A methodology for formally modeling and analyzing software architecture of mobile agent systems

A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

A static traffic assignment model combined with an artificial neural network delay model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Dissolved Black Nitrogen (DBN) in Freshwater Environments

Biomass burning results in the formation and accumulation of pyrogenic products such as black carbon (BC) and black nitrogen (BN) in soils. The ubiquitous presence of pyrogenic products in natural dissolved organic matter (DOM) and potential implications in global carbon cycling have recently been reported. However, little is known about the environmental dynamics or the importance in the global N cycle of dissolved BN (DBN; or heteroaromatic N). Here we report the coupling between DBN and dissolved BC (DBC) in ultrafiltered DOM from six headwater streams across a climatic region of North America, suggesting similar combustion sources, and that DOC may play an important role in the translocation of soil BN to the dissolved phase. The export of potentially recalcitrant riverine DBN to the ocean may affect the biogeochemical cycling of N and possibly the microbial community structure in aquatic environments.

Environmental Dynamics of Dissolved Black Carbon in Wetlands

Wetlands are ecosystems commonly characterized by elevated levels of dissolved organic carbon (DOC), and although they cover a surface area less than 2 % worldwide, they are an important carbon source representing an estimated 15 % of global annual DOC flux to the oceans. Because of their unique hydrological characteristics, fire can be an important ecological driver in pulsed wetland systems. Consequently, wetlands may be important sources not only of DOC but also of products derived from biomass burning, such as dissolved black carbon (DBC). However, the biogeochemistry of DBC in wetlands has not been studied in detail. The objective of this study is to determine the environmental dynamics of DBC in different fire-impacted wetlands. An intensive, 2-year spatial and temporal dynamics study of DBC in a coastal wetland, the Everglades (Florida) system, as well as one-time sampling surveys for the other two inland wetlands, Okavango Delta (Botswana) and the Pantanal (Brazil), were reported. Our data reveal that DBC dynamics are strongly coupled with the DOC dynamics regardless of location, season or recent fire history. The statistically significant linear regression between DOC and DBC was applied to estimate DBC fluxes to the coastal zone through two main riverine DOC export routes in the Everglades ecosystem. The presence of significant amounts of DBC in these three fire-impacted ecosystems suggests that sub-tropical wetlands could represent an important continental-ocean carrier of combustion products from biomass burning. The discrimination of DBC molecular structure (i.e. aromaticity) between coastal and terrestrial samples, and between samples collected in wet and dry season, suggests that spatially-significant variation in DBC source strength and/or degree of degradation may also influence DBC dynamics.

Dissolved Black Carbon in Grassland Streams: Is There an Effect of Recent Fire History?

While the existence of black carbon as part of dissolved organic matter (DOM) has been confirmed, quantitative determinations of dissolved black carbon (DBC) in freshwater ecosystem and information on factors controlling its concentration are scarce. In this study, stream surface water samples from a series of watersheds subject to different burn frequencies in Konza Prairie (Kansas, USA) were collected in order to determine if recent fire history has a noticeable effect on DBC concentration. The DBC levels detected ranged from 0.04 to 0.11 mg L−1, accounting for ca. 3.32 ± 0.51% of dissolved organic carbon (DOC). No correlation was found between DBC concentration and neither fire frequency nor time since last burn. We suggest that limited DBC flux is related to high burning efficiency, possibly greater export during periods of high discharge and/or the continuous export of DBC over long time scales. A linear correlation between DOC and DBC concentrations was observed, suggesting the export mechanisms determining DOC and DBC concentrations are likely coupled. The potential influence of fire history was less than the influence of other factors controlling the DOC and DBC dynamics in this ecosystem. Assuming similar conditions and processes apply in grasslands elsewhere, extrapolation to a global scale would suggest a global grasslands flux of DBC on the order of 0.14 Mt carbon year−1.

Application of biomarkers and compound specific stable isotopes for the assessment of hydrology as a driver of organic matter dynamics in the Everglades ecosystem

The Everglades is a sub-tropical coastal wetland characterized among others by its hydrological features and deposits of peat. Formation and preservation of organic matter in soils and sediments in this wetland ecosystem is critical for its sustainability and hydrological processes are important divers in the origin, transport and fate of organic matter. With this in mind, organic matter dynamics in the greater Florida Everglades was studied though various organic geochemistry techniques, especially biomarkers, bulk and compound specific δ13C and δD isotope analysis. The main objectives were focused on how different hydrological regimes in this ecosystem control organic matter dynamics, such as the mobilization of particulate organic matter (POM) in freshwater marshes and estuaries, and how organic geochemistry techniques can be applied to reconstruct Everglades paleo-hydrology. For this purpose organic matter in typical vegetation, floc, surface soils, soil cores, and estuarine suspended particulates were characterized in samples selected along hydrological gradients in the Water Conservation Area 3, Shark River Slough and Taylor Slough. ^ This research focused on three general themes: (1) Assessment of the environmental dynamics and source-specific particulate organic carbon export in a mangrove-dominated estuary. (2) Assessment of the origin, transport and fate of organic matter in freshwater marsh. (3) Assessment of historical changes in hydrological conditions in the Everglades (paleo-hydrology) though biomarkes and compound specific isotope analyses. This study reports the first estimate of particulate organic carbon loss from mangrove ecosystems in the Everglades, provides evidence for particulate organic matter transport with regards to the formation of ridge and slough landscapes in the Everglades, and demonstrates the applicability of the combined biomarker and compound-specific stable isotope approach as a means to generate paleohydrological data in wetlands. The data suggests that: (1) Carbon loss from mangrove estuaries is roughly split 50/50 between dissolved and particulate carbon; (2) hydrological remobilization of particulate organic matter from slough to ridge environments may play an important role in the maintenance of the Everglades freshwater landscape; and (3) Historical changes in hydrology have resulted in significant vegetation shifts from historical slough type vegetation to present ridge type vegetation. ^

A Static Traffic Assignment Model Combined with an Artificial Neural Network Delay Model

As traffic congestion continues to worsen in large urban areas, solutions are urgently sought. However, transportation planning models, which estimate traffic volumes on transportation network links, are often unable to realistically consider travel time delays at intersections. Introducing signal controls in models often result in significant and unstable changes in network attributes, which, in turn, leads to instability of models. Ignoring the effect of delays at intersections makes the model output inaccurate and unable to predict travel time. To represent traffic conditions in a network more accurately, planning models should be capable of arriving at a network solution based on travel costs that are consistent with the intersection delays due to signal controls. This research attempts to achieve this goal by optimizing signal controls and estimating intersection delays accordingly, which are then used in traffic assignment. Simultaneous optimization of traffic routing and signal controls has not been accomplished in real-world applications of traffic assignment. To this end, a delay model dealing with five major types of intersections has been developed using artificial neural networks (ANNs). An ANN architecture consists of interconnecting artificial neurons. The architecture may either be used to gain an understanding of biological neural networks, or for solving artificial intelligence problems without necessarily creating a model of a real biological system. The ANN delay model has been trained using extensive simulations based on TRANSYT-7F signal optimizations. The delay estimates by the ANN delay model have percentage root-mean-squared errors (%RMSE) that are less than 25.6%, which is satisfactory for planning purposes. Larger prediction errors are typically associated with severely oversaturated conditions. A combined system has also been developed that includes the artificial neural network (ANN) delay estimating model and a user-equilibrium (UE) traffic assignment model. The combined system employs the Frank-Wolfe method to achieve a convergent solution. Because the ANN delay model provides no derivatives of the delay function, a Mesh Adaptive Direct Search (MADS) method is applied to assist in and expedite the iterative process of the Frank-Wolfe method. The performance of the combined system confirms that the convergence of the solution is achieved, although the global optimum may not be guaranteed.

Three Essays on Taxation, Growth and Consumption

The purpose of this dissertation is to examine three distributional issues in macroeconomics. First I explore the effects fiscal federalism on economic growth across regions in China. Using the comprehensive official data set of China for 31 regions from 1952 until 1999, I investigate a number of indicators used by the literature to measure federalism and find robust support for only one such measure: the ratio of local total revenue to local tax revenue. Using a difference-in-difference approach and exploiting the two-year gap in the implementation of a tax reform across different regions of China, I also identify a positive relationship between fiscal federalism and regional economic growth. The second paper hypothesizes that an inequitable distribution of income negatively affects the rule of law in resource-rich economies and provides robust evidence in support of this hypothesis. By investigating a data set that contains 193 countries and using econometric methodologies such as the fixed effects estimator and the generalized method of moments estimator, I find that resource-abundance improves the quality of institutions, as long as income and wealth disparity remains below a certain threshold. When inequality moves beyond this threshold, the positive effects of the resource-abundance level on institutions diminish quickly and turn negative eventually. This paper, thus, provides robust evidence about the endogeneity of institutions and the role income and wealth inequality plays in the determination of long-run growth rates. The third paper sets up a dynamic general equilibrium model with heterogeneous agents to investigate the causal channels which run from a concern for international status to long-run economic growth. The simulation results show that the initial distribution of income and wealth play an important role in whether agents gain or lose from globalization.

Millennials in the Workplace

Today’s workplace is undergoing dramatic shifts due to the growth of Miillennials within the workforce and the insertion of their ideals, values, and identity in organizations. This article explores the workplace profile of Millennials, their use of technology, their workplace engagement, and the ultimate impact they have on organizational success.

Environmental Dynamics of Dissolved Black Carbon in Aquatic Ecosystems

Black carbon (BC), the incomplete combustion product from biomass and fossil fuel burning, is ubiquitously found in soils, sediments, ice, water and atmosphere. Because of its polyaromatic molecular characteristic, BC is believed to contribute significantly to the global carbon budget as a slow-cycling, refractory carbon pool. However, the mass balance between global BC generation and accumulation does not match, suggesting a removal mechanism of BC to the active carbon pool, most probable in a dissolved form. The presence of BC in waters as part of the dissolved organic matter (DOM) pool was recently confirmed via ultrahigh resolution mass spectrometry, and dissolved black carbon (DBC), a degradation product of charcoal, was found in marine and coastal environments. However, information on the loadings of DBC in freshwater environments and its global riverine flux from terrestrial systems to the oceans remained unclear. The main objectives of this study were to quantify DBC in diverse aquatic ecosystems and to determine its environmental dynamics. Surface water samples were collected from aquatic environments with a spatially significant global distribution, and DBC concentrations were determined by a chemical oxidation method coupled with HPLC detection. While it was clear that biomass burning was the main sources of BC, the translocation mechanism of BC to the dissolved phase was not well understood. Data from the regional studies and the developed global model revealed a strong positive correlation between DBC and dissolved organic carbon (DOC) dynamics, indicating a co-generation and co-translocation between soil OC and BC. In addition, a DOC-assistant DBC translocation mechanism was identified. Taking advantage of the DOC-DBC correlation model, a global riverine DBC flux to oceans on the order of 26.5 Mt C yr-1 (1 Mt = 1012 g) was determined, accounting for 10.6% of the global DOC flux. The results not only indicated that DOC was an important environmental intermediate for BC transfer and storage, but also provided an estimate of a major missing link in the global BC budget. The ever increasing DBC export caused by global warming will change the marine DOM quality and may have important consequences for carbon cycling in marine ecosystem.