Calibration Model for Water Distribution Network Using Pressures Estimated by Artificial Neural Networks

The success of hydraulic simulation models of water distribution networks is associated with the ability of these models to represent real systems accurately. To achieve this, the calibration phase is essential. Current calibration methods are based on minimizing the error between measured and simulated values of pressure and flow. This minimization is based on a search of parameter values to be calibrated, including pipe roughness, nodal demand, and leakage flow. The resulting hydraulic problem contains several variables. In addition, a limited set of known monitored pressure and flow values creates an indeterminate problem with more variables than equations. Seeking to address the lack of monitored data for the calibration of Water Distribution Networks (WDNs), this paper uses a meta-model based on an Artificial Neural Network (ANN) to estimate pressure on all nodes of a network. The calibration of pipe roughness applies a metaheuristic search method called Particle Swarm Optimization (PSO) to minimize the objective function represented by the difference between simulated and forecasted pressure values. The proposed method is evaluated at steady state and over an extended period for a real District Metering Area (DMA), named Campos do Conde II, and the hypothetical network named C-town, which is used as a benchmark for calibration studies.     

Numerical characterization and experimental verification of an in-plane MEMS-actuator with thin-film aluminum heater

In this paper, a novel concept of a thermo-mechanical MEMS actuator using aluminum thin-film heaters on a thermal oxide for electrical insulation is presented. The actuator is part of an universal tensile testing platform for thermo-mechanical material characterization of one dimensional materials on a micro- and nano-scopic scale under different environmental conditions, as varying temperatures, pressure, moisture or even vacuum and is realised in BDRIE technology. It is shown, that the actuator concept fulfills the requirements for the use in a tensile loading stage along with heterogeneously integrated nanofunctional elements, following a specimen centered approach in line with bottom-up self-assembly processes. Simulation and experiment agree very well in the thermal and mechanical domain and allow subsequent optimisation of the actuator performance.     

Single frame correction of motion artifacts in PMD-based time of flight cameras

One of the leading time of flight imaging technologies for depth sensing is based on Photonic Mixer Devices (PMD). In PMD sensors each pixel samples the correlation between emitted and received light signals. Current PMD cameras compute eight correlation samples per pixel in four sequential stages to obtain depth with invariance to signal amplitude and offset variations. With motion, PMD pixels capture different depths at each stage. As a result, correlation samples are not coherent with a single depth, producing artifacts. We propose to detect and remove motion artifacts from a single frame taken by a PMD camera. The algorithm we propose is very fast, simple and can be easily included in camera hardware. We recover depth of each pixel by exploiting consistency of the correlation samples and local neighbors of the pixel. In addition, our method obtains the motion flow of occluding contours in the image from a single frame. The system has been validated in real scenes using a commercial low-cost PMD camera and high speed dynamics. In all cases our method produces accurate results and it highly reduces motion artifacts.     

PHOTOCATALYTIC OXIDATION OF ALDEHYDES/PCE USING POROUS ANATASE TITANIA AND VISIBLE-LIGHT-RESPONSIVE BROOKITE TITANIA

We have synthesized an annealed porous aerogel titania (LUAG2), which demonstrates a very high photocatalytic activity for aldehydes and perchloroethylene (PCE) photocatalytic oxidation (PCO) in gas phase under blacklight and fluorescent light irradiation. LUAG2 has a BET surface area of 237 m²/g and a porosity of 0.31 (volume fraction). X-ray diffraction (XRD) analysis shows LUAG2 is nearly pure anatase. It has improved the destruction of PCE and aldehydes as a group by 10-34% with black light compared to Degussa P-25. The optimum water vapor to butyraldehyde molar ratio is around 1/3. LUAG2 also shows better mineralization to CO₂ than Degussa P-25 TiO₂ does. Under irradiation of a 4 W fluorescent lamp LUAG2 gives a consistently higher conversion than that of Degussa P-25. The highly active photocatalyst indicates potential applications in indoor and outdoor environmental pollution control. A visible-light-responsive TiO₂, NTB 200, is also investigated for comparison purposes.     

Estimating oxygen consumption from heart rate using adaptive neuro-fuzzy inference system and analytical approaches

In new approaches based on adaptive neuro-fuzzy systems (ANFIS) and analytical method, heart rate (HR) measurements were used to estimate oxygen consumption (VO₂). Thirty-five participants performed Meyer and Flenghi's step-test (eight of which performed regeneration release work), during which heart rate and oxygen consumption were measured. Two individualized models and a General ANFIS model that does not require individual calibration were developed. Results indicated the superior precision achieved with individualized ANFIS modelling (RMSE = 1.0 and 2.8 ml/kg min in laboratory and field, respectively). The analytical model outperformed the traditional linear calibration and Flex-HR methods with field data. The General ANFIS model's estimates of VO₂ were not significantly different from actual field VO₂ measurements (RMSE = 3.5 ml/kg min). With its ease of use and low implementation cost, the General ANFIS model shows potential to replace any of the traditional individualized methods for VO₂ estimation from HR data collected in the field.     

Some compositional properties of seeds and oils of eightAmaranthus species

Grain of 21Amaranthus accessions (eight species) was analyzed for crude fat, fatty acid profiles (FAP), and vitamin E (tocopherols and tocotrienols). Contents of (1→3), (1→4) β-glucan were determined in 12 accessions (four species), and trypsin inhibitor activity (TIA) in 20 accessions (six species). FAP and vitamin E profiles were compared to those of barley, buckwheat, corn, lupin, oat, and wheat oils. Crude fat content ranged from 5.2 to 7.7%, and of the oils examined, amaranth oil was most similar in FAP to corn and buckwheat oils. Amaranth was higher than all but wheat and lupin in tocopherol content but was virtually devoid of tocotrienols, which have been shown to have hypocholesterolemic activity. Amaranth grain did not contain (1→3), (1→4) β-glucans and was low in trypsin inhibitor activity (≤4.3 trypsin units inhibited/mg). Any hypocholesterolemic effects of dietary amaranth are apparently due to substances other than (1→3), (1→4) β-glucans or tocotrienols.     

Evolutionary Algorithms for Quantum Computers

In this article, we formulate and study quantum analogues of randomized search heuristics, which make use of Grover search (in Proceedings of the 28th Annual ACM Symposium on Theory of Computing, pp. 212–219. ACM, New York, 1996) to accelerate the search for improved offsprings. We then specialize the above formulation to two specific search heuristics: Random Local Search and the (1+1) Evolutionary Algorithm. We call the resulting quantum versions of these search heuristics Quantum Local Search and the (1+1) Quantum Evolutionary Algorithm. We conduct a rigorous runtime analysis of these quantum search heuristics in the computation model of quantum algorithms, which, besides classical computation steps, also permits those unique to quantum computing devices. To this end, we study the six elementary pseudo-Boolean optimization problems OneMax, LeadingOnes, Discrepancy, Needle, Jump, and TinyTrap. It turns out that the advantage of the respective quantum search heuristic over its classical counterpart varies with the problem structure and ranges from no speedup at all for the problem Discrepancy to exponential speedup for the problem TinyTrap. We show that these runtime behaviors are closely linked to the probabilities of performing successful mutations in the classical algorithms.     

Desalination by the improved vacuum freezing high pressure ice melting process

The VFPIM process has the following advantages: It does not require a compressor nor an absorbing solution for low pressure water vapor, nor a refrigeration loop (heat pump) to reuse the heat released in the condensation or desublimation of the low pressure water vapor in supplying the latent heat of melting ice. The process uses commercially available components and can thus be operated reliably.Some of the key unit operations are similar to those in existing vacuum freezing processes, but those unique to this process are: desublimation of low pressure vapor, pumping of an ice water slush containing a high ice content, melting of ice inside a heat conductive conduit and exchange ice formation operations. An extended surface freezer was found to have several advantages over the conventional spray freezer.     

Pole placement adaptive control with persistent jumps in the plant parameters

In this paper we consider the problem of adaptively stabilizing, and providing step tracking for, an uncertain linear time-varying system. We propose an adaptive pole placement controller which solves the problem for a single-input single-output plant whose parameters switch at a moderate rate among the elements of a compact set. The output feedback controller incorporates an integrator, and its action emulates the behaviour of a pole placement state feedback compensator; the controller is periodic and mildly nonlinear, is easy to implement, is noise tolerant, and tolerates a degree of unmodelled dynamics.     

Energieinformatik

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and highly dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.