1,014 research outputs found
Dynamic economic and emission dispatch model considering wind power under Energy Market Reform: A case study
With the increasing issues in the environmental and the high requirement for energy, the Energy Market Reform (EMR) was introduced by the UK government. This paper develops a novel Dynamic Economic and Emission Dispatch (DEED) model for a combined conventional and wind power system incorporating the carbon price floor (CPF) and the Emission Performance Standard (EPS) that is supported by the EMR. The proposed model aims to determine the optimal operation strategy for the given system on power dispatch taking into account wind power waste and reserve and also the environmental aspect, especially the CPF of greenhouse gases and the emission limit of the EPS for different decarbonisation scenarios. Case studies for the demand profile in the Sheffield region in the UK with different time intervals is presented. The results indicate that renewable power is superior in both the economics and emissions to a mid to long-term energy strategy in the UK
Sixty Years of Fractal Projections
Sixty years ago, John Marstrand published a paper which, among other things,
relates the Hausdorff dimension of a plane set to the dimensions of its
orthogonal projections onto lines. For many years, the paper attracted very
little attention. However, over the past 30 years, Marstrand's projection
theorems have become the prototype for many results in fractal geometry with
numerous variants and applications and they continue to motivate leading
research.Comment: Submitted to proceedings of Fractals and Stochastics
Using Battery Level as Metric for Graph Planarization
International audienceTopology control in wireless sensor networks is an important issue for scalability and energy efficiency. It is often based on graph reduction performed through the use of Gabriel Graph or Relative Neighborhood Graph. This graph reduction is usually based on geometric values. In this paper we tackle the problem of possible connectivity loss in the reduced graph by applying a battery level based reduction graph. Experiments are conducted to evaluate our proposition. Results are compared with RNG reduction which takes into account only the strength of the received signal (RSSI). Results show that our algorithm maintains network connectivity longer than solutions from the literature and balances the energy consumption over nodes
Uniaxial Phase Transition in Si : Ab initio Calculations
Based on a previously proposed thermodynamic analysis, we study the relative
stabilities of five Si phases under uniaxial compression using ab initio
methods. The five phases are diamond, beta-tin, sh, sc, and hcp structures. The
possible phase-transition patterns were investigated by considering the phase
transitions between any two chosen phases of the five phases. By analyzing the
different conributions to the relative pahse stability, we identified the most
important factors in reducing the phase-transition pressures at uniaxial
compression. We also show that it is possible to have phase transitions occur
only when the phases are under uniaxial compression, in spite of no phase
transition when under hydrostatic commpression. Taking all five phases into
consideration, the phase diagram at uniaxial compression was constructed for
pressures under 20 GPa. The stable phases were found to be diamond, beta-tin
and sh structures, i.e. the same as those when under hydrostatic condition.
According to the phase diagram, direct phase transition from the diamond to the
sh phase is possible if the applied uniaxial pressures, on increasing, satisfy
the condition of Px>Pz. Simiilarly, the sh-to-beta-tin transition on
increeasing pressures is also possible if the applied uniaxial pressures are
varied from the condition of Px>Pz, on which the phase of sh is stable, to that
of Px<Pz, on which the beta-tin is stable
Ball on a beam: stabilization under saturated input control with large basin of attraction
This article is devoted to the stabilization of two underactuated planar
systems, the well-known straight beam-and-ball system and an original circular
beam-and-ball system. The feedback control for each system is designed, using
the Jordan form of its model, linearized near the unstable equilibrium. The
limits on the voltage, fed to the motor, are taken into account explicitly. The
straight beam-and-ball system has one unstable mode in the motion near the
equilibrium point. The proposed control law ensures that the basin of
attraction coincides with the controllability domain. The circular
beam-and-ball system has two unstable modes near the equilibrium point.
Therefore, this device, never considered in the past, is much more difficult to
control than the straight beam-and-ball system. The main contribution is to
propose a simple new control law, which ensures by adjusting its gain
parameters that the basin of attraction arbitrarily can approach the
controllability domain for the linear case. For both nonlinear systems,
simulation results are presented to illustrate the efficiency of the designed
nonlinear control laws and to determine the basin of attraction
Persistence of a particle in the Matheron-de Marsily velocity field
We show that the longitudinal position of a particle in a
-dimensional layered random velocity field (the Matheron-de Marsily
model) can be identified as a fractional Brownian motion (fBm) characterized by
a variable Hurst exponent for . The
fBm becomes marginal at . Moreover, using the known first-passage
properties of fBm we prove analytically that the disorder averaged persistence
(the probability of no zero crossing of the process upto time ) has a
power law decay for large with an exponent for and
for (with logarithmic correction at ), results that
were earlier derived by Redner based on heuristic arguments and supported by
numerical simulations (S. Redner, Phys. Rev. E {\bf 56}, 4967 (1997)).Comment: 4 pages Revtex, 1 .eps figure included, to appear in PRE Rapid
Communicatio
Measurement of Trace I-129 Concentrations in CsI Powder and Organic Liquid Scintillator with Accelerator Mass Spectrometry
Levels of trace radiopurity in active detector materials is a subject of
major concern in low-background experiments. Procedures were devised to measure
trace concentrations of I-129 in the inorganic salt CsI as well as in organic
liquid scintillator with Accelerator Mass Spectrometry (AMS) which leads to
improvement in sensitivities by several orders of magnitude over other methods.
No evidence of their existence in these materials were observed. Limits of < 6
X 10^{-13} g/g and < 2.6 X 10^{-17} g/g on the contaminations of I-129 in CsI
and liquid scintillator, respectively, were derived.These are the first results
in a research program whose goals are to develop techniques to measure trace
radioactivity in detector materials by AMS.Comment: Proceedings of 10th International Conference on Accelerator Mass
Spectrometr
Exceptionally Slow Rise in Differential Reflectivity Spectra of Excitons in GaN: Effect of Excitation-induced Dephasing
Femtosecond pump-probe (PP) differential reflectivity spectroscopy (DRS) and
four-wave mixing (FWM) experiments were performed simultaneously to study the
initial temporal dynamics of the exciton line-shapes in GaN epilayers. Beats
between the A-B excitons were found \textit{only for positive time delay} in
both PP and FWM experiments. The rise time at negative time delay for the
differential reflection spectra was much slower than the FWM signal or PP
differential transmission spectroscopy (DTS) at the exciton resonance. A
numerical solution of a six band semiconductor Bloch equation model including
nonlinearities at the Hartree-Fock level shows that this slow rise in the DRS
results from excitation induced dephasing (EID), that is, the strong density
dependence of the dephasing time which changes with the laser excitation
energy.Comment: 8 figure
Monitoring and classification of dimensional faults for automotive body assembly
Sudden process changes occurring during automobile body assembly processes will influence the downstream assembly process and the functionality and final appearance of the vehicle. Furthermore, these faults could result in a decreased production rate and an increase in the cost if sudden process changes are so serious that the production line has to be stopped for investigation. Thus, sudden process changes should be detected and eliminated as soon as possible to prevent defective products from being produced and to reduce the cost of repairs/reworks. A monitoring algorithm is developed to detect, classify, and group process changes by analyzing the dimensional data of car bodies. The results of this monitoring algorithm can help diagnose the root causes of variation according to the locations of measurement points, body structure, assembly sequence, and tooling layout. Measurement data obtained from an optical coordinate measuring machine (OCMM) are used to demonstrate the monitoring technique.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45577/1/10696_2005_Article_BF01358905.pd
Multiclass CBCT image segmentation for orthodontics with deep learning
Accurate segmentation of the jaw (i.e., mandible and maxilla) and the teeth in cone beam computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment planning. Although various (semi)automated methods have been proposed to segment the jaw or the teeth, there is still a lack of fully automated segmentation methods that can simultaneously segment both anatomic structures in CBCT scans (i.e., multiclass segmentation). In this study, we aimed to train and validate a mixed-scale dense (MS-D) convolutional neural network for multiclass segmentation of the jaw, the teeth, and the background in CBCT scans. Thirty CBCT scans were obtained from patients who had undergone orthodontic treatment. Gold standard segmentation labels were manually created by 4 dentists. As a benchmark, we also evaluated MS-D networks that segmented the jaw or the teeth (i.e., binary segmentation). All segmented CBCT scans were converted to virtual 3-dimensional (3D) models. The segmentation performance of all trained MS-D networks was assessed by the Dice similarity coefficient and surface deviation. The CBCT scans segmented by the MS-D network demonstrated a large overlap with the gold standard segmentations (Dice similarity coefficient: 0.934 ± 0.019, jaw; 0.945 ± 0.021, teeth). The MS-D network–based 3D models of the jaw and the teeth showed minor surface deviations when compared with the corresponding gold standard 3D models (0.390 ± 0.093 mm, jaw; 0.204 ± 0.061 mm, teeth). The MS-D network took approximately 25 s to segment 1 CBCT scan, whereas manual segmentation took about 5 h. This study showed that multiclass segmentation of jaw and teeth was accurate and its performance was comparable to binary segmentation. The MS-D network trained for multiclass segmentation would therefore make patient-specific orthodontic treatment more feasible by strongly reducing the time required to segment multiple anatomic structures in CBCT scans
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