Modeling and solving the steelmaking and casting scheduling problem

We propose a general model for the problem of planning and scheduling steelmaking and casting activities obtained by combining common features and constraints of the operations from a real plant and the literature. For tackling the problem, we develop a simulated annealing approach based on a solution space made of job permutations, which uses as submodule a chronological constructive procedure that assigns processing times and resources to jobs. Our technique, properly tuned in a statistically principled way, is able to find good solutions for a large range of different settings and horizons. In addition, it outperforms both a greedy procedure and a constraint‐based solver developed for comparison purposes on almost all instances. Finally, we have collected several real‐world instances that we make available on the web along with the solution validator and our best results.     

Analysis of multispectral fields of satellite IR measurements: Using statistics of second spatial differential of spectral fields for measurement characterization

An approach using spatial analysis of satellite IR spectral measurements for quality assessment is presented. The second spatial differential is used as a model of measurement noise for spatially smooth radiative fields. Spatial differentiation significantly magnifies the noise contribution and reduces the physical signal amplitude because of differences in spatial distributions of instrument noise and atmospheric thermal fields. The second spatial differential represents a convenient and effective tool for numerical analysis of satellite IR measurements. This paper demonstrates that statistics of the second spatial differential are informative predictors for data‐quality characterization. Statistics of the second spatial differential are used for identifying anomalies in spectral channel data caused by detector noise, sensitivity loss to spatial shortwave thermal variations, and spatially (temporally) correlated noise.     

COMPLIANCE VERIFICATION OF AGENT INTERACTION: A LOGIC-BASED SOFTWARE TOOL

In open societies of agents, where agents are autonomous and heterogeneous, it is not realistic to assume that agents will always act so as to comply with interaction protocols. Thus, the need arises for a formalism to specify constraints on agent interaction, and for a tool able to observe and check for agent compliance with interaction protocols. In this paper we present a JAVA-PROLOG software component built on logic programming technology, which can be used to verify compliance of agent interaction to protocols, and that has been integrated with the PROSOCS platform.     

Data-driven and adaptive control applications to a wind turbine benchmark model

Wind turbines are complex dynamic systems forced by stochastic wind disturbances, as well as gravitational, centrifugal, and gyroscopic loads. Since their aerodynamics are nonlinear, wind turbine modelling is thus challenging. Moreover, accurate models should contain many degrees of freedom to capture the most important dynamic effects. Therefore, the design of control algorithms for wind turbines should account for these complexities. However, these algorithms must capture the most important turbine dynamics without being too complex and unwieldy. The main purpose of this study is thus to give two examples of viable and practical designs of control schemes with application to a wind turbine prototype model. Extensive simulations on the benchmark process and Monte-Carlo analysis are the tools for assessing experimentally the main features of the proposed control schemes, in the presence of modelling and measurement errors. These developed control methods are also compared with other different approaches, in order to evaluate advantages and drawbacks of the considered solutions. Finally, Hardware-In-the-Loop simulations serve to highlight the potential application of the proposed control strategies to real wind turbines.     

Objective quantification of acetylcholine receptor aggregation using fast Fourier transforms

A new approach for objectively analyzing the aggregation of acetylcholine receptors (AChRs) through power spectrum analysis derived from fast Fourier transform (FFT) of images has been developed. Presently, detection of AChR aggregates at neuromuscular junctions is not easily accomplished. Though the formation of AChR clusters results in periodic gray-level variations that differ with time, no study reporting their correlation with frequency information in the Fourier domain for aggregates' detection purposes exists. To this end, we processed time-lapse images of AChR aggregates' formation on murine myotubes to extract peak values of power spectra. To validate interpretation of the Fourier spectra analysis, a computer routine was developed to semi-automatically count AChR aggregates. We found: (1) logarithmic maxima of Fourier spectra correlated significantly with experimentation time; (2) cluster count correlated significantly with time only after clusters were discernable from images, signifying that this method heavily depended on definitive growth data and thresholding values; (3) exponents of Fourier maxima versus time and cluster count versus time profiles during this phase compared favorably, indicating that both methods were analyzing identical cluster growth rates. Our observations suggest that analysis via FFT power spectrum is sensitive and robust enough to automatically quantify AChR aggregates.     

The multimod application framework: a rapid application development tool for computer aided medicine

This paper describes a new application framework (OpenMAF) for rapid development of multimodal applications in computer-aided medicine. MAF applications are multimodal in data, in representation, and in interaction. The framework supports almost any type of biomedical data, including DICOM datasets, motion-capture recordings, or data from computer simulations (e.g. finite element modeling). The interactive visualization approach (multimodal display) helps the user interpret complex datasets, providing multiple representations of the same data. In addition, the framework allows multimodal interaction by supporting the simultaneous use of different input-output devices like 3D trackers, stereoscopic displays, haptics hardware and speech recognition/synthesis systems. The Framework has been designed to run smoothly even on limited power computers, but it can take advantage of all hardware capabilities. The Framework is based on a collection of portable libraries and it can be compiled on any platform that supports OpenGL, including Windows, MacOS X and any flavor of Unix/linux.     

Ambient occlusion and edge cueing to enhance real time molecular visualization

The paper presents a set of combined techniques to enhance the real-time visualization of simple or complex molecules (up to order of 106 atoms) space fill mode. The proposed approach includes an innovative technique for efficient computation and storage of ambient occlusion terms, a small set of GPU accelerated procedural impostors for space-fill and ball-and-stick rendering, and novel edge-cueing techniques. As a result, the user's understanding of the three-dimensional structure under inspection is strongly increased (even for still images), while the rendering still occurs in real time.     

Design and control of an IPMC wormlike robot.

This paper presents an innovative wormlike robot controlled by cellular neural networks (CNNs) and made of an ionic polymer-metal composite (IPMC) self-actuated skeleton. The IPMC actuators, from which it is made of, are new materials that behave similarly to biological muscles. The idea that inspired the work is the possibility of using IPMCs to design autonomous moving structures. CNNs have already demonstrated their powerfulness as new structures for bio-inspired locomotion generation and control. The control scheme for the proposed IPMC moving structure is based on CNNs. The wormlike robot is totally made of IPMCs, and each actuator has to carry its own weight. All the actuators are connected together without using any other additional part, thereby constituting the robot structure itself. Worm locomotion is performed by bending the actuators sequentially from "tail" to "head," imitating the traveling wave observed in real-world undulatory locomotion. The activation signals are generated by a CNN. In the authors' opinion, the proposed strategy represents a promising solution in the field of autonomous and light structures that are capable of reconfiguring and moving in line with spatial-temporal dynamics generated by CNNs.     

Modelling Calculi with Name Mobility using Graphs with Equivalences

In the theory of graph rewriting, the use of coalescing rules, i.e., of rules which besides deleting and generating graph items, can coalesce some parts of the graph, turns out to be quite useful for modelling purposes, but, at the same time, problematic for the development of a satisfactory partial order concurrent semantics for rewrites. Rewriting over graphs with equivalences, i.e., (typed hyper)-graphs equipped with an equivalence over nodes provides a technically convenient replacement of graph rewriting with coalescing rules, for which a truly concurrent semantics can be easily defined. The expressivity of such a formalism is tested in a setting where coalescing rules typically play a basic role: the encoding of calculi with name passing as graph rewriting systems. Specifically, we show how the (monadic fragment) of the solo calculus, one of the dialect of those calculi whose distinctive feature is name fusion, can be encoded as a rewriting system over graph with equivalences.