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Articles 61 - 90 of 1217
Full-Text Articles in Computer Engineering
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage
Electronic Theses and Dissertations
The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in …
A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab
A Transfer Learning Approach For Sentiment Classification., Omar Abdelwahab
Electronic Theses and Dissertations
The idea of developing machine learning systems or Artificial Intelligence agents that would learn from different tasks and be able to accumulate that knowledge with time so that it functions successfully on a new task that it has not seen before is an idea and a research area that is still being explored. In this work, we will lay out an algorithm that allows a machine learning system or an AI agent to learn from k different domains then uses some or no data from the new task for the system to perform strongly on that new task. In order …
Mindful: A Novel Virtual System Migration Decision-Making Framework For Automated Cyber-Resiliency, Nicholas James Lowing
Mindful: A Novel Virtual System Migration Decision-Making Framework For Automated Cyber-Resiliency, Nicholas James Lowing
Theses and Dissertations
Virtual system migration has revolutionized modern computing. As an advantageous byproduct of virtualization, virtual system migration has allowed for cheaper, more robust cloud management. The selection of a destination host during migration is a key component of migration management. However, there is currently no state-of-the-art, standardized framework for making this decision. Previous work related to automated load balancing is plentiful, but when load balancing is not the primary focus of the cloud management strategy there is a lack of research. We focus on this case, where virtual systems are no longer moved based on some predefined optimization pattern, but rather …
Low-Precision Linear Algebra For Neural Networks, Frost Bennion Mitchell
Low-Precision Linear Algebra For Neural Networks, Frost Bennion Mitchell
Undergraduate Honors Capstone Projects
Neural networks have been widely responsible for recent advances in machine learning, powering technologies such as digital assistants and AR photography. LPLANN (Low-Precision Linear Algebra for Neural Networks) is a cross-platform library written in C++ used for implementing neural networks. The software allows users to set specific levels of precision for calculations. Low-precision calculations use advanced parallelization techniques (SIMD, SWAR) to run neural networks at faster rates than full-precision calculations. This library is lightweight enough to run on embedded systems, only relies on OpenMP as a dependency, and is portable to any operating system. LPLANN also includes optimizations to provide …
Smart Surge Irrigation Using Microcontroller Based Embedded Systems And Internet Of Things, Prashant Dinkar Borhade
Smart Surge Irrigation Using Microcontroller Based Embedded Systems And Internet Of Things, Prashant Dinkar Borhade
Graduate Theses and Dissertations
Surge Irrigation is a type of furrow irrigation and one of many efficient irrigation techniques. It is one of the economical techniques and requires minimum labor for monitoring it. In surge irrigation, water is applied intermittently to a field to achieve uniform distribution of water along the furrows, which is important while irrigating, as it ensures that there is enough water near the root zone of the crop. The uneven distribution can cause a loss in crop productivity.
Surge irrigation uses a surge valve, which is an electro-mechanical device that irrigates a field. The commercial surge valves available on the …
A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson
A Scalable, Chunk-Based Slicer For Cooperative 3d Printing, Jace J. Mcpherson
Computer Science and Computer Engineering Undergraduate Honors Theses
Cooperative 3D printing is an emerging technology that aims to increase the 3D printing speed and to overcome the size limit of the printable object by having multiple mobile 3D printers (printhead-carrying mobile robots) work together on a single print job on a factory floor. It differs from traditional layer-by-layer 3D printing due to requiring multiple mobile printers to work simultaneously without interfering with each other. Therefore, a new approach for slicing a digital model and generating commands for the mobile printers is needed, which has not been discussed in literature before. We propose a chunk-by-chunk based slicer that divides …
Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown
Collaborative Robotic Path Planning For Industrial Spraying Operations On Complex Geometries, Steven Brown
Graduate Theses and Dissertations
Implementation of automated robotic solutions for complex tasks currently faces a few major hurdles. For instance, lack of effective sensing and task variability – especially in high-mix/low-volume processes – creates too much uncertainty to reliably hard-code a robotic work cell. Current collaborative frameworks generally focus on integrating the sensing required for a physically collaborative implementation. While this paradigm has proven effective for mitigating uncertainty by mixing human cognitive function and fine motor skills with robotic strength and repeatability, there are many instances where physical interaction is impractical but human reasoning and task knowledge is still needed. The proposed framework consists …
Building A Smart Nation: Singapore's Digital Journey, Siu Loon Hoe
Building A Smart Nation: Singapore's Digital Journey, Siu Loon Hoe
Research Collection School Of Computing and Information Systems
Singapore’s smart nation journey began when the drive was officially announced by the country’s Prime Minister Lee Hsien Loong in November 2014 (Lee, 2014). The vision is to improve people’s lives and create more opportunities through information and communications technology (ICT). The smart nation drive is an effort by the government to co-create innovative, people-centric solutions with citizens and businesses. The three priority areas, underpinned by cyber security, are elderly, transportation and data. Since then, various digital strategies and policies have been further articulated, and digital programmes and projects implemented in the country.
Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen
Logging, Visualization, And Analysis Of Network And Power Data Of Iot Devices, Neal Huynh Nguyen
Master's Theses
There are approximately 23.14 billion IoT(Internet of Things) devices currently in use worldwide. This number is projected to grow to over 75 billion by 2025. Despite their ubiquity little is known about the security and privacy implications of IoT devices. Several large-scale attacks against IoT devices have already been recorded.
To help address this knowledge gap, we have collected a year’s worth of network traffic and power data from 16 common IoT devices. From this data, we show that we can identify different smart speakers, like the Echo Dot, from analyzing one minute of power data on a shared power …
Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel
Automatically `Verifying’ Discrete-Time Complex Systems Through Learning, Abstraction And Refinement, Jingyi Wang, Jun Sun, Shengchao Qin, Cyrille Jegourel
Research Collection School Of Computing and Information Systems
Precisely modeling complex systems like cyber-physical systems is challenging, which often render model-based system verification techniques like model checking infeasible. To overcome this challenge, we propose a method called LAR to automatically ‘verify’ such complex systems through a combination of learning, abstraction and refinement from a set of system log traces. We assume that log traces and sampling frequency are adequate to capture ‘enough’ behaviour of the system. Given a safety property and the concrete system log traces as input, LAR automatically learns and refines system models, and produces two kinds of outputs. One is a counterexample with a bounded …
Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta
Co-Location Resistant Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta
Research Collection School Of Computing and Information Systems
Due to increasing number of avenues for conducting cross-virtual machine (VM) side-channel attacks, the security of public IaaS cloud data centers is a growing concern. These attacks allow an adversary to steal private information from a target user whose VM instance is co-located with that of the adversary. To reduce the probability of malicious co-location, we propose a novel VM placement algorithm called “Previously Co-Located Users First”. We perform a theoretical and empirical analysis of our proposed algorithm to evaluate its resource efficiency and security. Our results, obtained using real-world cloud traces containing millions of VM requests and thousands of …
Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong
Deep Unsupervised Pixelization, Chu Han, Qiang Wen, Shengfeng He, Qianshu Zhu, Yinjie Tan, Guoqiang Han, Tien-Tsin Wong
Research Collection School Of Computing and Information Systems
In this paper, we present a novel unsupervised learning method for pixelization. Due to the difficulty in creating pixel art, preparing the paired training data for supervised learning is impractical. Instead, we propose an unsupervised learning framework to circumvent such difficulty. We leverage the dual nature of the pixelization and depixelization, and model these two tasks in the same network in a bi-directional manner with the input itself as training supervision. These two tasks are modeled as a cascaded network which consists of three stages for different purposes. GridNet transfers the input image into multi-scale grid-structured images with different aliasing …
Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li
Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …
A Framework For Characterizing The Security Posture Of Cyber Systems, Matthew Ridley
A Framework For Characterizing The Security Posture Of Cyber Systems, Matthew Ridley
Theses and Dissertations
Modern day applications can be spread across multiple virtual or physical systems, and be accessed or attacked by pretty much any one any where. Cybersecurity is used to mitigate these cyber threats but there are limited resources that can be dedicated to security. As result, trade-offs and decisions must be made around what is prioritized and what isn’t. Cyber risk management provides methodologies for identifying threats, evaluating risks and making decisions, however, it can be difficult to determine whether the system is actually secure enough and the risk is actually within an acceptable parameters. This thesis provides a framework for …
Deploying, Improving And Evaluating Edge Bundling Methods For Visualizing Large Graphs, Jieting Wu
Deploying, Improving And Evaluating Edge Bundling Methods For Visualizing Large Graphs, Jieting Wu
School of Computing: Dissertations, Theses, and Student Research
A tremendous increase in the scale of graphs has been witnessed in a wide range of fields, which demands efficient and effective visualization techniques to assist users in better understandings of large graphs. Conventional node-link diagrams are often used to visualize graphs, whereas excessive edge crossings can easily incur severe visual clutter in the node-link diagram of a large graph. Edge bundling can effectively remedy visual clutter and reveal high-level graph structures. Although significant efforts have been devoted to developing edge bundling, three challenging problems remain. First, edge bundling techniques are often computationally expensive and are not easy to deploy …
“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth
“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth
Publications
Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of the child’s symptoms, activities, sleep, and treatment adherence can allow precise determination of asthma triggers and a reliable assessment of medication compliance and effectiveness. Digital phenotyping refers to moment-by-moment quantification of the individual-level human phenotype in situ using data from …
Asic Design To Support Low Power High Voltage Power Supply For Radiation Monitoring Applications, Daniel Rogge
Asic Design To Support Low Power High Voltage Power Supply For Radiation Monitoring Applications, Daniel Rogge
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
A low power high voltage power supply is designed for use in a long duration radiation monitoring system. The supply employs a flexible pulse frequency modulation switching controller implemented in a 0.35 $\mu$m CMOS technology. The controller drives and regulates a flyback transformer driven 12-stage Cockroft-Walton voltage multiplier chain. The chain provides bias for the dynodes of a photomultiplier tube. The supply voltage is selectable via a 12-bit on-chip digital to analog converter. The system is designed for low power operation and immunity to supply voltage variation as the application is battery-powered.
Advisors: Sina Balkir and Michael W. Hoffman
Evoalloy: An Evolutionary Approach For Analyzing Alloy Specifications, Jianghao Wang
Evoalloy: An Evolutionary Approach For Analyzing Alloy Specifications, Jianghao Wang
School of Computing: Dissertations, Theses, and Student Research
Using mathematical notations and logical reasoning, formal methods precisely define a program’s specifications, from which we can instantiate valid instances of a system. With these techniques, we can perform a variety of analysis tasks to verify system dependability and rigorously prove the correctness of system properties. While there exist well-designed automated verification tools including ones considered lightweight, they still lack a strong adoption in practice. The essence of the problem is that when applied to large real world applications, they are not scalable and applicable due to the expense of thorough verification process. In this thesis, I present a new …
Controller Evolution And Divergence: A Software Perspective, Balaji Balasubramaniam
Controller Evolution And Divergence: A Software Perspective, Balaji Balasubramaniam
School of Computing: Dissertations, Theses, and Student Research
Successful controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software.
In this thesis, we perform a first-of-its-kind study on the evolution of two popular open-source safety-critical autopilot control software -- ArduPilot, and Paparazzi, to better …
Assessing The Mean Neuronal Firing Rate Information Hypothesis Via Mutual Information, Greg W. Zdor
Assessing The Mean Neuronal Firing Rate Information Hypothesis Via Mutual Information, Greg W. Zdor
Honors Theses
While it is currently well accepted that the mean neuronal firing rate (MNFR) is a key parameter encoding information about sensory and motor events, in some cases the measured information due to MNFR is not adequate to explain the total neuron signal information content. In this study, several auditory neuron responses and corresponding MNFR--generated surrogates are analyzed using mutual information (MI) as a metric of information content. Results showed that for particular inter-spike gaps (ISG), data MI exceeded two standard deviations of the surrogate MNFR MI, indicating spike spacing and order also encode information.
Automatic Identification Of Animals In The Wild: A Comparative Study Between C-Capsule Networks And Deep Convolutional Neural Networks., Joel Kamdem Teto, Ying Xie
Automatic Identification Of Animals In The Wild: A Comparative Study Between C-Capsule Networks And Deep Convolutional Neural Networks., Joel Kamdem Teto, Ying Xie
Master of Science in Computer Science Theses
The evolution of machine learning and computer vision in technology has driven a lot of
improvements and innovation into several domains. We see it being applied for credit decisions, insurance quotes, malware detection, fraud detection, email composition, and any other area having enough information to allow the machine to learn patterns. Over the years the number of sensors, cameras, and cognitive pieces of equipment placed in the wilderness has been growing exponentially. However, the resources (human) to leverage these data into something meaningful are not improving at the same rate. For instance, a team of scientist volunteers took 8.4 years, …
An Electron‐Rich Calix[4]Arene‐Based Receptor With Unprecedented Binding Affinity For Nitric Oxide, Denan Wang, Lena V. Ivanova, Maxim V. Ivanov, Saber Mirzaei, Qadir K. Timerghazin, Scott A. Reid, Rajendra Rathore
An Electron‐Rich Calix[4]Arene‐Based Receptor With Unprecedented Binding Affinity For Nitric Oxide, Denan Wang, Lena V. Ivanova, Maxim V. Ivanov, Saber Mirzaei, Qadir K. Timerghazin, Scott A. Reid, Rajendra Rathore
Electrical and Computer Engineering Faculty Research and Publications
Calixarenes have found widespread application as building blocks for the design and synthesis of functional materials in host–guest chemistry. The ongoing desire to develop a detailed understanding of the nature of NO bonding to multichromophoric π‐stacked assemblies led us to develop an electron‐rich methoxy derivative of calix[4]arene (3), which we show exists as a single conformer in solution at ambient temperature. Here, we examine the redox properties of this derivative, generate its cation radical (3+.) using robust chemical oxidants, and determine the relative efficacy of its NO binding in comparison with model calixarenes. We find …
Best Trade-Off Point Method For Efficient Resource Provisioning In Spark, Peter P. Nghiem
Best Trade-Off Point Method For Efficient Resource Provisioning In Spark, Peter P. Nghiem
Computer Science and Engineering
Considering the recent exponential growth in the amount of information processed in Big Data, the high energy consumed by data processing engines in datacenters has become a major issue, underlining the need for efficient resource allocation for more energy-efficient computing. We previously proposed the Best Trade-off Point (BToP) method, which provides a general approach and techniques based on an algorithm with mathematical formulas to find the best trade-off point on an elbow curve of performance vs. resources for efficient resource provisioning in Hadoop MapReduce. The BToP method is expected to work for any application or system which relies on a …
Frequency Domain Decomposition Of Digital Video Containing Multiple Moving Objects, Victor M. Stone
Frequency Domain Decomposition Of Digital Video Containing Multiple Moving Objects, Victor M. Stone
Electrical and Computer Engineering ETDs
Motion estimation has been dominated by time domain methods such as block matching and optical flow. However, these methods have problems with multiple moving objects in the video scene, moving backgrounds, noise, and fractional pixel/frame motion. This dissertation proposes a frequency domain method (FDM) that solves these problems. The methodology introduced here addresses multiple moving objects, with or without a moving background, 3-D frequency domain decomposition of digital video as the sum of locally translational (or, in the case of background, a globally translational motion), with high noise rejection. Additionally, via a version of the chirp-Z, fractional pixel/frame motion detection …
Special Session: The Future Of Iot Security, Sibin Mohan, Mikael Asplund, Gedare Bloom, Ahmad-Reza Sadeghi, Ahmad Ibrahim, Negin Salajageh, Paul Griffioen, Bruno Sinopoli
Special Session: The Future Of Iot Security, Sibin Mohan, Mikael Asplund, Gedare Bloom, Ahmad-Reza Sadeghi, Ahmad Ibrahim, Negin Salajageh, Paul Griffioen, Bruno Sinopoli
Faculty Work Comprehensive List
The Internet-of-Things (IoT) is a large and complex domain. These systems are often constructed using a very diverse set of hardware, software and protocols. This, combined with the ever increasing number of IoT solutions/services that are rushed to market means that most such systems are rife with security holes. Recent incidents (e.g., the Mirai botnet) further highlight such security issues. With emerging technologies such as blockchain and software-defined networks (SDNs), new security solutions are possible in the IoT domain. In this paper we will explore future trends in IoT security: (a) the use of blockchains in IoT security, (b) data …
Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh
Transcribing Braille Code: Learning Equations Across Platforms, Deegan Atha, Courtney Balogh
Purdue Journal of Service-Learning and International Engagement
Deegan Atha, a graduating senior in electrical engineering and a future engineer, is interested in human-centered design and developing technology that helps students engage and be successful in STEM.
Courtney Balogh, a junior in mechanical engineering, is interested in human-centered design and the importance it plays in product development. Deegan and Courtney are members of the Purdue EPICS project, Learning Equations Across Platforms (LEAP). They partnered with the Indiana School for the Blind and Visually Impaired (ISBVI) to develop a braille transcription device and web application that converts braille to print in real time.
A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert
A Validation Study Of Time Series Data Forecasting Using Neural Networks, Marco Martinez, Jeremy Evert
Student Research
Artificial Intelligence(AI) is a growing topic in Computer Science and has many uses in real world applications. One application is using Al, or more specifically Neural Networks to model data and predict outcomes. Neural Networks have been used in the past to predict weather changes, create facial recognition software , and to create self-driving cars. Our project is a validation study of, “Modeling Time Series Data With Deep Fourier Neural Networks” by Gashler and Ashmore, 2016. Here we show that a neural network can be trained to be an effective predictor of weather patterns in Alaska over several years. Our …
Programmable Time-Domain Digital-Coding Metasurface For Non-Linear Harmonic Manipulation And New Wireless Communication Systems, Jie Zhao, Xi Yang, Jun Yan Dai, Qiang Cheng, Xiang Li, Ning Hua Qi, Jun Chen Ke, Guo Dong Bai, Shuo Liu, Shi Jin, Andrea Alù, Tie Jun Cui
Programmable Time-Domain Digital-Coding Metasurface For Non-Linear Harmonic Manipulation And New Wireless Communication Systems, Jie Zhao, Xi Yang, Jun Yan Dai, Qiang Cheng, Xiang Li, Ning Hua Qi, Jun Chen Ke, Guo Dong Bai, Shuo Liu, Shi Jin, Andrea Alù, Tie Jun Cui
Publications and Research
Optical non-linear phenomena are typically observed in natural materials interacting with light at high intensities, and they benefit a diverse range of applications from communication to sensing. However, controlling harmonic conversion with high efficiency and flexibility remains a major issue in modern optical and radio-frequency systems. Here, we introduce a dynamic time-domain digital-coding metasurface that enables efficient manipulation of spectral harmonic distribution. By dynamically modulating the local phase of the surface reflectivity, we achieve accurate control of different harmonics in a highly programmable and dynamic fashion, enabling unusual responses, such as velocity illusion. As a relevant application, we propose and …
Criticality Assessments For Improving Algorithmic Robustness, Thomas B. Jones
Criticality Assessments For Improving Algorithmic Robustness, Thomas B. Jones
Computer Science ETDs
Though computational models typically assume all program steps execute flawlessly, that does not imply all steps are equally important if a failure should occur. In the "Constrained Reliability Allocation" problem, sufficient resources are guaranteed for operations that prompt eventual program termination on failure, but those operations that only cause output errors are given a limited budget of some vital resource, insufficient to ensure correct operation for each of them.
In this dissertation, I present a novel representation of failures based on a combination of their timing and location combined with criticality assessments---a method used to predict the behavior of systems …
3d Wi-Fi Campus Coverage: Flying A Drone, Richard Thompson, Tyler Williams, Seth Pritchett, Tracy Whitlock
3d Wi-Fi Campus Coverage: Flying A Drone, Richard Thompson, Tyler Williams, Seth Pritchett, Tracy Whitlock
Posters-at-the-Capitol
Everyone in a college environment is immersed in their electronic devices. Whether it be in the quad, the classroom, the library or their favorite nook by the windows, they all need a reliable Wi-Fi signal to get their work done. In this era most of the tasks that has to be completed require some sort of connection between electronic devices especially if the individuals require information located on the internet. The main method of accessing the internet is using Wifi technology which uses electromagnetic waves to propagate information across a certain area. Considering the properties of these electromagnetic frequencies it …