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Articles 1 - 30 of 11748

Full-Text Articles in Engineering

Advanced Inflatable De-Orbit Solutions For Derelict Satellites And Orbital Debris, Aman Chandra, Greg Wilburn, Jekan Thanga Feb 2019

Advanced Inflatable De-Orbit Solutions For Derelict Satellites And Orbital Debris, Aman Chandra, Greg Wilburn, Jekan Thanga

Space Traffic Management Conference

The exponential rise in small-satellites and CubeSats in Low Earth Orbit (LEO) poses important challenges for future space traffic management. At altitudes of 600 km and lower, aerodynamic drag accelerates de-orbiting of satellites. However, placement of satellites at higher altitudes required for constellations pose important challenges. The satellites will require on-board propulsion to lower their orbits to 600 km and let aerodynamic drag take-over. In this work we analyze solutions for de-orbiting satellites at altitudes of up to 3000 km. We consider a modular robotic de-orbit device that has stowed volume of a regular CubeSat. The de-orbit device would be ...


End To End Satellite Servicing And Space Debris Management, Aman Chandra, Himangshu Kalita, Roberto Furfaro, Jekan Thanga Feb 2019

End To End Satellite Servicing And Space Debris Management, Aman Chandra, Himangshu Kalita, Roberto Furfaro, Jekan Thanga

Space Traffic Management Conference

There is growing demand for satellite swarms and constellations for global positioning, remote sensing and relay communication in higher LEO orbits. This will result in many obsolete, damaged and abandoned satellites that will remain on-orbit beyond 25 years. These abandoned satellites and space debris maybe economically valuable orbital real-estate and resources that can be reused, repaired or upgraded for future use. Space traffic management is critical to repair damaged satellites, divert satellites into warehouse orbits and effectively deorbit satellites and space debris that are beyond repair and salvage. Current methods for on-orbit capture, servicing and repair require a large service ...


American Sign Language Recognition Using Machine Learning And Computer Vision, Kshitij Bantupalli, Ying Xie Feb 2019

American Sign Language Recognition Using Machine Learning And Computer Vision, Kshitij Bantupalli, Ying Xie

Master of Science in Computer Science Theses

Speech impairment is a disability which affects an individual’s ability to communicate using speech and hearing. People who are affected by this use other media of communication such as sign language. Although sign language is ubiquitous in recent times, there remains a challenge for non-sign language speakers to communicate with sign language speakers or signers. With recent advances in deep learning and computer vision there has been promising progress in the fields of motion and gesture recognition using deep learning and computer vision-based techniques. The focus of this work is to create a vision-based application which offers sign language ...


Visualising The Complex Features Of Source Code, Ivan Bacher Feb 2019

Visualising The Complex Features Of Source Code, Ivan Bacher

Doctoral

Software development is a complex undertaking composed of several activities that include reading, writing, and modifying source code. Indeed, previous studies have shown that the majority of the effort invested in software development is dedicated to understanding code. This includes understanding the static structure, dynamic behaviour, and evolution of the code. Given these particular characteristics, as well as the high complexity of source code, it is reasonable to consider how visualisation can facilitate source code understanding. This work proposes to extend existing software development tools with visualisations that can be used to encode the various complex features within a source ...


State Feedback Of Complex Systems Using Fuzzy Cognitive Maps, Vassiliki Mpelogianni, Ioannis Arvanitakis, Peter P. Groumpos Feb 2019

State Feedback Of Complex Systems Using Fuzzy Cognitive Maps, Vassiliki Mpelogianni, Ioannis Arvanitakis, Peter P. Groumpos

International Journal of Business and Technology

Complex systems have become a research area with increasing interest over the last years. The emergence of new technologies, the increase in computational power with reduced resources and cost, the integration of the physical world with computer based systems has created the possibility of significantly improving the quality of life of humans. While a significant degree of automation within these systems exists and has been provided in the past decade with examples of the smart homes and energy efficient buildings, a paradigm shift towards autonomy has been noted. The need for autonomy requires the extraction of a model; while a ...


Maturity Level Of Kosovo Manufacturing Industry With Regard To Industry 4.0, Fatmir Azemi, Edmond Hajrizi, Bekim Maloku Feb 2019

Maturity Level Of Kosovo Manufacturing Industry With Regard To Industry 4.0, Fatmir Azemi, Edmond Hajrizi, Bekim Maloku

International Journal of Business and Technology

In this paper the concept of Maturity Level of Kosovo Industry will be presented according to the Industry 4.0. Digitalization of factory has impact the entire business environment and lead to Smart Enterprises. To create a model of Smart Factory, first we have analyzed the existing situation of Kosovo Manufacturing Industry with regard to revolution of Industry. In this paper we will describe the results of a recent research at the Kosovo manufacturing companies and are included metalworking and furniture industry, where is developed a Maturity Level for Kosovo Industry. To describe the Maturity Level of Kosovo Industry we ...


Decision Making Based On Data Analyses Using Data Warehouses, Valdrin Haxhiu Feb 2019

Decision Making Based On Data Analyses Using Data Warehouses, Valdrin Haxhiu

International Journal of Business and Technology

Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a transformation process in order ...


Characteristics And Temporal Behavior Of Internet Backbone Traffic, Artan Salihu, Muharrem Shefkiu, Arianit Maraj Feb 2019

Characteristics And Temporal Behavior Of Internet Backbone Traffic, Artan Salihu, Muharrem Shefkiu, Arianit Maraj

International Journal of Business and Technology

With the rapid increase demand for data usage, Internet has become complex and harder to analyze. Characterizing the Internet traffic might reveal information that are important for Network Operators to formulate policy decisions, develop techniques to detect network anomalies, help better provision network resources (capacity, buffers) and use workload characteristics for simulations (typical packet sizes, flow durations, common protocols).

In this paper, using passive monitoring and measurements, we show collected data traffic at Internet backbone routers. First, we reveal main observations on patterns and characteristics of this dataset including packet sizes, traffic volume for inter and intra domain and protocol ...


Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa Feb 2019

Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa

International Journal of Business and Technology

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s ...


A Need For An Integrative Security Model For Semantic Stream Reasoning Systems, Admirim Aliti, Edmond Jajaga, Kozeta Sevrani Feb 2019

A Need For An Integrative Security Model For Semantic Stream Reasoning Systems, Admirim Aliti, Edmond Jajaga, Kozeta Sevrani

International Journal of Business and Technology

State-of-the-art security frameworks have been extensively addressing security issues for web resources, agents and services in the Semantic Web. The provision of Stream Reasoning as a new area spanning Semantic Web and Data Stream Management Systems has eventually opened up new challenges. Namely, their decentralized nature, the metadata descriptions, the number of users, agents, and services, make securing Stream Reasoning systems difficult to handle. Thus, there is an inherent need of developing new security models which will handle security and automate security mechanisms to a more autonomous system that supports complex and dynamic relationships between data, clients and service providers ...


Clinical Research In Pneumonia: Role Of Artificial Intelligence, Timothy L. Wiemken, Robert R. Kelley, William A. Mattingly, Julio A. Ramirez Feb 2019

Clinical Research In Pneumonia: Role Of Artificial Intelligence, Timothy L. Wiemken, Robert R. Kelley, William A. Mattingly, Julio A. Ramirez

The University of Louisville Journal of Respiratory Infections

No abstract provided.


Towards Multi-Lingual Pneumonia Research Data Collection Using The Community-Acquired Pneumonia International Cohort Study Database, William A. Mattingly, Kimberley A. Buckner, Senen Pena Feb 2019

Towards Multi-Lingual Pneumonia Research Data Collection Using The Community-Acquired Pneumonia International Cohort Study Database, William A. Mattingly, Kimberley A. Buckner, Senen Pena

The University of Louisville Journal of Respiratory Infections

Background: Although multilingual interfaces are preferred by most users when they have a choice, organizations are often unable to support and troubleshoot problems involving multiple user languages. Software that has been structured with multiple languages and data interlinking considerations early in its development is more likely to be easily maintained. We describe the process of adding multilingual support to the CAPO international Cohort study database using REDCap.

Methods: Using Google Translate API we extend the supported Spanish language version of REDCap to the most recent version used by CAPO, 8.1.4. We then translate the English data dictionary for ...


The Scientific Information Exchange General Model At Digital Library Context: Internet Of Things, Nayere Soleimanzade, Asefeh Asemi, Mozafar Cheshmehsohrabi, Ahmad Shabani Jan 2019

The Scientific Information Exchange General Model At Digital Library Context: Internet Of Things, Nayere Soleimanzade, Asefeh Asemi, Mozafar Cheshmehsohrabi, Ahmad Shabani

Library Philosophy and Practice (e-journal)

Introduction: This paper aims to develop a Scientific Information Exchange General Model at Digital Library in Context of Internet of things, which would enable automated and efficient library services. To accomplish its objective, the main classes (Concepts), sub-classes, attributes are identified in order to introduce an appropriate model.

Methodology: The approach of this study is basic, exploratory, and developmental and is run through a mixed method consisting of documentary, Delphi, and data modeling methods. The study population in the documentary section includes the study of information resources retrieved in related subjects. The study population in the Delphi section is consist ...


Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels Jan 2019

Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels

SMU Data Science Review

As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as ...


Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal Jan 2019

Comparative Study Of Sentiment Analysis With Product Reviews Using Machine Learning And Lexicon-Based Approaches, Heidi Nguyen, Aravind Veluchamy, Mamadou Diop, Rashed Iqbal

SMU Data Science Review

In this paper, we present a comparative study of text sentiment classification models using term frequency inverse document frequency vectorization in both supervised machine learning and lexicon-based techniques. There have been multiple promising machine learning and lexicon-based techniques, but the relative goodness of each approach on specific types of problems is not well understood. In order to offer researchers comprehensive insights, we compare a total of six algorithms to each other. The three machine learning algorithms are: Logistic Regression (LR), Support Vector Machine (SVM), and Gradient Boosting. The three lexicon-based algorithms are: Valence Aware Dictionary and Sentiment Reasoner (VADER), Pattern ...


Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater Jan 2019

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide ...


Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche Jan 2019

Project Insight: A Granular Approach To Enterprise Cybersecurity, Sunna Quazi, Adam Baca, Sam Darsche

SMU Data Science Review

In this paper, we disambiguate risky activity corporate users are propagating with their software in real time by creating an enterprise security visualization solution for system administrators. The current problem in this domain is the lag in cyber intelligence that inhibits preventative security measure execution. This is partially due to the overemphasis of network activity, which is a nonfinite dataset and is difficult to comprehensively ingest with analytics. We address these concerns by elaborating on the beta of a software called "Insight" created by Felix Security. The overall solution leverages endpoint data along with preexisting whitelist/blacklist designations to unambiguously ...


A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), Basel Magableh Jan 2019

A Deep Recurrent Q Network Towards Self-Adapting Distributed Microservices Architecture (In Press), Basel Magableh

Articles

One desired aspect of microservices architecture is the ability to self-adapt its own architecture and behaviour in response to changes in the operational environment. To achieve the desired high levels of self-adaptability, this research implements the distributed microservices architectures model, as informed by the MAPE-K model. The proposed architecture employs a multi adaptation agents supported by a centralised controller, that can observe the environment and execute a suitable adaptation action. The adaptation planning is managed by a deep recurrent Q-network (DRQN). It is argued that such integration between DRQN and MDP agents in a MAPE-K model offers distributed microservice architecture ...


The St. Chad Gospels: Diachronic Manuscript Registration And Visualization, Stephen Parsons, C. Seth Parker, W. Brent Seales Jan 2019

The St. Chad Gospels: Diachronic Manuscript Registration And Visualization, Stephen Parsons, C. Seth Parker, W. Brent Seales

Manuscript Studies

This paper presents a software framework for the registration and visualization of layered image sets. To demonstrate the utility of these tools, we apply them to the St. Chad Gospels manuscript, relying on images of each page of the document as it appeared over time. An automated pipeline is used to perform non-rigid registration on each series of images. To visualize the differences between copies of the same page, a registered image viewer is constructed that enables direct comparisons of registered images. The registration pipeline and viewer for the resulting aligned images are generalized for use with other data sets.


Lowering Legal Barriers To Rpki Adoption, Christopher S. Yoo, David A. Wishnick Jan 2019

Lowering Legal Barriers To Rpki Adoption, Christopher S. Yoo, David A. Wishnick

Faculty Scholarship at Penn Law

Across the Internet, mistaken and malicious routing announcements impose significant costs on users and network operators. To make routing announcements more reliable and secure, Internet coordination bodies have encouraged network operators to adopt the Resource Public Key Infrastructure (“RPKI”) framework. Despite this encouragement, RPKI’s adoption rates are low, especially in North America.

This report presents the results of a year-long investigation into the hypothesis—widespread within the network operator community—that legal issues pose barriers to RPKI adoption and are one cause of the disparities between North America and other regions of the world. On the basis of interviews ...


An Automated Negotiation System For Ecommerce Store Owners To Enable Flexible Product Pricing, Jake O'Halloran Jan 2019

An Automated Negotiation System For Ecommerce Store Owners To Enable Flexible Product Pricing, Jake O'Halloran

Dissertations

If a store owner wishes to sell a product online, they traditionally have two options for deciding on a price. They can sell the product at a fixesd price like the products sold on sites like Amazon, or they can put the product in an auction and let demand from customers drive the final sales price like the products sold on sites like eBay. Both options have their pros and cons. An alternative option for deciding on a final sales price for the product is to enable negotiation on the product. With this, there is a dynamic nature to the ...


Predicting Customer Retention Of An App-Based Business Using Supervised Machine Learning, Jeswin Jose Jan 2019

Predicting Customer Retention Of An App-Based Business Using Supervised Machine Learning, Jeswin Jose

Dissertations

Identification of retainable customers is very essential for the functioning and growth of any business. An effective identification of retainable customers can help the business to identify the reasons of retention and plan their marketing strategies accordingly. This research is aimed at developing a machine learning model that can precisely predict the retainable customers from the total customer data of an e-learning business. Building predictive models that can efficiently classify imbalanced data is a major challenge in data mining and machine learning. Most of the machine learning algorithms deliver a suboptimal performance when introduced to an imbalanced dataset. A variety ...


The Next-Generation Retail Electricity Market In The Context Of Distributed Energy Resources: Vision And Integrating Framework, Josue Campos Do Prado, Wei Qiao, Liyan Qu, Julio Romero Aguero Jan 2019

The Next-Generation Retail Electricity Market In The Context Of Distributed Energy Resources: Vision And Integrating Framework, Josue Campos Do Prado, Wei Qiao, Liyan Qu, Julio Romero Aguero

Faculty Publications from the Department of Electrical and Computer Engineering

The increasing adoption of distributed energy resources (DERs) and smart grid technologies (SGTs) by end-user retail customers is changing significantly both technical and economic operations in the distribution grid. The next-generation retail electricity market will promote decentralization, efficiency, and competitiveness by accommodating existing and new agents through new business models and transactive approaches in an advanced metering infrastructure (AMI). However, these changes will bring several technical challenges to be addressed in transmission and distribution systems. Considerable activities have been carried out worldwide to study the impacts of integrating DERs into the grid and in the wholesale electricity market. However, the ...


Analyzing Twitter Feeds To Facilitate Crises Informatics And Disaster Response During Mass Emergencies, Arshdeep Kaur Jan 2019

Analyzing Twitter Feeds To Facilitate Crises Informatics And Disaster Response During Mass Emergencies, Arshdeep Kaur

Dissertations

It is a common practice these days for general public to use various micro-blogging platforms, predominantly Twitter, to share ideas, opinions and information about things and life. Twitter is also being increasingly used as a popular source of information sharing during natural disasters and mass emergencies to update and communicate the extent of the geographic phenomena, report the affected population and casualties, request or provide volunteering services and to share the status of disaster recovery process initiated by humanitarian-aid and disaster-management organizations. Recent research in this area has affirmed the potential use of such social media data for various disaster ...


Augmenting American Fuzzy Lop To Increase The Speed Of Bug Detection, Raviraj Mahajan Jan 2019

Augmenting American Fuzzy Lop To Increase The Speed Of Bug Detection, Raviraj Mahajan

Dissertations

Whitebox fuzz testing is a vital part of the software testing process in the software development life cycle (SDLC). It is used for bug detection and security vulnerability checking as well. But current tools lack the ability to detect all the bugs and cover the entire code under test in a reasonable time. This study will explore some of the various whitebox fuzzing techniques and tools (AFL, SAGE, Driller, etc.) currently in use followed by a discussion of their strategies and the challenges facing them. One of the most popular state-of-the-art fuzzers, American Fuzzy Lop (AFL) will be discussed in ...


An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari Jan 2019

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari

Dissertations

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner's experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating ...


Investigation Into The Perceptually Informed Data For Environmental Sound Recognition, Chenglin Kang Jan 2019

Investigation Into The Perceptually Informed Data For Environmental Sound Recognition, Chenglin Kang

Dissertations

Environmental sound is rich source of information that can be used to infer contexts. With the rise in ubiquitous computing, the desire of environmental sound recognition is rapidly growing. Primarily, the research aims to recognize the environmental sound using the perceptually informed data. The initial study is concentrated on understanding the current state-of-the-art techniques in environmental sound recognition. Then those researches are evaluated by a critical review of the literature. This study extracts three sets of features: Mel Frequency Cepstral Coefficients, Mel-spectrogram and sound texture statistics. Two kinds machine learning algorithms are cooperated with appropriate sound features. The models are ...


Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell Jan 2019

Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell

International Journal of Applied Management and Technology

Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to ...


Should Robots Prosecute And Defend?, Stephen E. Henderson Dec 2018

Should Robots Prosecute And Defend?, Stephen E. Henderson

Stephen E Henderson

Even when we achieve the ‘holy grail’ of artificial intelligence—machine intelligence that is at least as smart as a human being in every area of thought—there may be classes of decisions for which it is intrinsically important to retain a human in the loop. On the common account of American criminal adjudication, the role of prosecutor seems to include such decisions given the largely unreviewable declination authority, whereas the role of defense counsel would seem fully susceptible of automation. Even for the prosecutor, the benefits of automation might outweigh the intrinsic decision-making loss, given that the ultimate decision ...


Behind Emammal’S Success: A Data Curator With A Data Standard, Jennifer Y. Zhao, William J. Mcshea Dec 2018

Behind Emammal’S Success: A Data Curator With A Data Standard, Jennifer Y. Zhao, William J. Mcshea

Journal of eScience Librarianship

This paper explores the data challenges of a major collection method in the field of ecology: using infrared-activated cameras to detect wildlife. One such solution, eMammal, is now available to address these struggles. We delineate the key reason behind its success: a data curator who manages an established data standard and communicates with eMammal’s users and stakeholders. We outline the tasks of this data curator, mention how they can work with data librarians, and demonstrate that the data curator position is already applicable in several biological science fields with a few examples. We end by emphasizing the growth of ...