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Articles 18301 - 18330 of 25759
Full-Text Articles in Engineering
Prediction Of Peptides Binding To Mhc Class I And Ii Alleles By Temporal Motif Mining, Cem Meydan, Hasan H. Otu, Osman Ugur Sezerman
Prediction Of Peptides Binding To Mhc Class I And Ii Alleles By Temporal Motif Mining, Cem Meydan, Hasan H. Otu, Osman Ugur Sezerman
Department of Electrical and Computer Engineering: Faculty Publications
Background: MHC (Major Histocompatibility Complex) is a key player in the immune response of most vertebrates. The computational prediction of whether a given antigenic peptide will bind to a specific MHC allele is important in the development of vaccines for emerging pathogens, the creation of possibilities for controlling immune response, and for the applications of immunotherapy. One of the problems that make this computational prediction difficult is the detection of the binding core region in peptides, coupled with the presence of bulges and loops causing variations in the total sequence length. Most machine learning methods require the sequences to be …
Exploring The Microsoft .Net Micro Framework For Prototyping Applied Wireless Sensor Networks, Jay D. Carlson, Mateusz Mittek, Lance C. Pérez
Exploring The Microsoft .Net Micro Framework For Prototyping Applied Wireless Sensor Networks, Jay D. Carlson, Mateusz Mittek, Lance C. Pérez
Department of Electrical and Computer Engineering: Faculty Publications
Most Wireless Sensor Network platforms – such as the Mica, Iris, and Telos B families of motes – use lowpower 8-bit microprocessors which have limited memory and processing capabilities, thus requiring researchers to implement communication protocols and data processing routines using lowlevel programming practices that are tedious and cumbersome. Rich features available in modern desktop operating systems – such as threads, memory management, and exception-handling – are largely absent. The Microsoft .NET Micro Framework implements a scaled-back .NET framework suitable for development on low-cost, low-power wireless sensors, while providing developers a rapid software development environment for prototyping embedded applications. Here, …
Bearing Fault Diagnosis For Direct-Drive Wind Turbines Via Current-Demodulated Signals, Xiang Gong, Wei Qiao
Bearing Fault Diagnosis For Direct-Drive Wind Turbines Via Current-Demodulated Signals, Xiang Gong, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
Bearing faults account for a large portion of all faults in wind turbine generators (WTGs). Current-based bearing fault diagnosis techniques have great economic benefits and are potential to be adopted by the wind energy industry. This paper models the modulation effects of bearing faults on the stator currents of a direct-drive wind turbine equipped with a permanent-magnet synchronous generator (PMSG) operating with a variable shaft rotating frequency. Based on the analysis, a method consisting of appropriate current frequency and amplitude demodulation algorithms and a 1P-invariant power spectrum density algorithm is proposed for bearing fault diagnosis of variable-speed direct-drive wind turbines …
Inactivation Of E. Coli Affected By Medium Conductivity In Pulsed Electric Field Processing, Tanya Kirilova Gachovska, Jeyamkondan Subbiah, Harshavardhan Thippareddi, David Marx, Frazer Williams
Inactivation Of E. Coli Affected By Medium Conductivity In Pulsed Electric Field Processing, Tanya Kirilova Gachovska, Jeyamkondan Subbiah, Harshavardhan Thippareddi, David Marx, Frazer Williams
Department of Electrical and Computer Engineering: Faculty Publications
No abstract provided.
Vibration Energy Harvesting For Wireless Underground Sensor Networks, Salman Kahrobaee, Mehmet C. Vuran
Vibration Energy Harvesting For Wireless Underground Sensor Networks, Salman Kahrobaee, Mehmet C. Vuran
Department of Electrical and Computer Engineering: Faculty Publications
Recent developments in wireless underground communication have enabled the realization of underground sensor network applications. To this end, it is desirable to provide a sustainable operation for wireless underground sensor networks (WUSNs) with extended lifetimes as maintenance is significantly costly. One promising method towards sustainable operation is to harvest energy underground based on the vibration sources in the environment. However, to the best of our knowledge, underground vibration energy harvesting has not been investigated before. In this paper, the feasibility of vibration energy harvesting for WUSNs is investigated. First, an analytical framework is developed to model the maximum harvestable power …
Optimum Sizing Of Distributed Generation And Storage Capacity In Smart Households, Salman Kahrobaee, Sohrab Asgarpoor, Wei Qiao
Optimum Sizing Of Distributed Generation And Storage Capacity In Smart Households, Salman Kahrobaee, Sohrab Asgarpoor, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
In the near future, a smart grid will accommodate customers who are prepared to invest in generation-battery systems and employ energymanagement systems in order to cut down on their electricity bills. The main objective of this paper is to determine the optimum capacity of a customer’s distributed-generation system (such as a wind turbine) and battery within the framework of a smart grid. The proposed approach involves developing an electricity management system based on stochastic variables, such as wind speed, electricity rates, and load. Then, a hybrid stochastic method based on Monte Carlo simulation and particle swarm optimization is proposed to …
Real-Time Stereo Matching On Cuda Using An Iterative Refinement Method For Adaptive Support-Weight Correspondences, Jedrzej Kowalczuk, Eric T. Psota, Lance C. Pérez
Real-Time Stereo Matching On Cuda Using An Iterative Refinement Method For Adaptive Support-Weight Correspondences, Jedrzej Kowalczuk, Eric T. Psota, Lance C. Pérez
Department of Electrical and Computer Engineering: Faculty Publications
High-quality real-time stereo matching has the potential to enable various computer vision applications including semi-automated robotic surgery, teleimmersion, and 3-D video surveillance. A novel real-time stereo matching method is presented that uses a two-pass approximation of adaptive supportweight aggregation, and a low-complexity iterative disparity refinement technique. Through an evaluation of computationally efficient approaches to adaptive support-weight cost aggregation, it is shown that the two-pass method produces an accurate approximation of the support weights while greatly reducing the complexity of aggregation. The refinement technique, constructed using a probabilistic framework, incorporates an additive term into matching cost minimization and facilitates iterative processing …
Achievable Throughput Regions Of Fading Broadcast And Interference Channels Under Qos Constraints, Deli Qiao, Mustafa Cenk Gursoy, Senem Velipasalar
Achievable Throughput Regions Of Fading Broadcast And Interference Channels Under Qos Constraints, Deli Qiao, Mustafa Cenk Gursoy, Senem Velipasalar
Department of Electrical and Computer Engineering: Faculty Publications
Transmission over fading broadcast and interference channels in the presence of quality of service (QoS) constraints is studied. Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical QoS constraints, is employed as the performance metric. In the broadcast scenario, the effective capacity region achieved with superposition coding and successive interference cancellation is identified and is shown to be convex. Subsequently, optimal power control policies that achieve the boundary points of the effective capacity region are investigated, and an algorithm for the numerical computation of the optimal power adaptation schemes for …
Adaptive Threshold Displacement Algorithm For Removing Hidden Information From Digital Images, Fahimeh Rezaei, Michael Hempel, Tao Ma, Pradhumna Lal Shrestha, Dongming Peng, Hamid Sharif
Adaptive Threshold Displacement Algorithm For Removing Hidden Information From Digital Images, Fahimeh Rezaei, Michael Hempel, Tao Ma, Pradhumna Lal Shrestha, Dongming Peng, Hamid Sharif
Department of Electrical and Computer Engineering: Faculty Publications
The growth of the Internet and online social media, especially in recent years, also gave rise to a proliferation of online multimedia content creation and distribution. The use of modern steganography methods – the art of hiding information within multimedia – presents an unprecedented opportunity for malicious uses of these materials. Therefore, developing an effective technique to avoid the distribution of secret data is a significant problem that is addressed in this paper for digital images. We introduce a novel algorithm to remove the steganography information embedded in an image without changing the quality of the image and with no …
Adaptive Channel Allocation And Routing In Cognitive Radio Networks, Zhihui Shu, Jiazhen Zhou, Yi Qian, Rose Qingyang Hu
Adaptive Channel Allocation And Routing In Cognitive Radio Networks, Zhihui Shu, Jiazhen Zhou, Yi Qian, Rose Qingyang Hu
Department of Electrical and Computer Engineering: Faculty Publications
One of the biggest challenges in multi-hop cognitive radio networking is the dynamic change of channel availability to secondary users which could cause the breaking of routes and thus communications. To address this challenge, we propose an adaptive channel allocation and routing scheme in this paper. Our scheme is flexible so that it can react to the dynamic change of channel availability, and it can maximize the throughput by exploiting network coding opportunities. First, we model the primary users’ activity, channel availability and the interference among the secondary users in a cognitive radio network environment, and show how to implement …
Social Pervasive Systems: The Integration Of Social Networks And Pervasive Systems, Soumaia Al Ayyat
Social Pervasive Systems: The Integration Of Social Networks And Pervasive Systems, Soumaia Al Ayyat
Papers, Posters, and Presentations
Sensor technology embedded in smart mobile devices branded such devices as candidates for building innovative context-aware pervasive applications. On a parallel front, the notable evolution in the shape and form of social networking and their seamless accessibility from mobile devices founded a goldmine of contextual information. Utilizing an ecosystem that combines both mobile smart devices and a big data like environment in the form of social networks allows for the creation of an elitist set of services and applications that merge the two domains. In this paper, and following the footsteps of similar research efforts that attempted to combine both …
Research Project On Biometrics, Alia Hassan, Ingy Nazif
Research Project On Biometrics, Alia Hassan, Ingy Nazif
Papers, Posters, and Presentations
As technology evolves, and our personal details become more and more susceptible to hacking, one of the most important concerns we now have is being sure our phones, computers, networks are secure. We have begun to move on from simple password and motion patterns onto using facial recognition, and other forms of biometric recognition technology to protect our private information. The iPhone 5 for example, now presents features to identify uniquely the owner of the device, in the form of fingerprint detection. So we decided to focus on the topic biometrics for this research paper, which is basically how to …
Distributed Beamforming With Imperfect Phase Synchronization For Cognitive Radio Networks, Andrew Minturn, Deepraj Vernekar, Yaoqing Lamar Yang, Hamid Sharif
Distributed Beamforming With Imperfect Phase Synchronization For Cognitive Radio Networks, Andrew Minturn, Deepraj Vernekar, Yaoqing Lamar Yang, Hamid Sharif
Department of Electrical and Computer Engineering: Faculty Publications
In this paper, we present the analysis and simulation evaluation of a cognitive radio network employing a distributed beamforming technique with imperfect phase synchronization in the presence of a primary receiver. Our system model consists of a group of cognitive transmitters, each with an ideal isotropic antenna and equal transmit power, communicating with a secondary receiver in the farfield. The objective of the network of cognitive transmitters is to optimize its beampattern in the direction of the secondary receiver while minimizing the beampattern in the direction of the primary receiver to a certain threshold. The phases of the transmitted signals …
Robust Subspace Estimation Using Low-Rank Optimization. Theory And Applications In Scene Reconstruction, Video Denoising, And Activity Recognition., Omar Oreifej
Electronic Theses and Dissertations
In this dissertation, we discuss the problem of robust linear subspace estimation using low-rank optimization and propose three formulations of it. We demonstrate how these formulations can be used to solve fundamental computer vision problems, and provide superior performance in terms of accuracy and running time. Consider a set of observations extracted from images (such as pixel gray values, local features, trajectories . . . etc). If the assumption that these observations are drawn from a liner subspace (or can be linearly approximated) is valid, then the goal is to represent each observation as a linear combination of a compact …
Measuring The Evolving Internet Ecosystem With Exchange Points, Mohammad Zubair Ahmad
Measuring The Evolving Internet Ecosystem With Exchange Points, Mohammad Zubair Ahmad
Electronic Theses and Dissertations
The Internet ecosystem comprising of thousands of Autonomous Systems (ASes) now include Internet eXchange Points (IXPs) as another critical component in the infrastructure. Peering plays a significant part in driving the economic growth of ASes and is contributing to a variety of structural changes in the Internet. IXPs are a primary component of this peering ecosystem and are playing an increasing role not only in the topology evolution of the Internet but also inter-domain path routing. In this dissertation we study and analyze the overall affects of peering and IXP infrastructure on the Internet. We observe IXP peering is enabling …
Influence Of Task-Role Mental Models On Human Interpretation Of Robot Motion Behavior, Scott Ososky
Influence Of Task-Role Mental Models On Human Interpretation Of Robot Motion Behavior, Scott Ososky
Electronic Theses and Dissertations
The transition in robotics from tools to teammates has begun. However, the benefit autonomous robots provide will be diminished if human teammates misinterpret robot behaviors. Applying mental model theory as the organizing framework for human understanding of robots, the current empirical study examined the influence of task-role mental models of robots on the interpretation of robot motion behaviors, and the resulting impact on subjective ratings of robots. Observers (N = 120) were exposed to robot behaviors that were either congruent or incongruent with their task-role mental model, by experimental manipulation of preparatory robot task-role information to influence mental models (i.e., …
Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner
Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner
Electronic Theses and Dissertations
Computer-based instructors, just like their human counterparts, should monitor the emotional and cognitive states of their students in order to adapt instructional technique. Doing so requires a model of student state to be available at run time, but this has historically been difficult. Because people are different, generalized models have not been able to be validated. As a person’s cognitive and affective state vary over time of day and seasonally, individualized models have had differing difficulties. The simultaneous creation and execution of an individualized model, in real time, represents the last option for modeling such cognitive and affective states. This …
Life Long Learning In Sparse Learning Environments, John Reeder
Life Long Learning In Sparse Learning Environments, John Reeder
Electronic Theses and Dissertations
Life long learning is a machine learning technique that deals with learning sequential tasks over time. It seeks to transfer knowledge from previous learning tasks to new learning tasks in order to increase generalization performance and learning speed. Real-time learning environments in which many agents are participating may provide learning opportunities but they are spread out in time and space outside of the geographical scope of a single learning agent. This research seeks to provide an algorithm and framework for life long learning among a network of agents in a sparse real-time learning environment. This work will utilize the robust …
Mission Aware Energy Saving Strategies For Army Ground Vehicles, Macam Dattathreya
Mission Aware Energy Saving Strategies For Army Ground Vehicles, Macam Dattathreya
Wayne State University Dissertations
Fuel energy is a basic necessity for this planet and the modern technology to perform many activities on earth. On the other hand, quadrupled automotive vehicle usage by the commercial industry and military has increased fuel consumption. Military readiness of Army ground vehicles is very important for a country to protect its people and resources. Fuel energy is a major requirement for Army ground vehicles. According to a report, a department of defense has spent nearly $13.6 billion on fuel and electricity to conduct ground missions. On the contrary, energy availability on this plant is slowly decreasing. Therefore, saving energy …
Table Of Contents
Journal of Digital Forensics, Security and Law
No abstract provided.
Geospatial Virtual Heritage: A Gesture-Based 3d Gis To Engage The Public With Ancient Maya Archaeology, Heather Richards-Rissetto, Jim Robertsson, Jennifer Von Schwerin, Giorgio Agugario, Fabio Remondino, Gabrio Girardi
Geospatial Virtual Heritage: A Gesture-Based 3d Gis To Engage The Public With Ancient Maya Archaeology, Heather Richards-Rissetto, Jim Robertsson, Jennifer Von Schwerin, Giorgio Agugario, Fabio Remondino, Gabrio Girardi
Department of Anthropology: Faculty Publications
This paper presents our research to develop a gesture-based 3D GIS system to engage the public in cultural heritage. It compares two types of interaction—device-based vs. natural interaction— and summarizes the beta-testing results of a 3D GIS tool for archaeology, called QueryArch3D, in which participants used device-based interaction (i.e. mouse and keyboard). It follows with a description of the gesture-based system—that we developed in response to these beta-tests. The system uses QueryArch3D and Microsoft’s Kinect to enable people use body movements (in lieu of keyboard or mouse) to navigate a virtual reality landscape, query 3D objects, and call up photos, …
Substantive Collaboration: Are We Ready To Lead?, Mark Askren
Substantive Collaboration: Are We Ready To Lead?, Mark Askren
Information Technology Services: Publications
Although MOOCs have received the most attention in higher education this year, another issue is affecting colleges and universities and the IT community on a much broader scale: the perception that the higher education business model is “broken.” This isn’t an IT problem by definition, but IT leaders have not contributed effectively to a solution. At least not yet. So what can we, as IT leaders, do individually and collectively to change the outcome? The answer is clear. We have to collaborate. Substantially. And in ways that are far-reaching and very challenging. We have to change our core processes and …
Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice
Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice
Doctoral Dissertations
The power-law distribution can be used to describe various aspects of social group behavior. For mussels, sociobiological research has shown that the Lévy walk best describes their self-organizing movement strategy. A mussel's step length is drawn from a power-law distribution, and its direction is drawn from a uniform distribution. In the area of social networks, theories such as preferential attachment seek to explain why the degree distribution tends to be scale-free. The aim of this dissertation is to glean insight from these works to help solve problems in two domains: cloud computing systems and community detection.
Privacy and security are …
Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain
Adding Data Parallelism To Streaming Pipelines For Throughput Optimization, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger D. Chamberlain
All Computer Science and Engineering Research
The streaming model is a popular model for writing high-throughput parallel applications. A streaming application is represented by a graph of computation stages that communicate with each other via FIFO channels. In this report, we consider the problem of mapping streaming pipelines — streaming applications where the graph is a linear chain — in order to maximize throughput. In a parallel setting, subsets of stages, called components can be mapped onto different computing resources. The through-put of an application is determined by the throughput of the slowest component. Therefore, if some stage is much slower than others, then it may …
Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.
Efficient Parallel Real-Time Upsampling Of Ultrasound Vectors, William D. Richard Ph.D.
All Computer Science and Engineering Research
Upsampling is required prior to the summation step in most receive digital beamforming implementations to produce an accurate summed RF line or vector. This is true in both annular and linear array systems where receive echos are digitized first and then time delayed in the digital domain to achieve proper signal alignment. The efficient, parallel, real-time upsampling circuit presented here produces M upsampled values per ADC clock, where M is the desired upsampling factor. A circuit implementation that upsamples by a factor of M=4 is presented as an example of the more general technique.
Automated Color Calibration Of Display Devices, Andrew Shulman
Automated Color Calibration Of Display Devices, Andrew Shulman
All Computer Science and Engineering Research
If you compare two identical images on two different monitors, they will likely appear different. Every display device is supposed to adhere to a particular set of standards regulating the color and intensity of the image it outputs. However, in practice, very few do. Color calibration is the practice of modifying the signal path such that the colors produced more closely match reference standards. This is essential for graphics professionals who are mastering original content. They must ensure that the source material appears correct when viewed on a reference monitor. When viewed on a consumer panel, however, some error will …
Parallel Real-Time Scheduling Of Dags, Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, Christopher Gill
Parallel Real-Time Scheduling Of Dags, Abusayeed Saifullah, David Ferry, Jing Li, Kunal Agrawal, Chenyang Lu, Christopher Gill
All Computer Science and Engineering Research
Recently, multi-core processors have become mainstream in processor design. To take full advantage of multi-core processing, computation-intensive real-time systems must exploit intra-task parallelism. In this paper, we address the open problem of real-time scheduling for a general model of deterministic parallel tasks, where each task is represented as a directed acyclic graph (DAG) with nodes having arbitrary execution requirements. We prove processor-speed augmentation bounds for both preemptive and non-preemptive real-time scheduling for general DAG tasks on multi-core processors. We first decompose each DAG into sequential tasks with their own release times and deadlines. Then we prove that these decomposed tasks …
Ewa Model With Recency Effect And Limited Memory, Hang Xie
Ewa Model With Recency Effect And Limited Memory, Hang Xie
All Computer Science and Engineering Research
Game theory is an important field in economics; it studies how people make decisions amid conflict and cooperation. Various experiments have been carried to study the way people play those games, and economists study those data for various purposes. There has been a rise of need for using artificial agents to simulate the game, since we could save the cost of hiring human subjects for the experiments, and we could gain more control over the experiment settings.
Scanner: An Efficient And Accurate Trimming Tool For Illumina Next Generation Sequencing Reads, Xiang Zhou
Scanner: An Efficient And Accurate Trimming Tool For Illumina Next Generation Sequencing Reads, Xiang Zhou
All Computer Science and Engineering Research
Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an exact match of the 3’ adapter sequence. In this report, …
Real-Time Multi-Core Virtual Machine Scheduling In Xen, Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, Insup Lee
Real-Time Multi-Core Virtual Machine Scheduling In Xen, Sisu Xi, Meng Xu, Chenyang Lu, Linh T.X. Phan, Christopher Gill, Olga Sokolsky, Insup Lee
All Computer Science and Engineering Research
Recent years have witnessed two major trends in the development of complex real-time systems. First, to reduce cost and enhance flexibility, multiple systems are sharing common computing platforms via virtualization technology, instead of being deployed separately on physically isolated hosts. Second, multicore processors are increasingly being used in real-time systems. The integration of real-time systems as virtual machines (VMs) atop common multicore platforms raises significant new research challenges in meeting the real-time performance requirements of multiple systems.