Systems Architecture Commons^™

Mining Data On Traumatic Brain Injury With Reconstructability Analysis, Martin Zwick, Nancy Carney, Rosemary Nettleton

Complex Systems Faculty Publications and Presentations

This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical modeling technique known as reconstructability analysis (RA). The analysis shows the flexibility, power, and comprehensibility of RA modeling, which is well-suited for mining biomedical data. One finding of the analysis is that education is a confounding variable for the Digit Symbol Test in discriminating the severity of concussion; another - and anomalous - finding is that previous head injury predicts improved performance on the Reaction Time test. This analysis was exploratory, so its findings require follow-on confirmatory tests of their generalizability.

Ansi/Niso Z39.99-2017 Resourcesync Framework Specification, Kevin Ruthen, Jill Emery, Mark Doyle, Mark Needleman, Sue Baughman, Evan Owens, Oliver Pesch, Mike Dicus, Nassib Nassar, Tim Auger, Amy Kirchhoff, Sally Mccallum, Diana Magnoni, Paul Swanson, Gregory Grazevich, Nara Newcomer, Gregory Grazevich, Juha Hakala, Barbara Rapp, Beverly Geckle, Carol Brent, Gary Van Overborg, Rick Burke, Kristin Antelman, Scott Bernier, Pascal Calarco, John Dove, Lucy Harrison, Peter Murray, Christine Stohn, Julie Zhu, Todd Carpenter, Bernhard Haslhofer, Richard Jones, Martin Klein, Graham Klyne, Carl Lagoze, Stuart Lewis, Peter Murray, Michael Nelson, Shlomo Sanders, Robert Sanderson, Herbert Van De Sompel, Paul Walk, Simeon Warner, Zhiwu Xie, Jeff Young

Computer Science Faculty Publications

This ResourceSync specification describes a synchronization framework for the web consisting of various capabilities that allow third-party systems to remain synchronized with a server’s evolving resources. The capabilities may be combined in a modular manner to meet local or community requirements. This specification also describes how a server should advertise the synchronization capabilities it supports and how third-party systems may discover this information. The specification repurposes the document formats defined by the Sitemap protocol and introduces extensions for them.

Spatial Data Mining Analytical Environment For Large Scale Geospatial Data, Zhao Yang

University of New Orleans Theses and Dissertations

Nowadays, many applications are continuously generating large-scale geospatial data. Vehicle GPS tracking data, aerial surveillance drones, LiDAR (Light Detection and Ranging), world-wide spatial networks, and high resolution optical or Synthetic Aperture Radar imagery data all generate a huge amount of geospatial data. However, as data collection increases our ability to process this large-scale geospatial data in a flexible fashion is still limited. We propose a framework for processing and analyzing large-scale geospatial and environmental data using a “Big Data” infrastructure. Existing Big Data solutions do not include a specific mechanism to analyze large-scale geospatial data. In this work, we extend …

A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang

Research & Publications

The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.

Android Drone: Remote Quadcopter Control With A Phone, Aubrey John Russell

Computer Engineering

The purpose of the “Android Drone” project was to create a quadcopter that can be controlled by user input sent over the phone’s Wi-Fi connection or 4G internet connection. Furthermore, the purpose was also to be able to receive live video feedback over the internet connection, thus making the drone an inexpensive option compared to other, equivalent drones that might cost thousands of dollars. Not only that, but the Android phone also has a host of other useful features that could be utilized by the drone: this includes GPS, pathing, picture taking, data storage, networking and TCP/IP, a Java software …

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Non-Player-Characters (NPCs), as found in computer games, can be modelled as intelligent systems, which serve to improve the interactivity and playability of the games. Although reinforcement learning (RL) has been a promising approach to creating the behavior models of non-player characters (NPC), an initial stage of exploration and low performance is typically required. On the other hand, imitative learning (IL) is an effective approach to pre-building a NPC’s behavior model by observing the opponent’s actions, but learning by imitation limits the agent’s performance to that of its opponents. In view of their complementary strengths, this paper proposes a computational model …

Addsmart: Address Digitization And Smart Mailbox With Rfid Technology, Jonathon Ross Tew

Theses and Dissertations

ADDSMART is a research project focused on digitizing addresses of locations and building a smart mailbox by combining wireless sensors, cameras, locks, and RFID readers and tags into a system controlled by an Arduino board. The aim of the project is to explore the idea of address digitization (using RFID tags to store addresses) and incorporate it into a mailbox that can communicate wirelessly with the homeowner to provide mail status updates and home security footage through digital photographs. This paper demonstrates the proposed ideas, describes the design of a smart mailbox, the technology that has been used, and the …

A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.

An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan

Research Collection School Of Computing and Information Systems

Profitability of adopting Software-as-a-Service (SaaS) solutions forexisting applications is currently analyzed mostly in informal way. Informalanalysis is unreliable because of the many conflicting factors that affect costs andbenefits of offering applications on the cloud. We propose a quantitative economicmodel for evaluating profitability of migrating to SaaS that enables potentialservice providers to evaluate costs and benefits of various migration strategiesand choices of target service architectures. In previous work, we presented arudimentary conceptual SaaS economic model enumerating factors that have todo with service profitability, and defining qualitative relations among them. Aquantitative economic model presented in this paper extends the conceptualmodel with equations …

Prosense, Johnny Favazza Ii, Casey Glasgow, Matt Epperson

Computer Engineering

This project aims to gather advanced data sets from MEMS sensors and GPS and deliver it to the user, who can capitalize on the data. The once negligible half-degree difference of your board barreling down a wave can be recorded from a gyro and exploited for the perfect turn. The exact speed dreaded by longboarders where speed wobbles turn into a road rash can be analysed and consequently avoided. Ascertaining the summit of your flight using combined GPS sensors from the ski ramp allows for the correct timing of tricks. When it comes to pursuing excellence in professional sports, amateur …

Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang

Research Collection School Of Computing and Information Systems

Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …

Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …

Poster: Android Whole-System Control Flow Analysis For Accurate Application Behavior Modeling, Huu Hoang Nguyen

Research Collection School Of Computing and Information Systems

Android, the modern operating system for smartphones, together with its millions of apps, has become an important part of human life. There are many challenges to analyzing them. It is important to model the mobile systems in order to analyze the behaviors of apps accurately. These apps are built on top of interactions with Android systems. We aim to automatically build abstract models of the mobile systems and thus automate the analysis of mobile applications and detect potential issues (e.g., leaking private data, causing unexpected crashes, etc.). The expected results will be the accuracy models of actual various versions of …

Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish

Electronic Theses, Projects, and Dissertations

Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories …

The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson

Political Science Publications

Game theory is used to rationally and dispassionately examine the strategic behaviour of nations, especially superpower behaviour. This article explains how basic game theory - at its simplest level - was used by Anatol Rapoport to generate ideas about how to enhance world peace. Rapoport was at the forefront of the game theoreticians who sought to conceptualize strategies that could promote international cooperation. Accordingly, the basic logic of game theory is explained using the game models of ‘Chicken’ and ‘Prisoner’s Dilemma’. These models were used by Rapoport in his books and lectures in simple and complex ways. Then Rapoport’s revolutionary …

Survey Of Autonomic Computing And Experiments On Jmx-Based Autonomic Features, Adel R. Azzam

University of New Orleans Theses and Dissertations

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository.

In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using …

Internet Of Things-Based Smart Classroom Environment, Amir R. Atabekov

Master of Science in Computer Science Theses

Internet of Things (IoT) is a novel paradigm that is gaining ground in the Computer Science field. There’s no doubt that IoT will make our lives easier with the advent of smart thermostats, medical wearable devices, connected vending machines and others. One important research direction in IoT is Resource Management Systems (RMS). In the current state of RMS research, very few studies were able to take advantage of indoor localization which can be very valuable, especially in the context of smart classrooms. For example, indoor localization can be used to dynamically generate seat map of students in a classroom. Indoor …

Enabling Runtime Profiling To Hide And Exploit Heterogeneity Within Chip Heterogeneous Multiprocessor Systems (Chmps), Eugene Cartwright

Graduate Theses and Dissertations

The heterogeneity of multiprocessor systems on chip (MPSoC) has presented unique opportunities for furthering today’s diverse application needs. FPGA-based MPSoCs have the potential of bridging the gap between generality and specialization but has traditionally been limited to device experts. The flexibility of these systems can enable computation without compromise but can only be realized if this flexibility extends throughout the software stack. At the top of this stack, there has been significant effort for leveraging the heterogeneity of the architecture. However, the betterment of these abstractions are limited to what the bottom of the stack exposes: the runtime system.

The …

Hpc Made Easy: Using Docker To Distribute And Test Trilinos, Sean J. Deal

All College Thesis Program, 2016-2019

Virtualization is an enticing option for computer science research given its ability to provide repeatable, standardized environments, but traditional virtual machines have too much overhead cost to be practical. Docker, a Linux-based tool for operating-system level virtualization, has been quickly gaining popularity throughout the computer science field by touting a virtualization solution that is easily distributable and more lightweight than virtual machines. This thesis aims to explore if Docker is a viable option for conducting virtualized research by evaluating the results of parallel performance tests using the Trilinos project.