Spatially growing disturbances in a two-stream, coplanar jet

The influence of the outer stream on the instability of a two-stream, coplanar jet with only the primary (central) stream heated for a nominal outer-to-primary velocity ratio of 0.3 was investigated by means of inviscid linearized stability theory. The instability properties of spatially growing axisymmetric and first order azimuthal disturbances were studied. It was found that the instability characteristics of the two stream jet are very different from those of a single stream jet. The presence of the outer stream enhanced the instability of the jet and increased the unstable frequency range for the first order azimuthal mode

Fishing in the Stream: Similarity Search over Endless Data

Similarity search is the task of retrieving data items that are similar to a given query. In this paper, we introduce the time-sensitive notion of similarity search over endless data-streams (SSDS), which takes into account data quality and temporal characteristics in addition to similarity. SSDS is challenging as it needs to process unbounded data, while computation resources are bounded. We propose Stream-LSH, a randomized SSDS algorithm that bounds the index size by retaining items according to their freshness, quality, and dynamic popularity attributes. We analytically show that Stream-LSH increases the probability to find similar items compared to alternative approaches using the same space capacity. We further conduct an empirical study using real world stream datasets, which confirms our theoretical results

Probe measures characteristics of hot gas stream

Shielded, tubular flow calorimeter operated by valve position measures characteristics of a hot gas stream of unknown composition. Measurements of mass flow density and total heat content per unit mass, total heat content per unit mass only, and pitot pressure are made

Towards Meta-learning over Data Streams

Modern society produces vast streams of data. Many stream mining algorithms have been developed to capture general trends in these streams, and make predictions for future observations, but relatively little is known about which algorithms perform particularly well on which kinds of data. Moreover, it is possible that the characteristics of the data change over time, and thus that a different algorithm should be recommended at various points in time. Figure 1 illustrates this. As such, we are dealing with the Algorithm Selection Problem [9] in a data stream setting. Based on measurable meta-features from a window of observations from a data stream, a meta-algorithm is built that predicts the best classifier for the next window. Our results show that this meta-algorithm is competitive with state-of-the art data streaming ensembles, such as OzaBag [6], OzaBoost [6] and Leveraged Bagging [3]

Algorithm selection on data streams

We explore the possibilities of meta-learning on data streams, in particular algorithm selection. In a first experiment we calculate the characteristics of a small sample of a data stream, and try to predict which classifier performs best on the entire stream. This yields promising results and interesting patterns. In a second experiment, we build a meta-classifier that predicts, based on measurable data characteristics in a window of the data stream, the best classifier for the next window. The results show that this meta-algorithm is very competitive with state of the art ensembles, such as OzaBag, OzaBoost and Leveraged Bagging. The results of all experiments are made publicly available in an online experiment database, for the purpose of verifiability, reproducibility and generalizability

The extrastriate body area computes desired goal states during action planning

How do object perception and action interact at a neural level? Here we test the hypothesis that perceptual features, processed by the ventral visuoperceptual stream, are used as priors by the dorsal visuomotor stream to specify goal-directed grasping actions. We present three main findings, which were obtained by combining time-resolved transcranial magnetic stimulation and kinematic tracking of grasp-and-rotate object manipulations, in a group of healthy human participants (N 22). First, the extrastriate body area (EBA), in the ventral stream, provides an initial structure to motor plans, based on current and desired states of a grasped object and of the grasping hand. Second, the contributions of EBA are earlier in time than those of a caudal intraparietal region known to specify the action plan. Third, the contributions of EBA are particularly important when desired and current object configurations differ, and multiple courses of actions are possible. These findings specify the temporal and functional characteristics for a mechanism that integrates perceptual processing with motor planning

Predicting Stream Nitrogen Concentration From Watershed Features Using Neural Networks

The present work describes the development and validation of an artificial neural network (ANN) for the purpose of estimating inorganic and total nitrogen concentrations. The ANN approach has been developed and tested using 927 nonpoint source watersheds studied for relationships between macro-drainage area characteristics and nutrient levels in streams. The ANN had eight independent input variables of watershed parameters (five on land use features, mean annual precipitation, animal unit density and mean stream flow) and two dependent output variables (total and inorganic nitrogen concentrations in the stream). The predictive quality of ANN models was judged with “hold-out” validation procedures. After ANN learning with the training set of data, we obtained a correlation coefficient r of about 0.85 in the testing set. Thus, ANNs are capable of learning the relationships between drainage area characteristics and nitrogen levels in streams, and show a high ability to predict from the new data set. On the basis of the sensitivity analyses we established the relationship between nitrogen concentration and the eight environmental variables

Simulation of a hydrocarbon fueled scramjet exhaust

Exhaust nozzle flow fields for a fully integrated, hydrocarbon burning scramjet were calculated for flight conditions of M (undisturbed free stream) = 4 at 6.1 km altitude and M (undisturbed free stream) = 6 at 30.5 km altitude. Equilibrium flow, frozen flow, and finite rate chemistry effects are considered. All flow fields were calculated by method of characteristics. Finite rate chemistry results were evaluated by a one dimensional code (Bittker) using streamtube area distributions extracted from the equilibrium flow field, and compared to very slow artificial rate cases for the same streamtube area distribution. Several candidate substitute gas mixtures, designed to simulate the gas dynamics of the real engine exhaust flow, were examined. Two mixtures are found to give excellent simulations of the specified exhaust flow fields when evaluated by the same method of characteristics computer code