Extended principal component analysis and its applications to image analysis

The objectives of this research are to analyze and develop a modified Principal Component Analysis (PCA) and to develop a two-dimensional PCA with applications in image processing. PCA is a classical multivariate technique where its mathematical treatment is purely based on the eigensystem of positive-definite symmetric matrices. Its main function is to statistically transform a set of correlated variables to a new set of uncorrelated variables over $\IR\sp{n}$ by retaining most of the variations present in the original variables.^ The variances of the Principal Components (PCs) obtained from the modified PCA form a correlation matrix of the original variables. The decomposition of this correlation matrix into a diagonal matrix produces a set of orthonormal basis that can be used to linearly transform the given PCs. It is this linear transformation that reproduces the original variables. The two-dimensional PCA can be devised as a two successive of one-dimensional PCA. It can be shown that, for an $m\times n$ matrix, the PCs obtained from the two-dimensional PCA are the singular values of that matrix.^ In this research, several applications for image analysis based on PCA are developed, i.e., edge detection, feature extraction, and multi-resolution PCA decomposition and reconstruction. ^

Engineering access control for distributed enterprise applications

Access control (AC) is a necessary defense against a large variety of security attacks on the resources of distributed enterprise applications. However, to be effective, AC in some application domains has to be fine-grain, support the use of application-specific factors in authorization decisions, as well as consistently and reliably enforce organization-wide authorization policies across enterprise applications. Because the existing middleware technologies do not provide a complete solution, application developers resort to embedding AC functionality in application systems. This coupling of AC functionality with application logic causes significant problems including tremendously difficult, costly and error prone development, integration, and overall ownership of application software. The way AC for application systems is engineered needs to be changed. ^ In this dissertation, we propose an architectural approach for engineering AC mechanisms to address the above problems. First, we develop a framework for implementing the role-based access control (RBAC) model using AC mechanisms provided by CORBA Security. For those application domains where the granularity of CORBA controls and the expressiveness of RBAC model suffice, our framework addresses the stated problem. ^ In the second and main part of our approach, we propose an architecture for an authorization service, RAD, to address the problem of controlling access to distributed application resources, when the granularity and support for complex policies by middleware AC mechanisms are inadequate. Applying this architecture, we developed a CORBA-based application authorization service (CAAS). Using CAAS, we studied the main properties of the architecture and showed how they can be substantiated by employing CORBA and Java technologies. Our approach enables a wide-ranging solution for controlling the resources of distributed enterprise applications. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Enhanced zinc oxide and graphene nanostructures for electronics and sensing applications

Zinc oxide and graphene nanostructures are important technological materials because of their unique properties and potential applications in future generation of electronic and sensing devices. This dissertation investigates a brief account of the strategies to grow zinc oxide nanostructures (thin film and nanowire) and graphene, and their applications as enhanced field effect transistors, chemical sensors and transparent flexible electrodes. Nanostructured zinc oxide (ZnO) and low-gallium doped zinc oxide (GZO) thin films were synthesized by a magnetron sputtering process. Zinc oxide nanowires (ZNWs) were grown by a chemical vapor deposition method. Field effect transistors (FETs) of ZnO and GZO thin films and ZNWs were fabricated by standard photo and electron beam lithography processes. Electrical characteristics of these devices were investigated by nondestructive surface cleaning, ultraviolet irradiation treatment at high temperature and under vacuum. GZO thin film transistors showed a mobility of ∼5.7 cm2/V·s at low operation voltage of <5 V and a low turn-on voltage of ∼0.5 V with a sub threshold swing of ∼85 mV/decade. Bottom gated FET fabricated from ZNWs exhibit a very high on-to-off ratio (∼106) and mobility (∼28 cm2/V·s). A bottom gated FET showed large hysteresis of ∼5.0 to 8.0 V which was significantly reduced to ∼1.0 V by the surface treatment process. The results demonstrate charge transport in ZnO nanostructures strongly depends on its surface environmental conditions and can be explained by formation of depletion layer at the surface by various surface states. A nitric oxide (NO) gas sensor using single ZNW, functionalized with Cr nanoparticles was developed. The sensor exhibited average sensitivity of ∼46% and a minimum detection limit of ∼1.5 ppm for NO gas. The sensor also is selective towards NO gas as demonstrated by a cross sensitivity test with N2, CO and CO2 gases. Graphene film on copper foil was synthesized by chemical vapor deposition method. A hot press lamination process was developed for transferring graphene film to flexible polymer substrate. The graphene/polymer film exhibited a high quality, flexible transparent conductive structure with unique electrical-mechanical properties; ∼88.80% light transmittance and ∼1.1742Ω/sq k sheet resistance. The application of a graphene/polymer film as a flexible and transparent electrode for field emission displays was demonstrated.

Carbon nanotube based systems for high energy efficient applications

In the current age of fast-depleting conventional energy sources, top priority is given to exploring non-conventional energy sources, designing highly efficient energy storage systems and converting existing machines/instruments/devices into energy-efficient ones. ‘Energy efficiency’ is one of the important challenges for today’s scientific and research community, worldwide. In line with this demand, the current research was focused on developing two highly energy-efficient devices – field emitters and Li-ion batteries, using beneficial properties of carbon nanotubes (CNT). Interface-engineered, directly grown CNTs were used as cathode in field emitters, while similar structure was applied as anode in Li-ion batteries. Interface engineering was found to offer minimum resistance to electron flow and strong bonding with the substrate. Both field emitters and Li-ion battery anodes were benefitted from these advantages, demonstrating high energy efficiency. Field emitter, developed during this research, could be characterized by low turn-on field, high emission current, very high field enhancement factor and extremely good stability during long-run. Further, application of 3-dimensional design to these field emitters resulted in achieving one of the highest emission current densities reported so far. The 3-D field emitter registered 27 times increase in current density, as compared to their 2-D counterparts. These achievements were further followed by adding new functionalities, transparency and flexibility, to field emitters, keeping in view of current demand for flexible displays. A CNT-graphene hybrid structure showed appreciable emission, along with very good transparency and flexibility. Li-ion battery anodes, prepared using the interface-engineered CNTs, have offered 140% increment in capacity, as compared to conventional graphite anodes. Further, it has shown very good rate capability and an exceptional ‘zero capacity degradation’ during long cycle operation. Enhanced safety and charge transfer mechanism of this novel anode structure could be explained from structural characterization. In an attempt to progress further, CNTs were coated with ultrathin alumina by atomic layer deposition technique. These alumina-coated CNT anodes offered much higher capacity and an exceptional rate capability, with very low capacity degradation in higher current densities. These highly energy efficient CNT based anodes are expected to enhance capacities of future Li-ion batteries.

Switching patterns and steady-state analysis of grid-connected and stand-alone single-stage boost-inverters for PV applications

Renewable or sustainable energy (SE) sources have attracted the attention of many countries because the power generated is environmentally friendly, and the sources are not subject to the instability of price and availability. This dissertation presents new trends in the DC-AC converters (inverters) used in renewable energy sources, particularly for photovoltaic (PV) energy systems. A review of the existing technologies is performed for both single-phase and three-phase systems, and the pros and cons of the best candidates are investigated. In many modern energy conversion systems, a DC voltage, which is provided from a SE source or energy storage device, must be boosted and converted to an AC voltage with a fixed amplitude and frequency. A novel switching pattern based on the concept of the conventional space-vector pulse-width-modulated (SVPWM) technique is developed for single-stage, boost-inverters using the topology of current source inverters (CSI). The six main switching states, and two zeros, with three switches conducting at any given instant in conventional SVPWM techniques are modified herein into three charging states and six discharging states with only two switches conducting at any given instant. The charging states are necessary in order to boost the DC input voltage. It is demonstrated that the CSI topology in conjunction with the developed switching pattern is capable of providing the required residential AC voltage from a low DC voltage of one PV panel at its rated power for both linear and nonlinear loads. In a micro-grid, the active and reactive power control and consequently voltage regulation is one of the main requirements. Therefore, the capability of the single-stage boost-inverter in controlling the active power and providing the reactive power is investigated. It is demonstrated that the injected active and reactive power can be independently controlled through two modulation indices introduced in the proposed switching algorithm. The system is capable of injecting a desirable level of reactive power, while the maximum power point tracking (MPPT) dictates the desirable active power. The developed switching pattern is experimentally verified through a laboratory scaled three-phase 200W boost-inverter for both grid-connected and stand-alone cases and the results are presented.

Development and verification of control and protection strategies in hybrid AC/DC power systems for smart grid applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Research Note: Biometric Technology Applications and Trends in Hotels

The purpose of this study is to investigate the biometrics technologies adopted by hotels and the perception of hotel managers toward biometric technology applications. A descriptive, cross sectional survey was developed based on extensive review of literature and expert opinions. The population for this survey was property level executive managers in the U.S. hotels. Members of American Hotel and Lodging Association (AHLA) were selected as the target population for this study. The most frequent use of biometric technology is by hotel employees in the form of fingerprint scanning. Cost still seems to be one of the major barriers to adoption of biometric technology applications. The findings of this study showed that there definitely is a future in using biometric technology applications in hotels in the future, however, according to hoteliers; neither guests nor hoteliers are ready for it fully.

Stereoselective synthesis of vinyl germanes and silanes. Applications of tris(trimethyl)germanes and silanes in Pd-catalyzed cross -coupling reactions

Although group 14 organometallic compounds (Si, Sn) have been well developed as transmetallation reagents in cross-coupling reactions, the application of organogermanium compounds as cross-coupling reagents is still a relatively new area with few papers published. This study aimed to develop methods for the synthesis of new classes of vinyl germane and vinyl silane compounds, mainly Z and E tris(trimethylsilyl)germanes and silanes, which were then applied to Pd-catalyzed cross-couplings with aryl and alkenyl halides. The stereoselective radical-mediated desulfonylation of vinyl sulfones with tris(trimethyl)germanium or silane hydrides provided access to the synthesis of trans vinyl germanes or silanes. Alternatively hydrogermylation or hydrosilylation of terminal alkynes gave cis vinyl germanes or silanes. The application of these new classes of organometallic compounds in cross-coupling reactions with various aryl and alkenyl halides under aqueous [NaOH/H2O2/Pd(PPh 3)4] and anhydrous [KH/t-BuOOH/Pd(PPh 3)4] oxidative conditions were investigated. ^ It was found that the vinyl tris(trimethylsilyl)germanes successfully underwent Pd-catalyzed cross-couplings with aryl and alkenyl halides and aryl triflates under aqueous and anhydrous oxidative conditions. These procedures provided examples of "ligand-free" Pd-catalyzed coupling of organogermanes with aryl and alkenyl halides. Interestingly, couplings with fluorinated vinyl germanes appeared to occur more easily than with the corresponding (α-fluoro)vinyl stannanes and silanes since neither addition of an extra ligand nor activation with fluoride was necessary. The vinyl tris(trimethyl)silanes were found to be alternative substrates for the Hiyama reaction. The coupling of TTMS-silanes with various aryl, heteroaryl as well as alkenyl halides proceeded smoothly upon treatment with hydrogen peroxide in the presence of sodium hydroxide and fluoride ion. ^

An assessment of novel biodegradable magnesium alloys for endovascular biomaterial applications

Magnesium alloys have been widely explored as potential biomaterials, but several limitations to using these materials have prevented their widespread use, such as uncontrollable degradation kinetics which alter their mechanical properties. In an attempt to further the applicability of magnesium and its alloys for biomedical purposes, two novel magnesium alloys Mg-Zn-Cu and Mg-Zn-Se were developed with the expectation of improving upon the unfavorable qualities shown by similar magnesium based materials that have previously been explored. The overall performance of these novel magnesium alloys has been assessesed in three distinct phases of research: 1) analysing the mechanical properties of the as-cast magnesium alloys, 2) evaluating the biocompatibility of the as-cast magnesium alloys through the use of in-vitro cellular studies, and 3) profiling the degradation kinetics of the as-cast magnesium alloys through the use of electrochemical potentiodynamic polarization techqnique as well as gravimetric weight-loss methods. As compared to currently available shape memory alloys and degradable as-cast alloys, these experimental alloys possess superior as-cast mechanical properties with elongation at failure values of 12% and 13% for the Mg-Zn-Se and Mg-Zn-Se alloys, respectively. This is substantially higher than other as-cast magnesium alloys that have elongation at failure values that range from 7-10%. Biocompatibility tests revealed that both the Mg-Zn-Se and Mg-Zn-Cu alloys exhibit low cytotoxicity levels which are suitable for biomaterial applications. Gravimetric and electrochemical testing was indicative of the weight loss and initial corrosion behavior of the alloys once immersed within a simulated body fluid. The development of these novel as-cast magnesium alloys provide an advancement to the field of degradable metallic materials, while experimental results indicate their potential as cost-effective medical devices.^

Real-time scheduling of embedded applications on multi-core platforms

For the past several decades, we have experienced the tremendous growth, in both scale and scope, of real-time embedded systems, thanks largely to the advances in IC technology. However, the traditional approach to get performance boost by increasing CPU frequency has been a way of past. Researchers from both industry and academia are turning their focus to multi-core architectures for continuous improvement of computing performance. In our research, we seek to develop efficient scheduling algorithms and analysis methods in the design of real-time embedded systems on multi-core platforms. Real-time systems are the ones with the response time as critical as the logical correctness of computational results. In addition, a variety of stringent constraints such as power/energy consumption, peak temperature and reliability are also imposed to these systems. Therefore, real-time scheduling plays a critical role in design of such computing systems at the system level. We started our research by addressing timing constraints for real-time applications on multi-core platforms, and developed both partitioned and semi-partitioned scheduling algorithms to schedule fixed priority, periodic, and hard real-time tasks on multi-core platforms. Then we extended our research by taking temperature constraints into consideration. We developed a closed-form solution to capture temperature dynamics for a given periodic voltage schedule on multi-core platforms, and also developed three methods to check the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research by incorporating the power/energy constraint with thermal awareness into our research problem. We investigated the energy estimation problem on multi-core platforms, and developed a computation efficient method to calculate the energy consumption for a given voltage schedule on a multi-core platform. In this dissertation, we present our research in details and demonstrate the effectiveness and efficiency of our approaches with extensive experimental results.

Development of advanced capillary electrophoresis techniques with UV and mass spectrometry detection for forensic, pharmaceutical and environmental applications

Capillary electrophoresis (CE) is a modern analytical technique, which is electrokinetic separation generated by high voltage and taken place inside the small capillaries. In this dissertation, several advanced capillary electrophoresis methods are presented using different approaches of CE and UV and mass spectrometry are utilized as the detection methods. ^ Capillary electrochromatography (CEC), as one of the CE modes, is a recent developed technique which is a hybrid of capillary electrophoresis and high performance liquid chromatography (HPLC). Capillary electrochromatography exhibits advantages of both techniques. In Chapter 2, monolithic capillary column are fabricated using in situ photoinitiation polymerization method. The column was then applied for the separation of six antidepressant compounds. ^ Meanwhile, a simple chiral separation method is developed and presented in Chapter 3. Beta cycodextrin was utilized to achieve the goal of chiral separation. Not only twelve cathinone analytes were separated, but also isomers of several analytes were enantiomerically separated. To better understand the molecular information on the analytes, the TOF-MS system was coupled with the CE. A sheath liquid and a partial filling technique (PFT) were employed to reduce the contamination of MS ionization source. Accurate molecular information was obtained. ^ It is necessary to propose, develop, and optimize new techniques that are suitable for trace-level analysis of samples in forensic, pharmaceutical, and environmental applications. Capillary electrophoresis (CE) was selected for this task, as it requires lower amounts of samples, it simplifies sample preparation, and it has the flexibility to perform separations of neutral and charged molecules as well as enantiomers. ^ Overall, the study demonstrates the versatility of capillary electrophoresis methods in forensic, pharmaceutical, and environmental applications.^

Design of a dynamic e-commerce system with engineering applications

The primary purpose of this thesis was to design and develop a prototype e-commerce system where dynamic parameters are included in the decision-making process and execution of an online transaction. The system developed and implemented takes into account previous usage history, priority and associated engineering capabilities. The system was developed using three-tiered client server architecture. The interface was the Internet browser. The middle tiered web server was implemented using Active Server Pages, which form a link between the client system and other servers. A relational database management system formed the data component of the three-tiered architecture. It includes a capability for data warehousing which extracts needed information from the stored data of the customers as well as their orders. The system organizes and analyzes the data that is generated during a transaction to formulate a client's behavior model during and after a transaction. This is used for making decisions like pricing, order rescheduling during a client's forthcoming transaction. The system helps among other things to bring about predictability to a transaction execution process, which could be highly desirable in the current competitive scenario.