SOA-Based Model for Value-Added ITS Services Delivery

Integration is currently a key factor in intelligent transportation systems (ITS), especially because of the ever increasing service demands originating from the ITS industry and ITS users. The current ITS landscape is made up of multiple technologies that are tightly coupled, and its interoperability is extremely low, which limits ITS services generation. Given this fact, novel information technologies (IT) based on the service-oriented architecture (SOA) paradigm have begun to introduce new ways to address this problem. The SOA paradigm allows the construction of loosely coupled distributed systems that can help to integrate the heterogeneous systems that are part of ITS. In this paper, we focus on developing an SOA-based model for integrating information technologies (IT) into ITS to achieve ITS service delivery. To develop our model, the ITS technologies and services involved were identified, catalogued, and decoupled. In doing so, we applied our SOA-based model to integrate all of the ITS technologies and services, ranging from the lowest-level technical components, such as roadside unit as a service (RS S), to the most abstract ITS services that will be offered to ITS users (value-added services). To validate our model, a functionality case study that included all of the components of our model was designed.

On the use of finite field based modeling in polynomial manipulation,

Vita: p. 105.

A comparison of landslide inventories along the shoreline of Steamboat Island Peninsula, Thurston County, WA: office based protocol vs. field based protocol

The mountain ranges and coastlines of Washington State have steep slopes, and they are susceptible to landslides triggered by intense rainstorms, rapid snow melts, earthquakes, and rivers and waves removing slope stability. Over a 30-year timespan (1984-2014 and includes State Route (SR) 530), a total of 28 deep-seated landslides caused 300 million dollars of damage and 45 deaths (DGER, 2015). During that same timeframe, ten storm events triggered shallow landslides and debris flows across the state, resulting in nine deaths (DGER, 2015). The loss of 43 people, due to the SR 530 complex reactivating and moving at a rate and distance unexpected to residents, highlighted the need for an inventory of the stateís landslides. With only 13% of the state mapped (Lombardo et al., 2015), the intention of this statewide inventory is to communicate hazards to citizens and decision makers. In order to compile an accurate and consistent landslide inventory, Washington needs to adopt a graphic information system (GIS) based mapping protocol. A mapping protocol provides consistency for measuring and recording information about landslides, including such information as the type of landslide, the material involved, and the size of the movement. The state of Oregon shares similar landslide problems as Washington, and it created a GIS-based mapping protocol designed to inform its residents, while also saving money and reducing costly hours in the field (Burns and Madin, 2009). In order to determine if the Oregon Department of Geology and Mineral Industries (DOGAMI) protocol, developed by Burns and Madin (2009), could serve as the basis for establishing Washingtonís protocol, I used the office-based DOGAMI protocol to map landslides along a 40-50 km (25-30 mile) shoreline in Thurston County, Washington. I then compared my results to the field-based landslide inventory created in 2009 by the Washington Division of Geology and Earth Resources (DGER) along this same shoreline. If the landslide area I mapped reasonably equaled the area of the DGER (2009) inventory, I would consider the DOGAMI protocol useful for Washington, too. Utilizing 1m resolution lidar flown for Thurston County in 2011 and a GIS platform, I mapped 36 landslide deposits and scarp flanks, covering a total area of 879,530 m2 (9,467,160 ft2). I also found 48 recent events within these deposits. With an exception of two slides, all of the movements occurred within the last fifty years. Along this same coastline, the DGER (2009) recorded 159 individual landslides and complexes, for a total area of 3,256,570 m2 (35,053,400 ft2). At a first glance it appears the DGER (2009) effort found a larger total number and total area of landslides. However, in addition to their field inventory, they digitized landslides previously mapped by other researchers, and they did not field confirm these landslides, which cover a total area of 2,093,860 m2 (22,538,150 ft2) (DGER, 2009). With this questionable landslide area removed and the toes and underwater landslides accounted for because I did not have a bathymetry dataset, my results are within 6,580 m2 (70,840 ft2) of the DGERís results. This similarity shows that the DOGAMI protocol provides a consistent and accurate approach to creating a landslide inventory. With a few additional modifications, I recommend that Washington State adopts the DOGAMI protocol. Acquiring additional 1m lidar and adopting a modified DOGAMI protocol poises the DGER to map the remaining 87% of the state, with an ultimate goal of informing citizens and decision makers of the locations and frequencies of landslide hazards on a user-friendly GIS platform.

Field-based evaluation of semipermeable membrane devices (SPMDs) as passive air samplers of polyaromatic hydrocarbons (PAHs)

Semipermeable membrane devices (SPMDs) have been used as passive air samplers of semivolatile organic compounds in a range of studies. However, due to a lack of calibration data for polyaromatic hydrocarbons (PAHs), SPMD data have not been used to estimate air concentrations of target PAHs. In this study, SPMDs were deployed for 32 days at two sites in a major metropolitan area in Australia. High-volume active sampling systems (HiVol) were co-deployed at both sites. Using the HiVol air concentration data from one site, SPMD sampling rates were measured for 12 US EPA Priority Pollutant PAHs and then these values were used to determine air concentrations at the second site from SPMD concentrations. Air concentrations were also measured at the second site with co-deployed HiVols to validate the SPMD results. PAHs mostly associated with the vapour phase (Fluorene to Pyrene) dominated both the HiVol and passive air samples. Reproducibility between replicate passive samplers was satisfactory (CV < 20%) for the majority of compounds. Sampling rates ranged between 0.6 and 6.1 m(3) d(-1). SPMD-based air concentrations were calculated at the second site for each compound using these sampling rates and the differences between SPMD-derived air concentrations and those measured using a HiVol were, on average, within a factor of 1.5. The dominant processes for the uptake of PAHs by SPMDs were also assessed. Using the SPMD method described herein, estimates of particulate sorbed airborne PAHs with five rings or greater were within 1.8-fold of HiVol measured values. (C) 2004 Elsevier Ltd. All rights reserved.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

A patttern based model evolution approach

In this paper, we present a framework for pattern-based model evolution approaches in the MDA context. In the framework, users define patterns using a pattern modeling language that is designed to describe software design patterns, and they can use the patterns as rules to evolve their model. In the framework, design model evolution takes place via two steps. The first step is a binding process of selecting a pattern and defining where and how to apply the pattern in the model. The second step is an automatic model transformation that actually evolves the model according to the binding information and the pattern rule. The pattern modeling language is defined in terms of a MOF-based role metamodel, and implemented using an existing modeling framework, EMF, and incorporated as a plugin to the Eclipse modeling environment. The model evolution process is also implemented as an Eclipse plugin. With these two plugins, we provide an integrated framework where defining and validating patterns, and model evolution based on patterns can take place in a single modeling environment.

A risk-based model for inspection and maintenance of cross-country petroleum pipeline

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Blur adaptation explained by a norm-based model of contrast adaptation

Adapting to blurred images makes in-focus images look too sharp, and vice-versa (Webster et al, 2002 Nature Neuroscience 5 839 - 840). We asked how such blur adaptation is related to contrast adaptation. Georgeson (1985 Spatial Vision 1 103 - 112) found that grating contrast adaptation followed a subtractive rule: perceived (matched) contrast of a grating was fairly well predicted by subtracting some fraction k(~0.3) of the adapting contrast from the test contrast. Here we apply that rule to the responses of a set of spatial filters at different scales and orientations. Blur is encoded by the pattern of filter response magnitudes over scale. We tested two versions - the 'norm model' and 'fatigue model' - against blur-matching data obtained after adaptation to sharpened, in-focus or blurred images. In the fatigue model, filter responses are simply reduced by exposure to the adapter. In the norm model, (a) the visual system is pre-adapted to a focused world and (b) discrepancy between observed and expected responses to the experimental adapter leads to additional reduction (or enhancement) of filter responses during experimental adaptation. The two models are closely related, but only the norm model gave a satisfactory account of results across the four experiments analysed, with one free parameter k. This model implies that the visual system is pre-adapted to focused images, that adapting to in-focus or blank images produces no change in adaptation, and that adapting to sharpened or blurred images changes the state of adaptation, leading to changes in perceived blur or sharpness.

A rule based model for the objective determination of the e-business requirements of a manufacturing organisation

The starting point of this research was the belief that manufacturing and similar industries need help with the concept of e-business, especially in assessing the relevance of possible e-business initiatives. The research hypotheses was that it should be possible to produce a systematic model that defines, at a useful level of detail, the probable e-business requirements of an organisation based on objective criteria with an accuracy of 85%-90%. This thesis describes the development and validation of such a model. A preliminary model was developed from a variety of sources, including a survey of current and planned e-business activity and representative examples of e-business material produced by e-business solution providers. The model was subject to a process of testing and refinement based on recursive case studies, with controls over the improving accuracy and stability of the model. Useful conclusions were also possible as to the relevance of e-business functions to the case study participants themselves. Techniques were evolved to synthesise the e-business requirements of an organisation and present them at a management summary level of detail. The results of applying these techniques to all the case studies used in this research were discussed. The conclusion of the research was that the case study methodology employed was successful. A model was achieved suitable for practical application in a manufacturing organisation requiring help with a requirements definition process.

The emergence of knowledge exchange:an agent-based model of a software market

We investigate knowledge exchange among commercial organizations, the rationale behind it, and its effects on the market. Knowledge exchange is known to be beneficial for industry, but in order to explain it, authors have used high-level concepts like network effects, reputation, and trust. We attempt to formalize a plausible and elegant explanation of how and why companies adopt information exchange and why it benefits the market as a whole when this happens. This explanation is based on a multiagent model that simulates a market of software providers. Even though the model does not include any high-level concepts, information exchange naturally emerges during simulations as a successful profitable behavior. The conclusions reached by this agent-based analysis are twofold: 1) a straightforward set of assumptions is enough to give rise to exchange in a software market, and 2) knowledge exchange is shown to increase the efficiency of the market.

Risk-based model aids selection of pipeline inspection, maintenance strategies

The existing method of pipeline monitoring, which requires an entire pipeline to be inspected periodically, wastes time and is expensive. A risk-based model that reduces the amount of time spent on inspection has been developed. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction method and logical insurance plans.The risk-based model uses analytic hierarchy process, a multiple attribute decision-making technique, to identify factors that influence failure on specific segments and analyze their effects by determining the probabilities of risk factors. The severity of failure is determined through consequence analysis, which establishes the effect of a failure in terms of cost caused by each risk factor and determines the cumulative effect of failure through probability analysis.

Power industry restructuring and eco-efficiency changes:a new slacks-based model in Malmquist-Luenberger Index measurement

Measuring variations in efficiency and its extension, eco-efficiency, during a restructuring period in different industries has always been a point of interest for regulators and policy makers. This paper assesses the impacts of restructuring of procurement in the Iranian power industry on the performance of power plants. We introduce a new slacks-based model for Malmquist-Luenberger (ML) Index measurement and apply it to the power plants to calculate the efficiency, eco-efficiency, and technological changes over the 8-year period (2003-2010) of restructuring in the power industry. The results reveal that although the restructuring had different effects on the individual power plants, the overall growth in the eco-efficiency of the sector was mainly due to advances in pure technology. We also assess the correlation between efficiency and eco-efficiency of the power plants, which indicates a close relationship between these two steps, thus lending support to the incorporation of environmental factors in efficiency analysis. © 2014 Elsevier Ltd.

NLSE-based model of a random distributed feedback fiber laser

In this work we propose a NLSE-based model of power and spectral properties of the random distributed feedback (DFB) fiber laser. The model is based on coupled set of non-linear Schrödinger equations for pump and Stokes waves with the distributed feedback due to Rayleigh scattering. The model considers random backscattering via its average strength, i.e. we assume that the feedback is incoherent. In addition, this allows us to speed up simulations sufficiently (up to several orders of magnitude). We found that the model of the incoherent feedback predicts the smooth and narrow (comparing with the gain spectral profile) generation spectrum in the random DFB fiber laser. The model allows one to optimize the random laser generation spectrum width varying the dispersion and nonlinearity values: we found, that the high dispersion and low nonlinearity results in narrower spectrum that could be interpreted as four-wave mixing between different spectral components in the quasi-mode-less spectrum of the random laser under study could play an important role in the spectrum formation. Note that the physical mechanism of the random DFB fiber laser formation and broadening is not identified yet. We investigate temporal and statistical properties of the random DFB fiber laser dynamics. Interestingly, we found that the intensity statistics is not Gaussian. The intensity auto-correlation function also reveals that correlations do exist. The possibility to optimize the system parameters to enhance the observed intrinsic spectral correlations to further potentially achieved pulsed (mode-locked) operation of the mode-less random distributed feedback fiber laser is discussed.