A self -testing approach for autonomic software

As researchers and practitioners move towards a vision of software systems that configure, optimize, protect, and heal themselves, they must also consider the implications of such self-management activities on software reliability. Autonomic computing (AC) describes a new generation of software systems that are characterized by dynamically adaptive self-management features. During dynamic adaptation, autonomic systems modify their own structure and/or behavior in response to environmental changes. Adaptation can result in new system configurations and capabilities, which need to be validated at runtime to prevent costly system failures. However, although the pioneers of AC recognize that validating autonomic systems is critical to the success of the paradigm, the architectural blueprint for AC does not provide a workflow or supporting design models for runtime testing. ^ This dissertation presents a novel approach for seamlessly integrating runtime testing into autonomic software. The approach introduces an implicit self-test feature into autonomic software by tailoring the existing self-management infrastructure to runtime testing. Autonomic self-testing facilitates activities such as test execution, code coverage analysis, timed test performance, and post-test evaluation. In addition, the approach is supported by automated testing tools, and a detailed design methodology. A case study that incorporates self-testing into three autonomic applications is also presented. The findings of the study reveal that autonomic self-testing provides a flexible approach for building safe, reliable autonomic software, while limiting the development and performance overhead through software reuse. ^

Peak-to-Average Power Ratio Reduced Parallel Interference Cancellation Multicarrier-Code Division Multiple Access System with Anti-Interference Property

Orthogonal Frequency-Division Multiplexing (OFDM) has been proved to be a promising technology that enables the transmission of higher data rate. Multicarrier Code-Division Multiple Access (MC-CDMA) is a transmission technique which combines the advantages of both OFDM and Code-Division Multiplexing Access (CDMA), so as to allow high transmission rates over severe time-dispersive multi-path channels without the need of a complex receiver implementation. Also MC-CDMA exploits frequency diversity via the different subcarriers, and therefore allows the high code rates systems to achieve good Bit Error Rate (BER) performances. Furthermore, the spreading in the frequency domain makes the time synchronization requirement much lower than traditional direct sequence CDMA schemes. There are still some problems when we use MC-CDMA. One is the high Peak-to-Average Power Ratio (PAPR) of the transmit signal. High PAPR leads to nonlinear distortion of the amplifier and results in inter-carrier self-interference plus out-of-band radiation. On the other hand, suppressing the Multiple Access Interference (MAI) is another crucial problem in the MC-CDMA system. Imperfect cross-correlation characteristics of the spreading codes and the multipath fading destroy the orthogonality among the users, and then cause MAI, which produces serious BER degradation in the system. Moreover, in uplink system the received signals at a base station are always asynchronous. This also destroys the orthogonality among the users, and hence, generates MAI which degrades the system performance. Besides those two problems, the interference should always be considered seriously for any communication system. In this dissertation, we design a novel MC-CDMA system, which has low PAPR and mitigated MAI. The new Semi-blind channel estimation and multi-user data detection based on Parallel Interference Cancellation (PIC) have been applied in the system. The Low Density Parity Codes (LDPC) has also been introduced into the system to improve the performance. Different interference models are analyzed in multi-carrier communication systems and then the effective interference suppression for MC-CDMA systems is employed in this dissertation. The experimental results indicate that our system not only significantly reduces the PAPR and MAI but also effectively suppresses the outside interference with low complexity. Finally, we present a practical cognitive application of the proposed system over the software defined radio platform.

Low-dimensional, hinged bar-code metal oxide layers and free-standing, ordered organic nanostructures from turbostratic vanadium oxide

Both low-dimensional bar-coded metal oxide layers, which exhibit molecular hinging, and free-standing organic nanostructures can be obtained from unique nanofibers of vanadium oxide (VOx). The nanofibers are successfully synthesized by a simple chemical route using an ethanolic solution of vanadium pentoxide xerogel and dodecanethiol resulting in a double bilayered laminar turbostratic structure. The formation of vanadium oxide nanofibers is observed after hydrothermal treatment of the thiol-intercalated xerogel, resulting in typical lengths in the range 2–6 µm and widths of about 50–500 nm. We observe concomitant hinging of the flexible nanofiber lamina at periodic hinge points in the final product on both the nanoscale and molecular level. Bar-coded nanofibers comprise alternating segments of organic–inorganic (thiols–VOx) material and are amenable to segmented, localized metal nanoparticle docking. Under certain conditions free-standing bilayered organic nanostructures are realized.

Progenitor-Dependent Explosion Dynamics in Self-Consistent, Axisymmetric Simulations of Neutrino-Driven Core-Collapse Supernovae

We present self-consistent, axisymmetric core-collapse supernova simulations performed with the Prometheus-Vertex code for 18 pre-supernova models in the range of 11–28 M ⊙, including progenitors recently investigated by other groups. All models develop explosions, but depending on the progenitor structure, they can be divided into two classes. With a steep density decline at the Si/Si–O interface, the arrival of this interface at the shock front leads to a sudden drop of the mass-accretion rate, triggering a rapid approach to explosion. With a more gradually decreasing accretion rate, it takes longer for the neutrino heating to overcome the accretion ram pressure and explosions set in later. Early explosions are facilitated by high mass-accretion rates after bounce and correspondingly high neutrino luminosities combined with a pronounced drop of the accretion rate and ram pressure at the Si/Si–O interface. Because of rapidly shrinking neutron star radii and receding shock fronts after the passage through their maxima, our models exhibit short advection timescales, which favor the efficient growth of the standing accretion-shock instability. The latter plays a supportive role at least for the initiation of the re-expansion of the stalled shock before runaway. Taking into account the effects of turbulent pressure in the gain layer, we derive a generalized condition for the critical neutrino luminosity that captures the explosion behavior of all models very well. We validate the robustness of our findings by testing the influence of stochasticity, numerical resolution, and approximations in some aspects of the microphysics.

Investigation of the Impact of Dual-Lane Axle Spacing on Lateral Load Distribution, 2016

The spacing of adjacent wheel lines of dual-lane loads induces different lateral live load distributions on bridges, which cannot be determined using the current American Association of State Highway and Transportation Officials (AASHTO) Load and Resistance Factor Design (LRFD) or Load Factor Design (LFD) equations for vehicles with standard axle configurations. Current Iowa law requires dual-lane loads to meet a five-foot requirement, the adequacy of which needs to be verified. To improve the state policy and AASHTO code specifications, it is necessary to understand the actual effects of wheel-line spacing on lateral load distribution. The main objective of this research was to investigate the impact of the wheel-line spacing of dual-lane loads on the lateral load distribution on bridges. To achieve this objective, a numerical evaluation using two-dimensional linear elastic finite element (FE) models was performed. For simulation purposes, 20 prestressed-concrete bridges, 20 steel bridges, and 20 slab bridges were randomly sampled from the Iowa bridge database. Based on the FE results, the load distribution factors (LDFs) of the concrete and steel bridges and the equivalent lengths of the slab bridges were derived. To investigate the variations of LDFs, a total of 22 types of single-axle four-wheel-line dual-lane loads were taken into account with configurations consisting of combinations of various interior and exterior wheel-line spacing. The corresponding moment and shear LDFs and equivalent widths were also derived using the AASHTO equations and the adequacy of the Iowa DOT five-foot requirement was evaluated. Finally, the axle weight limits per lane for different dual-lane load types were further calculated and recommended to complement the current Iowa Department of Transportation (DOT) policy and AASHTO code specifications.

Flow Regime Identification Methodology with Mcnp-X Code And Artificial Neural Network

This paper presents flow regimes identification methodology in multiphase system in annular, stratified and homogeneous oil-water-gas regimes. The principle is based on recognition of the pulse height distributions (PHD) from gamma-ray with supervised artificial neural network (ANN) systems. The detection geometry simulation comprises of two NaI(Tl) detectors and a dual-energy gamma-ray source. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be explored. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to acquire information about the different flow regimes. The PHDs obtained by the detectors were used as input to ANN. The data sets required for training and testing the ANN were generated by the MCNP-X code from static and ideal theoretical models of multiphase systems. The ANN correctly identified the three different flow regimes for all data set evaluated. The results presented show that PHDs examined by ANN may be applied in the successfully flow regime identification.

Self-sealing of thermal fatigue and mechanical damage in fiber-reinforced composite materials

Fiber reinforced composite tanks provide a promising method of storage for liquid oxygen and hydrogen for aerospace applications. The inherent thermal fatigue of these vessels leads to the formation of microcracks, which allow gas phase leakage across the tank walls. In this dissertation, self-healing functionality is imparted to a structural composite to effectively seal microcracks induced by both mechanical and thermal loading cycles. Two different microencapsulated healing chemistries are investigated in woven glass fiber/epoxy and uni-weave carbon fiber/epoxy composites. Self-healing of mechanically induced damage was first studied in a room temperature cured plain weave E-glass/epoxy composite with encapsulated dicyclopentadiene (DCPD) monomer and wax protected Grubbs' catalyst healing components. A controlled amount of microcracking was introduced through cyclic indentation of opposing surfaces of the composite. The resulting damage zone was proportional to the indentation load. Healing was assessed through the use of a pressure cell apparatus to detect nitrogen flow through the thickness direction of the damaged composite. Successful healing resulted in a perfect seal, with no measurable gas flow. The effect of DCPD microcapsule size (51 um and 18 um) and concentration (0 - 12.2 wt%) on the self-sealing ability was investigated. Composite specimens with 6.5 wt% 51 um capsules sealed 67% of the time, compared to 13% for the control panels without healing components. A thermally stable, dual microcapsule healing chemistry comprised of silanol terminated poly(dimethyl siloxane) plus a crosslinking agent and a tin catalyst was employed to allow higher composite processing temperatures. The microcapsules were incorporated into a satin weave E-glass fiber/epoxy composite processed at 120C to yield a glass transition temperature of 127C. Self-sealing ability after mechanical damage was assessed for different microcapsule sizes (25 um and 42 um) and concentrations (0 - 11 vol%). Incorporating 9 vol% 42 um capsules or 11 vol% 25 um capsules into the composite matrix leads to 100% of the samples sealing. The effect of microcapsule concentration on the short beam strength, storage modulus, and glass transition temperature of the composite specimens was also investigated. The thermally stable tin catalyzed poly(dimethyl siloxane) healing chemistry was then integrated into a [0/90]s uniweave carbon fiber/epoxy composite. Thermal cycling (-196C to 35C) of these specimens lead to the formation of microcracks, over time, formed a percolating crack network from one side of the composite to the other, resulting in a gas permeable specimen. Crack damage accumulation and sample permeability was monitored with number of cycles for both self-healing and traditional non-healing composites. Crack accumulation occurred at a similar rate for all sample types tested. A 63% increase in lifetime extension was achieved for the self-healing specimens over traditional non-healing composites.

Dual Quorum Quenching Capsules: Disrupting two bacterial communication pathways that lead to virulence

Healthcare Associated Infections (HAIs) in the United States, are estimated to cost nearly $10 billion annually. And, while device-related infections have decreased, the 60% attributed to pneumonia, gastrointestinal pathogens and surgical site infections (SSIs) remain prevalent. Furthermore, these are often complicated by antibacterial resistance that ultimately cause 2 million illnesses and 23,000 deaths in the US annually. Antibacterial resistance is an issue increasing in severity as existing antibiotics are losing effectiveness, and fewer new antibiotics are being developed. As a result, new methods of combating bacterial virulence are required. Modulating communications of bacteria can alter phenotype, such as biofilm formation and toxin production. Disrupting these communications provides a means of controlling virulence without directly interacting with the bacteria of interest, a strategy contrary to traditional antibiotics. Inter- and intra-species bacterial communication is commonly called quorum sensing because the communication molecules have been linked to phenotypic changes based on bacterial population dynamics. By disrupting the communication, a method called ‘quorum quenching’, bacterial phenotype can be altered. Virulence of bacteria is both population and species dependent; each species will secrete different toxic molecules, and total population will affect bacterial phenotype9. Here, the kinase LsrK and lactonase SsoPox were combined to simultaneously disrupt two different communication pathways with direct ties to virulence leading to SSIs, gastrointestinal infection and pneumonia. To deliver these enzymes for site-specific virulence prevention, two naturally occurring polymers were used, chitosan and alginate. Chitosan, from crustacean shells, and alginate, from seaweed, are frequently studied due to their biocompatibility, availability, self-assembly and biodegrading properties and have already been verified in vivo for wound-dressing. In this work, a novel functionalized capsule of quorum quenching enzymes and biocompatible polymers was constructed and demonstrated to have dual-quenching capability. This combination of immobilized enzymes has the potential for preventing biofilm formation and reducing bacterial toxicity in a wide variety of medical and non-medical applications.

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).