General Computational Model Research Articles

An enhanced beam model for constrained layer damping and a parameter study of damping contribution

An enhanced analytical model is presented based on an extension of previous models for constrained layer damping (CLD) in beam-like structures. Most existing CLD models are based on the assumption that shear deformation in the core layer is the only source of damping in the structure. However, previous research has shown that other types of deformation in the core layer, such as deformations from longitudinal extension and transverse compression, can also be important. In the enhanced analytical model developed here, shear, extension, and compression deformations are all included. This model can be used to predict the natural frequencies and modal loss factors. The numerical study shows that compared to other models, this enhanced model is accurate in predicting the dynamic characteristics. As a result, the model can be accepted as a general computation model. With all three types of damping included and the formulation used here, it is possible to study the impact of the structure's geometry and boundary conditions on the relative contribution of each type of damping. To that end, the relative contributions in the frequency domain for a few sample cases are presented.

Modeling and Simulation of the Thermal and Psychrometric Transient Response of All-Electric Ships, Internal Compartments and Cabinets

We introduce a general computational model for all-electric ships and internal compartments (open and closed domains) that contain heat sources and sinks. A simplified physical model, which combines principles of classical thermodynamics and heat transfer, is developed and the resulting three-dimensional (3D) differential equations are discretized in space using a 3D cell-centered volume element scheme. The combination of the proposed simplified physical model with the adopted finite volume scheme for the numerical discretization of the differential equations is therefore called a volume element model (VEM). Two case studies are presented: a simulation of a whole ship at sea, and one of the ship's internal compartments (or cabinet). The proposed model was utilized to simulate numerically the steady-state responses of the systems in both cases. Of particular interest in the first case is the possibility of predicting the ship's thermal signature at sea. Mesh refinements were conducted to ensure the convergence of the numerical results. The converged mesh in both cases was relatively coarse (175 and 320 cells) and therefore the solutions were obtained with low computational time. Since accuracy and low computational time are combined, the model is shown to be efficient and could be used as a tool for simulation, design and optimization of thermal management of all-electric ships, internal compartments and cabinets. Finally, experiments are conducted in a test-bed facility to demonstrate, from simulated sea conditions, how to quantify the electric motors transient heat rejection to cooling water and the environment in a notional all-electric ship, with the objective of serving as known heat generation inputs to the mathematical model to simulate the transient thermal response of the entire ship and its compartments.

Use of “Bricks and Mortar” Model To Predict Transdermal Permeation: Model Development and Initial Validation

Presented in this paper is a general purpose computer model for predicting transdermal permeation of solutes in vivo. The bricks and mortar model is employed to represent the stratum corneum (SC), the main barrier to transdermal permeation. Transdermal permeation and absorption is modeled as a dynamic process of mass transfer in the heterogeneous stratum corneum including both the tortuous lipid pathway and the transcellular corneocytes pathway. The partition and diffusion properties of solutes in SC lipid matrix and corneocytes are calculated from the fundamental physical chemical properties of octanol-water partition coefficient, molecular size, and diffusion coefficients in water and lipid, using equations established elsewhere. To test the model, the in vivo tape striping data of 4-cyanophenol is simulated. Using the calculated partition and diffusion properties of 4-cyanophenol in SC lipids and corneocytes, the predicted dynamic profiles of 4-cyanophenol in the SC agreed very well with the experimental data. Results show that for a moderately hydrophobic solute like 4-cyanophenol, the transcellular pathway is also an important route of percutaneous absorption with about 2/3 of the absorbed 4-cyanophenol partitioned into the corneocytes. © 2008 American Chemical Society.

Towards a Quantum Calculus: (Work in Progress, Extended Abstract)

The aim of this paper is to introduce a general model of quantum computation, the quantum calculus: both unitary transformations and projective measurements are allowed; furthermore a complete classical control, including conditional structures and loops, is available. Complementary to its operational semantics, we introduce a pure denotational semantics for the quantum calculus. Based on probabilistic power domains [Jones, C. and G. D. Plotkin, A probabilistic powerdomain of evaluations, in: LICS, 1989, pp. 186–195. URL http://homepages.inf.ed.ac.uk/gdp/publications/Prob_Powerdomain.pdf], this pure denotational semantics associates with any description of a computation in the quantum calculus its action in a mathematical setting. Adequacy between operational and pure denotational semantics is established. Additionally to this pure denotational semantics, an observable denotational semantics is introduced. Following the work by Selinger, this observable denotational semantics is based on density matrices and super-operators. Finally, we establish an exact abstraction connection between these two semantics.

Selected Papers from InTech'05

The main objective of the annual International Conference on Intelligent Technologies (InTech) is to bring together researchers and practitioners who implement intelligent and fuzzy technologies in real-world environment. The Sixth International Conference on Intelligent Technologies InTech was held in Phuket, Thailand, on December 14-16, 2005. Topics of InTech'05 included mathematical foundations of intelligent technologies, traditional Artificial Intelligent techniques, uncertainty processing and methods of soft computing, learning/adaptive systems/data mining, and applications of intelligent technologies. This special issue contains extended versions of 11 selected papers originally presented at InTech'05. These papers cover most of the topics of the conference. Several papers describe intelligent applications of traditional data processing and signal processing techniques. H. Sawada et al. use advanced signal processing techniques to separate it sounds coming from different directions and thus, to enable user to it control robots by voice in noisy environments. N. Theera-Umpon uses a techniques of selecting a Region of Interest to enhance the behavior of the signal processing techniques when it detecting buried landmines. N. Shigei et al. describe innovative vector quantization technique which improve it image compression. T. A. Duong et al. use entropy approach to automatically it detect different it chemicals in the air. A few papers describe new applications of fuzzy and computing-with-words techniques. J. Han et al. describe how fuzzy it clustering techniques can be enhanced when we take into account that different factors may have different importance and thus, must be taken with different weights. J. Y. Zhang et al. show how fuzzy techniques – specifically, fuzzy causal models – can improve the efficiency of computer systems for it e-commerce. I. Kobayashi et al. use a new techniques (similar to computing with words) that helps to it personalize help for software users. Several papers take into account that in real life, knowledge is it hierarchical, and decision making and control are also hierarchical. T. H. Tran et al. show how a hierarchical combination of PID control with sliding-mode controllers can lead to robust non-overshoot high quality it control. L. Ding describes general challenges and ideas related to the need to take into account the hierarchical character of our knowledge. Finally, two papers deal with radically new approaches to intelligent data processing. Y. Murai et al. propose a new efficient method of it representing objects in space, a method in which an object A is described by “distance field” d(x) – describing the distance from an arbitrary point x to this object A. K. Akama et al. describe a new general computation model that is extremely useful in it checking program correctness. We want to thank all the authors for their outstanding work, the participants of InTech'05 for their helpful suggestions, the anonymous reviewers for their thorough analysis and constructive help, and – last but not the least – to Professor Kaoru Hirota for his kind suggestion to host this issue and to the entire staff of the journal for their tireless work.

A model for the self-organization of exit sites in the endoplasmic reticulum

Exit sites (ES) are specialized domains of the endoplasmic reticulum (ER) at which cargo proteins of the secretory pathway are packaged into COPII-coated vesicles. Although the essential COPII proteins (Sar1p, Sec23p-Sec24p, Sec13p-Sec31p) have been characterized in detail and their sequential binding kinetics at ER membranes have been quantified, the basic processes that govern the self-assembly and spatial organization of ERES have remained elusive. Here, we have formulated a generic computational model that describes the process of formation of ERES on a mesoscopic scale. The model predicts that ERES are arranged in a quasi-crystalline pattern, while their size strongly depends on the cargo-modulated kinetics of COPII turnover - that is, a lack of cargo leads to smaller and more mobile ERES. These predictions are in favorable agreement with experimental data obtained by fluorescence microscopy. The model further suggests that cooperative binding of COPII components, for example mediated by regulatory proteins, is a key factor for the experimentally observed organism-specific ERES pattern. Moreover, the anterograde secretory flux is predicted to grow when the average size of ERES is increased, whereas an increase in the number of (small) ERES only slightly alters the flux.

Π machines

P systems is a model of computation inspired by the way cells live and function. A typical P system consists of nested compartments surrounded by porous membranes, which contain data that are transformed by transformation rules. P systems can be simulated by a distributed computing system, where each compartment of a given system is simulated by a (remote) process, each running on a different node. By adopting a more "liberal" membrane structure where compartments do not necessarily form a tree-structure but a graph-structure, we get a more general model of computation, which we call graph structured P systems. Any instance of the new model can be implemented by a network of virtual machines, called Π machines, where each machine is able to implement the functionality of any simple compartment.

Dynamic clamp analysis of synaptic integration in sympathetic ganglia

Advances in modern neuroscience require the identification of principles that connect different levels of experimental analysis, from molecular mechanisms to explanations of cellular functions, then to circuits, and, ultimately, to systems and behavior. Here, we examine how synaptic organization of the sympathetic ganglia may enable them to function as use-dependent amplifiers of preganglionic activity and how the gain of this amplification may be modulated by metabotropic signaling mechanisms. The approach combines a general computational model of ganglionic integration together with experimental tests of the model using the dynamic clamp method. In these experiments, we recorded intracellularly from dissociated bullfrog sympathetic neurons and then mimicked physiological synapses with virtual computer-generated synapses. It thus became possible to analyze the synaptic gain by recording cellular responses to complex patterns of synaptic activity that normally arise in vivo from convergent nicotinic and muscarinic synapses. The results of these studies are significant because they illustrate how gain generated through ganglionic integration may contribute to the feedback control of important autonomic behaviors, in particular to the control of the blood pressure. We dedicate this paper to the memory of Professor Vladimir Skok, whose rich legacy in synaptic physiology helped establish the modern paradigm for connecting multiple levels of analysis in studies of the nervous system.

T-computers and the Origins of Time in the Brain

Recent research has identified the components of the brain that appear to time label information from observed sensory events, store the labeled information in memory and then using the time labels for two or more events to compute their time differences, time intervals, elapsed times or 'lifetimes'. Time differences are the basis of the 'time' numbers we read from clocks and compute in our brains. Time is our map of change. Maps are abstractions of information and can be used to construct useful devices such as space-time. A general time computer or T-computer model is outlined that shows how observed signals can be processed into time labeled information states infostates by our instruments or our brains. The observer can communicate the 'time' computed for observed events using consciousness and language signals to drive sound signals in the vocal cords for instance. The ‘problem of time’ is near a realistic solution now that the brain's T-computer has been identified. The brain is the 'local' creator of time, space, and space-time as our special maps of the reality we 'observe' and participate in.

A general computational model for predicting ribosomal frameshifts in genome sequences

Programmed ribosomal frameshifts are frequently used by RNA viruses to synthesize a single fusion protein from two or more overlapping open reading frames. We previously developed a program called FSFinder for predicting - 1 and + 1 frameshifts for Windows systems. With our new web application and web service called FSFinder2, users can predict frameshifts of any type from any web browser and operating system. We tested it on Shewanella oneidensis MR-1, for which exact frameshift sites are not known. FSFinder2 is the first program capable of finding frameshifts of general type and it is a powerful tool for predicting and analyzing genes that utilize frameshifts for their expression. FSFinder2 is available at http://wilab.inha.ac.kr/FSFinder.

Combinatorial promoter design for engineering noisy gene expression

Understanding the behavior of basic biomolecular components as parts of larger systems is one of the goals of the developing field of synthetic biology. A multidisciplinary approach, involving mathematical and computational modeling in parallel with experimentation, is often crucial for gaining such insights and improving the efficiency of artificial gene network design. Here we used such an approach and developed a combinatorial promoter design strategy to characterize how the position and multiplicity of tetO(2) operator sites within the GAL1 promoter affect gene expression levels and gene expression noise in Saccharomyces cerevisiae. We observed stronger transcriptional repression and higher gene expression noise as a single operator site was moved closer to the TATA box, whereas for multiple operator-containing promoters, we found that the position and number of operator sites together determined the dose-response curve and gene expression noise. We developed a generic computational model that captured the experimentally observed differences for each of the promoters, and more detailed models to successively predict the behavior of multiple operator-containing promoters from single operator-containing promoters. Our results suggest that the independent binding of single repressors is not sufficient to explain the more complex behavior of the multiple operator-containing promoters. Taken together, our findings highlight the importance of joint experimental-computational efforts and some of the challenges of using a bottom-up approach based on well characterized, isolated biomolecular components for predicting the behavior of complex, synthetic gene networks, e.g., the whole can be different from the sum of its parts.

Understanding the role of the tumour vasculature in the transport of drugs to solid cancer tumours

The vasculature of tumours imposes certain barriers that transport of anti-cancer drugs must overcome. Here follows an account of development of a general computational model that describes the mechanisms of drug transport to a solid tumour, with an emphasis on modelling the vasculature using solute transport concepts. Investigation into the biological parameters that enhance/prevent anticancer drug transport to the tumour provides a means to evaluate the effects of these parameters on the treatment process. Sensitivity analysis of these provides useful insights concerning anticancer drug transport mechanisms from the vasculature to the solid tumour for a non-specified drug and non-specified solid tumour by revealing the conditions that promote or prevent effective drug transport. The effect of the vasculature on transport efficiency is studied using a parametric analysis of some of the transport and biological parameters. Understanding the various transport mechanisms provides a basis to evaluate the effectiveness of the drug treatment a priori. It was found that increases in the capillary hydrostatic pressure, diffusive permeability coefficient and hydraulic conductivity all result in a decrease in tumour size. Similarly, decreases in the interstitium hydrostatic pressure and filtration constant result in a decrease in tumour size. Dependence of the change in the tumour size to changes in these parameters is non-linear. These results demonstrate the potential of the integrated computational model of the tumour and its vasculature to estimate efficacy of a particular treatment process. Regardless of the dependency of the outcome on the assumed model parameters and the assumed kinetics, mathematical models of this type can provide more explanation on the issues related to the transport barriers, the efficacy of the treatment, and the development of effective anticancer drugs. A case study also is presented to demonstrate the model's flexibility to accommodate a two-cell-glioma population.

Research on the bit computation model for time variable channel bandwidth

For the encoding bit-rate problem in H.264 wireless video communication, this paper analyzes the bit-rate computation model and the Mean Square Error distortion model, establishes the relation between the quantization parameter of the encoding bit-rate and the intra frame refresh rate of the macro block, and put forward a new ideal about the coding rate on the basis of general binomial computation model theory. Furthermore, this method not only can adaptively adjust the bit allocation and quantization parameter and prevents buffer from overflowing downward or upward under given network bandwidth, but also can apply the rate-distortion to optimize the solution method, control the encoding bits accurately and optimizes the allocation between the intra and inter frame encoding macro block.

Simulations of Chemotaxis and Random Motility in 2D Random Porous Domains

We discuss a generic computational model of eukariotic chemotaxis in 2D random porous domains. The model couples the fully time-dependent finite-difference solution of a reaction-diffusion equation for the concentration field of a chemoattractant to biased random walks representing individual chemotactic cells. We focus in particular on the influence of consumption of chemoattractant by the boundaries of obstacles with irregular shapes which are distributed randomly in the domain on the chemotactic response of the cells. Cells are stimulated to traverse a field of obstacles by a line source of chemoattractant. We find that the reactivity of the obstacle boundaries with respect to the chemoattractant strongly determines the transit time of cells through two primary mechanisms. The channeling effect arises because cells are effectively repelled from surfaces which consume chemoattractant, and opposing surfaces therefore act to keep cells in the middle of channels. This reduces traversal times relative to the case with unreactive boundaries, provided that the appropriate Péclet number relating the strength of reactivity to diffusion in governing chemoattractant transport is neither too low nor too high. The dead-zone effect arises due to a realistic threshold on the chemotactic response, which at steady state results in portions of the domain having no detectable gradient. Of these two, the channeling effect is responsible for 90% of the sensitivity of transit times to boundary reactivity. Based on these results, we speculate that it may be possible to tune the rates of cellular penetration into porous domains by engineering the reactivity of the internal surfaces to cytokines.

Damage mechanics of electromigration in microelectronics copper interconnects

Current density levels are expected to increase by orders of magnitude in nanoelectronics. Electromigration which occur under high current density is the major concern for the nanoelectronics industry. Using a general purpose computational model, which is capable of simulating coupled electromigration and thermo-mechanical stress evolution, several dual damascene copper interconnect structures have been investigated for electromigration damage. Different diffusion boundary conditions including blocking and non-blocking boundary conditions, current crowding effects, interface diffusion effects and material plasticity have been considered. Different damage criteria are used for quantifying material degradation. The computational simulation results match the experimental findings; therefore the model proves to be a useful tool for quantifying damage in nanoelectronics interconnects.

Towards cortex sized artificial neural systems

We propose, implement, and discuss an abstract model of the mammalian neocortex. This model is instantiated with a sparse recurrently connected neural network that has spiking leaky integrator units and continuous Hebbian learning. First we study the structure, modularization, and size of neocortex, and then we describe a generic computational model of the cortical circuitry. A characterizing feature of the model is that it is based on the modularization of neocortex into hypercolumns and minicolumns. Both a floating- and fixed-point arithmetic implementation of the model are presented along with simulation results. We conclude that an implementation on a cluster computer is not communication but computation bounded. A mouse and rat cortex sized version of our model executes in 44% and 23% of real-time respectively. Further, an instance of the model with 1.6 x 10(6) units and 2 x 10(11) connections performed noise reduction and pattern completion. These implementations represent the current frontier of large-scale abstract neural network simulations in terms of network size and running speed.

Generating and evaluating evaluative arguments

Evaluative arguments are pervasive in natural human communication. In countless situations people attempt to advise or persuade their interlocutors that something is desirable (vs. undesirable) or right (vs. wrong). With the proliferation of on-line systems serving as personal advisors and assistants, there is a pressing need to develop general and testable computational models for generating and presenting evaluative arguments. Previous research on generating evaluative arguments has been characterized by two major limitations. First, researchers have tended to focus only on specific aspects of the generation process. Second, the proposed approaches were not empirically tested. The research presented in this paper addresses both limitations. We have designed and implemented a complete computational model for generating evaluative arguments. For content selection and organization, we devised an argumentation strategy based on guidelines from argumentation theory. For expressing the content in natural language, we extended and integrated previous work in computational linguistics on generating evaluative arguments. The key knowledge source for both tasks is a quantitative model of user preferences. To empirically test critical aspects of our generation model, we have devised and implemented an evaluation framework in which the effectiveness of evaluative arguments can be measured with real users. Within the framework, we have performed an experiment to test two basic hypotheses on which the design of the computational model is based; namely, that our proposal for tailoring an evaluative argument to the addressee's preferences increases its effectiveness, and that differences in conciseness significantly influence argument effectiveness. The second hypothesis was confirmed in the experiment. In contrast, the first hypothesis was only marginally confirmed. However, independent testing by other researchers has recently provided further support for this hypothesis.

On Multi-threaded Metrical Task Systems

Traditionally, on-line problems have been studied under the assumption that there is a unique sequence of requests that must be served. This approach is common to most general models of on-line computation, such as Metrical Task Systems. However, there exist on-line problems in which the requests are organized in more than one independent thread. In this more general framework, at every moment the first unserved request of each thread is available. Therefore, apart from deciding how to serve a request, at each stage it is necessary to decide which request to serve among several possibilities. In this paper we introduce Multi-threaded Metrical Task Systems, that is, the generalization of Metrical Task Systems to the case in which there are many threads of tasks. We study the problem from a competitive analysis point of view, proving lower and upper bounds on the competitiveness of on-line algorithms. We consider finite and infinite sequences of tasks, as well as deterministic and randomized algorithms. In this work we present the first steps towards a more general framework for on-line problems which is not restricted to a sequential flow of information.

Computational approach to contact fatigue damage initiation analysis of gear teeth flanks

The paper describes a general computational model for the simulation of contact fatigue-damage initiation in the contact area of meshing gears. The model considers the continuum mechanics approach, where the use of homogenous and elastic material is assumed. The stress field in the contact area and the relationship between the cyclic contact loading conditions and observed contact points on the tooth flank are simulated with moving Hertzian contact pressure in the framework of the finite element method analysis. An equivalent model of Hertzian contact between two cylinders is used for evaluating contact conditions at the major point of contact of meshing gears. For the purpose of fatigue-damage analysis, the model, which is used for prediction of the number of loading cycles required for initial fatigue damage to appear, is based on the Coffin-Manson relationship between deformations and loading cycles. On the basis of computational results, and with consideration of some particular geometrical and material parameters, the initiation life of contacting spur gears in regard to contact fatigue damage can be estimated.

Computational model of solid-state, molecular, or atomic media for FDTD simulation based on a multi-level multi-electron system governed by Pauli exclusion and Fermi-Dirac thermalization with application to semiconductor photonics

We report a general computational model of complex material media for electrodynamics simulation using the Finite-Difference Time-Domain (FDTD) method. It is based on a multi-level multi-electron quantum system with electron dynamics governed by Pauli Exclusion Principle, state filling, and dynamical Fermi-Dirac Thermalization, enabling it to treat various solid-state, molecular, or atomic media. The formulation is valid at near or far off resonance as well as at high intensity. We show its FDTD application to a semiconductor in which the carriers' intraband and interband dynamics, energy band filling, and thermal processes were all incorporated for the first time. The FDTD model is sufficiently complex and yet computationally efficient, enabling it to simulate nanophotonic devices with complex electromagnetic structures requiring simultaneous solution of the mediumfield dynamics in space and time. Applications to direct-gap semiconductors, ultrafast optical phenomena, and multimode microdisk lasers are illustrated.