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Articles 1 - 24 of 24
Full-Text Articles in Engineering
Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Segmentation Of Intracranial Structures From Noncontrast Ct Images With Deep Learning, Evan Porter
Wayne State University Dissertations
Presented in this work is an investigation of the application of artificially intelligent algorithms, namely deep learning, to generate segmentations for the application in functional avoidance radiotherapy treatment planning. Specific applications of deep learning for functional avoidance include generating hippocampus segmentations from computed tomography (CT) images and generating synthetic pulmonary perfusion images from four-dimensional CT (4DCT).A single institution dataset of 390 patients treated with Gamma Knife stereotactic radiosurgery was created. From these patients, the hippocampus was manually segmented on the high-resolution MR image and used for the development of the data processing methodology and model testing. It was determined that …
Software As A Service: The Mediating Role Of Consequences Of Saas Diffusion On Firm Performance, Cristina Marie-Mccarthy Recchia
Software As A Service: The Mediating Role Of Consequences Of Saas Diffusion On Firm Performance, Cristina Marie-Mccarthy Recchia
Wayne State University Dissertations
ABSTRACTSOFTWARE AS A SERVICE: THE MEDIATING ROLE OF CONSEQUENCES OF SAAS DIFFUSION ON FIRM PERFORMANCE by CRISTINA MARIE-MCCARTHY RECCHIA DECEMBER 2021 Advisor: Dr. Ratna Babu Chinnam Major: Industrial Engineering Degree: Doctor of Philosophy There are ample studies that support a positive link between information technology and firm performance. Bharadwaj (2000) and Chae (2014, 2018) are two examples that provided a foundation for this work. These scholars looked at how capabilities associated with information technology contribute to improved financial performance using a specific set of financial ratios. In addition, there are studies that examine a positive link between Software-as-a-Service (SaaS) and …
Data-Driven Intelligent Scheduling For Long Running Workloads In Large-Scale Datacenters, Guoyao Xu
Data-Driven Intelligent Scheduling For Long Running Workloads In Large-Scale Datacenters, Guoyao Xu
Wayne State University Dissertations
Cloud computing is becoming a fundamental facility of society today. Large-scale public or private cloud datacenters spreading millions of servers, as a warehouse-scale computer, are supporting most business of Fortune-500 companies and serving billions of users around the world. Unfortunately, modern industry-wide average datacenter utilization is as low as 6% to 12%. Low utilization not only negatively impacts operational and capital components of cost efficiency, but also becomes the scaling bottleneck due to the limits of electricity delivered by nearby utility. It is critical and challenge to improve multi-resource efficiency for global datacenters.
Additionally, with the great commercial success of …
Integrated Strategies For Sustainable Wastewater-Based Algal Biofuel Production And Environmental Mitigation In The Us, Javad Roostaei
Integrated Strategies For Sustainable Wastewater-Based Algal Biofuel Production And Environmental Mitigation In The Us, Javad Roostaei
Wayne State University Dissertations
Integration of algae cultivation with wastewater treatment has received increasing interest as a cost-effective strategy for biofuel production. However, there has been no full assessment of algal biofuel production with wastewater on macro-scale by taking into account wastewater resources, land availability, CO2 emission resources, and geographic variation. This research addressed and evaluated the use of wastewater for algae cultivation, in terms of modeling and laboratory experiments. The first goal of this research was to develop a spatially explicit lifecycle model, by integrating life cycle assessment (LCA), and Geographic Information Systems (GIS) analysis, for the evaluation of the environmental and economic …
Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad
Data-Driven Modeling For Decision Support Systems And Treatment Management In Personalized Healthcare, Milad Zafar Nezhad
Wayne State University Dissertations
Massive amount of electronic medical records (EMRs) accumulating from patients and populations motivates clinicians and data scientists to collaborate for the advanced analytics to create knowledge that is essential to address the extensive personalized insights needed for patients, clinicians, providers, scientists, and health policy makers. Learning from large and complicated data is using extensively in marketing and commercial enterprises to generate personalized recommendations. Recently the medical research community focuses to take the benefits of big data analytic approaches and moves to personalized (precision) medicine. So, it is a significant period in healthcare and medicine for transferring to a new paradigm. …
Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi
Identification Of Streptococcus Pyogenes Using Raman Spectroscopy, Ehsan Majidi
Wayne State University Dissertations
Despite the attention that Raman Spectroscopy has gained recently in the area of pathogen identification, the spectra analyses techniques are not well developed. In most scenarios, they rely on expert intervention to detect and assign the peaks of the spectra to specific molecular vibration. Although some investigators have used machine-learning techniques to classify pathogens, these studies are usually limited to a specific application, and the generalization of these techniques is not clear. Also, a wide range of algorithms have been developed for classification problems, however, there is less insight to applying such methods on Raman spectra. Furthermore, analyzing the Raman …
Video Stream Adaptation In Computer Vision Systems, Yousef Sharrab Sharrab
Video Stream Adaptation In Computer Vision Systems, Yousef Sharrab Sharrab
Wayne State University Dissertations
Computer Vision (CV) has been deployed recently in a wide range of applications, including surveillance and automotive industries. According to a recent report, the market for CV technologies will grow to $33.3 billion by 2019. Surveillance and automotive industries share over 20% of this market. This dissertation considers the design of real-time CV systems with live video streaming, especially those over wireless and mobile networks. Such systems include video cameras/sensors and monitoring stations. The cameras should adapt their captured videos based on the events and/or available resources and time requirement. The monitoring station receives video streams from all cameras and …
Force Field Development With Gomc A Fast New Monte Carlo Molecular Simulation Code, Jason Richard Mick
Force Field Development With Gomc A Fast New Monte Carlo Molecular Simulation Code, Jason Richard Mick
Wayne State University Dissertations
In this work GOMC (GPU Optimized Monte Carlo) a new fast, flexible, and free molecular Monte Carlo code for the simulation atomistic chemical systems is presented. The results of a large Lennard-Jonesium simulation in the Gibbs ensemble is presented. Force fields developed using the code are also presented. To fit the models a quantitative fitting process is outlined using a scoring function and heat maps. The presented n-6 force fields include force fields for noble gases and branched alkanes. These force fields are shown to be the most accurate LJ or n-6 force fields to date for these compounds, capable …
A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park
A Prediction Modeling Framework For Noisy Welding Quality Data, Junheung Park
Wayne State University Dissertations
Numerous and various research projects have been conducted to utilize historical manufacturing process data in product design. These manufacturing process data often contain data inconsistencies, and it causes challenges in extracting useful information from the data. In resistance spot welding (RSW), data inconsistency is a well-known issue. In general, such inconsistent data are treated as noise data and removed from the original dataset before conducting analyses or constructing prediction models. This may not be desirable for every design and manufacturing applications since every data can contain important information to further explain the process. In this research, we propose a prediction …
Building Computing-As-A-Service Mobile Cloud System, Kun Wang
Building Computing-As-A-Service Mobile Cloud System, Kun Wang
Wayne State University Dissertations
The last five years have witnessed the proliferation of smart mobile devices, the explosion of various mobile applications and the rapid adoption of cloud computing in business, governmental and educational IT deployment. There is also a growing trends of combining mobile computing and cloud computing as a new popular computing paradigm nowadays. This thesis envisions the future of mobile computing which is primarily affected by following three trends: First, servers in cloud equipped with high speed multi-core technology have been the main stream today. Meanwhile, ARM processor powered servers is growingly became popular recently and the virtualization on ARM systems …
Novel Incorportation Of Biomedical Engineering Algorithms (Bispectral Index Guided Or Anesthetic Concentration Guided) In Real-Time Decision Support To Prevent Intraoperative Awareness Using An Electronic Anesthesia Information Mananagement System, Amy Melanie Shanks
Wayne State University Dissertations
Background: Intraoperative awareness with explicit recall (AWR) is a feared complication of surgery that can lead to significant psychological distress. Several large prospective trials have been completed comparing two methods of monitoring anesthetic depth [minimum alveolar concentration (MAC) or electroencephalography (EEG) monitoring using the bispectral index (BIS)] for the prevention of AWR. However, these trials were conducted in high risk populations, limiting generalizability.
Research Hypothesis: Real-time decision support with Anesthesia Information Management System alerts based on a novel anesthetic concentration algorithm (incorporating the use of intravenous anesthetics) or an EEG-guided algorithm will reduce the known incidence of AWR.
Methods: First, …
Building A Scalable And High-Performance Key-Value Store System, Yuehai Xu
Building A Scalable And High-Performance Key-Value Store System, Yuehai Xu
Wayne State University Dissertations
Contemporary web sites can store and process very large amounts of data. To provide timely service to their users, they have adopted key-value (KV) stores, which is a simple but effective caching infrastructure atop the conventional databases that store these data, to boost performance. Examples are Facebook, Twitter and Amazon. As yet little is known about the realistic workloads outside of the companies that operate them, this dissertation work provides a detailed workload study on Facebook's Memcached, which is one of the world's largest KV deployment. We analyze the Memcached workload from the perspective of server-side performance, request composition, caching …
The Design, Analysis, & Application Of Multi-Modal Real-Time Embedded Systems, Masud Ahmed
The Design, Analysis, & Application Of Multi-Modal Real-Time Embedded Systems, Masud Ahmed
Wayne State University Dissertations
For many hand-held computing devices (e.g., smartphones), multiple operational modes are preferred because of their flexibility. In addition to their designated purposes, some of these devices provide a platform for different types of services, which include rendering of high-quality multimedia. Upon such devices, temporal isolation among co-executing applications is very important to ensure that each application receives an acceptable level of quality-of-service. In order to provide strong guarantees on services, multimedia applications and real-time control systems maintain timing constraints in the form of deadlines for recurring tasks. A flexible real-time multi-modal system will ideally provide system designers the option to …
Advanced Optimization Techniques For Monte Carlo Simulation On Graphics Processing Units, Eyad Hailat
Advanced Optimization Techniques For Monte Carlo Simulation On Graphics Processing Units, Eyad Hailat
Wayne State University Dissertations
The objective of this work is to design and implement a self-adaptive parallel GPU optimized Monte Carlo algorithm for the simulation of adsorption in porous materials. We focus on Nvidia's GPUs and CUDA's Fermi architecture specifically. The resulting package supports the different ensemble methods for the Monte Carlo simulation, which will allow for the simulation of multi-component adsorption in porous solids. Such an algorithm will have broad applications to the development of novel porous materials for the sequestration of CO2 and the filtration of toxic industrial chemicals.
The primary objective of this work is the release of a massively parallel …
Visual Exploration And Information Analytics Of High-Dimensional Medical Images, Darshan Pai
Visual Exploration And Information Analytics Of High-Dimensional Medical Images, Darshan Pai
Wayne State University Dissertations
Data visualization has transformed how we analyze increasingly large and complex data sets. Advanced visual tools logically represent data in a way that communicates the most important information inherent within it and culminate the analysis with an insightful conclusion. Automated analysis disciplines - such as data mining, machine learning, and statistics - have traditionally been the most dominant fields for data analysis. It has been complemented with a near-ubiquitous adoption of specialized hardware and software environments that handle the storage, retrieval, and pre- and postprocessing of digital data. The addition of interactive visualization tools allows an active human participant in …
Learning With An Insufficient Supply Of Data Via Knowledge Transfer And Sharing, Samir Al-Stouhi
Learning With An Insufficient Supply Of Data Via Knowledge Transfer And Sharing, Samir Al-Stouhi
Wayne State University Dissertations
As machine learning methods extend to more complex and diverse set of problems, situations arise where the complexity and availability of data presents a situation where the information source is not "adequate" to generate a representative hypothesis. Learning from multiple sources of data is a promising research direction as researchers leverage ever more diverse sources of information. Since data is not readily available, knowledge has to be transferred from other sources and new methods (both supervised and un-supervised) have to be developed to selectively share and transfer knowledge. In this dissertation, we present both supervised and un-supervised techniques to tackle …
Opacity Of Discrete Event Systems: Analysis And Control, Majed Mohamed Ben Kalefa
Opacity Of Discrete Event Systems: Analysis And Control, Majed Mohamed Ben Kalefa
Wayne State University Dissertations
The exchange of sensitive information in many systems over a network can be manipulated
by unauthorized access. Opacity is a property to investigate security and
privacy problems in such systems. Opacity characterizes whether a secret information
of a system can be inferred by an unauthorized user. One approach to verify security
and privacy properties using opacity problem is to model the system that may leak confidential
information as a discrete event system. The problem that has not investigated
intensively is the enforcement of opacity properties by supervisory control. In other
words, constructing a minimally restrictive supervisor to limit the system's …
Rethinking The Design And Implementation Of The I/O Software Stack For High-Performance Computing, Xuechen Zhang
Rethinking The Design And Implementation Of The I/O Software Stack For High-Performance Computing, Xuechen Zhang
Wayne State University Dissertations
Current I/O stack for high-performance computing is composed of multiple software layers in order to hide users from complexity of I/O performance optimization. However, the design and implementation of a specific layer is usually carried out separately with limited consideration of its impact on other layers, which could result in suboptimal I/O performance because data access locality is weakened, if not lost, on hard disk, a widely used storage medium in high-end storage systems.
In this dissertation, we experimentally demonstrated such issues in four different layers, including operating system process management layer and MPI-IO middleware layer on compute server side, …
Querying And Managing Opm-Compliant Scientific Workflow Provenance, Chunhyeok Lim
Querying And Managing Opm-Compliant Scientific Workflow Provenance, Chunhyeok Lim
Wayne State University Dissertations
Provenance, the metadata that records the derivation history of scientific results, is important in scientific workflows to interpret, validate, and analyze the result of scientific computing. Recently,
to promote and facilitate interoperability among heterogeneous provenance systems, the Open Provenance Model (OPM) has been proposed and has played an important role in the community.
In this dissertation, to efficiently query and manage OPM-compliant provenance, we first propose a provenance collection framework that collects both prospective provenance, which captures
an abstract workflow specification as a recipe for future data derivation and retrospective provenance, which captures past workflow execution and data derivation information. …
A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina
A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina
Wayne State University Dissertations
Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and …
Efficient Channel Allocation And Medium Access Organization Algorithms For Vehicular Networking, Zaydoun Yahya Rawashdeh
Efficient Channel Allocation And Medium Access Organization Algorithms For Vehicular Networking, Zaydoun Yahya Rawashdeh
Wayne State University Dissertations
Due to the limited bandwidth available for Vehicular Ad-hoc Networks (VANETs), organizing the wireless channel access to efficiently use the bandwidth is one of the main challenges in VANET. In this dissertation, we focus on channel allocation and media access organization for Vehicle-to-Roadside Units (V2R) and Vehicle-to-Vehicle (V2V) communications. An efficient channel allocation algorithm for Roadside Unit (RSU) access is proposed. The goal of the algorithm is to increase system throughput by admitting more tasks (vehicles) and at the same time reduce the risk of the admitted tasks. The algorithm admits the new requests only when their requirements can be …
Unified Role Assignment Framework For Wireless Sensor Networks, Manish Mahendra Kumar Kochhal
Unified Role Assignment Framework For Wireless Sensor Networks, Manish Mahendra Kumar Kochhal
Wayne State University Dissertations
Wireless sensor networks are made possible by the continuing improvements in embedded sensor, VLSI, and wireless radio technologies. Currently, one of the important challenges in sensor networks is the design of a systematic network management framework that allows localized and collaborative resource control uniformly across all application services such as sensing, monitoring, tracking, data aggregation, and routing.
The research in wireless sensor networks is currently oriented toward a cross-layer network abstraction that supports appropriate fine or course grained resource controls for energy efficiency. In that regard, we have designed a unified role-based service paradigm for wireless sensor networks. We pursue …
Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery, Lavie Pinchas Golenberg
Task Analysis, Modeling, And Automatic Identification Of Elemental Tasks In Robot-Assisted Laparoscopic Surgery, Lavie Pinchas Golenberg
Wayne State University Dissertations
Robotic microsurgery provides many advantages for surgical operations, including tremor filtration, an increase in dexterity, and smaller incisions. There is a growing need for a task analyses on robotic laparoscopic operations to understand better the tasks involved in robotic microsurgery cases. A few research groups have conducted task observations to help systems automatically identify surgeon skill based on task execution. Their gesture analyses, however, lacked depth and their class libraries were composed of ambiguous groupings of gestures that did not share contextual similarities.
A Hierarchical Task Analysis was performed on a four-throw suturing task using a robotic microsurgical platform. Three …
Filter Scheduling Function Model In Internet Server: Resource Configuration, Performance Evaluation And Optimal Scheduling, Minghua Xu
Wayne State University Dissertations
ABSTRACT
FILTER SCHEDULING FUNCTION MODEL IN INTERNET SERVER:
RESOURCE CONFIGURATION, PERFORMANCE EVALUATION AND
OPTIMAL SCHEDULING
by
MINGHUA XU
August 2010
Advisor: Dr. Cheng-Zhong Xu
Major: Computer Engineering
Degree: Doctor of Philosophy
Internet traffic often exhibits a structure with rich high-order statistical properties like selfsimilarity
and long-range dependency (LRD). This greatly complicates the problem of
server performance modeling and optimization. On the other hand, popularity of Internet
has created numerous client-server or peer-to-peer applications, with most of them,
such as online payment, purchasing, trading, searching, publishing and media streaming,
being timing sensitive and/or financially critical. The scheduling policy in Internet servers …