Physics-inspired methods for networking and communications

Advances in statistical physics relating to our understanding of large-scale complex systems have recently been successfully applied in the context of communication networks. Statistical mechanics methods can be used to decompose global system behavior into simple local interactions. Thus, large-scale problems can be solved or approximated in a distributed manner with iterative lightweight local messaging. This survey discusses how statistical physics methodology can provide efficient solutions to hard network problems that are intractable by classical methods. We highlight three typical examples in the realm of networking and communications. In each case we show how a fundamental idea of statistical physics helps solve the problem in an efficient manner. In particular, we discuss how to perform multicast scheduling with message passing methods, how to improve coding using the crystallization process, and how to compute optimal routing by representing routes as interacting polymers.

Challenges in teaching English to young learners:global perspectives and local realities

Drawing on data from a recent research international research project, this article focuses on the challenges faced by teachers of English to young learners against the backdrop of the global rise of English. A mixed-methods approach was used to obtain the data, including a survey, which was completed by 4,459 teachers worldwide, and case studies, including observations and interviews with teachers, in five different primary schools in five different countries. A number of challenges emerged as affecting large numbers of teachers in different educational contexts, namely, teaching speaking, motivation, differentiating learning, teaching large classes, discipline, teaching writing, and teaching grammar. Importantly, some of these challenges have not been highlighted in the literature on young learner teaching to date. Other challenges are more localised, such as developing teachers' English competence. The article argues that teacher education should focus less on introducing teachers to general approaches to English language teaching and more on supporting teachers to meet the challenges that they have identified.

Methods of Color Images Procession for Further Identification of the Object

The offered paper deals with the problems of color images preliminary procession. Among these are: interference control (local ones and noise) and extraction of the object from the background on the stage preceding the process of contours extraction. It was considered for a long time that execution of smoothing in segmentation through the boundary extraction is inadmissible, but the described methods and the obtained results evidence about expedience of using the noise control methods.

Distributed Genetic Algorithm Implementation by Means of Remote Methods Invocation Technique – Java RMI

The aim of this work is distributed genetic algorithm implementation (so called island algorithm) to accelerate the optimum searching process in space of solutions. Distributed genetic algorithm has also smaller chances to fall in local optimum. This conception depends on mutual cooperation of the clients which realize separate working of genetic algorithms on local machines. As a tool for implementation of distributed genetic algorithm, created to produce net's applications Java technology was chosen. In Java technology, there is a technique of remote methods invocation - Java RMI. By means of invoking remote methods it can send objects between clients and server RMI.

Operational Methods in the Environment of a Computer Algebra System

This article presents the principal results of the doctoral thesis “Direct Operational Methods in the Environment of a Computer Algebra System” by Margarita Spiridonova (Institute of mathematics and Informatics, BAS), successfully defended before the Specialised Academic Council for Informatics and Mathematical Modelling on 23 March, 2009.

Steffensen Methods for Solving Generalized Equations

2000 Mathematics Subject Classification: 65G99, 65K10, 47H04.

Towards probabilistic synchronization of local controllers

The traditional use of global and centralised control methods, fails for large, complex, noisy and highly connected systems, which typify many real world industrial and commercial systems. This paper provides an efficient bottom up design of distributed control in which many simple components communicate and cooperate to achieve a joint system goal. Each component acts individually so as to maximise personal utility whilst obtaining probabilistic information on the global system merely through local message-passing. This leads to an implied scalable and collective control strategy for complex dynamical systems, without the problems of global centralised control. Robustness is addressed by employing a fully probabilistic design, which can cope with inherent uncertainties, can be implemented adaptively and opens a systematic rich way to information sharing. This paper opens the foreseen direction and inspects the proposed design on a linearised version of coupled map lattice with spatiotemporal chaos. A version close to linear quadratic design gives an initial insight into possible behaviours of such networks.

Identifying spatially overlapping local cortical networks with MEG

Recent modelling studies (Hadjipapas et al. [2009]: Neuroimage 44:1290-1303) have shown that it may be possible to distinguish between different neuronal populations on the basis of their macroscopically measured (EEG/MEG) mean field. We set out to test whether the different orientation columns contributing to a signal at a specific cortical location could be identified based on the measured MEG signal. We used 1.5deg square, static, obliquely oriented grating stimuli to generate sustained gamma oscillations in a focal region of primary visual cortex. We then used multivariate classifier methods to predict the orientation (left or right oblique) of the stimuli based purely on the time-series data from this one location. Both the single trial evoked response (0-300 ms) and induced post-transient power spectra (300-2,300 ms, 20-70 Hz band) due to the different stimuli were classifiable significantly above chance in 11/12 and 10/12 datasets respectively. Interestingly, stimulus-specific information is preserved in the sustained part of the gamma oscillation, long after perception has occurred and all neuronal transients have decayed. Importantly, the classification of this induced oscillation was still possible even when the power spectra were rank-transformed showing that the different underlying networks give rise to different characteristic temporal signatures. © 2009 Wiley-Liss, Inc.

Federal tax deductibility for local taxes and its effect on local revenue policies

This dissertation analyzes whether and how changes in federal tax policy affect local tax policies, specifically, the elimination of the federal deductibility of state and local taxes for individual taxpayers by the Tax Reform Act of 1986 (TRA86) in 59 California cities. Two methods are used in the study: a survey of local revenue officials and a time event time-series/cross sectional sales tax reliance study.^ The reliance study uses a covariance model to pool cross-section and time-series observations. The results of the reliance study indicate a statistically significant overall decline in sales tax reliance after 1986. The results of the survey indicate that local policy makers generally do not believe that federal deductibility is an important factor when considering raising local sales taxes. Further analysis shows that local revenue officials claiming federal deductibility is not an important factor are associated mostly with cities that registered no significant decline in sales tax reliance after 1986. Similarly, local revenue officials claiming federal deductibility is an important factor when considering local tax policy are associated mostly with cities that suffered a significant decline in sales tax reliance after 1986.^ Of that group, further analysis shows that the declines in sales tax reliance are associated mostly with cities located in the southwestern part of the state. When compared to other cities in the state, an analysis of variance reveals that there are a series of statistically significant factors associated with southwestern cities which may contribute to the decline in sales tax reliance following the enactment of the Tax Reform Act of 1986. ^

Determinants of local government pension funding: Empirical evidence from Florida

The financial community is well aware that continued underfunding of state and local government pension plans poses many public policy and fiduciary management concerns. However, a well-defined theoretical rationale has not been developed to explain why and how public sector pension plans underfund. This study uses three methods: a survey of national pension experts, an incomplete covariance panel method, and field interviews.^ A survey of national public sector pension experts was conducted to provide a conceptual framework by which underfunding could be evaluated. Experts suggest that plan design, fiscal stress, and political culture factors impact underfunding. However, experts do not agree with previous research findings that unions actively pursue underfunding to secure current wage increases.^ Within the conceptual framework and determinants identified by experts, several empirical regularities are documented for the first time. Analysis of 173 local government pension plans, observed from 1987 to 1992, was conducted. Findings indicate that underfunding occurs in plans that have lower retirement ages, increased costs due to benefit enhancements, when the sponsor faces current year operating deficits, or when a local government relies heavily on inelastic revenue sources. Results also suggest that elected officials artificially inflate interest rate assumptions to reduce current pension costs, consequently shifting these costs to future generations. In concurrence with some experts there is no data to support the assumption that highly unionized employees secure more funding than less unionized employees.^ Empirical results provide satisfactory but not overwhelming statistical power, and only minor predictive capacity. To further explore why underfunding occurs, field interviews were carried out with 62 local government officials. Practitioners indicated that perceived fiscal stress, the willingness of policymakers to advance funding, bargaining strategies used by union officials, apathy by employees and retirees, pension board composition, and the level of influence by internal pension experts has an impact on funding outcomes.^ A pension funding process model was posited by triangulating the expert survey, empirical findings, and field survey results. The funding process model should help shape and refine our theoretical knowledge of state and local government pension underfunding in the future. ^

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

Assessing an automated, information -sharing technology in the post "9 -11" era: Do local law enforcement officers think it meets their needs?

In the wake of the “9-11” terrorists' attacks, the U.S. Government has turned to information technology (IT) to address a lack of information sharing among law enforcement agencies. This research determined if and how information-sharing technology helps law enforcement by examining the differences in perception of the value of IT between law enforcement officers who have access to automated regional information sharing and those who do not. It also examined the effect of potential intervening variables such as user characteristics, training, and experience, on the officers' evaluation of IT. The sample was limited to 588 officers from two sheriff's offices; one of them (the study group) uses information sharing technology, the other (the comparison group) does not. Triangulated methodologies included surveys, interviews, direct observation, and a review of agency records. Data analysis involved the following statistical methods: descriptive statistics, Chi-Square, factor analysis, principal component analysis, Cronbach's Alpha, Mann-Whitney tests, analysis of variance (ANOVA), and Scheffe' post hoc analysis. ^ Results indicated a significant difference between groups: the study group perceived information sharing technology as being a greater factor in solving crime and in increasing officer productivity. The study group was more satisfied with the data available to it. As to the number of arrests made, information sharing technology did not make a difference. Analysis of the potential intervening variables revealed several remarkable results. The presence of a strong performance management imperative (in the comparison sheriff's office) appeared to be a factor in case clearances and arrests, technology notwithstanding. As to the influence of user characteristics, level of education did not influence a user's satisfaction with technology, but user-satisfaction scores differed significantly among years of experience as a law enforcement officer and the amount of computer training, suggesting a significant but weak relationship. ^ Therefore, this study finds that information sharing technology assists law enforcement officers in doing their jobs. It also suggests that other variables such as computer training, experience, and management climate should be accounted for when assessing the impact of information technology. ^

"New" Social Movements: Alternative Modernities, (Trans)local Nationalisms, and Solidarity Economies

My dissertation is the first project on the Haitian Platform for Advocacy for an Alternative Development- PAPDA, a nation-building coalition founded by activists from varying sectors to coordinate one comprehensive nationalist movement against what they are calling an Occupation. My work not only provides information on this under-theorized popular movement but also situates it within the broader literature on the postcolonial nation-state as well as Latin American and Caribbean social movements. The dissertation analyzes the contentious relationship between local and global discourses and practices of citizenship. Furthermore, the research draws on transnational feminist theory to underline the scattered hegemonies that intersect to produce varied spaces and practices of sovereignty within the Haitian postcolonial nation-state. The dissertation highlights how race and class, gender and sexuality, education and language, and religion have been imagined and co-constituted by Haitian social movements in constructing ‘new’ collective identities that collapse the private and the public, the rural and the urban, the traditional and the modern. My project complements the scholarship on social movements and the postcolonial nation-state and pushes it forward by emphasizing its spatial dimensions. Moreover, the dissertation de-centers the state to underline the movement of capital, goods, resources, and populations that shape the postcolonial experience. I re-define the postcolonial nation-state as a network of local, regional, international, and transnational arrangements between different political agents, including social movement actors. To conduct this interdisciplinary research project, I employed ethnographic methods, discourse and textual analysis, as well as basic mapping and statistical descriptions in order to present a historically-rooted interpretation of individual and organizational negotiations for community-based autonomy and regional development.

Developing brownfields ranking models using decision analytic methods

The redevelopment of Brownfields has taken off in the 1990s, supported by federal and state incentives, and largely accomplished by local initiatives. Brownfields redevelopment has several associated benefits. These include the revitalization of inner-city neighborhoods, creation of jobs, stimulation of tax revenues, greater protection of public health and natural resources, the renewal and reuse existing civil infrastructure and Greenfields protection. While these benefits are numerous, the obstacles to Brownfields redevelopment are also very much alive. Redevelopment issues typically embrace a host of financial and legal liability concerns, technical and economic constraints, competing objectives, and uncertainties arising from inadequate site information. Because the resources for Brownfields redevelopment are usually limited, local programs will require creativity in addressing these existing obstacles in a manner that extends their limited resources for returning Brownfields to productive uses. Such programs may benefit from a structured and defensible decision framework to prioritize sites for redevelopment: one that incorporates the desired objectives, corresponding variables and uncertainties associated with Brownfields redevelopment. This thesis demonstrates the use of a decision analytic tool, Bayesian Influence Diagrams, and related decision analytic tools in developing quantitative decision models to evaluate and rank Brownfields sites on the basis of their redevelopment potential.

Application of Numerical Methods to Study Arrangement and Fracture of Lithium-Ion Microstructure

The focus of this work is to develop and employ numerical methods that provide characterization of granular microstructures, dynamic fragmentation of brittle materials, and dynamic fracture of three-dimensional bodies.

We first propose the fabric tensor formalism to describe the structure and evolution of lithium-ion electrode microstructure during the calendaring process. Fabric tensors are directional measures of particulate assemblies based on inter-particle connectivity, relating to the structural and transport properties of the electrode. Applying this technique to X-ray computed tomography of cathode microstructure, we show that fabric tensors capture the evolution of the inter-particle contact distribution and are therefore good measures for the internal state of and electronic transport within the electrode.

We then shift focus to the development and analysis of fracture models within finite element simulations. A difficult problem to characterize in the realm of fracture modeling is that of fragmentation, wherein brittle materials subjected to a uniform tensile loading break apart into a large number of smaller pieces. We explore the effect of numerical precision in the results of dynamic fragmentation simulations using the cohesive element approach on a one-dimensional domain. By introducing random and non-random field variations, we discern that round-off error plays a significant role in establishing a mesh-convergent solution for uniform fragmentation problems. Further, by using differing magnitudes of randomized material properties and mesh discretizations, we find that employing randomness can improve convergence behavior and provide a computational savings.

The Thick Level-Set model is implemented to describe brittle media undergoing dynamic fragmentation as an alternative to the cohesive element approach. This non-local damage model features a level-set function that defines the extent and severity of degradation and uses a length scale to limit the damage gradient. In terms of energy dissipated by fracture and mean fragment size, we find that the proposed model reproduces the rate-dependent observations of analytical approaches, cohesive element simulations, and experimental studies.

Lastly, the Thick Level-Set model is implemented in three dimensions to describe the dynamic failure of brittle media, such as the active material particles in the battery cathode during manufacturing. The proposed model matches expected behavior from physical experiments, analytical approaches, and numerical models, and mesh convergence is established. We find that the use of an asymmetrical damage model to represent tensile damage is important to producing the expected results for brittle fracture problems.

The impact of this work is that designers of lithium-ion battery components can employ the numerical methods presented herein to analyze the evolving electrode microstructure during manufacturing, operational, and extraordinary loadings. This allows for enhanced designs and manufacturing methods that advance the state of battery technology. Further, these numerical tools have applicability in a broad range of fields, from geotechnical analysis to ice-sheet modeling to armor design to hydraulic fracturing.