High efficiency GaN-based light-emitting diodes with embedded air voids/SiO2 nanomasks

In this paper, the high performance GaN-based light-emitting diodes (LEDs) with embedded microscale air voids and an SiO(2) nanomask by metal-organic chemical vapor deposition (MOCVD) were demonstrated. Microscale air voids and an SiO(2) nanomask were clearly observed at the interface between GaN nanorods (NRs) and the overgrown GaN layer by scanning electron microscopy (SEM). From the reflectance spectra we show strong reflectance differences due to the different refractive index gradient between the GaN grown on the nanotemplate and sapphire. It can increase the light extraction efficiency due to additional light scattering. The transmission electron microscopy (TEM) images show the threading dislocations were suppressed by nanoscale epitaxial lateral overgrowth (NELOG). The LEDs with embedded microscale air voids and an SiO(2) nanomask exhibit smaller reverse-bias current and large enhancement of the light output (65% at 20 mA) compared with conventional LEDs.     

Inter-joint sharing of total support moments in the lower extremities during gait in narrow-heeled shoes of different heights

The study aimed to investigate the influence of the base and height of shoe heels on the total support moment (Ms) and individual joint contributions during gait. Fifteen healthy females walked barefoot and with narrow-heeled shoes (heel heights: 3.9, 6.3 and 7.3 cm) while kinematic and kinetic data were measured. Compared with the barefoot condition, the subjects maintained unaltered Ms in the sagittal plane in shod conditions. This was achieved by increasing the knee extensor moment to compensate for the diminished ankle plantarflexor moments in medium and high heel conditions. In the frontal plane, subjects in shod conditions had to sustain an increased Ms for balance control during late single-leg stance with increased knee abductor and ankle pronator moments as a result of the reduced base of the heels. The results will be helpful for future shoe designs to reduce fall risks and prevent relevant musculoskeletal problems     

RedTweet: recommendation engine for reddit

Twitter and Reddit are two of the most popular social media sites used today. In this paper, we study the use of machine learning and WordNet-based classifiers to generate an interest profile from a user’s tweets and use this to recommend loosely related Reddit threads which the reader is most likely to be interested in. We introduce a genre classification algorithm using a similarity measure derived from WordNet lexical database for English to label genres for nouns in tweets. The proposed algorithm generates a user’s interest profile from their tweets based on a referencing taxonomy of genres derived from the genre-tagged Brown Corpus augmented with a technology genre. The top K genres of a user’s interest profile can be used for recommending subreddit articles in those genres. Experiments using real life test cases collected from Twitter have been done to compare the performance on genre classification by using the WordNet classifier and machine learning classifiers such as SVM, Random Forests, and an ensemble of Bayesian classifiers. Empirically, we have obtained similar results from the two different approaches with a sufficient number of tweets. It seems that machine learning algorithms as well as the WordNet ontology are viable tools for developing recommendation engine based on genre classification. One advantage of the WordNet approach is simplicity and no learning is required. However, the WordNet classifier tends to have poor precision on users with very few tweets.     

Circular Stable Matching and 3-way Kidney Transplant

We consider the following version of the stable matching problem. Suppose that men have preferences for women, women have preferences for dogs, and dogs have preferences for men. The goal is to organize them into family units so that no three of them have incentive to desert their assigned family members to join in a new family. This problem is called circular stable matching, allegedly originated by Knuth. We also investigate a generalized version of this problem, in which every participant has preference among all others. The goal is similarly to partition them into oriented triples so that no three persons have incentive to deviate from the assignment. This problem is motivated by recent innovations in kidney exchange, and we call it the 3-way kidney transplant problem. We report complexity, structural and counting results on these two problems.     

Human action recognition based on graph-embedded spatio-temporal subspace

Human action recognition is an important issue in the pattern recognition field, with applications ranging from remote surveillance to the indexing of commercial video content. However, human actions are characterized by non-linear dynamics and are therefore not easily learned and recognized. Accordingly, this study proposes a silhouette-based human action recognition system in which a three-step procedure is used to construct an efficient discriminant spatio-temporal subspace for k-NN classification purposes. In the first step, an Adaptive Locality Preserving Projection (ALPP) method is proposed to obtain a low-dimensional spatial subspace in which the linearity in the local data structure is preserved. To resolve the problem of overlaps in the spatial subspace resulting from the ambiguity of the human body shape among different action classes, temporal data are extracted using a Non-base Central-Difference Action Vector (NCDAV) method. Finally, the Large Margin Nearest Neighbor (LMNN) metric learning method is applied to construct an efficient spatio-temporal subspace for classification purposes. The experimental results show that the proposed system accurately recognizes a variety of human actions in real time and outperforms most existing methods. In addition, a robustness test with noisy data indicates that our system is remarkably robust toward noise in the input images.     

Prevention Efficiencies of Woven Straw to Reduce PM10 Emissions from Exposed Area

Woven straw has been demonstrated to be a cheap and effective method to prevent fugitive particular matter (PM), which is a typical air pollution source emitted from the exposed area, like farmland or a construction site. From the engineering application point of view, an approach using dimensionless analysis with a multivariable regression method based on experimental data would be worth exploring to predict the prevention efficiencies of woven straw to reduce the fugitive PM10 (PM sized less than 10?μm). A series of field-analogous experiments were carried out to continuously measure PM10 using β-attenuation particle monitors in an artificial wind tunnel system. It was found that the prevention efficiencies of woven straw to reduce PM10 is significantly dependent on the coverage ratio of woven straw, and the maximum prevention efficiency of PM10 is about 42%. It is emphasized that the prevention efficiency approaches zero as the coverage ratio is less than about 40%. This implies that PM10 reduction was inefficient if the exposed area was not covered enough with woven straw. Another point of interest is that total elimination of PM10 emission is not possible using full coverage woven straw. The effects of wind velocity, silt content, and moisture on prevention efficiency are also discussed in this paper. Correlated with major parameters, a useful equation is proposed to estimate the prevention efficiencies that would be valid under the appropriate conditions suggested by this work.     

The performance of an adaptive array combining reference signal and steering vector

Using the knowledge of signal arrival direction and the stochastic characteristics of the steering vector and reference signal, the performance of an adaptive array combining reference signal and steering vector algorithms is presented. Expressions for output signal power, interference power, and noise power are obtained to show that the array sensitivity to the random steering vector error is reduced. Computational results of signal-to-interference-plus-noise ratio (SINR) as a function of random steering vector error are presented, showing that the sensitivity is reduced.     

Optical phase-locked loop (OPLL) for an amplitude modulatedcommunications link using solid-state lasers

Theoretical analysis is formulated for a solid state laser based optical phase-locked loop (OPLL) disturbed by shot noise, amplitude modulated noise, and frequency noise. The frequency noise spectral density of solid state lasers is modeled to contain a white component, a 1/f component, and a strong 1/f² component at the laser output. This model is verified and the spectral content of each component is measured using an open-loop RF frequency discriminator. The choice of loop filter is made by considering the frequency noise components, transient effects, and the loop damping factor ζ. The total phase error variance as a function of loop bandwidth is displayed for several values of carrier signal-to-noise ratio for the measured frequency noise spectrum. Optimal loop bandwidth is also calculated as a function of carrier signal-to-noise ratio. An OPLL experiment is performed, and measured phase error variance is compared with the theoretical predictions using the measured frequency noise spectrum. The results show that the measured phase error variance closely matches the theoretical predictions     

The effect of non-reactive alloying elements on the growth kinetics of the intermetallic compound between liquid Sn-based eutectic solders and Ni substrates

The effect of non-reactive alloying elements on the growth kinetics of the intermetallic compound formed between liquid Sn-based eutectic solders and Ni substrates at 250–280 °C was studied, with Ag, Pb and Bi as the alloying elements. Experimental results showed that only the intermetallic compound (IMC) Ni₃Sn₄ was present as the reaction product. Based on the diffusion controlled reaction mechanism, a parabolic kinetic equation in which both Sn concentration and alloying element effects were quantified, was derived and verified by comparing the kinetic data obtained by using four different solders with different Sn concentrations and alloying elements. The apparent activation energies for pure Sn and eutectic Sn–Ag, Sn–Pb and Bi–Sn solders reacting with Ni, the substrate, are in the range of 28.7–32.7 kJ mol⁻¹, which indicates slight variations in activation energy. The similarity between the activation energies of these four solders suggests that the diffusion of Sn atoms through the IMC is the rate controlling step. The effect of non-reactive alloying elements exerted on the pre-exponential factor of the equilibrium constant which multiplied by the bulk concentration of Sn in solder gives the surface concentration of Sn in Ni₃Sn₄.