Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical Use of Autonomous English Pronunciation Learning System for Japanese Students

We have developed an original CALL system designed to detect and diagnose English pronunciation errors in Japanese learners’ speech. We have begun using the system in an English class at Kyoto University in Kyoto, Japan. The class consists of approximately 40 students, and the students have practiced pronunciation using this system on four separate occasions. Sixty minutes was allocated for each practice session, providing a total of 9600 minutes of practice time per academic calender year. We have examined the recorded speech data and corresponding speech recognition results obtained for the first semester of the preceeding academic year.
Generalized sampling , infinite-dimensional compressed sensing , and semi-random sampling for asymptotically incoherent dictionaries

Recent developments in sampling in abstract Hilbert spaces have led to a new theory of compressed sensing for infinitedimensional signals. In this paper, we continue with this theme by introducing a new type of subsampling for infinite-dimensional sparse recovery problems, known as semi-random sampling. As we demonstrate, this allows for subsampling in problems which previously had not been amenable to more conventional compressed sensing tools. More specifically, semi-random sampling allows one to overcome the so-called incoherence barrier, which limits the potential for subsampling via standard random sampling techniques. The key to this improvement is a property known as asymptotic incoherence. In the final part of this paper we provide specific estimates for this property in several important cases, and illustrate via numerical example the benefit of semi-random sampling.
Feature Selection for Finger Knuckle Print-based Multimodal Biometric System

In this paper, feature level fusion of finger knuckle prints (FKP‟s) is implemented. To overcome the curse of dimensionality, feature selection using the triangular norms is proposed. There has been no effort on feature selection using the t-norms in the literature. In this paper we address the problem of feature selection on the finger knuckle print using the t-norms. An unknown parameter in t-norms is learnt using Reinforced Hybrid evolutionary technique. Feature level fusion is performed by combining the significant features of all FKP‟s. Results show an improvement in the accuracy when the features are selected by a divergence function derived from the new entropy function using t-norms on two pairs of training features taken at a time. Results of both identification and verification rates show a significant improvement in the performance with feature level fusion.
An exploration into the effects of L1 explanatory notes on L2 oral production: liberation of the mind or shackles of dependency?

Based on the premise that novice EAL learners have limited working memory resources to comprehend academic text, L1 explanatory notes were seen as a possible instrument to use in decreasing the cognitive demands of reading and increase the available working memory resources available for discussions. The hypotheses of this study were largely unsupported but from the data emerged a new hypothesis for second language acquisition; The Formality Hypothesis. This hypothesis posits that the presence or absence of the L1 signals various levels of formality in the learning task. Isolation of the L2 may therefore signal high levels of formality leading to the development of learners’ CALP (Cummins, 1979) whereas incorporation of the L1 into L2 input signals lower levels of formality leading to the development of learners’ BICS (Cummins, 1979).
Using semantic technologies to improve grid resource management

The effectiveness of complex Grid systems strongly depends on the availability, accuracy and relevance of information on all connected resources, their characteristics and state. An access to this information plays a very important role in any Grid system, providing necessary information for other Grid components and users. We believe that application of semantic technologies can improve Grid utilization and enhance user interaction with the system. In this paper we present our vision of the semantic Grid resource information service.
Six Sigma for Agile Teams

Purpose – This paper addresses the most common pain points in agile software development. Methodology/Approach – Many experts agree that agile software development methodologies make good use of best practices – but how can they be measured quantitatively? Agile literature provides surprises for software measurement professionals: for instance, time-consu ming size measurement approaches are proposed that produce unreliable and non-reproducible results. However, measurements for agile software d evelopment are readily available and less painful than in traditional envi ronments. In this paper a combination of techniques used in S ix Sigma for Software – Functional Size Measurement, Six Steps to Completio n, and Quality Function Deployment – is presented making agile dev elopment processes lean and measurable. We use Six Sigma transfer func tions to map development project controls onto process responses . Findings – Agile software development methodologies treat s oftware development as knowledge acquisition by embracing c hange. They better map reality than traditional approaches do. This fa cilitates measuring software processes for performance and quality. The findings are valid for all kind of lean softwar e development. Originality – The work originates from workshops at the PROFES 2010 conference in Limerick and the IWSM / MetriKon / Me nsura conference in Stuttgart 2010 and has not yet been published in an i ternational journal.
A Survey on Web based Interactive Information Retrieval 1

Information retrieval is a fundamental component of human information behavior. The ability to extract useful information from large electronic resources not only is one of the main activities of individuals online but is an essential skill for most professional groups and a means of achieving competitive advantage. Information retrieval or search plays an important role in a wide range of information management and electronic commerce tasks. In spite of the importance of information retrieval, search systems are often poorly designed from a human computer interaction perspective. The goal of this paper is to articulate some of the opportunities and challenges in designing and evaluating highly interactive information retrieval systems called WEB.
Sex differences in the toxicity of polyethylene glycol-coated gold nanoparticles in mice

Gold nanoparticles have received wide interest in disease diagnosis and therapy, but one of the important issues is their toxicological effects in vivo. Sex differences in the toxicity of gold nanoparticles are not clear. In this work, body weight, organ weight, hematology, and biochemistry were used to evaluate sex differences in immune response and liver and kidney damage. Pathology was used to observe the general toxicity of reproductive organs. The immune response was influenced significantly in female mice, with obvious changes in spleen and thymus index. Hematology results showed that male mice treated with 22.5 nm gold nanoparticles received more significant infection and inflammation than female mice. Meanwhile, the biochemistry results showed that 4.4 and 22.5 nm gold nanoparticles caused more significant liver damage in male mice than female mice, while 22.5, 29.3, and 36.1 nm gold nanoparticles caused more significant kidney damage in female mice than male mice. No significant toxicological response was found in the reproductive system for female or male mice. It was found that gold nanoparticles caused more serious liver toxicity and infection in male mice than female mice. These findings indicated that sex differences may be one of the important elements for in vivo toxicity of gold nanoparticles.
Symbolic Rule Representation in Neural Network Models

Symbolic knowledge extraction from mapping/extrapolating neural networks is presented in the paper. An algorithm to obtain crisp rules in the form of logical implications which roughly describe the neural network mapping is introduced. The number of extracted rules can be selected using an uncertainty margin parameter as well as by changing the precision of the soft quantization of the inputs. A fuzzy decision system for a medication dosage problem has been developed and tested to demonstrate this approach.
Future Generation Computer Systems

A Grid system is comprised of large sets of heterogeneous and geographically distributed resources that are aggregated as a virtual computing platform for executing large-scale scientific applications. As the number of resources in Grids increases rapidly, selecting appropriate resources for jobs has become a crucial issue. To avoid single point of failure and server overload problems, bidding provides an alternative means of resource selection in distributed systems. However, under the bidding model, the key challenge of resource selection is that there is no global information system to facilitate optimum decision-making; hence requesters can only obtain partial information revealed by resource providers. To address this problem, we propose a set of resource selection heuristics to minimize the turnaround time in anon-reserved bidding-based Grid environment, while consideringthe level of information about competing jobs revealed by providers. We also present the results of experiments conducted to evaluate the performance of the proposed heuristics.
De novo Transcriptome Assembly and the Putative Biosynthetic Pathway of Steroidal Sapogenins of Dioscorea composita

The plant Dioscorea composita has important applications in the medical and energy industries, and can be used for the extraction of steroidal sapogenins (important raw materials for the synthesis of steroidal drugs) and bioethanol production. However, little is known at the genetic level about how sapogenins are biosynthesized in this plant. Using Illumina deep sequencing, 62,341 unigenes were obtained by assembling its transcriptome, and 27,720 unigenes were annotated. Of these, 8,022 unigenes were mapped to 243 specific pathways, and 531 unigenes were identified to be involved in 24 secondary metabolic pathways. 35 enzymes, which were encoded by 79 unigenes, were related to the biosynthesis of steroidal sapogenins in this transcriptome database, covering almost all the nodes in the steroidal pathway. The results of real-time PCR experiments on ten related transcripts (HMGR, MK, SQLE, FPPS, DXS, CAS, HMED, CYP51, DHCR7, and DHCR24) indicated that sapogenins were mainly biosynthesized by the mevalonate pathway. The expression of these ten transcripts in the tuber and leaves was found to be much higher than in the stem. Also, expression in the shoots was low. The nucleotide and protein sequences and conserved domains of four related genes (HMGR, CAS, SQS, and SMT1) were highly conserved between D. composita and D. zingiberensis; but expression of these four genes is greater in D. composita. However, there is no expression of these key enzymes in potato and no steroidal sapogenins are synthesized.
Unconstrained mining of transcript data reveals increased alternative splicing complexity in the human transcriptome

Mining massive amounts of transcript data for alternative splicing information is paramount to help understand how the maturation of RNA regulates gene expression. We developed an algorithm to cluster transcript data to annotated genes to detect unannotated splice variants. A higher number of alternatively spliced genes and isoforms were found compared to other alternative splicing databases. Comparison of human and mouse data revealed a marked increase, in human, of splice variants incorporating novel exons and retained introns. Previously unannotated exons were validated by tiling array expression data and shown to correspond preferentially to novel first exons. Retained introns were validated by tiling array and deep sequencing data. The majority of retained introns were shorter than 500 nt and had weak polypyrimidine tracts. A subset of retained introns matching small RNAs and displaying a high GC content suggests a possible coordination between splicing regulation and production of noncoding RNAs. Conservation of unannotated exons and retained introns was higher in horse, dog and cow than in rodents, and 64% of exon sequences were only found in primates. This analysis highlights previously bypassed alternative splice variants, which may be crucial to deciphering more complex pathways of gene regulation in human.
The ATLAS Insertable B-Layer: from construction to operation

The ATLAS Insertable B-Layer (IBL) is the innermost layer of pixel detectors, and was installed in May 2014 at a radius of 3.3 cm from the beam axis, between the existing Pixel detector and a new smaller radius beam-pipe. The new detector, built to cope with high radiation and occupancy, is the first large scale application of 3D sensors and CMOS 130 nm technology. The IBL detector construction was completed within about two years (2012 – 2014), and the key features and challenges met during the IBL project are presented, as well as its commissioning and operational experience at the LHC.
Hardware design for the 32×32 IDCT of the HEVC video coding standard

This paper is focused in the inverse transforms defined in the video coding standard HEVC - High Efficiency Video Coding. The transforms stage is one of the innovations proposed by HEVC since it allows the use of the biggest number of transforms sizes (four) and also the biggest transform sizes (till 32×32) when compared with previous standards. The inverse DCT is performed by the video encoder and decoder as well. This paper presents an efficient hardware design for the 32×32 HEVC IDCT based on the separability principle. The hardware design was planned to reach real time processing (at least 30 frames per second) for high resolution videos, exploiting a high parallelism level (32 samples consumed per clock cycle). The architecture was also planned to reach a low latency and a low cost, then it was designed in a purely combinational way and using a multiplierless approach. The synthesis process was targeted to an Altera Stratix IV FPGA. The synthesis results show that the designed architecture is capable to process more than 30 QFHD frames (3840×2160 pixels) per second, with a latency of 33 clock cycles.
Novel Analysis of Transition Probabilities in Randomized K-Sat Algorithm

In this paper, we propose a new analysis for randomized 2-SAT and 3-SAT algorithms, and show that we could determine more precise boundaries for transition probability of Markov chain using Karnaugh map. In our analysis we will show the probability that the selected literal has been flipped correctly is so close to 3 2 and 7 4 , respectively for 2-SAT and 3-SAT with large number of variables. Then we will extend our result to k-SAT and show that both transition probability of Markov chain in randomized algorithm for kSAT approaches to 0.5. Finally we use this result to determine the probability and complexity of finding the satisfying assignment for randomized k-SAT algorithm. It will be shown that the probability of finding satisfying assignment and its complexity respectively are within a polynomial factor of ) 9272 . 0 ( n and
Kinetic Study on the CsXH3−X PW12O40/Fe-SiO2 Nanocatalyst for Biodiesel Production

The kinetic of the transesterification reaction over the CsXH3−XPW12O40/Fe-SiO2 catalyst prepared using sol-gel and impregnation procedures was investigated in different operational conditions. Experimental conditions were varied as follows: reaction temperature 323–333 K, methanol/oil molar ratio = 12/1, and the reaction time 0–240 min. The H3PW12O40 heteropolyacid has recently attracted significant attention due to its potential for application in the production of biodiesel, in either homogeneous or heterogeneous catalytic conditions. Although fatty acids esterification reaction has been known for some time, data is still scarce regarding kinetic and thermodynamic parameters, especially when catalyzed by nonconventional compounds such as H3PW12O40. Herein, a kinetic study utilizing Gc-Mas in situ allows for evaluating the effects of operation conditions on reaction rate and determining the activation energy along with thermodynamic constants including ΔG, ΔS, and ΔH. It indicated that the CsXH3−XPW12O40/Fe-SiO2 magnetic nanocatalyst can be easily recycled with a little loss by magnetic field and can maintain higher catalytic activity and higher recovery even after being used 5 times. Characterization of catalyst was carried out by using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), N2 adsorption-desorption measurements methods, thermal gravimetric analysis (TGA), and differential scanning calorimetry (DSC).
The Design and Implementation of a Virtual Cluster Management System

To fully utilize resources in computer center, virtualization techniques are getting popular and several systems are proposed for this purpose. However, they just provide set of virtualized nodes, not the ‘virtual clusters’; i.e., they are not able to install and configure middlewares and tools that makes ‘set of nodes’ into ‘cluster’. Another problem is that they just virtualize nodes, leaving storage resources and networks, which are equivalently essential for clusters, un-virtualized. we propose a virtual cluster management system which virtualizes compute resouces, as well as disk storage and network, and install and setup softwares that are essential for cluster operation, using Rocks, a cluster provisioning system. We vitualize storage with iSCSI and network with tagged VLAN.
Semantics of Knowledge Map Visualization

One of the major problems of knowledge mapping tools is rather static content or its slow generation. Our main objective is to provide a visualization of personal knowledge network as a part of knowledge mapping framework together with capturing of academic knowledge assets. We are going to use the Topic Map-based ontology and use its main advantages. Among its greatest positive features is that it supports free associations and it can be used as a system structure for building one’s personal work portfolio. Thus, creative thinking can be easily structured and set within a narrow context for better orientation when it is more suitable to organize documents and thoughts. The paper goes through the theoretical background of knowledge mapping, semantic standards, necessary model extensions, describes a use case and considers visualization specifics in relation to the user interface for suggested tool. Key–Words: Knowledge Map, Knowledge Visualization, Ontology
Angiotensin-converting enzyme gene and plasma protein level in Alzheimer's disease in Taiwanese.

BACKGROUND angiotensin-converting enzyme (ACE) gene insertion/deletion (indel) polymorphism is considered a biomarker for Alzheimer's disease (AD). However, the associations of ACE gene and protein level to AD are undetermined among Taiwanese. METHODS this study investigated 257 Taiwanese cases with AD and 137 ethnically matched controls using ACE gene indel genotype association methods with logistic regression adjusted for other variables. Besides, 65 out of 257 AD patients, 11 with D/D genotype, 28 with I/I genotype and 26 with I/D genotype were recruited. Their plasma ACE protein levels were measured by enzyme-linked immuno-sorbent assay and compared for their corresponding ACE gene indel polymorphism. RESULTS patients with ACE-I/I homozygote were less likely to be associated with AD, compared with both I/D and D/D (OR: 0.601; 95% CI: 0.372-0.969; P = 0.037), or only I/D genotype (OR: 0.584; 95% CI: 0.349-0.976; P = 0.040). There were significantly different plasma ACE protein levels among these three different genotype groups (P = 0.023). The I/I genotype group had significantly lower ACE plasma levels [114.79 ± 31.32 ng/ml (mean ± SD)], compared with D/D (164.07 ± 86.36 ng/ml; P = 0.010), but not I/D (141.45 ± 51.50 ng/ml; P = 0.064). CONCLUSION ACE-I/I homozygote corresponds to lower plasma ACE protein level and it is independently but less likely to be associated with AD. These findings signal the importance of ACE indel polymorphisms to their corresponding protein levels and to AD.
Interaural Intensity Difference Processing in Auditory Midbrain Neurons: Effects of a Transient Early Inhibitory Input

Interaural intensity differences (IIDs) are important cues that animals use to localize high-frequency sounds. Neurons sensitive to IIDs are excited by stimulation of one ear and inhibited by stimulation of the other ear, such that the response magnitude of the cell depends on the relative strengths of the two inputs, which in turn depends on the sound intensities at the ears. In the auditory midbrain nucleus, the inferior colliculus (IC), many IID-sensitive neurons have response functions that decline steeply from maximum to zero spikes as a function of IID. However, there are also many neurons with much more shallow response functions that do not decline to zero spikes. We present evidence from single-unit recordings in the Free-tailed bat’s IC that this partially inhibited response pattern is a result of the inhibitory input to these cells being very brief (∼2 msec). Of the cells sampled, 54 of 137 (40%) achieved partial inhibition when tested with 60 msec tones, and the inhibition to these 54 cells occurred primarily during the first few milliseconds of the excitatory response. Consequently, the initial component of the response was highly sensitive to IIDs, whereas the later component was primarily insensitive to IIDs. Each of the 54 “partially inhibited” cells was able to reach complete inhibition with very short stimuli, such as simulated bat echolocation calls that invoked only the initial, IID-sensitive component. Local application of inhibitory transmitter antagonists disabled the short inhibitory input, indicating that this response pattern is created within the IC.
Sensitivity and Accuracy Comparison of the Algorithms for the Abnormality Extraction of the MRI Slice Images of a GUI based Intelligent Diagnostic Imaging System

Intelligent diagnostic Imaging System (IDIS) is a developing imaging modality that is beginning to show promise of detecting and characterizing abnormalities of the brain. The abnormalities of the brain are due to Intracranial Neoplasm, Cerebral Infections and Inflammations, Stroke, Cerebral Aneurysms, Vascular Malformations, Central Nervous System Trauma and Neurodegenerative Disorders. The abnormalities are detected mostly by scanning the brain. MRI is an effective technique to find the abnormalities of the brain. This paper is concerned with the development of image processing tools and intelligent algorithms that will automatically detect the abnormalities of the brain and sensitivity and accuracy comparison of the Algorithms for the of abnormality extraction.