Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Colour filtering in a-SiC : H based p-i-n-p-i-n cells: A trade-off between bias polarity and absorption regions

A large area colour imager optically addressed is presented. The colour imager consists of a thin wide band gap p-i-n a-SiC:H filtering element deposited on the top of a thick large area a-SiC:H(-p)/a-Si:H(-i)/a-SiC:H(-n) image sensor, which reveals itself an intrinsic colour filter. In order to tune the external applied voltage for full colour discrimination the photocurrent generated by a modulated red light is measured under different optical and electrical bias. Results reveal that the integrated device behaves itself as an imager and a filter giving information not only on the position where the optical image is absorbed but also on it wavelength and intensity. The amplitude and sign of the image signals are electrically tuneable. In a wide range of incident fluxes and under reverse bias, the red and blue image signals are opposite in sign and the green signal is suppressed allowing blue and red colour recognition. The green information is obtained under forward bias, where the blue signal goes down to zero and the red and green remain constant. Combining the information obtained at this two applied voltages a RGB colour image picture can be acquired without the need of the usual colour filters or pixel architecture. A numerical simulation supports the colour filter analysis.

Improved matching criterion for frame rate upconversion with trilateral filtering

Frame rate upconversion (FRUC) is an important post-processing technique to enhance the visual quality of low frame rate video. A major, recent advance in this area is FRUC based on trilateral filtering which novelty mainly derives from the combination of an edge-based motion estimation block matching criterion with the trilateral filter. However, there is still room for improvement, notably towards reducing the size of the uncovered regions in the initial estimated frame, this means the estimated frame before trilateral filtering. In this context, proposed is an improved motion estimation block matching criterion where a combined luminance and edge error metric is weighted according to the motion vector components, notably to regularise the motion field. Experimental results confirm that significant improvements are achieved for the final interpolated frames, reaching PSNR gains up to 2.73 dB, on average, regarding recent alternative solutions, for video content with varied motion characteristics.

Teaching and learning with social software in higher education: content management systems integrated with Web-based applications as a key factor for success

The change of paradigm imposed by the Bologna process, in which the student will be responsible for their own learning, and the presence of a new generation of students with higher technological skills, represent a huge challenge for higher education institutions. The use of new Web Social concepts in teaching process, supported by applications commonly called Web 2.0, with which these new students feel at ease, can bring benefits in terms of motivation and the frequency and quality of students' involvement in academic activities. An e-learning platform with web-based applications as a complement can significantly contribute to the development of different skills in higher education students, covering areas which are usually in deficit.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Single-function approach to calibrating whatman n.º 42 filter paper based on suction versus water content relationships

Several suction–water-content (s-w) calibrations for the filter paper method (FPM) used for soil-suction measurement have been published. Most of the calibrations involve a bilinear function (i.e., two different equations) with an inflection point occurring at 60 kPa

Proactive ontology-based content provision in the context of e-learning

Magdeburg, Univ., Fak. für Informatik, Diss., 2008

Sexually dimorphic melanin-based colour polymorphism, feather melanin content, and wing feather structure in the barn owl (Tyto alba)

Feathers confer protection against biophysical agents and determine flying ability. The geometry and arrangement of the barbs, together with the keratin and pigments deposited in the feathers, determine the mechanical stability of the vane, and its stiffness and resistance to abrasive agents. In colour-polymorphic species, individuals display alternative colour morphs, which can be associated with different foraging strategies. Each morph may therefore require specific flying abilities, and their feathers may be exposed to different abrasive agents. Feathers of differently coloured individuals may thus have a specific structure, and colour pigments may help resist abrasive agents and improve stiffness. We examined these predictions in the barn owl (Tyto alba), a species for which the ventral body side varies from white to dark reddish pheomelanic, and in the number and size of black spots located at the tip of the feathers. White and reddish birds show different foraging strategies, and the size of black feather spots is associated with several phenotypic attributes. We found that birds displaying a darker reddish coloration on the ventral body side deposit more melanin pigments in their remiges, which also have fewer barbs. This suggests that wear resistance increases with darkness, whereas feathers of lighter coloured birds may bend less easily. Accordingly, individuals displaying a lighter reddish coloration on the ventral body side, and those displaying larger black spots, displayed more black transverse bars on their remiges: as larger-spotted individuals are heavier and longer-winged birds also have more transverse bars, these bars may reduce feather bending when flying. We conclude that differently coloured individuals produce wing feathers of different strengths to adopt alternative behavioural and life history strategies

Effect of a general school-based physical activity intervention on bone mineral content and density: A cluster-randomized controlled trial.

Background: Specific physical loading leads to enhanced bone development during childhood. A general physical activity program mimicking a real-life situation was successful at increasing general physical health in children. Yet, it is not clear whether it can equally increase bone mineral mass. We performed a cluster-randomized controlled trial in children of both gender and different pubertal stages to determine whether a school-based physical activity (PA) program during one school-year influences bone mineral content (BMC) and density (BMD), irrespective of gender.Methods: Twenty-eight 1st and 5th grade (6-7 and 11-12 year-old) classes were cluster randomized to an intervention (INT, 16 classes, n = 297) and control (CON; 12 classes, n = 205) group. The intervention consisted of a multi-component PA intervention including daily physical education with at least 10 min of jumping or strength training exercises of various intensities. Measurements included anthropometry, and BMC and BMD of total body, femoral neck, total hip and lumbar spine using dual-energy X-ray absorptiometry (DXA). PA was assessed by accelerometers and Tanner stages by questionnaires. Analyses were performed by a regression model adjusted for gender, baseline height and weight, baseline PA, post-intervention pubertal stage, baseline BMC, and cluster.Results: 275 (72%) of 380 children who initially agreed to have DXA measurements had also post-intervention DXA and PA data. Mean age of prepubertal and pubertal children at baseline was 8.7 +/- 2.1 and 11.1 +/- 0.6 years, respectively. Compared to CON, children in INT showed statistically significant increases in BMC of total body, femoral neck, and lumbar spine by 5.5%, 5.4% and 4.7% (all p < 0.05), respectively, and BMD of total body and lumbar spine by 8.4% and 7.3% (both p < 0.01), respectively. There was no gender*group, but a pubertal stage*group interaction consistently favoring prepubertal children.Conclusion: A general school-based PA intervention can increase bone health in elementary school children of both genders, particularly before puberty. (C) 2010 Elsevier Inc. All rights reserved.

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Success of a general school-based physical activity intervention on bone mineral content depends on pubertal stage but not on gender

Aims: We performed a randomised controlled trial in children of both gender and different pubertal stages to determine whether a school-based physical activity (PA) program during a full schoolyear influences bone mineral content (BMC) and whether there are differences in response for boys and girls before and during puberty. Methods: Twenty-eight 1st and 5th grade classes were cluster randomised to an intervention (INT, 16 classes, n=297) and control (CON; 12 classes, n=205) group. The intervention consisted of a multi-component PA intervention including daily physical education during a full school year. Each lesson was predetermined, included about ten minutes of jumping or strength training exercises of various intensity and was the same for all children. Measurements included anthropometry (height and weight), tanner stages (by self-assessment), PA (by accelerometry) and BMC for total body, femoral neck, total hip and lumbar spine using dualenergy X-ray absorptiometry (DXA). Bone parameters were normalized for gender and tanner stage (pre- vs. puberty). Analyses were performed by a regression model adjusted for gender, baseline height, baseline weight, baseline PA, post-intervention tanner stage, baseline BMC, and cluster. Researchers were blinded to group allocation. Children in the control group did not know about the intervention arm. Results: 217 (57%) of 380 children who initially agreed to have DXA measurements had also post-intervention DXA and PA data. Mean age of prepubertal and pubertal children at baseline was 9.0±2.1 and 11.2±0.6 years, respectively. 47/114 girls and 68/103 boys were prepubertal at the end of the intervention. Compared to CON, children in INT showed statistically significant increases in BMC of total body (adjusted z-score differences: 0.123; 95%>CI 0.035 to 0.212), femoral neck (0.155; 95%>CI 0.007 to 0.302), and lumbar spine (0.127; 95%>CI 0.026 to 0.228). Importantly, there was no gender*group, but a tanner*group interaction consistently favoring prepubertal children. Conclusions: Our findings show that a general, but stringent school-based PA intervention can improve BMC in elementary school children. Pubertal stage, but not gender seems to determine bone sensitivity to physical activity loading.

Brief DISCERN, six questions for the evaluation of evidence-based content of health-related websites.

OBJECTIVE: To extract and to validate a brief version of the DISCERN which could identify mental health-related websites with good content quality. METHOD: The present study is based on the analysis of data issued from six previous studies which used DISCERN and a standardized tool for the evaluation of content quality (evidence-based health information) of 388 mental health-related websites. After extracting the Brief DISCERN, several psychometric properties (content validity through a Factor analysis, internal consistency by the Cronbach's alpha index, predictive validity through the diagnostic tests, concurrent validity by the strength of association between the Brief DISCERN and the original DISCERN scores) were investigated to ascertain its general applicability. RESULTS: A Brief DISCERN composed of two factors and six items was extracted from the original 16 items version of the DISCERN. Cronbach's alpha coefficients were more than acceptable for the complete questionnaire (alpha=0.74) and for the two distinct domains: treatments information (alpha=0.87) and reliability (alpha=0.83). Sensibility and specificity of the Brief DISCERN cut-off score > or =16 in the detection of good content quality websites were 0.357 and 0.945, respectively. Its predictive positive and negative values were 0.98 and 0.83, respectively. A statistically significant linear correlation was found between the total scores of the Brief DISCERN and those of the original DISCERN (r=0.84 and p<0.0005). CONCLUSION: The Brief DISCERN seems to be a reliable and valid instrument able to discriminate between websites with good and poor content quality. PRACTICE IMPLICATIONS: The Brief DISCERN is a simple tool which could facilitate the identification of good information on the web by patients and general consumers.