Global Optimal Image Reconstruction from Blurred Noisy Data by a Bayesian Approach

In this paper, a procedure is presented which allows the optimal reconstruction of images from blurred noisy data. The procedure relies on a general Bayesian approach, which makes proper use of all the available information. Special attention is devoted to the informative content of the edges; thus, a preprocessing phase is included, with the aim of estimating the jump sizes in the gray level. The optimization phase follows; existence and uniqueness of the solution is secured. The procedure is tested against simple simulated data and real data.     

Validation and verification of social processes within agent-based computational organization models

The use of simulation modeling in computational analysis of organizations is becoming a prominent approach in social science research. However, relying on simulations to gain intuition about social phenomena has significant implications. While simulations may give rise to interesting macro-level phenomena, and sometimes even mimic empirical data, the underlying micro and macro level processes may be far from realistic. Yet, this realism may be important to infer results that are relevant to existing theories of social systems and to policy making. Therefore, it is important to assess not only predictive capability but also explanation accuracy of formal models in terms of the degree of realism reflected by the embedded processes. This paper presents a process-centric perspective for the validation and verification (V&V) of agent-based computational organization models. Following an overview of the role of V&V within the life cycle of a simulation study, emergent issues in agent-based organization model V&V are outlined. The notion of social contract that facilitates capturing micro level processes among agents is introduced to enable reasoning about the integrity and consistency of agent-based organization designs. Social contracts are shown to enable modular compositional verification of interaction dynamics among peer agents. Two types of consistency are introduced: horizontal and vertical consistency. It is argued that such local consistency analysis is necessary, but insufficient to validate emergent macro processes within multi-agent organizations. As such, new formal validation metrics are introduced to substantiate the operational validity of emergent macro-level behavior. Levent Yilmaz is Assistant Professor of Computer Science and Engineering in the College of Engineering at Auburn University and co-founder of the Auburn Modeling and Simulation Laboratory of the M&SNet. Dr. Yilmaz received his Ph.D. and M.S. degrees from Virginia Polytechnic Institute and State University (Virginia Tech). His research interests are on advancing the theory and methodology of simulation modeling, agent-directed simulation (to explore dynamics of socio-technical systems, organizations, and human/team behavior), and education in simulation modeling. Dr. Yilmaz is a member of ACM, IEEE Computer Society, Society for Computer Simulation International, and Upsilon Pi Epsilon. URL: http://www.eng.auburn.edu/~yilmaz     

慢速饮酒血液中酒精含量的数学模型

描述的是在一定时间内慢慢地匀速喝完一定数量酒的问题,并建立了相应的数学模型.同时也建立了快速饮酒的数学模型,以及证明了在各次饮酒后的某时刻酒精含量的可叠加性.     

Incubation period in the 2,2,4,4‐tetramethyl‐1‐piperidinyloxy‐mediated thermal autopolymerization of styrene: Kinetics and simulations

Mechanisms and simulations of the induction period and the initial polymerization stages in the nitroxide‐mediated autopolymerization of styrene are discussed. At 120–125 °C and moderate 2,2,4,4‐tetramethyl‐1‐piperidinyloxy (TEMPO) concentrations (0.02–0.08 M), the main source of radicals is the hydrogen abstraction of the Mayo dimer by TEMPO [with the kinetic constant of hydrogen abstraction (k_h)]. At higher TEMPO concentrations ([N?] > 0.1 M), this reaction is still dominant, but radical generation by the direct attack against styrene by TEMPO, with kinetic constant of addition k_ad, also becomes relevant. From previous experimental data and simulations, initial estimates of k_h ≈ 1 and k_ad ≈ 6 × 10^?7 L mol^?1 s^?1 are obtained at 125 °C. From the induction period to the polymerization regime, there is an abrupt change in the dominant mechanism generating radicals because of the sudden decrease in the nitroxide radicals. Under induction‐period conditions, the simulations confirm the validity of the quasi‐steady‐state assumption (QSSA) for the Mayo dimer in this regime; however, after the induction period, the QSSA for the dimer is not valid, and this brings into question the scientific basis of the well‐known expression k_th[M]³ (where [M] is the monomer concentration and k_th is the kinetic constant of autoinitiation) for the autoinitiation rate in styrene polymerization. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 6962‐6979, 2006     

Spatiotemporal and Thermal Analysis of VCSEL for Short-range Gigabit Optical Links

High-speed Optoelectronic Modules using Vertical Cavity Surface Emitting Lasers (VCSEL) coupled to Multi Mode Fibers (MMF) are a performing and low-cost solution for 10 Gigabit Ethernet (10 GbE) in short-distance optical links. A complete model of the spatiotemporal behavior of multimode VCSELs, through static and dynamic response, noise, thermal effects, and its coupling to MMF has been investigated. Relative Intensity Noise shows modal dependence and can be affected by spatial filtering due to coupling and fiber propagation. Simulations permit to evaluate critical parameters, such as modulation formats, launching conditions, and operating temperature for global bandwidth and eye diagram optimization up to 10 Gb/s. Simulation results are compared to measurements on prototype optoelectronic modules.     

血液净化用吸附剂脱附过程的数学模型研究

对已吸附了低密度脂蛋白（ＬＤＬ）及极低密度脂蛋白（ＶＬＤＬ）达到饱和程度的吸附柱，用１ｍｏｌ／Ｌ的生理盐水进行脱附，采用修正Ｌａｎｇｍｕｉｒ吸附式建立了连续脱附过程的数学模型，计算结果与实验测定值吻合，表明该数学模型适用于描述类似于ＬＤＬ及ＶＬＤＬ这类蛋白质大分子的脱附过程。     

Multistage Electrochemical Reactions with the Transfer of Intermediates between Near-Electrode Layer and Bulk Solution: Analysis of a Kinetic Model and Computer-Aided Modeling

Kinetic equations for a multistage electrode process complicated by the transfer of intermediates between the near-electrode layer and bulk solution are derived and analyzed. Computer-aided modeling of the kinetics of processes of this kind is performed. Conditions under which the share of diffused intermediates is no longer vanishingly small are determined. Effect of various factors on the individual stages is established. Techniques of processing experimental data for determining kinetic parameters of separate stages are suggested.     

Modeling Studies of the Formation and Destruction of NO in Pulsed Barrier Discharges in Nitrogen and Air

This paper presents the results of modeling studies on the formation and destruction of NO in pulsed barrier discharges in nitrogen and air. The goals of this work are to identify the major processes involved in the formation and destruction of NO in air discharges, to distinguish between oxidative and reductive paths for NO destruction, to explore the potential importance of excited state reactions, to evaluate the role of water in such systems, and to identify the final products in the absence of heterogeneous processes. In all cases, the systems were modeled with 100×10^–4% (100 ppm) of added NO, with and without 3% added water. The focus in all of this work is chemistry in the post-pulse regime.     

Phenomenological and neural-network modeling of cephalosporin C production bioprocess

Cephalosporin C production process withCephalosporium acremonium ATCC 48272 in synthetic medium was investigated and the experimental results allowed the development of a mathematical model describing the process behavior. The model was able to explain fairly well the diauxic phenomenon, higher growth rate during the glucose-consumption phase, and the production occurring only in the sucrose-consumption phase. Moreover, the process was simulated utilizing the neural-networks technique. Two feed-forward neural-networks with one hidden layer were employed. Both models, phenomenological and neural-networks based, satisfactorily describe the bioprocess. The difficulties in determining kinetic parameters are avoided when neural networks are utilized.