. Standards and best practices for software quality guide on handling each quality characteristic individually, but not when two or more characteristics come into conflict such as security and usability. The objectives of this paper are twofold: (a) to argue on the importance of handling the conflicts between quality characteristics in general; (b) to formulate a framework for conflict examination of the software quality characteristics, we do so while considering the specific case of security and usability. In line with the …
Applications Of Bi-Framelet Systems For Solving Fractional Order Differential Equations, Mutaz Mohammad, Carlo Cattani
Applications Of Bi-Framelet Systems For Solving Fractional Order Differential Equations, Mutaz Mohammad, Carlo Cattani
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© 2020 CSIRO Framelets and their attractive features in many disciplines have attracted a great interest in the recent years. This paper intends to show the advantages of using bi-framelet systems in the context of numerical fractional differential equations (FDEs). We present a computational method based on the quasi-affine bi-framelets with high vanishing moments constructed using the generalized (mixed) oblique extension principle. We use this system for solving some types of FDEs by solving a series of important examples of FDEs related to many mathematical applications. The quasi-affine bi-framelet-based methods for numerical FDEs show the advantages of using sparse matrices …
Bodacious-Instance Coverage Mechanism For Wireless Sensor Network, Shahzad Ashraf, Omar Alfandi, Arshad Ahmad, Asad Masood Khattak, Bashir Hayat, Kyong Hoon Kim, Ayaz Ullah
Bodacious-Instance Coverage Mechanism For Wireless Sensor Network, Shahzad Ashraf, Omar Alfandi, Arshad Ahmad, Asad Masood Khattak, Bashir Hayat, Kyong Hoon Kim, Ayaz Ullah
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Copyright © 2020 Shahzad Ashraf et al. Due to unavoidable environmental factors, wireless sensor networks are facing numerous tribulations regarding network coverage. These arose due to the uncouth deployment of the sensor nodes in the wireless coverage area that ultimately degrades the performance and confines the coverage range. In order to enhance the network coverage range, an instance (node) redeployment-based Bodacious-instance Coverage Mechanism (BiCM) is proposed. The proposed mechanism creates new instance positions in the coverage area. It operates in two stages; in the first stage, it locates the intended instance position through the Dissimilitude Enhancement Scheme (DES) and moves …
Business Process Specification, Verification, And Deployment In A Mono-Cloud, Multi-Edge Context, Saoussen Cheikhrouhou, Slim Kallel, Ikbel Guidara, Zakaria Maamar
Business Process Specification, Verification, And Deployment In A Mono-Cloud, Multi-Edge Context, Saoussen Cheikhrouhou, Slim Kallel, Ikbel Guidara, Zakaria Maamar
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© 2020, ComSIS Consortium. All rights reserved. Despite the prevalence of cloud and edge computing, ensuring the satisfaction of time-constrained business processes, remains challenging. Indeed, some cloud/edge-based resources might not be available when needed leading to delaying the execution of these processes’ tasks and/or the transfer of these processes’ data. This paper presents an approach for specifying, verifying, and deploying time-constrained business processes in a mono-cloud, multi-edge context. First, the specification and verification of processes happen at design-time and run-time to ensure that these processes’ tasks and data are continuously placed in a way that would mitigate the violation of …
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 …
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 …
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 …
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 …
Investigating Bias In Facial Analysis Systems: A Systematic Review, Ashraf Khalil, Soha Glal Ahmed, Asad Masood Khattak, Nabeel Al-Qirim
Investigating Bias In Facial Analysis Systems: A Systematic Review, Ashraf Khalil, Soha Glal Ahmed, Asad Masood Khattak, Nabeel Al-Qirim
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© 2013 IEEE. Recent studies have demonstrated that most commercial facial analysis systems are biased against certain categories of race, ethnicity, culture, age and gender. The bias can be traced in some cases to the algorithms used and in other cases to insufficient training of algorithms, while in still other cases bias can be traced to insufficient databases. To date, no comprehensive literature review exists which systematically investigates bias and discrimination in the currently available facial analysis software. To address the gap, this study conducts a systematic literature review (SLR) in which the context of facial analysis system bias is …
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.
Explicit Determinantal Formula For A Class Of Banded Matrices, Yerlan Amanbek, Zhibin Du, Yogi Erlangga, Carlos M. Da Fonseca, Bakytzhan Kurmanbek, António Pereira
Explicit Determinantal Formula For A Class Of Banded Matrices, Yerlan Amanbek, Zhibin Du, Yogi Erlangga, Carlos M. Da Fonseca, Bakytzhan Kurmanbek, António Pereira
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© 2020 Yerlan Amanbek et al., published by De Gruyter 2020. In this short note, we provide a brief proof for a recent determinantal formula involving a particular family of banded matrices.
Benzimidazole Containing Acetamide Derivatives Attenuate Neuroinflammation And Oxidative Stress In Ethanol-Induced Neurodegeneration, Muhammad Imran, Lina Tariq Al Kury, Humaira Nadeem, Fawad Ali Shah, Muzaffar Abbas, Shagufta Naz, Arif Ullah Khan, Shupeng Li
Benzimidazole Containing Acetamide Derivatives Attenuate Neuroinflammation And Oxidative Stress In Ethanol-Induced Neurodegeneration, Muhammad Imran, Lina Tariq Al Kury, Humaira Nadeem, Fawad Ali Shah, Muzaffar Abbas, Shagufta Naz, Arif Ullah Khan, Shupeng Li
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© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Oxidative stress-induced neuroinflammation is the prominent feature of neurodegenerative disorders, and is characterized by a gradual decline of structure and function of neurons. Many biochemical events emerge thanks to the result of this neurodegeneration, and ultimately provoke neuroinflammation, activation of microglia, and oxidative stress, leading to neuronal death. This cascade not only explains the complexity of events taking place across different stages, but also depicts the need for more effective therapeutic agents. The present study was designed to investigate the neuroprotective effects of newly synthesized benzimidazole containing acetamide derivatives, 3a (2-(4-methoxyanilino)-N-[1-(4-methylbenzene-1-sulfonyl)-1H-benzimidazol-2-yl] …