An aspect-oriented approach to designing role-based access control services

Access control (AC) limits access to the resources of a system only to authorized entities. Given that information systems today are increasingly interconnected, AC is extremely important. The implementation of an AC service is a complicated task. Yet the requirements to an AC service vary a lot. Accordingly, the design of an AC service should be flexible and extensible in order to save development effort and time. Unfortunately, with conventional object-oriented techniques, when an extension has not been anticipated at the design time, the modification incurred by the extension is often invasive. Invasive changes destroy design modularity, further deteriorate design extensibility, and even worse, they reduce product reliability. ^ A concern is crosscutting if it spans multiple object-oriented classes. It was identified that invasive changes were due to the crosscutting nature of most unplanned extensions. To overcome this problem, an aspect-oriented design approach for AC services was proposed, as aspect-oriented techniques could effectively encapsulate crosscutting concerns. The proposed approach was applied to develop an AC framework that supported role-based access control model. In the framework, the core role-based access control mechanism is given in an object-oriented design, while each extension is captured as an aspect. The resulting framework is well-modularized, flexible, and most importantly, supports noninvasive adaptation. ^ In addition, a process to formalize the aspect-oriented design was described. The purpose is to provide high assurance for AC services. Object-Z was used to specify the static structure and Predicate/Transition net was used to model the dynamic behavior. Object-Z was extended to facilitate specification in an aspect-oriented style. The process of formal modeling helps designers to enhance their understanding of the design, hence to detect problems. Furthermore, the specification can be mathematically verified. This provides confidence that the design is correct. It was illustrated through an example that the model was ready for formal analysis. ^

Carbon nanotube reinforced aluminum based nanocomposite fabricated by thermal spray forming

The present research concentrates on the fabrication of bulk aluminum matrix nanocomposite structures with carbon nanotube reinforcement. The objective of the work was to fabricate and characterize multi-walled carbon nanotube (MWCNT) reinforced hypereutectic Al-Si (23 wt% Si, 2 wt% Ni, 1 wt% Cu, rest Al) nanocomposite bulk structure with nanocrystalline matrix through thermal spray forming techniques viz. plasma spray forming (PSF) and high velocity oxy-fuel (HVOF) spray forming. This is the first research study, which has shown that thermal spray forming can be successfully used to synthesize carbon nanotube reinforced nanocomposites. Microstructural characterization based on quantitative microscopy, scanning and transmission electron microscopy (SEM and TEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Raman spectroscopy and X ray photoelectron spectroscopy (XPS) confirms (i) retention and macro/sub-macro level homogenous distribution of multiwalled carbon nanotubes in the Al-Si matrix and (ii) evolution of nanostructured grains in the matrix. Formation of ultrathin β-SiC layer on MWCNT surface, due to chemical reaction of Si atoms diffusing from Al-Si alloy and C atoms from the outer walls of MWCNTs has been confirmed theoretically and experimentally. The presence of SiC layer at the interface improves the wettability and the interfacial adhesion between the MWCNT reinforcement and the Al-Si matrix. Sintering of the as-sprayed nanocomposites was carried out in an inert environment for further densification. As-sprayed PSF nanocomposite showed lower microhardness compared to HVOF, due to the higher porosity content and lower residual stress. The hardness of the nanocomposites increased with sintering time due to effective pore removal. Uniaxial tensile test on CNT-bulk nanocomposite was carried out, which is the first ever study of such nature. The tensile test results showed inconsistency in the data attributed to inhomogeneous microstructure and limitation of the test samples geometry. The elastic moduli of nanocomposites were computed using different micromechanics models and compared with experimentally measured values. The elastic moduli of nanocomposites measured by nanoindentation technique, increased gradually with sintering attributed to porosity removal. The experimentally measured values conformed better with theoretically predicted values, particularly in the case of Hashin-Shtrikman bound method.

The relationship between alkaloid-based chemical defenses and diet in dendrobatid poison frogs

Chemical defenses are common among organisms and represent some of the most complex adaptations for avoiding predation, yet our understanding of the ecological nature of these systems remains incomplete. Poison frogs are a group of chemically defended organisms that are dependent entirely on diet for chemical defense. In this study, I identified the dietary arthropods responsible for chemical defense in poison frogs, described spatial and temporal patterns in alkaloid composition of poison frogs, and established links between patterns of variation in alkaloid defense and arthropod diet in poison frogs. Identifying dietary sources and studying patterns of variation in alkaloid composition is fundamental to understanding the ecology and evolution of chemical defense in poison frogs. ^ The dendrobatid poison frog Oophaga pumilio shares many alkaloids in common with other poison frogs and is known to vary in alkaloid composition throughout its geographic range. I designed my dissertation to take advantage of these characteristics and use O. pumilio as a model species for the study of chemical defense in poison frogs. Here, I identified siphonotid millipedes as a source for spiropyrrolizidine alkaloids, formicine ants as a source for pumiliotoxin alkaloids, and oribatid mites as dietary sources for the majority of alkaloids found in poison frogs. I found that alkaloid composition varied spatially and temporally, on both small and large scales, within and among populations of O. pumilio. Alkaloid variation between populations was related to geographic distance, and closer populations tended to have alkaloid compositions more similar to each other than to distant populations. ^ The findings of my study suggest that oribatid mites are the most important dietary source of alkaloids in poison frogs. However, overall alkaloid defense in poison frogs is based on a combination of dietary arthropods, including mites, ants, millipedes, and beetles. Variation in chemical defenses of poison frogs is due to (1) spatial and temporal differences in the presence of alkaloids in certain arthropods and (2) differences in the availability of certain alkaloid-containing arthropods, which are likely the result of differences as well as successional changes in forest structure among locations and through time. ^

How do partnerships lead to a competitive advantage? Applying the resource based view to nascent social ventures

This dissertation is one of the earliest to systematically apply and empirically test the resource-based view (RBV) in the context of nascent social ventures in a large scale study. Social ventures are entrepreneurial ventures organized as nonprofit, for-profit, or hybrid organizations whose primary purpose is to address unmet social needs and create social value. Nascent social ventures face resource gaps and engage in partnerships or alliances as one means to access external resources. These partnerships with different sectors facilitate social venture innovative and earned income strategies, and assist in the development of adequate heterogeneous resource conditions that impact competitive advantage. Competitive advantage in the context of nascent social ventures is achieved through the creation of value and the achievement of venture development activities and launching. The relationships between partnerships, heterogeneous resource conditions, strategies, and competitive advantage are analyzed in the context of nascent social ventures that participated in business plan competitions. A content analysis of 179 social venture business plans and an exploratory follow-up survey of 72 of these ventures are used to analyze these relationships using regression, ANOVA, correlations, t-tests, and non-parametric statistics. The findings suggest a significant positive relationship between competitive advantage and partnership diversity, heterogeneous resource conditions, social innovation, and earned income. Social capital is the type of resource most significantly related to competitive advantage. Founder previous start-up experience, client location, and business plan completeness are also found to be significant in the relationship between partnership diversity and competitive advantage. Finally the findings suggest that hybrid social ventures create a greater competitive advantage than nonprofit or for-profit social ventures. Consequently, this dissertation not only provides academics further insight into the factors that impact nascent social value creation, venture development, and ability to launch, but also offers practitioners guidance on how best to organize certain processes to create a competitive advantage. As a result more insight is gained into the nascent social venture creation process and how these ventures can have a greater impact on society.

The nature of microvariability in blazar 0716+714

We organized an international campaign to observe the blazar 0716+714 in the optical band. The observations took place from February 24, 2009 to February 26, 2009. The global campaign was carried out by observers from more that sixteen countries and resulted in an extended light curve nearly seventy-eight hours long. The analysis and the modeling of this light curve form the main work of this dissertation project. In the first part of this work, we present the time series and noise analyses of the data. The time series analysis utilizes discrete Fourier transform and wavelet analysis routines to search for periods in the light curve. We then present results of the noise analysis which is based on the idea that each microvariability curve is the realization of the same underlying stochastic noise processes in the blazar jet. ^ Neither reoccuring periods nor random noise can successfully explain the observed optical fluctuations. Hence in the second part, we propose and develop a new model to account for the microvariability we see in blazar 0716+714. We propose that the microvariability is due to the emission from turbulent regions in the jet that are energized by the passage of relativistic shocks. Emission from each turbulent cell forms a pulse of emission, and when convolved with other pulses, yields the observed light curve. We use the model to obtain estimates of the physical parameters of the emission regions in the jet.^

Tin oxide based composites derived using electrostatic spray deposition technique as anodes for lithium-ion batteries

Recent advances in the electric & hybrid electric vehicles and rapid developments in the electronic devices have increased the demand for high power and high energy density lithium ion batteries. Graphite (theoretical specific capacity: 372 mAh/g) used in commercial anodes cannot meet these demands. Amorphous SnO2 anodes (theoretical specific capacity: 781 mAh/g) have been proposed as alternative anode materials. But these materials have poor conductivity, undergo a large volume change during charging and discharging, large irreversible capacity loss leading to poor cycle performances. To solve the issues related to SnO2 anodes, we propose to synthesize porous SnO2 composites using electrostatic spray deposition technique. First, porous SnO2/CNT composites were fabricated and the effects of the deposition temperature (200, 250, 300 °C) & CNT content (10, 20, 30, 40 wt %) on the electrochemical performance of the anodes were studied. Compared to pure SnO2 and pure CNT, the composite materials as anodes showed better discharge capacity and cyclability. 30 wt% CNT content and 250 °C deposition temperature were found to be the optimal conditions with regard to energy capacity whereas the sample with 20% CNT deposited at 250 °C exhibited good capacity retention. This can be ascribed to the porous nature of the anodes and the improvement in the conductivity by the addition of CNT. Electrochemical impedance spectroscopy studies were carried out to study in detail the change in the surface film resistance with cycling. By fitting EIS data to an equivalent circuit model, the values of the circuit components, which represent surface film resistance, were obtained. The higher the CNT content in the composite, lower the change in surface film resistance at certain voltage upon cycling. The surface resistance increased with the depth of discharge and decreased slightly at fully lithiated state. Graphene was also added to improve the performance of pure SnO2 anodes. The composites heated at 280 °C showed better energy capacity and energy density. The specific capacities of as deposited and post heat-treated samples were 534 and 737 mAh/g after 70 cycles. At the 70th cycle, the energy density of the composites at 195 °C and 280 °C were 1240 and 1760 Wh/kg, respectively, which are much higher than the commercially used graphite electrodes (37.2–74.4 Wh/kg). Both SnO2/CNTand SnO2/grapheme based composites with improved energy densities and capacities than pure SnO2 can make a significant impact on the development of new batteries for electric vehicles and portable electronics applications.

An epistemic event -based correlation scheme for pervasive network management

Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

An Epistemic Event-based Correlation Scheme for Pervasive Network Management

Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

The Nature of Microvariability in Blazar 0716+714

We organized an international campaign to observe the blazar 0716+714 in the optical band. The observations took place from February 24, 2009 to February 26, 2009. The global campaign was carried out by observers from more that sixteen countries and resulted in an extended light curve nearly seventy-eight hours long. The analysis and the modeling of this light curve form the main work of this dissertation project. In the first part of this work, we present the time series and noise analyses of the data. The time series analysis utilizes discrete Fourier transform and wavelet analysis routines to search for periods in the light curve. We then present results of the noise analysis which is based on the idea that each microvariability curve is the realization of the same underlying stochastic noise processes in the blazar jet. Neither reoccuring periods nor random noise can successfully explain the observed optical fluctuations. Hence in the second part, we propose and develop a new model to account for the microvariability we see in blazar 0716+714. We propose that the microvariability is due to the emission from turbulent regions in the jet that are energized by the passage of relativistic shocks. Emission from each turbulent cell forms a pulse of emission, and when convolved with other pulses, yields the observed light curve. We use the model to obtain estimates of the physical parameters of the emission regions in the jet.

Tin Oxide Based Composites Derived Using Electrostatic Spray Deposition Technique as Anodes for Li-Ion Batteries

Recent advances in the electric & hybrid electric vehicles and rapid developments in the electronic devices have increased the demand for high power and high energy density lithium ion batteries. Graphite (theoretical specific capacity: 372 mAh/g) used in commercial anodes cannot meet these demands. Amorphous SnO2 anodes (theoretical specific capacity: 781 mAh/g) have been proposed as alternative anode materials. But these materials have poor conductivity, undergo a large volume change during charging and discharging, large irreversible capacity loss leading to poor cycle performances. To solve the issues related to SnO2 anodes, we propose to synthesize porous SnO2 composites using electrostatic spray deposition technique. First, porous SnO2/CNT composites were fabricated and the effects of the deposition temperature (200,250, 300 oC) & CNT content (10, 20, 30, 40 wt %) on the electrochemical performance of the anodes were studied. Compared to pure SnO2 and pure CNT, the composite materials as anodes showed better discharge capacity and cyclability. 30 wt% CNT content and 250 oC deposition temperature were found to be the optimal conditions with regard to energy capacity whereas the sample with 20% CNT deposited at 250 oC exhibited good capacity retention. This can be ascribed to the porous nature of the anodes and the improvement in the conductivity by the addition of CNT. Electrochemical impedance spectroscopy studies were carried out to study in detail the change in the surface film resistance with cycling. By fitting EIS data to an equivalent circuit model, the values of the circuit components, which represent surface film resistance, were obtained. The higher the CNT content in the composite, lower the change in surface film resistance at certain voltage upon cycling. The surface resistance increased with the depth of discharge and decreased slightly at fully lithiated state. Graphene was also added to improve the performance of pure SnO2 anodes. The composites heated at 280 oC showed better energy capacity and energy density. The specific capacities of as deposited and post heat-treated samples were 534 and 737 mAh/g after 70 cycles. At the 70th cycle, the energy density of the composites at 195 °C and 280 °C were 1240 and 1760 Wh/kg, respectively, which are much higher than the commercially used graphite electrodes (37.2-74.4 Wh/kg). Both SnO2/CNTand SnO2/grapheme based composites with improved energy densities and capacities than pure SnO2 can make a significant impact on the development of new batteries for electric vehicles and portable electronics applications.