Optimal methods for resource allocation and scheduling: a cross-disciplinary survey

Classical scheduling formulations typically assume static resource requirements and focus on deciding when to start the problem activities, so as to optimize some performance metric. In many practical cases, however, the decision maker has the ability to choose the resource assignment as well as the starting times: this is a far-from-trivial task, with deep implications on the quality of the final schedule. Joint resource assignment and scheduling problems are incredibly challenging from a computational perspective. They have been subject of active research in Constraint Programming (CP) and in Operations Research (OR) for a few decades, with quite difference techniques. Both the approaches report individual successes, but they overall perform equally well or (from a different perspective) equally poorly. In particular, despite the well known effectiveness of global constraints for scheduling, comparable results for joint filtering of assignment and scheduling variables have not yet been achieved. Recently, hybrid approaches have been applied to this class of problems: most of them work by splitting the overall problem into an assignment and a scheduling subparts; those are solved in an iterative and interactive fashion with a mix of CP and OR techniques, often reporting impressive speed-ups compared to pure CP and OR methods. Motivated by the success of hybrid algorithms on resource assignment and scheduling, we provide a cross-disciplinary survey on such problems, including CP, OR and hybrid approaches. The main effort is to identify key modeling and solution techniques: they may then be applied in the construction of new hybrid algorithms, or they may provide ideas for novel filtering methods (possibly based on decomposition, or on alternative representations of the domain store). In detail, we take a constraint-based perspective and, according to the equation CP = model + propagation + search, we give an overview of state-of-art models, propagation/bounding techniques and search strategies.     

Multimodal workflow for the creation of interactive presentations of 360 spin images of historical violins

Multimedia Tools and Applications - The adoption of multimedia and multimodal applications inside museums and exhibitions is becoming a common practice. These installations proved to be...     

Maximum-throughput mapping of SDFGs on multi-core SoC platforms

Data-Flow models are attracting renewed attention because they lend themselves to efficient mapping on multi-core architectures. The key problem of finding a maximum-throughput allocation and scheduling of Synchronous Data-Flow graphs (SDFGs) onto a multi-core architecture is NP-hard and has been traditionally solved by means of heuristic (incomplete) algorithms with no guarantee of global optimality. In this paper we propose an exact (complete) algorithm for the computation of a maximum-throughput mapping of applications specified as SDFG onto multi-core architectures. This is, to the best of our knowledge, the first complete algorithm for generic SDF graphs, including those with loops and a finite iteration bound. Our approach is based on Constraint Programming, it guarantees optimality and can handle realistic instances in terms of size and complexity. Extensive experiments on a large number of SDFGs demonstrate that our approach is effective and robust.     

Surfactant‐Free Shape Control of Gold Nanoparticles Enabled by Unified Theoretical Framework of Nanocrystal Synthesis

Gold nanoparticles have unique properties that are highly dependent on their shape and size. Synthetic methods that enable precise control over nanoparticle morphology currently require shape‐directing agents such as surfactants or polymers that force growth in a particular direction by adsorbing to specific crystal facets. These auxiliary reagents passivate the nanoparticles' surface, and thus decrease their performance in applications like catalysis and surface‐enhanced Raman scattering. Here, a surfactant‐ and polymer‐free approach to achieving high‐performance gold nanoparticles is reported. A theoretical framework to elucidate the growth mechanism of nanoparticles in surfactant‐free media is developed and it is applied to identify strategies for shape‐controlled syntheses. Using the results of the analyses, a simple, green‐chemistry synthesis of the four most commonly used morphologies: nanostars, nanospheres, nanorods, and nanoplates is designed. The nanoparticles synthesized by this method outperform analogous particles with surfactant and polymer coatings in both catalysis and surface‐enhanced Raman scattering.     

A reduced‐order representation of the Poincaré–Steklov operator: an application to coupled multi‐physics problems

This work investigates a model reduction method applied to coupled multi‐physics systems. The case in which a system of interest interacts with an external system is considered. An approximation of the Poincaré–Steklov operator is computed by simulating, in an offline phase, the external problem when the inputs are the Laplace–Beltrami eigenfunctions defined at the interface. In the online phase, only the reduced representation of the operator is needed to account for the influence of the external problem on the main system. An online basis enrichment is proposed in order to guarantee a precise reduced‐order computation. Several test cases are proposed on different fluid–structure couplings. Copyright © 2016 John Wiley & Sons, Ltd.     

Monitor unit calculation in 6 MV irregularly shaped beams--accuracy in clinical practice

The results of an investigation of the accuracy of monitor unit (MU) calculation in clinical shaped beams are presented. Measured doses at the reference depth on the beam central axis (isocentre) or on a beam axis representative of the irradiated area (when the isocentre lies under a block or near the edges of the block's shadow) were compared with the expected doses when calculating MUs, by applying different methods normally used in clinical practice. Empirical (areas weighted, Wrede) and scatter summation (Clarkson) methods as well as a pencil-beam based algorithm were applied. 40 irregular fields (6 MV X-rays, CLinac, Varian 6/100), divided into six categories, were considered. Dose measurements were performed with a NE2571 ionization chamber in an acrylic 30 x 30 x 30 cm3 phantom. The depths in acrylic were converted into water-equivalent depths through a correction factor derived from TMR measurements. The method of dose measurements in acrylic was found to be sufficiently accurate for the purpose of this study by comparing expected and measured doses in open square and rectangular fields (mean deviation +0.2%, SD = 0.5%). Results show that all the considered methods are sufficiently reliable in calculating MUs in clinical situations. Mean deviations between measured and expected dose values are around 0 for all the methods; standard deviations range from 1% for the Wrede method to 0.75% for the pencil-beam method. The differences between expected and measured doses were within 1% for about 3/4 of the fields when calculating MUs with all the considered methods. Maximum deviations range from 1.6% (pencil-beam) to 3% (Wrede). Slight differences among the methods of MU calculation were revealed within the different categories of blocked fields analysed. The surprising agreement between measured and expected dose values obtained by using empirical methods (area weighted and Wrede) is probably due to the fact that the reference points were positioned in a "central" region of the unblocked areas.     

Monomer Control for Error Tolerance in DNA Self-Assembly

This paper proposes the control of monomer concentration as a novel improvement of the kinetic Tile Assembly Model (kTAM) to reduce the error rate in DNA self-assembly. Tolerance to errors in this process is very important for manufacturing scaffolds for highly dense ICs; the proposed technique significantly decreases error rates (i.e. it increases error tolerance) by controlling the concentration of the monomers (tiles) for a specific pattern to be assembled. By profiling, this feature is shown to be applicable to different tile sets. A stochastic analysis based on a new state model is presented. The analysis is extended to the cases of single, double and triple bondings. The kinetic trap model is modified to account for the different monomer concentrations. Different scenarios (such as dynamic and adaptive) for monomer control are proposed: in the dynamic (adaptive) control case, the concentration of each tile is assessed based on the current (average) demand during growth as found by profiling the pattern. Significant error rate reductions are found by evaluating the proposed schemes compared to a scheme with constant concentration. One of the significant advantages of the proposed schemes is that it doesn’t entail an overhead such as increase in size and a slow growth, while still achieving a significant reduction in error rate. Simulation results are provided.     

The calibration of a model for simulating the thermal and electrical performance of a 2.8 kWAC solid-oxide fuel cell micro-cogeneration device

The concurrent production of heat and electricity within residential buildings using solid-oxide fuel cell (SOFC) micro-cogeneration devices has the potential to reduce primary energy consumption, greenhouse gas emissions, and air pollutants. A realistic assessment of this emerging technology requires the accurate simulation of the thermal and electrical production of SOFC micro-cogeneration devices concurrent with the simulation of the building, its occupants, and coupled plant components. The calibration of such a model using empirical data gathered from experiments conducted with a 2.8 kW_AC SOFC micro-cogeneration device is demonstrated. The experimental configuration, types of instrumentation employed, and the operating scenarios examined are treated. The propagation of measurement uncertainty into the derived quantities that are necessary for model calibration are demonstrated by focusing upon the SOFC micro-cogeneration system’s gas-to-water heat exchanger. The calibration coefficients necessary to accurately simulate the thermal and electrical performance of this prototype device are presented and the types of analyses enabled to study the potential of the technology are demonstrated.     

A Novel Statistical Timing and Leakage Power Characterization of Partially Depleted Silicon-on-Insulator Gates

This paper presents a novel statistical characterization for accurate timing and a new probabilistic-based analysis for estimating the leakage power in partially depleted silicon-on-insulator (PD-SOI) circuits in 100-nm BSIMSOI3.2 technology. This paper shows that the accuracy of modeling the leakage current in PD-SOI complementary metal-oxide-semiconductor (CMOS) circuits is improved by considering the interactions between the subthreshold leakage and the gate tunneling leakage, the stacking effect, the history effect, and the fan-out effect, along with a new input-independent method for estimating the leakage power based on a probabilistic approach. The proposed timing and leakage power estimate algorithms are implemented in MATLAB, HSPICE, and C. The proposed methodology is applied to ISCAS85 benchmarks, and the results show that the error is within 5%, compared with random simulation results.