Computer Model

The EPA Storm Water Management Model (SWMM) is a widely used program for simulating urban runoff quantity and quality. Its existing documentation includes a User's Manual that describes how to run the program and a Reference Manual that covers its theory and algorithms. A new manual, the ''SWMM Applications Manual'', has been added to this collection. It contains nine worked-out examples addressing common stormwater management and design problems encountered in practice. The manual will be especially useful for new SWMM users who need additional guidance in applying this powerful tool to urban drainage design and analysis.

Soil is a major reservoir for contaminants as it posseses an ability to bind various chemicals. These chemicals can exist in various forms in soil and different forces keep them bound to soil particles. It is essential to study these interactions because the toxicity of ...

O rganizational structure affects both the overall behavior of firms and the situations of individuals and subunits within firms. The effect of exogenous changes in the environment (market prices, costs, or regulations) on organizations can be partitioned into the immediate direct effect of the change and the full effect after organizational structure has had time to adjust. This paper develops a computational model of the diffusion of a profitable innovation through a firm, and uses numerical simulations to calculate the relative importance of the direct and structural adjustment components of changes in profitability. One finding is that a failure to recognize the importance of organizational structure on the performance of firms will lead to serious bias in estimation of the costs or benefits of a change in external circumstances. The type of network model developed also has implications for the individuals and divisions that make up the firm. We examine some of the structural characteristics of well-adapted organizations, and show that asymmetries and economic inequalities emerge even when the individual agents' personal characteristics are identical.

In this paper, we propose a computational model of the recognition of real world scenes that bypasses the segmentation and the processing of individual objects or regions. The procedure is based on a very low dimensional representation of the scene, that we term the Spatial Envelope. We propose a set of perceptual dimensions (naturalness, openness, roughness, expansion, ruggedness) that represent the dominant spatial structure of a scene. Then, we show that these dimensions may be reliably estimated using spectral and coarsely localized information. The model generates a multidimensional space in which scenes sharing membership in semantic categories (e.g., streets, highways, coasts) are projected closed together. The performance of the spatial envelope model shows that specific information about object shape or identity is not a requirement for scene categorization and that modeling a holistic representation of the scene informs about its probable semantic category.

The assumption that people possess a repertoire of strategies to solve the inference problems they face has been raised repeatedly. However, a computational model specifying how people select strategies from their repertoire is still lacking. The proposed strategy selection learning (SSL) theory predicts a strategy selection process on the basis of reinforcement learning. The theory assumes that individuals develop subjective expectations for the strategies they have and select strategies proportional to their expectations, which are then updated on the basis of subsequent experience. The learning assumption was supported in 4 experimental studies. Participants substantially improved their inferences through feedback. In all 4 studies, the best-performing strategy from the participants' repertoires most accurately predicted the inferences after sufficient learning opportunities. When testing SSL against 3 models representing extensions of SSL and against an exemplar model assuming a memory-based inference process, the authors found that SSL predicted the inferences most accurately.

Why is language the way it is? How did language come to be this way? And why is our species alone in having complex language? These are old unsolved questions that have seen a renaissance in the dramatic recent growth in research being published on the origins and evolution of human language. This review provides a broad overview of some of the important current work in this area. We highlight new methodologies (such as computational modeling), emerging points of consensus (such as the importance of pre-adaptation), and the major remaining controversies (such as gestural origins of language). We also discuss why language evolution is such a difficult problem, and suggest probable directions research may take in the near future.

Most organisms facing a choice between multiple stimuli will look repeatedly at them, presumably implementing a comparison process between the items' values. Little is known about the nature of the comparison process in value-based decision-making or about the role of visual fixations in this process. We created a computational model of value-based binary choice in which fixations guide the comparison process and tested it on humans using eye-tracking. We found that the model can quantitatively explain complex relationships between fixation patterns and choices, as well as several fixation-driven decision biases.

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data. Moreover, the recent advances in Web technology has made it easy for any user to provide and consume content of any form. This has called for a paradigm shift in the computing architecture and large scale data processing mechanisms. Cloud computing is associated with a new paradigm for the provision of computing infrastructure. This paradigm shifts the location of this infrastructure to the network to reduce the costs associated with the management of hardware and software resources. This paper gives a comprehensive survey of numerous approaches and mechanisms of deploying data-intensive applications in the cloud which are gaining a lot of momentum in both research and industrial communities. We analyze the various design decisions of each approach and its suitability to support certain classes of applications and end-users. A discussion of some open issues and future challenges pertaining to scalability, consistency, economical processing of large scale data on the cloud is provided. We highlight the characteristics of the best candidate classes of applications that can be deployed in the cloud.

The many motivations for employing agent-based computation in the social sciences are reviewed. It is argued that there exist three distinct uses of agent modeling techniques. One such use -the simplest -is conceptually quite close to traditional simulation in operations research. This use arises when equations can be formulated that completely describe a social process, and these equations are explicitly soluble, either analytically or numerically. In the former case, the agent model is merely a tool for presenting results, while in the latter it is a novel kind of Monte Carlo analysis. A second, more commonplace usage of computational agent models arises when mathematical models can be written down but not completely solved. In this case the agent-based model can shed significant light on the solution structure, illustrate dynamical properties of the model, serve to test the dependence of results on parameters and assumptions, and be a source of counter-examples. Finally, there are important classes of problems for which writing down equations is not a useful activity. In such circumstances, resort to agent-based computational models may be the only way available to explore such processes systematically, and constitute a third distinct usage of such models.

Despite their many advantages, e-Businesses lag behind brick and mortar businesses in several fundamental respects. This paper concerns one of these: relationships based on trust and reputation. Recent studies on simple reputation systems for e-Businesses such as eBay have pointed to the importance of such rating systems for deterring moral hazard and encouraging trusting interactions. However, despite numerous studies on trust and reputation systems, few have taken studies across disciplines to provide an integrated account of these concepts and their relationships. This paper first surveys existing literatures on trust, reputation and a related concept: reciprocity. Based on sociological and biological understandings of these concepts, a computational model is proposed. This model can be implemented in a real system to consistently calculate agents' trust and reputation scores.

Computational color constancy is a fundamental prerequisite for many computer vision applications. This paper presents a survey of many recent developments and state-of-theart methods. Several criteria are proposed that are used to assess the approaches. A taxonomy of existing algorithms is proposed and methods are separated in three groups: static methods, gamut-based methods and learning-based methods. Further, the experimental setup is discussed including an overview of publicly available data sets. Finally, various freely available methods, of which some are considered to be state-of-the-art, are evaluated on two data sets.

The constitutive parameters of a Teflon sample of arbitrary thickness are retrieved from scattering parameters experimentally measured with a vector network analyzer and a waveguide system into which the test sample is inserted by filling the transverse section of the X-band waveguide. Based on the Nicolson-Ross-Weir (NRW) method and modified to eliminate the phase ambiguity inherent to the NRW procedure, the algorithm used is able to correctly retrieve over the frequency range considered (8.20 to 12.40 GHz) the permittivity and permeability without any divergence at half-wavelength resonant frequencies for either dielectric or magnetic materials.

This thesis is motivated by the impact that information technology has had on supply chain management. In particular, information technology has changed the way companies interact with suppliers and customers. For example, in quick response, suppliers receive Point-of-Sales (POS) data from retailers and use this information to improve their forecast and better manage production and inventory activities.

Instead of merely combining theories of self-regulation, the current paper articulates a dynamic process theory of the underlying cognitive subsystems that explain relationships among longused constructs like goals, expectancies, and valence. Formal elements of the theory are presented in an attempt to encourage the building of computational models of human actors, thinkers, and learners in organizational contexts. Discussion focuses on the application of these models for understanding the dynamics of individuals interacting in their organizations.

NOTICE: This report was prepared as an account of work sponsored by an agency of the United States Government. N either t he U nited S tates Government, n or an y a gency t hereof, n or an y o f their e mployees, nor a ny of t heir c ontractors, s ubcontractors, or t heir e mployees, m ake an y warranty, e xpress or i mplied, or a ssume a ny l egal l iability or responsibility for t he a ccuracy, completeness, or us efulness of a ny i nformation, a pparatus, pr oduct, or process di sclosed, or represent t hat its us e would not infringe pr ivately owned r ights. R eference h erein t o an y s pecific commercial p roduct, p rocess, o r s ervice b y t rade n ame, t rademark, m anufacturer, o r o therwise, does not ne cessarily c onstitute or i mply i ts e ndorsement, r ecommendation, or f avoring b y t he United States Government, any agency thereof, or any of their contractors or subcontractors. T he views and opinions expressed herein do not necessarily state or reflect those of the United States Government, any agency thereof, or any of their contractors.

The “smart grid” refers to various efforts to modernize the power grid through the application of alternate sources of energy and intelligent devices. The present national interest in smart grid applications has generated many questions concerning the role of distribution engineering in the future. What features do utility engineers need in distribution system analysis tools to support the future smart grid? This paper will discuss some relevant Electric Power Research Institute research in this area that focuses on selected issues related to smart grid analysis relevant to rural utilities. The essential characteristics of distribution system analysis tools to support analysis of these issues are discussed.

This paper reports studies of subject-verb agreement errors with speakers of Spanish and English; we used a sentence completion task, first introduced by Bock and Miller (199t). In a series of four experiments, we assessed the role of semantic information carried by the sentential subject in the induction of subject-verb agreement errors. For Spanish speakers, a sentence preamble such as la etiqueta sobre las botellas (the label on the bottles), which is usually interpreted to denote several labels, induced more agreement errors than preambles that normally denote a single entity. This finding replicates previous research with Italian . English speakers, on the other hand, were not sensitive to this semantic dimension, as was found earlier by .

We present a novel approach to the computational study of creativity, called Artificial Creativity. Artificial Creativity promotes the study of the creative behaviour of individuals and societies in artificial societies of agents. It is similar to the approach to that taken by Artificial Life researchers involved in developing computational models. We present a framework for developing Artificial Creativity systems as an adaptation of Liu’s dual generate-and-test model of creativity. An example implementation of an Artificial Creativity system is presented to illustrate the potential benefits of our new approach as a way of investigating the emergent nature of creativity in societies of communicating agents. Finally, we discuss some future research directions that are possible by extending the abilities of individuals and studying the emergent behaviour of societies.

Abstract—By taking into account the properties and limitations of the human visual system (HVS), images can be more efficiently compressed, colors more accurately reproduced, prints better rendered, to mention a few major advantages. To achieve these goals it is necessary to build a computational model of the HVS. In this paper we give an introduction to the general issue of HVS-modeling and review the specific applications of visual quality assessment and HVS-based image compression, which are closely related. On one hand, ...

A shake-table series of experiments has provided valuable data for liquefaction-induced lateral spreading effects on pile foundations. In this paper, this data is employed to estimate peak soil pressure on single piles embedded in a laterally spreading liquefied layer, and to calibrate a nonlinear elasto-plastic computational model, within the open framework for simulation OpenSees. On this basis, a user interface

The acquisition of new skills over a life span is a remarkable human ability. This ability, however, is constrained by age of acquisition (AoA); that is, the age at which learning occurs significantly affects the outcome. This is most clearly reflected in domains such as language, music, and athletics. This article provides a perspective on the neural and computational mechanisms underlying AoA in language acquisition. The authors show how AoA modulates both monolingual lexical processing and bilingual language acquisition. They consider the conditions under which syntactic processing and semantic processing may be differentially sensitive to AoA effects in second-language acquisition. The authors conclude that AoA effects are pervasive and that the neural and computational mechanisms underlying learning and sensorimotor integration provide a general account of these effects.

Hydrogels can absorb irrigation and rain water and help to reduce deep percolation by using gravitational water as well as capillary water. The objective of this study was to evaluate the effect of hydrogels on soil water retention characteristic curve (WRC) using RETC computer model. The hydrogels, PR3005A and Tarawat A100 in four levels, 2, 4, 6, and 8 g/kg, were mixed with three soil textures, sandy loam, loamy and clay. The results showed that for each texture, hydrogels caused the residual water content (θ r ) and saturated water content (θ s ) to increase. Air entry value (h b ), was observed to increase in sandy loam soil and decrease in the other soils. The results of the statistical analysis showed that there is significant difference between samples containing hydrogels and the control (without hydrogels) due to both the level of hydrogel application, and the type of hydrogel applied Available water content increased 1.8 fold of control in clay and 2.2 to 3.2 fold in loamy and sandy loam soil, respectively, with a hydrogel application of 8 g/kg.

What is the time course of visual attention? Attentional blink studies have found that the 2nd of 2 targets is often missed when presented within about 500 ms from the 1st target, resulting in theories about relatively long-lasting capacity limitations or bottlenecks. Earlier studies, however, reported quite the opposite finding: Attention is transiently enhanced, rather than reduced, for several hundreds of milliseconds after a relevant event. The authors present a general theory, as well as a working computational model, that integrate these findings. There is no central role for capacity limitations or bottlenecks. Central is a rapidly responding gating system (or attentional filter) that seeks to enhance relevant and suppress irrelevant information. When items sufficiently match the target description, they elicit transient excitatory feedback activity (a "boost" function), meant to provide access to working memory. However, in the attentional blink task, the distractor after the target is accidentally boosted, resulting in subsequent strong inhibitory feedback response (a "bounce"), which, in effect, closes the gate to working memory. The theory explains many findings that are problematic for limited-capacity accounts, including a new experiment showing that the attentional blink can be postponed. . We are also very grateful to David Huber for making us simplify and improve the model so much more. We thank Andrew Leber for planting the term "bouncer" in our minds. The computational model is available in Excel format from 836 there is little opportunity for waiting, because a distractor quickly follows T2, overwrites its vulnerable first-stage representation, and causes an attentional blink as a result. Thus, distractors play two important roles in two-stage theories: (a) They render T1 processing more difficult, resulting in longer waiting times and, thus, a more profound blink; and (b) they interfere with the T2 representation, such that T2 becomes sensitive to the temporary resource depletion (Brehaut). According to their interference theory, T1, T2, and the respective subsequent distractors are uploaded into visual short-term memory (VSTM). Within VSTM, these items then compete for conscious report. However, because VSTM resources are limited, the competition is biased in favor of those items that entered first, with further biases toward those items that closely resemble the targets. Thus, T1 and the distractor immediately following it often win the competition for retrieval, rather than T1 and T2. Within interference theory, the attentional blink period corresponds to the time needed for T1 to win the competition and be transferred to a report stage, so that

Developmental dyslexia was investigated within a well-understood and fully specified computational model of reading aloud: the dual route cascaded model (DRC [Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J.C. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108,). Four tasks were designed to assess each representational level of the DRC: letter level, orthographic lexicon, phonological lexicon, and phoneme system. The data showed no single cause of dyslexia, but rather a complex pattern of phonological, phonemic, and letter processing deficits. Importantly, most dyslexics had deficits in more than one domain. Subtyping analyses also suggested that both the phonological and surface dyslexics almost always had more than a single underlying deficit. To simulate the reading performance for each individual with the DRC, we added 0010-0277/$ -see front matter Ó

Reservoir computing (RC) refers to a new class of state-space models with a fixed state transition structure (the "reservoir") and an adaptable readout form the state space. The reservoir is supposed to be sufficiently complex so as to capture a large number of features of the input stream that can be exploited by the reservoir-to-output readout mapping. The field of RC has been growing rapidly with many successful applications. However, RC has been criticized for not being principled enough. Reservoir construction is largely driven by a series of randomized model building stages, with both researchers and practitioners having to rely on a series of trials and errors. To initialize a systematic study of the field, we concentrate on one of the most popular classes of reservoir computing methods -Echo State Network (ESN) -and ask: What is the minimal complexity of reservoir construction for obtaining competitive models and what is the memory capacity of such simplified reservoirs? On a number of widely used time series benchmarks of different origin and characteristics, as well as by conducting a theoretical analysis we show: A simple deterministically constructed cycle reservoir is comparable to the standard echo state network methodology. The (short term) memory capacity of linear cyclic reservoirs can be made arbitrarily close to the proved optimal value.

The purpose of this thesis is to develop a sound model that can be used as a creative tool by professional musicians. Post-production editing suites are used for compiling and arranging music tracks, and for creating soundtracks and voice-overs for the radio, television and film industries. A sound model would bring a new dimension of flexibility to these systems, allowing the user to stretch and mould sounds as they please.

Due to its unique morphological and physiological characteristics, vetiver grass is tolerant to many adverse climatic and edaphic conditions, and recently it has been found to show a large capacity for recovering N and P from wastewater and polluted water. As a part of a project conducted to calibrate vetiver for use in a computer model - MEDLI (Model for

The status and some recent developments in computational modeling of flexible multibody systems are summarized. Discussion focuses on a number of aspects of flexible multibody dynamics including: modeling of the flexible components, constraint modeling, solution techniques, control strategies, coupled problems, design, and experimental studies. The characteristics of the three types of reference frames used in modeling flexible multibody systems, namely, floating frame, corotational frame, and inertial frame, are compared. Future directions of research are identified. These include new applications such as micro-and nano-mechanical systems; techniques and strategies for increasing the fidelity and computational efficiency of the models; and tools that can improve the design process of flexible multibody systems. This review article cites 877 references.

The increased interactivity and connectivity of computational devices along with the spreading of computational tools and computational thinking across the fields, has changed our understanding of the nature of computing. In the course of this development computing models have been extended from the initial abstract symbol manipulating mechanisms of stand-alone, discrete sequential machines, to the models of natural computing in the physical world, generally concurrent asynchronous processes capable of modelling living systems, their informational structures and dynamics on both symbolic and sub-symbolic information processing levels. Present account of models of computation highlights several topics of importance for the development of new understanding of computing and its role: natural computation and the relationship between the model and physical implementation, interactivity as fundamental for computational modelling of concurrent information processing systems such as living organisms and their networks, and the new developments in logic needed to support this generalized framework. Computing understood as information processing is closely related to natural sciences; it helps us recognize connections between sciences, and provides a unified approach for modeling and simulating of both living and non-living systems.

This paper introduces a computational model for emotion regulation formalising the model informally described by Gross (1998). The model has been constructed using a highlevel modelling language, and integrates both quantitative aspects (such as levels of emotional response) and qualitative aspects (such as decisions to regulate one's emotion). A number of simulation experiments have been performed, demonstrating that the computational model successfully reflects the model as described by Gross.

In the context of various developing countries where many old structures require retrofitting or strengthening work to mitigate earthquake hazards, a cost-effective method is the retrofitting of damaged masonry-infilled reinforced concrete (RC) frames using ferrocement overlays, and the strengthening of existing infilled RC frames with ferrocement. However, no reliable mathematical or computational tool is accessible in the open literature to estimate the effect of such a retrofitting technique quantitatively. The present study is a numerical investigation of the retrofitting effect of masonry-infilled RC frames using ferrocement. A finite element technique has been used effectively to develop a computational model for analysing bare RC frames, together with unretrofitted and retrofitted masonry-infilled RC frames. The proposed model accounts for the material nonlinearities of both concrete and masonry, and the yielding of reinforcing steel. It is shown that the proposed model can be used effectively in predicting the load carrying capacity of existing RC frames, as well as the required degree of strengthening when ferrocement overlays are applied as a retrofitting scheme. A parametric study was performed using the proposed model on bare and infilled frames to quantify the effects of different parameters. This enabled the development of a simplified equation for predicting the ultimate load carrying capacity of masonry-infilled RC frames, which proved to be reasonably accurate and which was validated by both experimental and numerical results.

The progress on the research and application of water mist systems in fire suppression has been substantial over the last decade. To bring this work into focus, a review has been undertaken to identify future developments and potential efficacy improvements for water mist fire suppression systems. This paper, as a first step, provides a review of the fundamental research in water mist fire suppression systems. This includes a review of extinguishing mechanisms and the factors that influence the performance of water mist, such as spray characteristics, enclosure effects, dynamic mixing, the use of additives and methods of generating water mist. Recent studies on the use of computer modelling for the development of water mist fire suppression systems are also reviewed and discussed.

The SNARC (spatial numerical associations of response codes) effect reflects the tendency to respond faster with the left hand to relatively small numbers and with the right hand to relatively large numbers (S. Dehaene, S. Bossini, & P. . Using computational modeling, the present article aims to provide a framework for conceptualizing the SNARC effect. In line with models of spatial stimulusresponse congruency, the authors modeled the SNARC effect as the result of parallel activation of preexisting links between magnitude and spatial representation and short-term links created on the basis of task instructions. This basic dual-route model simulated all characteristics associated with the SNARC effect. In addition, 2 experiments tested and confirmed new predictions derived from the model.

This paper presents a systematic development process of whole-building energy models as performance benchmarks for retrofit projects. Statistical regression-based models and computational performance models are being used for retrofit projects in industry but these require existing utility data for calibration and validation. Furthermore, a common retrofit design question is the prioritization of choices for replacement of building components and systems yielding optimal energy performance for a given budget.

Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected.

This study presents an initial computational model of shared situation awareness (SA) based upon data collected from a simulated training exercise, designed to mimic real life events in a military personnel recovery center. Situation awareness was measured during the exercise using the Situation Awareness Global Assessment Technique (SAGAT). Our initial model examined how well five factors (social network distance, physical distance, rank similarity, branch similarity, and experience similarity) predicted shared SA. Overall, regression analyses highlighted the significant influence of geographical distribution (physical distance) on the development of shared SA and frequency of communications amongst team members. The discussion centers on the need for developing useful technological tools and techniques for supporting communication and collaboration among distributed teams.

Excessive flexion and internal rotation of the hip is a common gait abnormality among individuals with cerebral palsy. The purpose of this study was to examine the influence of hip flexion on the rotational moment arms of the hip muscles. We hypothesized that flexion of the hip would increase internal rotation moment arms and decrease external rotation moment arms of the primary hip rotators. To test this hypothesis we measured rotational moment arms of the gluteus maximus (six compartments), gluteus medius (four compartments), gluteus minimus (three compartments) iliopsoas, piriformis, quadratus femoris, obturator internus, and obturator externus. Moment arms were measured at hip flexion angles of 0, 20, 45, 60, and 90°in four cadavers. A three-dimensional computer model of the hip muscles was developed and compared to the experimental measurements. The experimental results and the computer model showed that the internal rotation moment arms of some muscles increase with flexion; the external rotation moment arms of other muscles decrease, and some muscles switch from external rotation to internal rotation as the hip is flexed. This trend toward internal rotation with hip flexion was apparent in 15 of the 18 muscle compartments we examined, suggesting that excessive hip flexion may exacerbate internal rotation of the hip. The gluteus maximus was found to have a large capacity for external rotation. Enhancing the activation of the gluteus maximus, a muscle that is frequently underactive in persons with cerebral palsy, may help correct excessive flexion and internal rotation of the hip.

Industrial mining through the process of heap leaching of low grade ores can be employed in the extraction of a range of base and precious metals, such as copper, gold, silver, nickel, zinc and uranium. The process involves the percolation of a leaching solution, typically cyanide, sulfuric acid or acidic ferric sulfate, through crushed ore interacting with a range of oxide and sulfide minerals. These systems involve a complex suite of interrelated fluid, gas, thermal and chemical reactions. A comprehensive computational model needs to account for variably saturated liquid and gas flow in porous media together with the transport of many species through a continually growing geometry, plus multi-phase heat and mass transfer arising from a range of phase change and gas-liquid-solid chemical reaction processes. A number of computational modeling tools employing CFD technology have been developed for the analysis of metals recovery through stockpile leaching. This contribution describes some of the technologies developed particularly to address the key challenges of modeling a full scale industrial heap. Specifically, a 'process' heap model is detailed which captures all the key phenomena of a full 3D heap but with significantly reduced simulation times, and so enables rapid analysis by engineers in an operating environment for evaluating a range of 'what if' scenarios in production planning.