Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Methods for Hyperbolic Conservation Laws With Stiff Relaxation I. Spurious Solutions

The author considers the numerical solution of hyperbolic systems of conservation laws with relaxation using a shock-capturing finite difference scheme on a fixed, uniform spatial grid. It is conjectured that certain a priori criteria ensure that the numerical method does not produce spurious solutions as the relaxation time vanishes. One criterion is that the limits of vanishing relaxation time and vanishing viscosity commute for the viscous regularization of the hyperbolic system. A second criterion is that a certain “subcharacteristic”condition be satisfied by the hyperbolic system. This conjecture is supported with analytical and numerical results for a specific example, the solution of generalized Riemann problems of a model system of equations with a fractional step scheme in which Godunov’s method is coupled with the backward Euler method. Similar ideas are applied to the numerical solution of stiff detonation problems.
Graph-based automatic suggestion of relationships among images of illuminated manuscripts

Scientific research on illuminated manuscripts includes the disclosure of relationships among images belonging to different manuscripts. Relationships can be modeled as typed links, which induce an hypertext over the archive. In this paper we present a formal model for annotations, which is the basis to build methods for automatically processing existing relationships among link types and exploiting the properties of the graph which models the hypertext. The result of this processing is twofold: new relationships can be suggested to help users in their research work, and the existing ones can be semantically validated to check for inconsistencies.
Reverberant speech separation based on audio-visual dictionary learning and binaural cues

Probabilistic models of binaural cues, such as the interaural phase difference (IPD) and the interaural level difference (ILD), can be used to obtain the audio mask in the time-frequency (TF) domain, for source separation of binaural mixtures. Those models are, however, often degraded by acoustic noise. In contrast, the video stream contains relevant information about the synchronous audio stream that is not affected by acoustic noise. In this paper, we present a novel method for modeling the audio-visual (AV) coherence based on dictionary learning. A visual mask is constructed from the video signal based on the learnt AV dictionary, and incorporated with the audio mask to obtain a noise-robust audio-visual mask, which is then applied to the binaural signal for source separation. We tested our algorithm on the XM2VTS database, and observed considerable performance improvement for noise corrupted signals.
A Systematic Comparison of SVM and Maximum Entropy Classifiers for Translation Error Detection

In recent years, the translation error detection or confidence estimation for SMT has been becoming a hot question, especially in the localization industry. This paper mainly focuses on a systematic comparison on two different classifiers Maximum Entropy (MaxEnt) and SVM over different features to illustrate their error detection capabilities. Three typical word posterior probabilities (WPP) and three linguistic features are introduced and fairly compared over two classifiers on Chinese to-English NIST datasets. Experimental results show that the combination of WPP with linguistic features can significantly reduce the CER, and the SVM classifier outperforms the MaxEnt classifier in terms of the CER and F measure.
Optimizing boundary maps for image segmentation

We propose an algorithm for image segmentation using the output of any boundary detector. Our algorithm constructs closed regions from the brittle boundaries of boundary maps which are usually obtained when boundary detectors are used for natural images. The proposed algorithm works on a bottom-up process which analyzes neighbourhoods of boundary points to detect discontinuities and connects them. We call this process optimization of boundary maps which is followed by dilation of boundaries and the watershed transform to obtain image segments. The segmentation results can be controlled with user-tuned parameters.
Shadow Detection and Reconstruction in High-Resolution Satellite Images via Morphological Filtering and Example-Based Learning

The shadows in high-resolution satellite images are usually caused by the constraints of imaging conditions and the existence of high-rise objects, and this is particularly so in urban areas. To alleviate the shadow effects in high-resolution images for their further applications, this paper proposes a novel shadow detection algorithm based on the morphological filtering and a novel shadow reconstruction algorithm based on the example learning method. In the shadow detection stage, an initial shadow mask is generated by the thresholding method, and then, the noise and wrong shadow regions are removed by the morphological filtering method. The shadow reconstruction stage consists of two phases: the example-based learning phase and the inference phase. During the example-based learning phase, the shadow and the corresponding nonshadow pixels are first manually sampled from the study scene, and then, these samples form a shadow library and a nonshadow library, which are correlated by a Markov random field (MRF). During the inference phase, the underlying land-cover pixels are reconstructed from the corresponding shadow pixels by adopting the Bayesian belief propagation algorithm to solve the MRF. Experimental results on QuickBird and WorldView-2 satellite images have demonstrated that the proposed shadow detection algorithm can generate accurate and continuous shadow masks and also that the estimated nonshadow regions from the proposed shadow reconstruction algorithm are highly compatible with their surrounding nonshadow regions. Finally, we examine the effects of the reconstructed image on the application of classification by comparing the classification maps of images before and after shadow reconstruction.
License Plate Recognition

License Plate Recognition (LPR) system is an application of computer vision and image processing technology that takes video of vehicles and take the vehicle frame as input image and by extracting their number plate from whole vehicle image, it displays the number plate information into text. The overall accuracy and efficiency of whole LPR system depends on number plate extraction phase as character segmentation and character recognition phases are also depend on the output of this phase. Higher be the quality of captured input vehicle image more will be the chances of proper extraction of vehicle number plate area. The approach used to segment the image is bilateral filtering algorithm and canny edge detection algorithm. Then we predict the license plate from processed image using py–tesseract OCR and match the retrieved text which is vehicle number plate with database. Finally we get the details of the particular vehicle from the database.
The Effects of Multimedia Annotation and Summary Writing on Taiwanese EFL Students' Reading Comprehension.

The present study investigates the effects of multimedia annotation through the discourse scheme and summary writing through the grounding theory (Chang, 1997) on text comprehension. Specifically, the study focuses on examining the influences of multimedia annotation from a special perspective, namely, the use of modified discourse scheme to trigger EFL learners’ active reading process, rather than a passive way of receiving different types of annotations. Summary writing, a newly applied means to test learners’ reading comprehension (Trites & McGroarty, 2005), is probed to see whether there exist wash back effects in assisting learners’ reading performance. One hundred Taiwanese EFL university freshmen were divided into four groups, each group receiving a different treatment within a pretest-posttest-delay post-test design. Results of ANOVA indicated that both multimedia annotation and summary writing had significant positive effects on learners’ reading performance, with obvious variances in the post and delayed post-test. Moreover, the repeated measure was applied to examine the lasting effects of the treatments. In addition, qualitative interview data relating to the participants’ ideas and attitudes are also discussed.
Teachers’ Literal and Inferential Talk in Early Childhood and Special Education Classrooms

ABSTRACT Research Findings: This study examined preschool teachers’ literal talk (LT) and inferential talk (IT) during shared book readings in early childhood education (ECE) and early childhood special education (ECSE) classrooms. We aimed to characterize and compare teachers’ LT and IT in these 2 classroom contexts and determine whether differences in LT and IT are predicted by classroom type, teachers’ educational background, or children’s average language skills. We examined the shared book reading activities of 52 teachers (26 ECE classrooms, 26 ECSE classrooms). Results revealed that ECSE teachers used significantly more LT and showed more variability in their LT and IT than ECE teachers. ECSE classroom type predicted teachers’ use of LT when we controlled for teacher education and children’s language skills, whereas teacher education predicted teachers’ use of IT when we controlled for classroom type and children’s language skills. Practice or Policy: These findings have implications for best practice guidelines and policies, particularly for ECSE environments.
Enveloped by Ocean Life: Experiences of Scuba Diving

This arts-informed, phenomenological, and heuristic inquiry focuses on what it means to immerse deeply into experiences within the natural world. Through attention and reflection on emotional and somatic aspects of my own ocean SCUBA diving experiences, and those of beginner and practiced divers, a method and the significance of learning through personal experiences and others’ shared stories is illuminated. Readers are invited to imagine or revisit what it is like to be enveloped by ocean life through an artful narrative account of the ocean diving experience. Crafted in meandering ways, through the aesthetics of photographic images, divers’ evocative descriptions and poetic text, and interspersed with remembrances and imaginations and contemplations of self and world, the narrative reflects the diversity, richness and resonance of divers’ shared stories, and the reverberating and nurturing beauty and mystery of the ocean world. Through five narrative sections that embody a sense of movement deeper into the experience – into relations with the natural world, (‘Immersing’ ‘Opening Pathways of Exploration’, ‘Widening Circles of Compassion’, ‘Nature Reveals Her Open Secret’ and ‘Surfacing’), I encourage readers to wander amongst ocean life to expand ways of experiencing the natural world.
Formal analysis of SEP protocol using the interpretation function-based method

Electronic payment is the very important step of the electronic business system, and its security must be ensured. The Secure Electronic protocol (SEP) [1] was proposed to protect online payment transactions against the fraud without involving the third party such as Visa or MasterCard. SEP protocol avoids the complexities relating to the implementation unlike SET and 3D-secure, integration and utilization are also easier than before. Then it's crucial to ensure that this protocol respect security properties such as confidentiality, authentication and integrity. In this paper, we analyze the SEP protocol with respect to the confidentiality (secrecy) property. To perform this analysis, we use the interpretation functions-based method [2, 3]. The main idea behind the interpretation functions-based technique is to give sufficient conditions that allow to guarantee that a cryptographic protocol respects the secrecy property. The flexibility of the proposed conditions allows the verification of daily life protocols such us SEP.
Characterization of Polymers using TGA

TGA measures the amount and rate (velocity) of change in the mass of a sample as a function of temperature or time in a controlled atmosphere. The measurements are used primarily to determine the thermal and/or oxidative stabilities of materials as well as their compositional properties. The technique can analyze materials that exhibit either mass loss or gain due to decomposition, oxidation or loss of volatiles (such as moisture). It is especially useful for the study of polymeric materials, including thermoplastics, thermosets, elastomers, composites, films, fibers, coatings and paints.
Application Deployment and Management in the Cloud

Cloud computing is a revolutionary paradigm that allows to acquire infinite resources on demand and pay only for the actual use. Together with novel software development methodologies, such as Agile and DevOps, the cloud can really help companies in responding to market demand for continuous delivering innovative services, enabling the shift from a silo based release process, where customers, developers and system administrators are almost conflicting among each other, to a unified process, where the shared final objective is that of making the product available to the user. There are two main challenges that have to be faced when approaching the cloud. First of all, the heterogeneity of the offer. More and more cloud services are growing from different providers with no standard yet defined, driving companies towards the lock-in problem. Second, having the possibility to scale from 10s to 1000s of machines implies huge effort in IT management without smart automation systems. This paper is an attempt to review some of the tools among the currently available ones that may help companies simplifying their application release process.
YouTube celebrities and parasocial interaction: Using feedback channels in mediatized relationships

Young media consumers are increasingly using online video platforms, as YouTube in particular registers extremely high numbers of viewers and subscribers. These numbers then increase the popularity of the celebrities who present themselves in the videos on the platform. With their far-reaching influence, through involvement in the public sphere as well as broad marketing concepts, they draw in viewers and gain attention worldwide. It can thus be understood that YouTube users also form a bond with the celebrities featured online, as formulated theoretically in the concept of parasocial relationships. In this study, an exploratory online survey examines quantitatively whether these parasocial relationships are predominantly formed with YouTubers via the platform’s feedback channels. As the results show, however, the strength of these parasocial relationships is not influenced to any great extent by use of the feedback functions.
Star formation in close pairs selected from the Sloan Digital Sky Survey

The effect of galaxy interactions on star formation has been investigated using Data Release 1 of the Sloan Digital Sky Survey (SDSS). Both the imaging and spectroscopy data products have been used to construct a catalogue of nearest companions to a volume limited (0:03< z< 0:1) sample of galaxies drawn from the main galaxy sample of SDSS. Of the 13973 galaxies in the volume limited sample, we have identified 12492 systems with companions at projected separations less than 300 kpc. Star-formation rates for the volume-limited sample have been calculated from extinction and aperture corrected Hα luminosities and, where available, IRAS data. Specific star formation rates were calculated by estimating galaxy masses from z-band luminosities, and r-band concentration indices were used as an indicator of morphological class. The mean specific star-formation rate is found to be strongly enhanced for projected separations of less than 30 kpc. For late-type galaxies the correlation extends out to projected separations of 300 kpc and is most pronounced in actively star-forming systems. The specific star-formation rate is observed to decrease with increasing recessional velocity difference, but the magnitude of this effect is small compared to that associated with the projected separation. We also observe a tight relationship between the concentration index and pair separation; the mean concentration index is largest for pairs with separations of approximately 75 kpc and declines rapidly for separations smaller than this. This is interpreted as being due to the presence of tidally-triggered nuclear starbursts in close pairs. Further, we find no dependence of star formation enhancement on the morphological type or mass of the companion galaxy.
Ecological Validity as a Key Feature of External Validity in Research on Human Development

This issue addresses the topic of ecological validity in research in human development across the life span. Although recent developments in study design, data collection methods, and data analysis techniques have greatly advanced researchers’ ability to collect large amounts of data on large groups of individuals in natural settings, it is important to approach these data with a reflected understanding of their ecological validity. Just because data were collected using everyday and familiar stimuli or ecological momentary assessment methods does not mean automatically that the ecological validity of these data is guaranteed and can go unquestioned.
Use of complementary and alternative medicine in cancer patients: a European survey.

BACKGROUND The aim of this study was to explore the use of complementary and alternative medicine (CAM) in cancer patients across a number of European countries. METHODS A descriptive survey design was developed. Fourteen countries participated in the study and data was collected through a descriptive questionnaire from 956 patients. RESULTS Data suggest that CAM is popular among cancer patients with 35.9% using some form of CAM (range among countries 14.8% to 73.1%). A heterogeneous group of 58 therapies were identified as being used. Herbal medicines and remedies were the most commonly used CAM therapies, together with homeopathy, vitamins/minerals, medicinal teas, spiritual therapies and relaxation techniques. Herbal medicine use tripled from use before diagnosis to use since diagnosis with cancer. Multivariate analysis suggested that the profile of the CAM user was that of younger people, female and with higher educational level. The source of information was mainly from friends/family and the media, while physicians and nurses played a small part in providing CAM-related information. The majority used CAM to increase the body's ability to fight cancer or improve physical and emotional well-being, and many seemed to have benefited from using CAM (even though the benefits were not necessarily related to the initial reason for using CAM). Some 4.4% of patients, however, reported side-effects, mostly transient. CONCLUSIONS It is imperative that health professionals explore the use of CAM with their cancer patients, educate them about potentially beneficial therapies in light of the limited available evidence of effectiveness, and work towards an integrated model of health-care provision.
Optimal hybrid power system design for rural electrification

Both grid-tied and off-grid diesel power plants are operational throughout the country. Integration of wind power into traditional diesel-only power supply system reduces the green house gases and thereby global warming. Many researches are conducted in improving the performance of the system but unfortunately the actual design of a hybrid wind-diesel system is less worked upon. In this work, we have built and simulated a wind-diesel hybrid system using the Hybrid Optimization Model for Electric Renewable (HOMER) and compared the operational and economic parameters with traditional diesel system parameters, widely used in rural India. The economic perspective in the design is highlighted with suitable graphical plots.
Field Emissivity Measurements during the ReSeDA Experiment

Emissivity measurements were made during the ReSeDA experiment. Emissivities are necessary for obtaining surface temperatures from remote sensing data in the thermal infrared, and they enter the radiative balance in the atmosphere-surface system. The objective of this study was to assess the spatial variation of surface emissivity in the area, with special regard to the spectral variation of emissivity in the 8-14 μm band. Field broadband (8-14 μm) measurements were performed for the main crops of the Alpilles experimental site (wheat, corn, sunflower and alfalfa). The box method was used for the field campaigns. This methodology is suitable for “in situ” emissivity measurements and permits covering the major crops and surface types, which gives us a good picture of the emissivity variability in the area In addition, laboratory spectral measurements were made to assess the spectral variation of emissivity. These measurements could only be made for soil samples, however, the spectral variation of green vegetation is known to be small. The field and laboratory measurements, together with estimates of plant dimensions and cover, were used in an emissivity model to derive effective spectral emissivities for various surface types and crops. In addition, we have shown that broadband (8-14 μm) integrated emissivities are a good approximation to equivalent hemispheric emissivities for the estimation of the longwave radiative balance.
Low Complexity, High Efficiency Probability Model for Hyper-spectral Image Coding

This paper describes a low-complexity, high-efficiency lossy-to-lossless coding scheme for hyper-spectral images. Together with only a 2D wavelet transform on individual image components, the proposed scheme achieves coding performance similar to that achieved by a 3D transform strategy that adds one level of wavelet decomposition along the depth axis of the volume. The proposed schemes operates by means of a probability model for symbols emitted by the bit plane coding engine. This probability model captures the statistical behavior of hyper-spectral images with high precision. The proposed method is implemented in the core coding system of JPEG2000 reducing computational costs by 25%.
Indoor pseudo-ranging of mobile devices using ultrasonic chirps

In this demonstration, we show an indoor location tracking system that broadcasts ranging data to mobile phones using ultrasonic signals. The system capitalizes on the ability for many smart-phones to detect audio above the human hearing range. This approach provides enhanced ranging capabilities to mobile devices without adding to or modifying their hardware. In [1], we describe a modulation scheme based on rate-adaptive wide-band linear frequency modulated chirp pulses that can be transmitted from standard audio tweeters at just above the human hearing frequency range. Acoustic data transmissions (even outside of the human hearing range), typically introduce audible noises (clicks) due to the non-ideal impulse response of speakers. Our scheme is optimized to avoid these artifacts by using slowly changing power-levels and gradual shifts in frequency. Each speaker simultaneously transmits a uniquely identifiably signature that can be geolocated on a map. By then applying a time-difference-of-arrival (TDOA) pseudo-ranging technique the mobile devices can localize themselves without synchronizing with the broadcasting infrastructure. This design is not only scalable with respect to the number of transmitters and tracked devices, but also improves user privacy since the mobile device can compute its position locally.