A model of the interdiffused multilayer process

The interdiffused multilayer process (IMP) is a novel approach to growing Hg_1−xCd_xTe. In this process, alternating thin films of HgTe and CdTe are grown and allowed to interdiffuse resulting in a bulk material of constant composition. A model of the IMP must include the effects of both the deposition of new material and the interdiffusion of the material. It must also be able handle the flush phases of the IMP where the growth rate decays to zero. Existing approaches to modeling epitaxial growth of Hg_1−xCd_xTe treat growth and interdiffusion as separate, sequential steps resulting in numerical stability problems, pseudodiffusion effects, or flush phase modeling problems. The model presented here, however, is based on an incremental balance where growth and diffusion occur simultaneously, resulting in a model exhibiting none of the difficulties mentioned above. The IMP growth model is integrated with a model for calculating reflectance from a laser directed at near normal incidence angle. The predicted reflectance is compared to experimental measurements and showed a good preliminary fit when the model employed default parameters. The agreement is greatly improved after parameter fitting.     

Variational Solutions for Externally Induced Sloshing in Horizontal-Cylindrical and Spherical Vessels

A mathematical model is developed for calculating linear sloshing effects in the dynamic response of horizontal-cylindrical and spherical liquid containers under external excitation, with emphasis on earthquake excitation. The velocity potential is expressed in a series form, where each term is the product of a time function and the associated spatial function. Because of the configuration of the containers, the associated spatial functions are nonorthogonal and the problem is not separable, resulting in a system of coupled nonhomogeneous ordinary linear differential equations of motion. The solution can be obtained through either direct integration or modal analysis. Particular emphasis is given on the rate of convergence of the solution. The cases of half-full cylinders and spheres are examined in detail, where explicit expressions for the coefficients of the governing equations are derived. Using the proposed methodology, sloshing frequencies and masses are calculated rigorously for arbitrary liquid height of horizontal-cylindrical or spherical containers, and the response under two characteristic seismic events is obtained. The results describe the linear dynamic response of such containers and can be used for an efficient seismic analysis and design of industrial pressure vessels.     

OmniStore: Automating data management in a personal system comprising several portable devices

The ever growing amount of data generated and consumed on the move using portable devices gives rise to serious data management issues. The fact that each person may own and is likely to carry several such devices further aggravates this problem. On the other hand, new opportunities for achieving cleverer device interaction emerge due to the increased wireless networking capabilities of wearable and portable devices. This paper introduces OmniStore, a system that combines portable devices and infrastructure-based services to relieve the user from explicit and time consuming file management tasks. Our approach is to let devices communicate with each other as well as with a repository service, in an opportunistic and asynchronous fashion, to perform a variety of file movement and copying actions behind the scenes, which would have typically required considerable explicit user interaction.     

Preparation of ZnO nanoparticles by thermal decomposition of zinc alginate

A new method to produce zinc oxide nanocrystals is presented. The method is based on the thermal decomposition of zinc alginate gels. The gels were produced in the form of beads by ionic gelation between a zinc solution and sodium alginate. The wet beads were heated at 800 and 450 °C for 24 h and the products were characterized by X-ray diffraction (XRD), Scanning Electron Microscopy (SEM) and Transmission electron microscopy (TEM) and micro-Raman spectroscopy. XRD analysis showed that all obtained samples are of wurtzite structure. TEM analysis combined with electron diffraction also showed the presence of single crystals indexed as ZnO hexagonal phase. Crystal size was determined by measuring individual crystals from SEM pictures. It was found that heating temperature and the kind of zinc agent influence the crystal size. Raman scattering revealed the existence of defects in the structure of nanoparticles whose cringing was discussed in the context of recent studies in this field.     

A Novel Scheme for Human-Friendly and Time-Delays Robust Neuropredictive Teleoperation

A novel Neuropredictive Teleoperation (NPT) Scheme is presented. The design results from two key ideas: the exploitation of the measured or estimated neural input to the human arm or its electromyograph (EMG) as the system input and the employment of a predictor of the arm movement, based on this neural signal and an arm model, to compensate for time delays in the system. Although a multitude of such models, as well as measuring devices for the neural signals and the EMG, have been proposed, current telemanipulator research has only been considering highly simplified arm models. In the present design, the bilateral constraint that the master and slave are simultaneously compliant to each other's state (equal positions and forces) is abandoned, thus obtaining a simple to analyze succession of only locally controlled modules, and a robustness to time delays of up to 500 ms. The proposed designs were inspired by well established physiological evidence that the brain, rather than controlling the movement on-line, programs the arm with an action plan of a complete movement, which is then executed largely in open loop, regulated only by local reflex loops. As a model of the human arm the well-established Stark model is employed, whose mathematical representation is modified to make it suitable for an engineering application. The proposed scheme is however valid for any arm model. BIBO-stability and passivity results for a variety of local control laws are reported. Simulation results and comparisons with traditional designs also highlight the advantages of the proposed design.     

A simple model for diauxic growth of denitrifying bacteria

A simple model has been formulated to simulate diauxic growth of denitrifying bacteria. It is capable of fitting the experimental results of batch growth experiments with Pseudomonas denitrificans under various conditions. It successfully predicts the observed lags when a pure culture of this bacterium switches from oxygen to nitrate as terminal electron acceptor. The model includes the effect of carbon substrate limitation and length of aerobic phase and does not run into problems when switching from anoxic to aerobic conditions, unlike prior models of diauxic growth.     

Ammonia emission controls as a cost-effective strategy for reducing atmospheric particulate matter in the Eastern United States

Current regulation aimed at reducing inorganic atmospheric fine particulate matter (PM2.5) is focused on reductions in sulfur dioxide (SO2) and oxides of nitrogen (NO(x) = NO + NO2); however, controls on these pollutants are likely to increase in cost and decrease in effectiveness in the future. A supplementary strategy is reduction in ammonia (NH3) emissions, yet an evaluation of controls on ammonia has been limited by uncertainties in emission levels and in the cost of control technologies. We use state of the science emission inventories, an emission-based regional air quality model, and an explicit treatment of uncertainty to estimate the cost-effectiveness and uncertainty of ammonia emission reductions on inorganic particulate matter in the Eastern United States. Since a paucity of data on agricultural operations precludes a direct calculation of the costs of ammonia control, we calculate the "ammonia savings potential", defined as the minimum cost of applying SO2 and NO(x) emission controls in order to achieve the same reduction in ambient inorganic PM2.5 concentration as obtained from a 1 ton decrease in ammonia emissions. Using 250 scenarios of NH3, SO2, and NO(x) emission reductions, we calculate the least-cost SO2 and NO(x) control scenarios that achieve the same reduction in ambient inorganic PM2.5 concentration as a decrease in ammonia emissions. We find that the lower-bound ammonia savings potential in the winter is $8,000 per ton NH3; therefore, many currently available ammonia control technologies are cost-effective compared to current controls on SO2 and NO(x) sources. Larger reductions in winter inorganic particulate matter are available at lower cost through controls on ammonia emissions.     

A multimedia application for watermarking digital images based on a content based image retrieval technique

The current work is focused on the implementation of a robust multimedia application for watermarking digital images, which is based on an innovative spread spectrum analysis algorithm for watermark embedding and on a content-based image retrieval technique for watermark detection. The existing highly robust watermark algorithms are applying “detectable watermarks” for which a detection mechanism checks if the watermark exists or not (a Boolean decision) based on a watermarking key. The problem is that the detection of a watermark in a digital image library containing thousands of images means that the watermark detection algorithm is necessary to apply all the keys to the digital images. This application is non-efficient for very large image databases. On the other hand “readable” watermarks may prove weaker but easier to detect as only the detection mechanism is required. The proposed watermarking algorithm combine’s the advantages of both “detectable” and “readable” watermarks. The result is a fast and robust multimedia application which has the ability to cast readable multibit watermarks into digital images. The watermarking application is capable of hiding 2¹⁴ different keys into digital images and casting multiple zero-bit watermarks onto the same coefficient area while maintaining a sufficient level of robustness.     

Computational Intelligence Techniques for Short-Term Electric Load Forecasting

Electric load forecasting has received an increasing attention over the years by academic and industrial researchers and practitioners due to its major role for the effective and economic operation of power utilities. The aim of this paper is to provide a collective unified survey study on the application of computational intelligence (CI) model-free techniques to the short-term load forecasting of electric power plants. All four classes of CI methodologies, namely neural networks (NNs), fuzzy logic (FL), genetic algorithms (GAs) and chaos are addressed. The paper starts with some background material on model-based and knowledge-based forecasting methodologies revealing a number of key issues. Then, the pure NN-based and FL-based forecasting methodologies are presented in some detail. Next, the hybrid neurofuzzy forecasting methodology (ANFIS, GARIC and Fuzzy ART variations), and three other hybrid CI methodologies (KB-NN, Chaos-FL, Neurofuzzy-GA) are reviewed. The paper ends with eight representative case studies, which show the relative merits and performance that can be achieved by the various forecasting methodologies under a large repertory of geographic, weather and other peculiar conditions. An overall evaluation of the state-of-art of the field is provided in the conclusions.     

Optimal Node Visitation in Acyclic Stochastic Digraphs with Multi-threaded Traversals and Internal Visitation Requirements

The original definition of the problem of optimal node visitation (ONV) in acyclic stochastic digraphs concerns the identification of a routing policy that will enable the visitation of each leaf node a requested number of times, while minimizing the expected number of the graph traversals. The original work of Bountourelis and Reveliotis (2006) formulated this problem as a Stochastic Shortest Path (SSP) problem, and since the state space of this SSP formulation is exponentially sized with respect to the number of the target nodes, it also proposed a suboptimal policy that is computationally tractable and asymptotically optimal. This paper extends the results of Bountourelis and Reveliotis (2006) to the cases where (i) the tokens traversing the graph can “split” during certain transitions to a number of (sub-)tokens, allowing, thus, the satisfaction of many visitation requirements during a single graph traversal, and (ii) there are additional visitation requirements attached to the internal graph nodes, which, however, can be served only when the visitation requirements of their successors have been fully met. In addition, the presented set of results establishes stronger convergence properties for the proposed suboptimal policies, and it provides a formal complexity analysis of the considered ONV formulations. From a practical standpoint, the extension of the original results performed in this paper enables their effective usage in the application domains that motivated the ONV problem, in the first place.