Open Access. Powered by Scholars. Published by Universities.®

OS and Networks Commons

Open Access. Powered by Scholars. Published by Universities.®

1289 Full-Text Articles 1379 Authors 259401 Downloads 79 Institutions

All Articles in OS and Networks

Faceted Search

1289 full-text articles. Page 1 of 35.

Understanding Inactive Yet Available Assignees In Github, Jing JIANG, David LO, Xinyu MA, Fuli FENG, Li ZHANG 2017 Singapore Management University

Understanding Inactive Yet Available Assignees In Github, Jing Jiang, David Lo, Xinyu Ma, Fuli Feng, Li Zhang

Research Collection School Of Information Systems

Context In GitHub, an issue or a pull request can be assigned to a specific assignee who is responsible for working on this issue or pull request. Due to the principle of voluntary participation, available assignees may remain inactive in projects. If assignees ever participate in projects, they are active assignees; otherwise, they are inactive yet available assignees (inactive assignees for short). Objective Our objective in this paper is to provide a comprehensive analysis of inactive yet available assignees in GitHub. Method We collect 2,374,474 records of activities in 37 popular projects, and 797,756 records of activities ...


Network Technologies Used To Aggregate Environmental Data, Paul Stasiuk, Konstantin Läufer, George K. Thiruvathukal 2017 Loyola University Chicago

Network Technologies Used To Aggregate Environmental Data, Paul Stasiuk, Konstantin Läufer, George K. Thiruvathukal

Konstantin Läufer

The goal of the Loyola Weather Service (lws) project is to design and build a system of functioning environmental monitoring widgets that can intelligently and autonomously control the environment around them based on set thresholds and triggers. The widgets will also have the ability to aggregate their data and easily display this data in various ways: through a user interface in the room that the widget is placed, via a web application, and programmatically via a RESTful web service.


Building Capable, Energy-Efficient, Flexible Visualization And Sensing Clusters From Commodity Tablets, Thomas Delgado Dias, Xian Yan, Konstantin Läufer, George K. Thiruvathukal 2017 Loyola University Chicago

Building Capable, Energy-Efficient, Flexible Visualization And Sensing Clusters From Commodity Tablets, Thomas Delgado Dias, Xian Yan, Konstantin Läufer, George K. Thiruvathukal

Konstantin Läufer

We explore the application of clusters of commodity tablet devices to problems spanning a “trilogy” of concerns: visualization, sensing, and computation. We conjecture that such clusters provide a low-cost, energy-efficient, flexible, and ultimately effective platform to tackle a wide range of problems within this trilogy. This is a work in progress, and we now elaborate our position and give a preliminary status report.

A wide range of Android tablet devices are available in terms of price and capabilities. “You get what you pay for” w.r.t. display resolution, sensors, and chipset---corresponding to the trilogy. $200 gets one a 1280x800-pixel ...


Discovering Explanatory Models To Identify Relevant Tweets On Zika, RoopTeja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine 2017 Wright State University - Main Campus

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Tanvi Banerjee

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the ...


A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran 2017 Wright State University - Main Campus

A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

Amit P. Sheth

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test ...


What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, And Prevention, Michele Miller, Tanvi Banerjee, RoopTeja Muppalla, William L. Romine, Amit Sheth 2017 Wright State University - Main Campus

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, And Prevention, Michele Miller, Tanvi Banerjee, Roopteja Muppalla, William L. Romine, Amit Sheth

Amit P. Sheth

Background: In order to harness what people are tweeting about Zika, there needs to be a computational framework that leverages machine learning techniques to recognize relevant Zika tweets and, further, categorize these into disease-specific categories to address specific societal concerns related to the prevention, transmission, symptoms, and treatment of Zika virus.

Objective: The purpose of this study was to determine the relevancy of the tweets and what people were tweeting about the 4 disease characteristics of Zika: symptoms, transmission, prevention, and treatment.

Methods: A combination of natural language processing and machine learning techniques was used to determine what people were ...


Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor 2017 The Graduate Center, City University of New York

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

All Graduate Works by Year: Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world ...


Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica 2017 University of Arkansas, Fayetteville

Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica

Theses and Dissertations

Operating system (OS) identification tools, sometimes called fingerprinting tools, are essential for the reconnaissance phase of penetration testing. While OS identification is traditionally performed by passive or active tools that use fingerprint databases, very little work has focused on using machine learning techniques. Moreover, significantly more work has focused on IPv4 than IPv6. We introduce a collaborative neural network ensemble that uses a unique voting system and a random forest ensemble to deliver accurate predictions. This approach uses IPv6 features as well as packet metadata features for OS identification. Our experiment shows that our approach is valid and we achieve ...


Transaction Cost Optimization For Online Portfolio Selection, Bin LI, Jialei WANG, Dingjiang HUANG, Steven C. H. HOI 2017 Singapore Management University

Transaction Cost Optimization For Online Portfolio Selection, Bin Li, Jialei Wang, Dingjiang Huang, Steven C. H. Hoi

Research Collection School Of Information Systems

To improve existing online portfolio selection strategies in the case of non-zero transaction costs, we propose a novel framework named Transaction Cost Optimization (TCO). The TCO framework incorporates the L1 norm of the difference between two consecutive allocations together with the principles of maximizing expected log return. We further solve the formulation via convex optimization, and obtain two closed-form portfolio update formulas, which follow the same principle as Proportional Portfolio Rebalancing (PPR) in industry. We empirically evaluate the proposed framework using four commonly used data-sets. Although these data-sets do not consider delisted firms and are thus subject to survival bias ...


Transaction Cost Optimization For Online Portfolio Selection, Bin LI, Jialei WANG, Dingjiang HUANG, Steven C. H. HOI 2017 Singapore Management University

Transaction Cost Optimization For Online Portfolio Selection, Bin Li, Jialei Wang, Dingjiang Huang, Steven C. H. Hoi

Research Collection School Of Information Systems

To improve existing online portfolio selection strategies in the case of non-zero transaction costs, we propose a novel framework named Transaction Cost Optimization (TCO). The TCO framework incorporates the L1 norm of the difference between two consecutive allocations together with the principles of maximizing expected log return. We further solve the formulation via convex optimization, and obtain two closed-form portfolio update formulas, which follow the same principle as Proportional Portfolio Rebalancing (PPR) in industry. We empirically evaluate the proposed framework using four commonly used data-sets. Although these data-sets do not consider delisted firms and are thus subject to survival bias ...


Discovering Explanatory Models To Identify Relevant Tweets On Zika, RoopTeja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine 2017 Wright State University - Main Campus

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Kno.e.sis Publications

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the ...


Automated Android Application Permission Recommendation, Lingfeng BAO, David LO, Xin XIA 2017 Singapore Management University

Automated Android Application Permission Recommendation, Lingfeng Bao, David Lo, Xin Xia

Research Collection School Of Information Systems

The number of Android applications has increased rapidly as Android is becoming the dominant platform in the smartphone market. Security and privacy are key factors for an Android application to be successful. Android provides a permission mechanism to ensure security and privacy. This permission mechanism requires that developers declare the sensitive resources required by their applications. On installation or during runtime, users are required to agree with the permission request. However, in practice, there are numerous popular permission misuses, despite Android introducing official documents stating how to use these permissions properly. Some data mining techniques (e.g., association rule mining ...


Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli YANG, David LO, Xin XIA, Jianling SUN 2017 Singapore Management University

Tlel: A Two-Layer Ensemble Learning Approach For Just-In-Time Defect Prediction, Xinli Yang, David Lo, Xin Xia, Jianling Sun

Research Collection School Of Information Systems

Context:Defect prediction is a very meaningful topic, particularly at change-level. Change-level defectprediction, which is also referred as just-in-time defect prediction, could not only ensure software qualityin the development process, but also make the developers check and fix the defects in time [1].Objective: Ensemble learning becomes a hot topic in recent years. There have been several studies aboutapplying ensemble learning to defect prediction [2–5]. Traditional ensemble learning approaches onlyhave one layer, i.e., they use ensemble learning once. There are few studies that leverages ensemblelearning twice or more. To bridge this research gap, we try to hybridize various ...


How Technology Is Reshaping Financial Services: Essays On Consumer Behavior In Card, Channel And Cryptocurrency Services, Dan GENG 2017 Singapore Management University

How Technology Is Reshaping Financial Services: Essays On Consumer Behavior In Card, Channel And Cryptocurrency Services, Dan Geng

Dissertations and Theses Collection

The financial services sector has seen dramatic technological innovations in the last several years associated with the “fintech revolution.” Major changes have taken place in channel management, credit card rewards marketing, cryptocurren-cy, and wealth management, and have influenced consumers’ banking behavior in different ways. As a consequence, there has been a growing demand for banks to rethink their business models and operations to adapt to changing consumer be-havior and counter the competitive pressure from other banks and non-bank play-ers. In this dissertation, I study consumer behavior related to different aspects of financial innovation by addressing research questions that are motivated ...


A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, RoopTeja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth 2017 Wright State University - Main Campus

A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, Roopteja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth

Kno.e.sis Publications

With the rapid increase in urban development, it is critical to utilize dynamic sensor streams for traffic understanding, especially in larger cities where route planning or infrastructure planning is more critical. This creates a strong need to understand traffic patterns using ubiquitous sensors to allow city officials to be better informed when planning urban construction and to provide an understanding of the traffic dynamics in the city. In this study, we propose our framework ITSKG (Imagery-based Traffic Sensing Knowledge Graph) which utilizes the stationary traffic camera information as sensors to understand the traffic patterns. The proposed system extracts image-based features ...


Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis-A Framework For Intelligent Routing In Large Communication Networks., Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

An Object Oriented Approach To Modeling And Simulation Of Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

The complexity (number of entities, interactions between entities, and resulting emergent dynamic behavior) of large communication environments which contain hundreds of nodes and links make simulation an important tool for the study of such systems. Given the difficulties associated with complete analytical treatment of complex dynamical systems, it is often the only practical tool that is available. This paper presents an example of a flexible, modular, object-oriented toolbox designed to support modeling and experimental analysis of a large family of heuristic knowledge representation and decision functions for adaptive self-managing communication networks with particular emphasis on routing strategies. It discusses in ...


Feature Selection In Intrusion Detection System Over Mobile Ad-Hoc Network, Xia Wang, Tu-liang Lin, Johnny S. Wong 2017 Iowa State University

Feature Selection In Intrusion Detection System Over Mobile Ad-Hoc Network, Xia Wang, Tu-Liang Lin, Johnny S. Wong

Johnny Wong

As Mobile ad-hoc network (MANET) has become a very important technology the security problem, especially, intrusion detection technique research has attracted many people�s effort. MANET is more vulnerable than wired network and suffers intrusion like wired network. This paper investigated some intrusion detection techniques using machine learning and proposed a profile based neighbor monitoring intrusion detection method. Further analysis shows that the features collected by each node are too many for wireless devices with limited capacity. We apply Markov Blanket algorithm [1] to the feature selection of the intrusion detection method. Experimental studies have shown that Markov Blanket algorithm ...


Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar 2017 Iowa State University

Quo Vadis - Adaptive Heuristics For Routing In Large Communication Networks, Armin Mikler, Johnny S. Wong, Vasant Honavar

Johnny Wong

This paper presents Quo Vadis, an evolving framework for intelligent traffic management in very large communication networks. Quo Vadis is designed to exploit topological properties of large networks as well as their spatio-temporal dynamics to optimize multiple performance criteria through cooperation among nodes in the network. It employs a distributed representation of network state information using local load measurements supplemented by a less precise global summary. Routing decisions in Quo Vadis are based on parameterized heuristics designed to optimize various performance metrics in an anticipatory or pro-active as well as compensatory or reactive mode and to minimize the overhead associated ...


The Methodology For Evaluating Response Cost For Intrusion Response Systems, Christopher Roy Strasburg, Natalia Stakhanova, Samik Basu, Johnny S. Wong 2017 Iowa State University

The Methodology For Evaluating Response Cost For Intrusion Response Systems, Christopher Roy Strasburg, Natalia Stakhanova, Samik Basu, Johnny S. Wong

Johnny Wong

Recent advances in the field of intrusion detection brought new requirements to intrusion prevention and response. Traditionally, the response to the detected attack was selected and deployed manually, in the recent years the focus has shifted towards developing automated and semi-automated methodologies for responding to intrusions. In this context, the cost-sensitive intrusion response models have gained the most interest mainly due to their emphasis on the balance between potential damage incurred by the intrusion and cost of the response. However, one of the challenges in applying this approach is defining consistent and adaptable measurement of these cost factors on the ...


Digital Commons powered by bepress