An Improved Neural Network Application for Short-Term Load Forecasting in Power Systems

In this paper an improved neural network application for short-term load forecasting purposes is presented. To speed up the learning process on one side, and not to jeopardize the stability performance of the learning process on the other side, the adaptive approach to the learning-rate parameter has been employed. Also, instead of learning overall load characteristics, the preprocessing of input data has been designed with the idea to learn only load demand behavior that is important for a certain period. The proposed neural network has shown good performance, even in the case of the incomplete data temperature set and at high irregularities in weekly load data.     

The influence of finite element meshes on the results of a spatial polycrystalline aggregate model

The influence of the microstructural inhomogenities in materials on the life-time of safety significant components of nuclear power plants is still not fully characterized. One of the most important sources of inhomogenities in metals is their grain structure. Differences in crystallographic orientations of grains lead to different responses under the applied loads and increased stresses at the grain boundaries. Engineering tools which are used to assess a response of a structural component to the applied loads are typically based upon the mechanics of continuum and are not able to account for these effects. Dedicated polycrystalline aggregate models are therefore being developed to study the effects of the microstructure on the load carrying capabilities of materials. However, a limited number of finite element types can be used due to the geometrical complexity of such models. A procedure for testing the behaviour of different finite elements in simulations involving explicit models of randomly shaped and oriented grains described by crystalline elasticity and crystal plasticity is therefore proposed. Cumulative distributions of the stress/strain tensors in all integration points in the model are compared, enabling comparison of the “average” (macroscopic) as well as “extreme” (local) behaviour of different meshes. Such an approach provides an easy to use probabilistic measure of the quality of results obtained using different element types, formulations and mesh densities.     

Sound Velocity of Kaolin in the Temperature Range from 20 °C to 1100 °C

The sound velocity of Sedlec kaolin during heating from 20 °C to 1100 °C was investigated by modulated force thermomechanical analysis (mf-TMA). In the interval from 20 °C to 250 °C, the sound velocity increases which can be explained by liberation of the water molecules from pores and micropores. Dehydroxylation (450 °C to 650 °C) presents itself with a decrease of the sound velocity. After dehydroxylation, a two-step increase of the sound velocity was observed. The first step of the increase of the sound velocity is due to solid-state sintering at low temperatures. The second step starts at 950 °C as a consequence of the collapse of the metakaolinite structure. After the maximum, a steep increase of the sound velocity follows as a result of solid-state sintering.     

Toward a multi-culture adaptive virtual tour guide agent with a modular approach

Embodied conversational agents (ECAs) are computer-generated, human-like characters that interact with human users in face-to-face conversations. ECA is a powerful tool for representing cultural differences and is suitable for interactive training or edutainment systems. This article presents preliminary results from the development of a culture-adaptive virtual tour guide agent for serving Japanese, Croatian, and general Western users by displaying appropriate verbal and non-verbal behaviors. It is being implemented in Generic ECA Framework, a modular framework for developing ECAs. Dividing the ECA functions into reusable and loosely coupled modules minimizes the effort required to implement additional behavior and facilitates incremental scale up of the system.     

Broadly tunable deep blue laser based on a star-shaped oligofluorene truxene

We report amplified spontaneous emission (ASE) and optically pumped deep-blue-emitting distributed feedback (DFB) lasers based on a star-shaped oligofluorene truxene molecule. A low ASE threshold of 2.1 kW/cm² at 439 nm was achieved. The material exhibits a high net gain of 38 cm^?1 and also low optical loss coefficient of 3.5 cm^?1. Second-order DFB lasers show tuning of the emission wavelength from 422 to 473 nm, and a minimum threshold density of 515 W/cm². This is the broadest tuning range (51 nm) reported for organic deep-blue/blue lasing materials.     

Co and Ni supported on CeO2 as selective bimetallic catalyst for dry reforming of methane

Co/CeO₂ (Co 7.5 wt.%), Ni/CeO₂ (Ni 7.5 wt.%) and Co–Ni/CeO₂ (Co 3.75 wt.%, Ni 3.75 wt.%) catalysts were prepared by surfactant assisted co-precipitation method. Samples were characterized by X-Ray diffraction, BET surface areas measurements, temperature programmed reduction and tested for the dry reforming of methane CH₄ + CO₂ → 2CO + 2H₂ in the temperature range 600–800 °C with a CH₄:CO₂:Ar 20:20:60 vol.% feed mixture and a total flow rate of 50 cm³ min⁻¹ (GHSW = 30,000 mL g⁻¹ h⁻¹). The bimetallic Co–Ni/CeO₂ catalyst showed higher CH₄ conversion in comparison with monometallic systems in the whole temperature range, being 50% at 600 °C and 97% at 800 °C. H₂/CO selectivity decreased in the following order: Co–Ni/CeO₂ > Ni/CeO₂ > Co/CeO₂. Carbon deposition on spent catalysts was analyzed by thermal analysis (TG-DTA). After 20 h under stream at 750 °C, cobalt-containing catalysts, Co/CeO₂ and Co–Ni/CeO₂, showed a stable operation in presence of a deposited amorphous carbon of 6 wt.%, whereas Ni/CeO₂ showed an 8% decrease of catalytic activity due to a massive presence of amorphous and graphitic carbon (25 wt.%).     

Traveling-wave Phenomena in a Model of Autocrine Signaling Coupled with Dynamics of the MAPK Cascade

Recently we have revealed a minimal reaction subnetwork in the MAPK (mitogen-activated protein kinase) cascade that is responsible for the emergence of bistable and oscillatory behavior. Here we examine a possible mechanism that provides for the propagation of increased MAPK activity in cell populations by interconnecting the intracellular MAPK subnetwork with the ligand-receptor signaling machinery. Such approach allows for significant reduction of the dimensionality of the parameter space on one hand and the conservation of dynamical complexity of the system on the other hand. The coupled model predicts coexistence of one, two or three different stable steady states, or the coexistence of a stable steady state and periodic solution. We found two robust and physiologically relevant characteristics of the proposed model: (i) There is a very large region of coexistence of at least one stable steady state with non-zero MAPK activity and one steady state with zero MAPK activity in the parameter space. (ii) Spontaneous traveling front waves always switching originally inactive cells into ligand releasing cells emerge in adjacent cell populations, e. g. in healthy and injured tissues. Moreover, the formation of composite traveling front waves and spatial oscillatory patterns of MAPK activity are predicted and discussed.     

Risk based management of contaminated sediments: consideration of spatial and temporal patterns in exposure modeling

This paper addresses interactions among foraging behavior, habitat preferences, site characteristics, and spatial distribution of contaminants in developing PCB exposure estimates for winter flounder at a hypothetical open water dredged material disposal site in the coastal waters of New York and New Jersey (NY-NJ). The implications of these interactions for human health risk estimates for local recreational anglers who fish for and eat flounder are described. The models implemented in this study include a spatial submodel to account for spatial and temporal characteristics of fish exposures and a probabilistic adaptation of the Gobas bioaccumulation model that accounts for temporal variation in concentrations of hydrophobic contaminants in sediment and water. We estimated the geographic distribution of a winter flounder subpopulation offshore of NY-NJ based on species biology and its vulnerability to local recreational fishing, the foraging area of individual fish, and their migration patterns. We incorporated these parameters and an estimate of differential attraction to a management site into a spatially explicit model to assess the range of exposures within the population. The output of this modeling effort, flounder PCB tissue concentrations, provided exposure point concentrations for an estimate of human health risk through ingestion of locally caught flounder. The risks obtained for the spatially nonexplicit case are as much as 1 order of magnitude higher than those obtained with explicit consideration of spatial and temporal characteristics of winter flounder foraging and seasonal migration. This practice of "defaulting" to extremely conservative estimates for exposure parameters in the face of uncertainty ill serves the decision-making process for management of contaminated sediments in general and specifically for disposal of dredged materials. Consideration of realistic spatial and temporal scales in food chain models can help support sediment management decisions by providing a quantitative expression of the confidence in risk estimates.     

General perturbation technique for the calculation of radiative effects in scattering and absorbing media

Recently it has been shown that the perturbation technique, based on joint use of both the direct and the adjoint solutions of the radiative transfer equation, is a powerful tool to solve and analyze various time-independent one-dimensional problems of atmospheric physics such as the calculation of weighting functions, prediction of radiative effects, and development of retrieval algorithms. Our primary goal is to obtain a general formulation of the perturbation technique for the most general case of the radiative transfer problem: time-dependent problems, with regard to polarization, and any possible external sources of radiation such as laser beams and solar illumination. Possible areas of application of the perturbation technique are discussed, and several examples to illustrate them are provided. The accuracy of this technique is discussed by considering the particular examples.     

Processing radio frequency ultrasound images: a robust method for local spectral features estimation by a spatially constrained parametric approach

Spectral estimation is a major component in studies aiming at characterizing biological tissues through the analysis of backscattered radio frequency (RF) ultrasonic signals and images. However, conventional spectral estimation techniques yield a well-known trade-off between spatial resolution and variance. The backscattered signals are stochastic by nature, so short-term local analysis results in a high variance of the estimates, which cannot efficiently be reduced through conventional spatial averaging. We address this issue by describing a spectral estimation technique that reduces the variance of the estimates (by smoothing the local estimates in spectrally homogeneous regions) while preserving spectral discontinuities (i.e., the smoothing is not performed across regions with different spectral contents). The proposed approach is set in a Bayesian framework and is based on local autoregressive (AR) estimation, constrained by smoothness priors. These smoothness priors are introduced through a Markov random field in which the associated potential functions are nonquadratic, allowing thereby to preserve discontinuity. The method is validated on simulated RF images and tested on echocardiographic images acquired in vivo. The results are compared to the estimates provided by the conventional Burg technique. These results clearly demonstrate the ability of the proposed approach to improve spectral estimation in terms of variance reduction and discontinuity detection.