Identification of rational approximate models inH∞ using generalized orthonormal basis

Robust identification with FIR models fails to be successful when the number of coefficients to be estimated becomes large, caused by lightly damped modes of the plant or poles very close to the unit circle. The paper presents a two-stage algorithm to obtain a low-order approximate model in frequency domain in a generalized orthonormal basis with guaranteed H^∞ error bound for deterministic linear time-invariant stable systems, the first stage being an L^∞ rational approximation and the second nonlinear step being an H ^∞ rational approximation     

Evolutionary multiobjective optimization for base station transmitter placement with frequency assignment

We propose a new solution to the problem of positioning base station transmitters of a mobile phone network and assigning frequencies to the transmitters, both in an optimal way. Since an exact solution cannot be expected to run in polynomial time for all interesting versions of this problem (they are all NP-hard), our algorithm follows a heuristic approach based on the evolutionary paradigm. For this evolution to be efficient, i.e., goal-oriented and sufficiently random at the same time, problem-specific knowledge is embedded in the operators. The problem requires both the minimization of the cost and of the channel interference. We examine and compare two standard multiobjective techniques and a new algorithm - the steady-state evolutionary algorithm with Pareto tournaments. One major finding of the empirical investigation is a strong influence of the choice of the multiobjective selection method on the utility of the problem-specific recombination leading to a significant difference in the solution quality.     

Optimization of bistable viscoelastic systems

We consider the flow of a viscoelastic fluid in a symmetric cross geometry. For small driving pressures the flow is symmetric, but beyond a certain critical pressure the symmetric flow becomes unstable; two stable asymmetric solutions appear, and forcing of the unstable symmetric flow beyond the critical pressure gives rise to increased hydraulic resistance. We have combined a state-of-the-art implementation for viscoelastic flow modeling with topology optimization in a high level finite element package (COMSOL). We use this framework on the cross geometry with the aim to reduce the critical driving pressure corresponding to the point of bistability, such that the effect is enhanced. The point of bistability is, however, not explicitly contained in the solution, so we opt for a heuristic approach based on the dissipation ratio between the asymmetric and unstable symmetric flow solutions. We find a design that significantly reduces the driving pressure required for bistability, and furthermore is in agreement with the approach followed by experimental researchers. Furthermore, by comparing the two asymmetric solutions, we succesfully apply the same approach to a problem with two fluids meeting in the cross.     

An Analytical Method for Predicting the Performance of Parallel Image Processing Operations

This paper presents an analytical performance prediction model and methodology that can be used to predict the execution time, speedup, scalability and similar performance metrics of a large set of image processing operations running on a p-processor parallel system. The model which requires only a few parameters obtainable on a minimal system can help in the systematic design, evaluation and performance tuning of parallel image processing systems. Using the model one can reason about the performance of a parallel image processing system prior to implementation. The method can also support programmers in detecting critical parts of an implementation and system designers in predicting hardware performance and the effect of hardware parameter changes on performance. The execution of parallel image processing operations was studied and operations were arranged in three main problem classes based on data locality and the communication patterns of the algorithms. The core of the method is the derivation of the overhead function, as it is the overhead that determines the achievable speedup. The overheads were examined and modelled for each class. The use of the method is illustrated by four class-representative image processing algorithms: image-scalar addition, convolution, histogram calculation and the Fast Fourier Transform. The developed performance model has been validated on a 16-node parallel machine and it has been shown that the model is able to predict the parallel run-time and other performance metrics of parallel image processing operations accurately.     

Parametric estimation of affine deformations of planar shapes

We consider the estimation of affine transformations aligning a known 2D shape and its distorted observation. The classical way to solve this registration problem is to find correspondences between the shapes and then compute the transformation parameters from these landmarks. Here we propose a novel approach where the exact transformation is obtained as the solution of a polynomial system of equations. The method has been tested on synthetic as well as on real images and its robustness in the presence of segmentation errors and additive geometric noise has also been demonstrated. We have successfully applied the method for the registration of hip prosthesis X-ray images. The advantage of the proposed solution is that it is fast, easy to implement, has linear time complexity, works without established correspondences and provides an exact solution regardless of the magnitude of transformation.     

Science in the Cloud: Allocation and Execution of Data-Intensive Scientific Workflows

An important challenge for the adoption of cloud computing in the scientific community remains the efficient allocation and execution of data-intensive scientific workflows to reduce execution time and the size of transferred data. The transferred data overhead is becoming significant with emerging scientific workflows that have input/output files and intermediate data products ranging in the hundreds of gigabytes. The allocation of scientific workflows on public clouds can be described through a variety of perspectives and parameters, and has been proved to be NP-complete. This paper proposes an evolutionary approach for task allocation on public clouds considering data transfer and execution time. In our framework, a solution is represented using an allocation chromosome that encodes the allocation of tasks to nodes, and an ordering chromosome that defines the execution order according to the scientific workflow representation. We propose a multi-objective optimization that relies on a cloud cost model and employs tailored evolution operators. Starting from a population of possible solutions, we employ crossover and mutation operators on both chromosomes aiming at optimizing the data transferred between nodes as well as the total workflow runtime. The crossover operators combine parts of solutions to reduce data overhead, whereas the mutation operators swamp between parts of the same chromosome according to pre-defined rules. Our experimental study compares between the proposed approach and current state-of-the art approaches using synthetic and real-life workflows. Our algorithm performs similarly to existing heuristics for small workflows and shows up to 80 % improvements for larger synthetic workflows. To further validate our approach we compare between the allocation and scheduling obtained by our approach with that obtained by popular scientific workflow managers, when real workflows with hundreds of tasks are executed on a public cloud. The results show a 10 % improvement in runtime over existing schedulers, caused by a 80 % reduction in transferred data and optimized allocation and ordering of tasks. This improved data locality has greater impact as it can be employed to improve and study data provenance and facilitate data persistence for scientific workflows.     

Thermal dynamic model of precision wire-wound resistors

Wire-wound type resistors are often used as reference elements in high-precision electronic instruments of industrial frequencies (50-60 Hz). One of the main factors in the measurement uncertainty of these instruments is the "self-heating" affected drift of the built-in wire-wound resistors. The materials, geometry, construction and the thermal environment of the resistors determine the dynamics of the load-affected drift. This paper investigates a thermal model that can be used for on-line estimation of the load-affected thermal dynamic drift of commercially available encapsulated precision wire-wound resistors. Using the suggested model, the achievable estimation error of the relative change in resistance is below 10%. The model and the model-based on-line error estimation allow reducing the measurement uncertainty of industrial high-precision calibrators and extending the power range of standard resistors in laboratories.     

Modeling of pressure effects in HVDC cables

A model is developed for the prediction of pressure effects in HVDC mass impregnated cables as a result of temperature changes. To test the model assumptions, experiments were performed in cable like geometries. It is concluded that the model may predict the formation of gas cavities     

Quality-by-control of intensified continuous filtration-drying of active pharmaceutical ingredients

Continuous manufacturing and closed-loop quality control are emerging technologies that are pivotal for next-generation pharmaceutical modernization. We develop a process control framework for a continuous carousel for integrated filtration-drying of crystallization slurries. The proposed control system includes model-based monitoring and control routines, such as state estimation and real-time optimization, implemented in a hierarchical, three-layer quality-by-control (QbC) framework. We implement the control system in ContCarSim, a publicly available carousel simulator. We benchmark the proposed control system against simpler methods, comprising a reduced subset of the elements of the overall control system, and against open-loop operation (the current standard in pharmaceutical manufacturing). The proposed control system demonstrates superior performance in terms of higher consistency in product quality and increased productivity, proving the benefits of closed-loop control and of model-based techniques in pharmaceutical manufacturing. This study represents a step forward toward end-to-end continuous pharmaceutical processing, and in the evolution of quality-by-design toward quality-by-control.