MSCS Faculty Research and PublicationsCopyright (c) 2014 Marquette University All rights reserved.
http://epublications.marquette.edu/mscs_fac
Recent documents in MSCS Faculty Research and Publicationsen-usSun, 28 Sep 2014 01:36:05 PDT3600Topological Partitions of Euclidean Space by Spheres
http://epublications.marquette.edu/mscs_fac/216
http://epublications.marquette.edu/mscs_fac/216Fri, 26 Sep 2014 12:19:19 PDTPaul Bankston et al.H-enrichments and their Homeomorphism Groups II
http://epublications.marquette.edu/mscs_fac/215
http://epublications.marquette.edu/mscs_fac/215Fri, 26 Sep 2014 12:00:56 PDTH-enrichments of topologies are larger (i.e., inclusive) topologies that also have larger homeomorphism groups. The study of H-enrichments of the Euclidean and rational topologies via generalized Baire category arguments is continued. New results concern lower bounds on the number of H-enrichments, connectedness, and separation properties of such topologies and certain of their cardinal invariants.
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Paul BankstonOn the Classification of Minimally Free Rings of Continuous Functions
http://epublications.marquette.edu/mscs_fac/214
http://epublications.marquette.edu/mscs_fac/214Fri, 26 Sep 2014 11:51:29 PDTPaul Bankston et al.PriGen: A Generic Framework to Preserve Privacy of Healthcare Data in the Cloud
http://epublications.marquette.edu/mscs_fac/213
http://epublications.marquette.edu/mscs_fac/213Fri, 26 Sep 2014 11:41:30 PDT
With the rise of Healthcare IT infrastructures, the need of healthcare data sharing and integration has become extremely important. Cloud computing paradigm is one of the most popular healthcare IT infrastructures for facilitating electronic health record sharing and integration. Many predict that managing healthcare applications with clouds will make revolutionary change in the way we do healthcare today. Enabling the access to ubiquitous healthcare not only will help us improve healthcare as our data will always be accessible from anywhere at any time, but also it helps cutting down the costs drastically. However, since healthcare data contains lots of sensitive private information, how to protect data privacy within the untrusted cloud is facing a huge challenge. Thus, a mechanism to protect the privacy of healthcare data is needed when these data are stored and processed within the cloud to provide various medical services. To address this issue, in this paper, we present a generic framework named PriGen that preserves the privacy of sensitive healthcare data in the cloud. PriGen allows the users to preserve privacy while accessing cloud based healthcare service without the help of a trusted third party. With making use of homomorphic encryption function on sensitive private information; our proposed framework maintains confidentiality of private information sent by the cloud users to untrusted cloud based healthcare service providers. In this paper, we also present a brief discussion of different components of PriGen framework.
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Farzana Rahman et al.Identifying Phases of Gait and Development of Walking Model from Pressure and Accelerometer Data and Its' Ramifications in Elderly Walking
http://epublications.marquette.edu/mscs_fac/212
http://epublications.marquette.edu/mscs_fac/212Fri, 26 Sep 2014 09:29:05 PDT
Locomotion is a feature of all animals. Whereas quadruped are fast and stable, human’s bipedal gait is less stable and less efficient. Human gait analysis is going on for a long time. Such analysis usually used force data applied on the ground during different phases of gait. In this paper, we have analyzed the pressure data collected from pressure sensors placed on shoes along with accelerometer data collected from cell phones during walking activity. We identified different phases of walking activity using the pressure data. We also have developed a biomechanical model of gait based on the pressure and acceleration data.
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Ferdaus Kawsar et al.Elderly Safety: A Smartphone Based Real Time Approach
http://epublications.marquette.edu/mscs_fac/211
http://epublications.marquette.edu/mscs_fac/211Fri, 26 Sep 2014 09:21:52 PDT
As the number of elderly people living worldwide and average life expectancy increases, older adults’ safety assurance has become increasingly important. There are many works on safety issues of the elderly focusing on human activity classification. Most of them use external sensor devices and/or completely or partially user input based classification and prediction systems. In this paper, we have developed an algorithmic model, monitored and documented elderly people‘s daily activities by using the gyroscope and accelerometer of a smartphone and with the use of those data and model, we calculated how much activity is required or overdone for a subject in order to maintain a healthy lifestyle. More importantly, we built a real time system that could not only judge what basic activity the subject is currently doing, but also protect the subject from possible injury that might happen to the subject if abnormal data is received.
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Mohammad Arif Ul Alam et al.Lung Uptake of 99mTc- Hexamethylpropyleneamine Oxime (99mTc-HMPAO) in Two Unique Rat Models of Pulmonary Oxygen Toxicity
http://epublications.marquette.edu/mscs_fac/210
http://epublications.marquette.edu/mscs_fac/210Fri, 26 Sep 2014 09:06:48 PDTAnne V. CloughTowards Improving Reliability of Computational RFID Based Smart Healthcare Monitoring Systems
http://epublications.marquette.edu/mscs_fac/209
http://epublications.marquette.edu/mscs_fac/209Fri, 12 Sep 2014 09:01:49 PDT
Advances in networking and small sensors (motes, RFID tags, etc) have made it possible to monitor and provide medical assistance to people in need at their homes. Recently, WISP tags, one advanced technology of Radio Frequency Identification (RFID) tags, have been used to monitor indoor activity, vital signs, sleep quality, and health status remotely. These types of systems take collaborative decision based on the data collected from all the WISP tags of the system. Any missing tag data within the environment may introduce critical error in the system’s decision and this eventually may jeopardize system’s decision reliability. In order to maintain system’s reliability, a monitoring protocol needs to be executed frequently and it should be made efficient in terms of execution time. This paper studies the problem of monitoring a large set of WISP tags and identifying the missing ones. In this paper, based on probabilistic methods, we propose a monitoring protocol for WISP based Smart Healthcare Monitoring Systems. The goal of this protocol is to improve the security and reliability of a smart healthcare monitoring system by detecting missing tags and reporting back only the data of the existing tags.
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Farzana Rahman et al.Longitudinal Investigation of the Effect of Middle School Curriculum on Learning in High School
http://epublications.marquette.edu/mscs_fac/208
http://epublications.marquette.edu/mscs_fac/208Thu, 11 Sep 2014 09:37:24 PDTJohn C. MoyerExploring the Relationship between K-8 Prospective Teachers’ Algebraic Thinking Proficiency and the Questions They Pose during Diagnostic Algebraic Thinking Interviews
http://epublications.marquette.edu/mscs_fac/207
http://epublications.marquette.edu/mscs_fac/207Fri, 05 Sep 2014 12:17:08 PDT
In this study, we explored the relationship between prospective teachers’ algebraic thinking and the questions they posed during one-on-one diagnostic interviews that focused on investigating the algebraic thinking of middle school students. To do so, we evaluated prospective teachers’ algebraic thinking proficiency across 125 algebra-based tasks and we analyzed the characteristics of questions they posed during the interviews. We found that prospective teachers with lower algebraic thinking proficiency did not ask any probing questions. Instead, they either posed questions that simply accepted and affirmed student responses or posed questions that guided the students toward an answer without probing student thinking. In contrast, prospective teachers with higher algebraic thinking proficiency were able to pose probing questions to investigate student thinking or help students clarify their thinking. However, less than half of their questions were of this probing type. These results suggest that prospective teachers’ algebraic thinking proficiency is related to the types of questions they ask to explore the algebraic thinking of students. Implications for mathematics teacher education are discussed.
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Leigh A. Van den Kieboom et al.Ricean over Gaussian Modelling in Magnitude fMRI Analysis—added Complexity with Negligible Practical Benefits
http://epublications.marquette.edu/mscs_fac/206
http://epublications.marquette.edu/mscs_fac/206Thu, 04 Sep 2014 10:05:31 PDT
It is well known that Gaussian modelling of functional magnetic resonance imaging (fMRI) magnitude time-course data, which are truly Rice distributed, constitutes an approximation, especially at low signal-to-noise ratios (SNRs). Based on this fact, previous work has argued that Rice-based activation tests show superior performance over their Gaussian-based counterparts at low SNRs and should be preferred in spite of the attendant additional computational and estimation burden. Here, we revisit these past studies and, after identifying and removing their underlying limiting assumptions and approximations, provide a more comprehensive comparison. Our experimental evaluations using Receiver Operating Characteristic (ROC) curve methodology show that tests derived using Ricean modelling are substantially superior over the Gaussian-based activation tests only for SNRs below 0.6, that is, SNR values far lower than those encountered in fMRI as currently practiced.
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Daniel W. Adrian et al.Quantifying the Statistical Impact of GRAPPA in fcMRI Data with a Real-Valued Isomorphism
http://epublications.marquette.edu/mscs_fac/205
http://epublications.marquette.edu/mscs_fac/205Thu, 04 Sep 2014 09:56:44 PDT
The interpolation of missing spatial frequencies through the generalized auto-calibrating partially parallel acquisitions (GRAPPA) parallel magnetic resonance imaging (MRI) model implies a correlation is induced between the acquired and reconstructed frequency measurements. As the parallel image reconstruction algorithms in many medical MRI scanners are based on the GRAPPA model, this study aims to quantify the statistical implications that the GRAPPA model has in functional connectivity studies. The linear mathematical framework derived in the work of Rowe , 2007, is adapted to represent the complex-valued GRAPPA image reconstruction operation in terms of a real-valued isomorphism, and a statistical analysis is performed on the effects that the GRAPPA operation has on reconstructed voxel means and correlations. The interpolation of missing spatial frequencies with the GRAPPA model is shown to result in an artificial correlation induced between voxels in the reconstructed images, and these artificial correlations are shown to reside in the low temporal frequency spectrum commonly associated with functional connectivity. Through a real-valued isomorphism, such as the one outlined in this manuscript, the exact artificial correlations induced by the GRAPPA model are not simply estimated, as they would be with simulations, but are precisely quantified. If these correlations are unaccounted for, they can incur an increase in false positives in functional connectivity studies.
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Iain P. Bruce et al.A Statistical fMRI Model for Differential T2* Contrast Incorporating T1 and T2* of Gray Matter
http://epublications.marquette.edu/mscs_fac/204
http://epublications.marquette.edu/mscs_fac/204Thu, 04 Sep 2014 09:49:36 PDT
Relaxation parameter estimation and brain activation detection are two main areas of study in magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI). Relaxation parameters can be used to distinguish voxels containing different types of tissue whereas activation determines voxels that are associated with neuronal activity. In fMRI, the standard practice has been to discard the first scans to avoid magnetic saturation effects. However, these first images have important information on the MR relaxivities for the type of tissue contained in voxels, which could provide pathological tissue discrimination. It is also well-known that the voxels located in gray matter (GM) contain neurons that are to be active while the subject is performing a task. As such, GM MR relaxivities can be incorporated into a statistical model in order to better detect brain activation. Moreover, although the MR magnetization physically depends on tissue and imaging parameters in a nonlinear fashion, a linear model is what is conventionally used in fMRI activation studies. In this study, we develop a statistical fMRI model for Differential T_{2}^{⁎} ConTrast Incorporating T_{1} and T_{2}^{⁎} of GM, so-called DeTeCT-ING Model, that considers the physical magnetization equation to model MR magnetization; uses complex-valued time courses to estimate T_{1} and T_{2}^{⁎} for each voxel; then incorporates gray matter MR relaxivities into the statistical model in order to better detect brain activation, all from a single pulse sequence by utilizing the first scans.
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M Muge Karaman et al.Varieties of P-Restriction Semigroups
http://epublications.marquette.edu/mscs_fac/203
http://epublications.marquette.edu/mscs_fac/203Tue, 02 Sep 2014 08:59:48 PDT
The restriction semigroups, in both their one-sided and two-sided versions, have arisen in various fashions, meriting study for their own sake. From one historical perspective, as “weakly E-ample” semigroups, the definition revolves around a “designated set” of commuting idempotents, better thought of as projections. This class includes the inverse semigroups in a natural fashion. In a recent paper, the author introduced P-restriction semigroups in order to broaden the notion of “projection” (thereby encompassing the regular *-semigroups). That study is continued here from the varietal perspective introduced for restriction semigroups by V. Gould. The relationship between varieties of regular *-semigroups and varieties of P-restriction semigroups is studied. In particular, a tight relationship exists between varieties of orthodox *-semigroups and varieties of “orthodox” P-restriction semigroups, leading to concrete descriptions of the free orthodox P-restriction semigroups and related structures. Specializing further, new, elementary paths are found for descriptions of the free restriction semigroups, in both the two-sided and one-sided cases.
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Peter R. JonesStatistical Image Reconstruction of Two Simultaneously Excited fMRI Slices
http://epublications.marquette.edu/mscs_fac/202
http://epublications.marquette.edu/mscs_fac/202Tue, 26 Aug 2014 13:44:41 PDT
In functional MRI, each slice in a volume is traditionally excited individually, measuring enough data in a single k-space array to reconstruct an image for that slice. However, simultaneously exciting multiple slices that make up a volume can produce sufficient data in a single k-space array to represent multiple slices. This single array of k-space data can be reconstructed into a single image representing the aliased slices, and then separated into individual images for each slice. A statistical description of an image representing two aliased slices using a single channel coil is presented. Image separation, utilizing calibration reference scans of each slice, through both an existing magnitudeonly approach and a new complex-valued approach are described, and the statistical properties of these two image separation approaches are presented. Through examining the expected mean image and covariance matrix of the separated images, it is theoretically shown that correlations remain between images of slices through both approaches. Since the image separation process is not the inverse of the image aliasing process, the separated images have different statistical properties than slices excited individually. Through both theoretical and experimental data, the complex-valued approach is shown to out-perform the magnitude-only approach.
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Daniel B. Rowe et al.Topological Extensions and Subspaces of ηα-sets
http://epublications.marquette.edu/mscs_fac/201
http://epublications.marquette.edu/mscs_fac/201Tue, 12 Aug 2014 10:27:48 PDT
The η_{x}-sets of Hausdorff have large compactifications (of cardinality ≽ exp(α); and of cardinality ≽ exp(exp(2^{<}^{α})) in the Stone-Čech case). If Q_{α} denotes the unique (when it exists) η_{α }-set of cardinality α, then Q_{α} can be decomposed (= partitioned) into homeomorphs of any prescribed nonempty subspace; moreover the subspaces of Q_{α} can be characterized as those which arc regular T_{1}, of cardinality and weight ≼ α, whose topologies are closed under < α intersections.
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Paul BankstonA System Implementation of Interruption Management for Mobile Devices
http://epublications.marquette.edu/mscs_fac/200
http://epublications.marquette.edu/mscs_fac/200Thu, 07 Aug 2014 14:08:27 PDT
As the number of worldwide cellular subscriptions approaches the world's population, the negative effects of cell phone disruption have become increasingly apparent. With advances in mobile phones, specifically their sensor technology, mobile phones are now capable of moderating interruptions based on whether or not the user would want an interruption. Research into the area of interruption management has provided models and architectures for the creation of such an application. However, to our knowledge, there are no interruption management systems currently available in the Android or iPhone app stores that utilize a probabilistic model to moderate cell phone interruptions. A probabilistic model would be an improvement over current binary decision models as the user would not need to predetermine every possible outcome. In this project, we have used a probabilistic model to implement an interruption management system for Android OS 4.0 which utilizes five contexts: schedule, time of day, location, caller relationship, and driving. Our system intercepts the call, calculates the probability of interruption, and then changes the phone's audio profile to vibrate, silent, or ring based on our model. Our performance evaluations indicate minor application foot print size, reasonable battery consumption, and very little time overhead for the application.
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William Vilwock et al.A2E: Adaptively Aggressive Energy Efficient DVFS Scheduling for Data Intensive Applications
http://epublications.marquette.edu/mscs_fac/199
http://epublications.marquette.edu/mscs_fac/199Thu, 07 Aug 2014 13:39:51 PDT
Featured by high portability and programmability, Dynamic Voltage and Frequency Scaling (DVFS) has been widely employed to achieve energy efficiency for high performance applications on distributed-memory architectures nowadays through various scheduling algorithms. Generally, different forms of slack from load imbalance, network latency, communication delay, memory and disk access stalls, etc. are exploited as energy saving opportunities where peak CPU performance is not necessary, with little or limited performance loss. The deployment of DVFS for communication intensive applications is straightforward due to the explicit boundary between Energy Saving Blocks (ESBs) at source code level, while for data (e.g., memory and disk access) intensive applications it is difficult for applying DVFS since ESB boundary is implicit due to mixed types of workloads. We propose an adaptively aggressive DVFS scheduling strategy to achieve energy efficiency for data intensive applications, and further save energy via speculation to mitigate DVFS overhead for imbalanced branches. We implemented and evaluated our approach using five memory and disk access intensive benchmarks with imbalanced branches against another two energy saving approaches. The experimental results indicate an average of 32.6% energy savings were achieved with 6.2% average performance loss compared to the original executions on a power-aware 64-core cluster.
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Li Tan et al.Using Intelligent Prefetching to Reduce the Energy Consumption of a Large-scale Storage System
http://epublications.marquette.edu/mscs_fac/198
http://epublications.marquette.edu/mscs_fac/198Thu, 07 Aug 2014 13:30:40 PDT
Many high performance large-scale storage systems will experience significant workload increases as their user base and content availability grow over time. The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) center hosts one such system that has recently undergone a period of rapid growth as its user population grew nearly 400% in just about three years. When administrators of these massive storage systems face the challenge of meeting the demands of an ever increasing number of requests, the easiest solution is to integrate more advanced hardware to existing systems. However, additional investment in hardware may significantly increase the system cost as well as daily power consumption. In this paper, we present evidence that well-selected software level optimization is capable of achieving comparable levels of performance without the cost and power consumption overhead caused by physically expanding the system. Specifically, we develop intelligent prefetching algorithms that are suitable for the unique workloads and user behaviors of the world's largest satellite images distribution system managed by USGS EROS. Our experimental results, derived from real-world traces with over five million requests sent by users around the globe, show that the EROS hybrid storage system could maintain the same performance with over 30% of energy savings by utilizing our proposed prefetching algorithms, compared to the alternative solution of doubling the size of the current FTP server farm.
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Brian Romoser et al.Regularization of Multivariate Regression Models with Skew Errors
http://epublications.marquette.edu/mscs_fac/197
http://epublications.marquette.edu/mscs_fac/197Thu, 07 Aug 2014 07:51:43 PDT
We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding L_{1}-penalties on the entries of the two matrices. Taking advantage of the hierarchical representation of skew-t distributions, and using the expectation conditional maximization (ECM) algorithm, we reduce the problem to penalized normal likelihood and develop a procedure to minimize the ensuing objective function. Using a simulation study the performance of the method is assessed, and the methodology is illustrated using a real data set with a 24-dimensional response vector.
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Lianfu Chen et al.