Miracle-dz/UniFAR-FTUs huggingface dataset:
A new approach to estimate discretization error for multidisciplinary and multidirectional mesh refinement

Discretization error estimation in the system output of multidisciplinary simulations, where each disciplinary simulation has multidirectional mesh refinement, is considered in this paper. In such systems, the governing equations for each discipline are numerically solved by a different computational code, and each discipline has different mesh size parameters. The general case of three-dimensional steady state problems is considered in the current paper. Two aspects of discretization error, that are of interest in multidisciplinary analysis, are considered: disciplinary mesh sizes, and the mismatch of disciplinary meshes at the interface at which boundary conditions are exchanged. Two alternate representations for discretization error for the above specified generic case are presented: (1) ignoring mesh mismatch at the interface, and (2) considering mesh mismatch at the interface. Polynomial, rational function, and Gaussian process error models are used to represent the discretization error. The proposed error models are illustrated using a three-dimensional fluid-structure interaction problem of an aircraft wing using ANSYS multifield module.
Accelerating hyperspectral manifold learning using graphical processing units

Manifold learning has been widely studied in pattern recognition, image processing, and machine learning. A large number of nonlinear manifold learning methods have been proposed attempting to preserve a different geometrical property of the underlying manifold. In contrast, its application to hyperspectral images is computationally difficult due to the calculation of distances among spectral values in high-dimensional spaces. This paper compares feature extraction algorithms using isomap, Laplacian Eigenmaps, and local linear embedding in real hyperspectral images. They are implemented using massively parallel general purpose Graphical Processor Units (GPUs) to speed up computation. Their performance in classification of hyperspectral images and speed up of their computation is presented. Results using real and synthetic hyperspectral scenarios are presented. Additionally, a formulation including spatial information in these manifold learning algorithms is presented.
Caption Region Detection in Video Images by Improved Corner Detector

Caption region detection is significant for text segmentation and recognition in video images. In this paper, caption region detection includes the following three steps: text corner detection, candidate text region generation, non-text region elimination. Firstly, an improved Harris corner detection algorithm based on second difference, called sHarris, is proposed to detect text corners. sHarris detector is effective to detect text corners existing in video image. Secondly, morphologic operations are utilized to generate candidate text regions after text corner points are detected. Finally, non-text regions are eliminated from candidate text regions by some validation rules. In the end of this paper, experiments are used to analyze and evaluate the detection results of caption regions, which indicate the effectiveness of the proposed method.
Medical image compression using cubic spline interpolation for low bit-rate telemedicine applications

In this paper, a new medical image compression algorithm using cubic spline interpolation (CSI) is presented for telemedicine applications. The CSI is developed in order to subsample image data with minimal distortion and to achieve image compression. It has been shown in literatures that the CSI can be combined with the JPEG or JPEG2000 algorithm to develop a modified JPEG or JPEG2000 codec, which obtains a higher compression ratio and a better quality of reconstructed image than the standard JPEG and JPEG2000 codecs. This paper further makes use of the modified JPEG codec to medical image compression. Experimental results show that the proposed scheme can increase 25~30% compression ratio of original JPEG medical data compression system with similar visual quality. This system can reduce the loading of telecommunication networks and is quite suitable for low bit-rate telemedicine applications.
University Presses in the Twenty-first Century: The Potential Impact of Big Data and Predictive Analytics on Scholarly Book Marketing

The use of ‘big data’ and predictive analytics has transformed a sizeable number of industries, from insurance companies to print and e-book online retailers, and both the mass media and the scholarly literature have covered these developments. Online retailers have used big data systems to capture tremendous amounts of data about consumers and their purchases, which has enabled them to use predictive analytics and collaborative filtering systems to make purchase suggestions to consumers. Unfortunately, many university presses—even the largest presses with substantial endowments—have not been able to capitalize on the formidable marketing assets offered by big data and predictive analytics. In this article, the authors review the published literature and significant data sets, and present suggestions for the Canadian and US university press community to launch a non-profit direct-to-consumer Web site generating continuous-time sales and marketing data.
Vitamin D Abnormalities: More Common in US Children with T1D than in Healthy Children

Background: Pediatric patients with type 1 diabetes (T1D) have increased risk for low bone mineral density, which may be due in part to low 25-hydroxyvitamin D levels. Vitamin D levels are influenced by sunlight exposure and thus display geographical variation. We hypothesize that the prevalence of 25-hydroxyvitamin D deficiency ( duration, HbA1c, or insulin dose/kg and 25-hydroxyvitamin D levels. Conclusions: There is an increased prevalence of 25-hydroxyvitamin D deficiency and insufficiency in US. children with T1D compared with geographically similar children without diabetes. Further research is needed to determine whether decreased serum 25-hydroxyvitamin D can be alleviated via dietary or behavioral modifications in this population.
Design tradeoffs for software-managed TLBs

An increasing number of architectures provide virtual memory support through software-managed TLBs. However, software management can impose considerable penalties, which are highly dependent on the operating system's structure and its use of virtual memory. This work explores software-managed TLB design tradeoffs and their interaction with a range of operating systems including monolithic and microkernel designs. Through hardware monitoring and simulations, we explore TLB performance for benchmarks running on a MIPS R2000-based workstation running Ultrix, OSF/1, and three versions of mach 3.0. Results: New operating systems are changing the relative frequency of different types of TLB misses, some of which may not be efficiently handled by current architectures. For the same application binaries, total TLB service time varies by as much as an order of magnitude under different operating systems. Reducing the handling cost for kernel TLB misses reduces total TLB service time up to 40%. For TLBs between 32 and 128 slots, each doubling of the TLB size reduces total TLB service time up to 50%.
Java in a Nutshell

The sixth edition of Java in a Nutshell helps experienced Java programmers get the most out of Java 7 and 8, but its also a learning path for new developers. With examples rewritten to take full advantage of modern Java APIs and development best practices, this fully updated book brings you up to date and gets you ready to develop Java applications for the future.Learn how lambda expressions make your programs shorter, and easier to write and understandExplore Nashorn, the brand new implementation of Javascript on the Java Virtual MachineStart using the new I/O APIs to make your code cleaner, shorter, and saferUnderstand Javas concurrency model and learn how to write multithreaded code with confidence
Kobold: a neural coprocessor for backpropagation with online learning

In this paper we propose an architecture of a neural coprocessor for on-board learning standard backpropagation. The hardware implementation works as a neural coprocessor connected to a personal computer by a special asynchronous interface. The coprocessor consists of several equal submodules representing one column of the neural net. So the architecture allows to compose any size of neural net depending on the specific application and, additionally, recurrency is allowed. Kobold speeds up the performance in contrast to earlier hardware implementations because of its new specialized control and communication structure. The subprocessors communicate asynchronously and locally with their nearest neighbours and synchronously by a global bus. The operations are controlled by dataflow. This means, a neuron calculates its weighted sum as soon as all inputs are available.
A Survey of the Index Schemes based on Flash Memory

Since a NAND-flash memory is able to store mass data in a small sized chip and consumes low power, it is exploited on various hand-held devices, such as a smart phone and a sensor node, etc. To process efficiently mass data stored in the flash memory, it is required to use an index. However, since the write operation of the flash memory is slower than the read operation and an overwrite operation is not supported, the usage of existing index schemes degrades the performance of the index. In this paper, we survey the previous researches of index schemes for the flash memory and classify the researches by the methods to solve problems. We also present the performance factor to be considered when we design the index scheme on the flash memory.
An Experimental Study on the English Vowel Lengths Using the Praat Software Program

The purpose of this experimental study is to investigate and compare the vowel lengths of the English diphthongs, /e? / and /a? /, and the front low vowel /ae/ among English-speaking natives with Korean college students using the Praat software program. To do this English sentences were uttered and recorded by twelve subjects, six Korean subjects and six English-speaking native subjects. All the subjects are female and their age ranges from 23 to 35. Acoustic features(duration) were measured from a sound spectrogram with the help of the Praat software program and analyzed through statistical analysis. Results showed that the vowel lengths of the English diphthongs and the front low vowel between native English speakers and Korean collegians were different. In the pronunciation of the diphthongs /e? / and /a? /, Korean subjects pronounced longer than native subjects did, but the difference was not significant. However, in the pronunciation of the English front low vowel /ae/, native subjects pronounced significantly longer than Korean subjects did. From the data of the overall sum of words and vowels between the two subject groups, we were able to find out that the differences of lengths of both the three words and the two diphthongs /e? / and /a? / were not significant, but those of / ae / were significant.
Discrete design method of transverse gradient coils for MRI

A method is presented for designing transverse gradient coils for mag- netic resonance imaging. This method is based on the set of Z intercepts of the coils' current patterns with the z axis in the unfolded z-arc plane. We show that the set of Z intercepts combined with a description of the coil topology, as defined by the necessary azimuthal harmonics, the axial symmetry and the directions of the current flow, is suffi- cient for designing a practical gradient coil. The theory and design of transverse coils with Z intercepts is illustrated with examples of a symmetric unshielded insert gradient coil for small animal imaging, a human head unshielded symmetric insert gradient coil with shoulder cutouts, and a self-shielded short whole-body gradient coil. The Z-inter- cept method has also been extended to design higher-order transverse shims. This is illustrated with the design of a ZX shim. Additional design capabilities of the Z-intercepts method are also discussed. 2007 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 31B: 95-115, 2007
Compressed sensing techniques for arbitrary frequency-sparse signals in structural health monitoring

Structural health monitoring requires collection of large number sample data and sometimes high frequent vibration data for detecting the damage of structures. The expensive cost for collecting the data is a big challenge. The recent proposed Compressive Sensing method enables a potentially large reduction in the sampling, and it is a way to meet the challenge. The Compressed Sensing theory requires sparse signal, meaning that the signals can be well-approximated as a linear combination of just a few elements from a known discrete basis or dictionary. The signal of structure vibration can be decomposed into a few sinusoid linear combinations in the DFT domain. Unfortunately, in most cases, the frequencies of decomposed sinusoid are arbitrary in that domain, which may not lie precisely on the discrete DFT basis or dictionary. In this case, the signal will lost its sparsity, and that makes recovery performance degrades significantly. One way to improve the sparsity of the signal is to increase the size of the dictionary, but there exists a tradeoff: the closely-spaced DFT dictionary will increase the coherence between the elements in the dictionary, which in turn decreases recovery performance. In this work we introduce three approaches for arbitrary frequency signals recovery. The first approach is the continuous basis pursuit (CBP), which reconstructs a continuous basis by introducing interpolation steps. The second approach is a semidefinite programming (SDP), which searches the sparest signal on continuous basis without establish any dictionary, enabling a very high recovery precision. The third approach is spectral iterative hard threshold (SIHT), which is based on redundant DFT dictionary and a restricted union-of-subspaces signal model, inhibiting closely spaced sinusoids. The three approaches are studied by numerical simulation. Structure vibration signal is simulated by a finite element model, and compressed measurements of the signal are taken to perform signal recovery. Comparison of the performance of the three approaches is made, and future work on design of compressive sampling testing system for vibration signal is proposed.
Non-invasive glucose monitoring using impedance spectroscopy

Continuous blood glucose monitoring provides maximal information about shifting blood glucose levels and facilitates optimal treatment decisions for the diabetic patient, by identifying and preventing unwanted episodes of hypoglycaemia and hyperglycaemia. Non-invasive techniques provide comfort and easier accessibility to the user in comparison to the invasive blood glucose monitoring systems. This paper presents a novel approach towards non-invasive glucose monitoring via impedance spectroscopy. Impedance spectroscopy refers to measurement of dielectric properties of the medium with change in frequency. Changing blood glucose levels affects its dielectric characteristics which changes blood impedance. Blood is modelled in the form of Ringer’s solution and tested using Ag/AgCl reference electrodes. Four-electrode impedance measurement is used to assess impedance changes as a function of frequency. With changes in glucose concentration in the solution, subsequent readings of impedance are recorded and the correlations provide a proof of change in blood impedance with glucose level fluctuations.
A study of web-based library classification schemes

The study deals with web-based library classification schemes. In the emerging digital paradigm, the library classification schemes sparked dynamically print into web in the beginning of 21st century. Web-based library classification schemes are completely different from traditional classification schemes. The study discusses three web-based schemes viz WebDewey 2.0, UDC (universal decimal classification) online and classification web. WebDewey 2.0 is a Web-based product of DDC 23rd ed., UDC online is of UDC and classification web of LCC(Library of Congress Classification). These are constantly updated, revised and up-to date web-based library classification schemes. This study is significant in that it provided a description of current trends of library classification schemes. Investigative method is used to identify web-based library classification schemes. The databases have been accessed through trial accounts of their official websites. This study mainly compares the aspects of WebDewey 2.0, UDC online, and classification web. It concludes that DDC (Dewey Decimal Classification) is the most updated library classification scheme in the world. Key words: Web-based library classification schemes, WebDewey 2.0, Universal Decimal Classification online, classification web.
CELP coding at 4.0 kb/sec and below: improvements to FS-1016

While code excited linear prediction (CELP) speech coders can produce high levels of output speech quality at rates near 4 kb/s, they may not be suitable for toll quality communications. The authors propose several modifications to improve the quality of the standard CELP algorithm while simultaneously reducing its transmission rate. The modifications include a multimode excitation that increases the convergence rate of the adaptive (pitch) codebook. A low-complexity spectral vector quantization algorithm is also developed that reduces the coding rate and decreases the spectral distortion. SNR improvements of 2 dB and a significant reduction in perceptual artifacts have been observed. <<ETX>>
An efficient CPLD technology mapping under the time constraint

In this paper, we proposed a new technology mapping algorithm for CPLD under a time constraint (TMCPLD). In our technology mapping algorithm, a given Boolean network generated a feasible cluster. The generated feasible cluster creates clusters with minimum area under the time constraint. A covered Boolean network is transformed to a Boolean equation. The transformed equations are reconstructed in order to fit the architecture of a selected target CPLD using collapsing and bin-packing. To demonstrate the efficiency of our approach, we applied our algorithm to MCNC benchmarks and compared the results with those of the existing algorithms. The experimental results show that our approach is better than any of the existing algorithms in the number of logic blocks.
A novel deregistration strategy for mobile networks

In this paper a novel deregistration scheme-lazy deregistration-for mobile systems is proposed. In the proposed scheme, instead of sending a registration cancellation message to the old visitor location register (VLR) right after each registration, the home location register (HLR) keeps the identification of the mobile terminal (MT) in a list associated with the old VLR. When the next registration from the old VLR arrives, the MT identifications maintained in the list are sent to the old VLR along with the registration acknowledgement message. The old VLR then deregisters these MTs that have left its service area since the last registration from this VLR. Compared to the standard scheme deployed in existing systems, the proposed scheme greatly reduces both the signaling traffic and the database access rate due to deregistration. Compared to other proposed deregistration schemes, in our scheme no valid records in the VLR are deleted and no storage increase in the VLR is required.
Qualitative Comparative Analysis and Analytical Induction

This article bridges two research traditions, analytical induction (AI) and qualitative comparative analysis (QCA) in the context of a study of early welfare state formation. First, the article differentiates classical AI from neoanalytical induction (NAI), tracing the latter to the former and identifying some problems with NAI. Next, it outlines QCA and identifies some problems with it. Third, it sketches two bridges, along with solutions that they offer for some limitations of NAI and QCA. One bridge links NAI's method, in essence a logical implementation of the idea of the working hypothesis, to QCA's powerful Boolean technology. The second bridge joins AI's stress on the reformulation of hypotheses in the face of negative evidence to QCA's capacities for complex inductive and logical specifications of the relations of explanatory to dependent variables. Following that, the article summarizes portions of a study of early 20th-century welfare state formation and uses them to illustrate the bridges. It concludes with a discussion of the analytical promise of a variant of QCA that stresses theory building in the AI tradition.
Large‐video‐display‐format conversion

Abstract— High‐quality video‐format converters apply motion estimation and motion compensation to prevent jitter resulting from picture‐rate conversion, and aliasing due to de‐interlacing, in sequences with motion. Although initially considered as too expensive, high‐quality conversion is now economically feasible, and since 1995 has been available in consumer television ICs. This paper addresses the issues in format conversion and shows recent progress, introducing a new high‐quality video‐format‐conversion IC for consumer applications.
Parallel subtitle corpora and their applications in machine translation and translatology

SUMAT is a project funded through the EU ICT Policy Support Programme (2011–2014). It involves four subtitling companies (InVision, DDS, Titelbild, VSI) and five technical partners (ALS, ATC, TextShuttle, University of Maribor, Vicomtech). For the SUMAT project, translated subtitles for seven language pairs have been collected. Four subtitling companies have contributed to this effort, which has so far resulted in collections numbering between 200,000 and 2 million subtitles per language pair. This paper describes the process of converting, classifying and aligning the subtitles. Conversion to a common text format and cross-language alignment were automatically done, using specially built converters, whilst classifying the subtitles according to text genre was a manual process, performed by the teams harvesting the subtitles.The resulting subtitle corpora are perfectly suited for various applications. The focus of the SUMAT project is to use them as training material for statistical machine translation systems, and this paper will report on the initial experiences with some of the language pairs. In addition, the parallel corpora may serve as input data for parallel concordancing systems. As part of the project, a small prototype has been built which shows how word-aligned parallel subtitles offer new insights for translation science.
Recent Advances in Radical Fluorination

Abstract The importance of fluorinated compounds in pharmaceutical, agrochemical, and material chemistry has led to the development of numerous methods for electrophilic and nucleophilic fluorination. Radical fluorination represents an interesting complementary approach, but it had been limited due to the paucity of selective radical fluorinating agents. The recent uncovering of easier to handle atomic fluorine sources has led to significant advances in radical fluorination in the past few years. This review presents the newly developed methods for fluorination involving radicals as reactive intermediates. 1 Introduction 2 Atomic Fluorine Sources 2.1 Fluorine as a Selective Radical Fluorinating Agent 2.2 Fluoroxy Reagents 2.3 XeF2 2.4 N–F Reagents as Atomic Fluorine Sources 3 Methodologies for Radical Fluorination 3.1 Decarboxylative Fluorination 3.2 Fluorination of Alkenes 3.3 Fluorination of Boronic Acid Derivatives 3.4 C(sp3)–H Fluorination 3.5 C–C Bond Activation 4 Conclusion