Experimental study on condensation heat transfer inside a single circular minichannel

The measurement of the condensation heat transfer coefficient inside micro- and minichannels is still somewhat elusive due to the difficult task of getting accurate values of the heat transfer coefficients during the condensation process, particularly when studied within single minichannels. The present paper reports local heat transfer coefficients obtained from the measurement of the local heat flux and the direct measurement of the saturation and wall temperatures during condensation of R134a and R32 within a single circular 0.96 mm diameter minichannel. Except for the lowest mass velocity, the test results do not show significant discrepancy from the trends expected for macroscale tubes.     

Assessing the health research’s social impact: a systematic review

Scientometrics - In recent year, a growing attention is dedicated to the assessment of research’s social impact. While prior research has often dealt with results of research, the last decade...     

Saddle-node equilibrium points on the stability boundary of nonlinear autonomous dynamical systems

A complete characterization of the stability boundary of an asymptotically stable equilibrium point in the presence of type-k saddle-node non-hyperbolic equilibrium points, with k ≥ 0, on the stability boundary is developed in this paper. Under the transversality condition, it is shown that the stability boundary is composed of the stable manifolds of the hyperbolic equilibrium points on the stability boundary, the stable manifolds of type-0 saddle-node equilibrium points on the stability boundary and the stable centre and centre manifolds of the type-r saddle-node equilibrium points with r ≥ 1 on the stability boundary. This characterization is the first step to understanding the behaviour of stability regions and stability boundaries in the occurrence of saddle-node bifurcations on the stability boundary.     

PolyMorph: Increasing the Spelling Efficiency of P300 by Selection Matrix PolyMorphism and Sentence-Based Predictions

One application of the P300 brain electric signal is sentence spelling, which enables subjects who have lost control of their motor pathways to communicate by selecting characters in a matrix containing all alphabet symbols. This technology still suffers from both low communication/high error rates. A P300 speller, named PolyMorph, which jointly introduces the selection matrix polymorphism (reducing the matrix size by removing useless symbols) and sentence-based predictions (which forecast words on the basis of language statistics) is presented. This is accomplished by using a custom dynamic knowledge-base, tailored to the subject lexicon, and updated in real time with the selections of the subject. The effectiveness of the presented speller is measured in vivo and in silico. The results suggest that the use of PolyMorph increases the number of spelt characters per time unit and reduces the error rate.     

Physico-chemical characterization of protein fraction from stabilized wheat germ

Food Science and Biotechnology - Wheat germ shows the highest nutritional value of the kernel. It is highly susceptible to rancidity due to high content of unsaturated fat and presence of oxidative...     

The use of joint coordinates to monitor patients in a movement-based interaction system

Universal Access in the Information Society - Movement-based interaction has brought about new possibilities in healthcare environments. Concretely, rehabilitation therapies represent an adequate...     

Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach

Although the relevance problem in recommender systems, which typically refers to the similarity between the preference of the user and the items the system recommends, has been well studied, the issue of making recommendations in right orders has barely been mentioned before. The order defines the way in which items should be better consumed in relation to each other. The analysis of real-world data sets demonstrates strong item consumption patterns in the degree of order. In this paper, we propose a novel method to tackle the right-order recommendation problem based on a graph structure that incorporates the item consumption orders. The proposed method can combine relevance and order effects in recommendations. We attempt to recommend the relevant items in the consecutive steps within a user session so that the user’s selected items in the consecutive steps can be stringed together in a right order. The experimental evaluation conducted on three real-world data sets shows that the recommendation accuracy is improved by considering item consumption orders compared with the baseline recommendation methods. In addition, the study on right-order recommendation contributes to the exploration on recommendation appropriateness besides relevance.