Miracle-dz/UniFAR-FTUs huggingface dataset:
A Memory Model for Scientific Algorithms on Graphics Processors

We present a memory model to analyze and improve the performance of scientific algorithms on graphics processing units (GPUs). Our memory model is based on texturing hardware, which uses a 2D block-based array representation to perform the underlying computations. We incorporate many characteristics of GPU architectures including smaller cache sizes, 2D block representations, and use the 3C's model to analyze the cache misses. Moreover, we present techniques to improve the performance of nested loops on GPUs. In order to demonstrate the effectiveness of our model, we highlight its performance on three memory-intensive scientific applications - sorting, fast Fourier transform and dense matrix-multiplication. In practice, our cache-efficient algorithms for these applications are able to achieve memory throughput of 30-50 GB/s on a NVIDIA 7900 GTX GPU. We also compare our results with prior GPU-based and CPU-based implementations on high-end processors. In practice, we are able to achieve 2-5x performance improvement
Steganalysis of MP3Stego

In this article, we propose a scheme for detecting hidden messages in compressed audio files produced by MP3Stego, as our literature search has found no previous work on successful steganalysis of MP3Stego. We extract moment statistical features on the second derivatives, as well as Markov transition features and neighboring joint density of the MDCT coefficients based on each specific frequency band on MPEG-1 Audio Layer 3. A support vector machine is applied to different feature sets for classification. Experimental results show that our approach is successful to discriminate MP3 covers and the steganograms generated by using MP3Stego.
Auto-scaled Bayesian browsing model in massive data

In the field of information retrieval, the method of building a click model by mining click logs to improve the effect of the search engine has been widely studied. And Bayesian Browsing Model (BBM), for the calculation of the operability and the effectiveness of the result, is widely used. However, when applied in engineering, especially for the situation of large scale data, this model will not perform properly. This problem is described analytically and shown by numerical experiments in this paper. For this problem, an auto-scaled BBM method is proposed. Experiments show that the new method solves the problem of original BBM, and have a better performance in terms of NDCG.
Text-Line Extraction Using a Convolution of Isotropic Gaussian Filter with a Set of Line Filters

Text-line extraction is a key task in document analysis. Methods based on an isotropic Gaussian filtering and ridge detection have shown good results. This paper describes performance improvements to these technique based on the use of a convolution of isotropic Gaussian filter with line filters. These new filter banks are motivated by a matched filter approach to text-lines and, in addition, require fewer operations to compute. We evaluate the performance of the new filter bank in combination with ridge detection on the public DFKI-I (CBDAR 2007 dewarping contest) dataset, which contains camera captured document images and demonstrate improvements in performance to previous state-of-the-art techniques.
A Novel Approach to improve Speech Intelligibility through Critical Band Enhancement

In communication systems involving speech, two different environments can be identified. These are categorized as far-end environment and the near-end environment. These different environments lead to different causes for reduction in speech intelligibility for the listener. By applying noise reduction techniques, the impact of acoustical noise sources in the far-end environment can be minimized. However, the effect of the noises present at the near-end environment cannot be negated because the listener perceives the speech and noise simultaneously. Thus near-end listening enhancement approach must be employed to enhance the speech signal to improve the speech intelligibility, when the near-end noise dominates. This work focuses on developing an approach to enhance the speech signal critical band-wise, after analyzing far-end speech and near-end (background) noise energy. Enhancedspeech signal intelligibility is assessed in terms of Speech Intelligibility Index (SII). The results obtained indicate an improvement in speech intelligibility, which can be confirmed through the values of SII.
Microcontact Printing of Proteins on Mixed Self-Assembled Monolayers

Microcontact printing of proteins from an elastomeric stamp has been demonstrated on a limited number of substrates. This work explores the generality of this method of patterning proteins by examining the role of surface wettability of both the substrate and the stamp in microcontact printing. The substrates used in this study consisted of two-component, mixed self-assembled monolayers (SAMs) of alkanethiols on gold presenting −CH3 and polar groups −COOH, −OH, or −(OCH2CH2)6OH. We found that protein adsorbed on a stamp successfully transfers onto a mixed SAM only when the mole fraction of polar functionality on the SAM exceeded a particular threshold. Although the mole fraction of polar groups required was different for each of the three types of mixed SAMs, the advancing water contact angles on these surfaces nearly coincided. Moreover, the minimum wettability of the SAM needed for the transfer of proteins decreased when the wettability of the stamp was decreased. Our findings suggest that the differenc.
Real Network Codes Sachin Katti Saurabh Shintre Sidharth Jaggi Dina Katabi Muriel Medard

Network coding has been shown to improve throughput and reliability in a variety of theoretical and practical settings. But it has had limited success in areas like sensor networks due to it’s two limitations. First, network codes are ”all-or-nothing” codes; the sink cannot decode any information unless it receives as many coded packets as the original number of packets. Second, sensor networks often measure physical signals which show a high degree of spatial correlation; present network coding techniques cannot perform in-network lossy compression to take advantage of the spatial correlation. This paper presents ”Real” Network Codes that are linear over real fields. We build on recent results from Compressed Sensing to develop new codes which can be decoded to get progressively more accurate approximations as more coded packets are received at the sink. Further, they can compress distributed correlated data inside the network without requiring that the nodes know how the data is correlated. Thus, Real Network Codes combine two exciting but hitherto separate areas, Network Coding and Compressed Sensing, allowing them to keep the advantages of network coding, but also make them capable of finding low distortion approximations with partial information and perform distributed compression of correlated data.
An Analytic Network Process Model of Trust in B2C E-Commerce

Online consumer trust in Business to Consumer (B2C) e-commerce trust has been viewed as a key differentiator that determines the success or failure of many companies conducting their business over the Internet. In order to explore the influence factor of consumer trust and their priority, and to look for the way to promote consumer trust, an Analytic Network Process (ANP) model is constructed in this paper. Based on three dimension of consumer trust, an index system is suggested. By analyzing the interaction of indicators, the ANP model can rationally calculate the weight of each indicator with Super Decisions software. From data analysis, the research comes to a conclusion that brand of the company, law and technique, scale of the company and reputation of the website have a great impact on consumer trust. And at the present stage, consumers take more attention to competence and integrity dimension than benevolence dimension. Besides, the model also shows that 360buy wins the most consumer trust compared with the other two selected B2C companies. The consistence with the reality proves that the ANP model can effectively find the priority of influence factors.
The home literacy environment of school‐aged children with autism spectrum disorders

For typically developing (TD) children, the home literacy environment (HLE) impacts reading competence, yet few studies have explored the HLE of children with autism spectrum disorders (ASD). We collected information about the HLE of children aged 7–13 with ASD and their TD peers via a parental questionnaire and examined whether there were any differences in home literacy practices. Subtle group differences emerged. Children with ASD and concomitant language disorder (autism language disorder [ALD]) were engaged in shared reading and reading discussion more frequently than were TD children and children with ASD and age-appropriate language skills (autism language normal [ALN]). However, both ALN and ALD children engaged in shared reading for a shorter duration than their TD peers. Across groups, frequency and duration of independent reading were positively associated with reading ability and attitude. Thus, home literacy practices appear to reflect child characteristics, and parents are well placed to facilitate their children's literacy development through encouragement and scaffolding.
Track 7. Buying and Selling Across countries: Marketing and Supply Chain Management Competitive Paper “A proposal for classifying export barriers: an empirical analysis of small and medium

One of the most important research questions in the international business literature is “why do some firms export more than others? ” An important explanation offered by previous research is the different perception of substantial obstacles (or barriers) to exporting (e.g., Bilkey and Tesar, 1977; Kedia and Chhokar, 1986; Sharkey, Lim and Kim, 1989). Since various authors in the last twenty-five years have addressed the study of export barriers without reaching agreement on classification (e.g., Rabino, 1980; Bauerschmidt, Sullivan and Gillespie, 1985; Kedia and Chhokar, 1986; Schroath and Korth, 1989; Yang, Leone and Alden, 1992; Leonidou, 1995; Hise, 2001; Da Silva, 2001; Westhead, Wright and Ucbasaran, 2002), our aim in this article is to review the main theoretical and empirical studies of export barriers, propose an integral classification for them and empirically check how they are perceived by small and medium-sized firms.
Interference-Based Topology Control Algorithm for Delay-Constrained Mobile Ad Hoc Networks

As the foundation of routing, topology control should minimize the interference among nodes, and increase the network capacity. With the development of mobile ad hoc networks (MANETs), there is a growing requirement of quality of service (QoS) in terms of delay. In order to meet the delay requirement, it is important to consider topology control in delay constrained environment, which is contradictory to the objective of minimizing interference. In this paper, we focus on the delay-constrained topology control problem, and take into account delay and interference jointly. We propose a cross-layer distributed algorithm called interference-based topology control algorithm for delay-constrained (ITCD) MANETs with considering both the interference constraint and the delay constraint, which is different from the previous work. The transmission delay, contention delay and the queuing delay are taken into account in the proposed algorithm. Moreover, the impact of node mobility on the interference-based topology control algorithm is investigated and the unstable links are removed from the topology. The simulation results show that ITCD can reduce the delay and improve the performance effectively in delay-constrained mobile ad hoc networks.
Enhancement of fibrinolysis with 40-kHz ultrasound.

BACKGROUND Ultrasound at frequencies of 0.5 to 1 MHz and intensities of > or =0.5 W/cm2 accelerates enzymatic fibrinolysis in vitro and in some animal models, but unacceptable tissue heating can occur, and limited penetration would restrict application to superficial vessels. Tissue heating is less and penetration better at lower frequencies, but little information is available regarding the effect of lower-frequency ultrasound on enzymatic fibrinolysis. We therefore examined the effect of 40-kHz ultrasound on fibrinolysis, tissue penetration, and heating. METHODS AND RESULTS 125I-fibrin-radiolabeled plasma clots in thin-walled tubes were overlaid with plasma containing tissue plasminogen activator (tPA) and exposed to ultrasound. Enzymatic fibrinolysis was measured as solubilization of radiolabel. Tissue attenuation and heating were examined in samples of porcine rib cage. Fibrinolysis was increased significantly in the presence of 40-kHz ultrasound at 0.25 W/cm2, reaching 39+/-7% and 93+/-11% at 60 minutes and 120 minutes, compared with 13+/-8% and 37+/-4% in the absence of ultrasound (P<0.0001). The acceleration of fibrinolysis increased at higher intensities. Attenuation of the ultrasound field was only 1.7+/-0.5 dB/cm through the intercostal space and 3.4+/-0.9 dB/cm through rib. Temperature increments in rib were <1 C/(W/cm2). CONCLUSIONS These findings indicate that 40-kHz ultrasound significantly accelerates enzymatic fibrinolysis at intensities of > or =0.25 W/cm2 with excellent tissue penetration and minimal heating. Externally applied 40-kHz ultrasound at low intensities is a potentially useful therapeutic adjunct to enzymatic fibrinolysis with sufficient tissue penetration for both peripheral vascular and coronary applications.
Fas ligand (gld)‐ and Fas (lpr)‐deficient mice do not show alterations in the extravasation or apoptosis of inflammatory neutrophils

Apoptosis of neutrophils plays a critical role in the resolution of acute inflammation. Neutrophils from human peripheral blood express Fas (CD95) and are sensitive to Fas ligand (FasL)/Fas‐mediated apoptosis. Mice carrying spontaneous mutations in the genes for fas ligand (B6/gld) or fas (B6/lpr) were used to assess the role of FasL/Fas in the kinetics and magnitude of neutrophil extravasation to the thioglycolate (TG)‐inflamed peritoneum and in the spontaneous apoptosis of TG‐elicited neutrophils. The results showed that TG‐elicited neutrophils (defined by flow cytometry as GR‐1/Ly‐6Ghi cells) from normal (B6) and B6/gld mice, but not from the Fas‐deficient B6/lpr mice, express high levels of Fas. The TG‐elicited neutrophil response began at 2 h, peaked at 4 h, and subsided by 24–48 h after TG administration in all three strains. However, the response was more prolonged in B6 mice, such that B6/gld and B6/lpr mice had fewer neutrophils at 6 h after TG administration than did B6 mice. Further studies showed that 4 h TG‐elicited neutrophils from B6, B6/gld and B6/lpr mice undergo apoptosis in vitro at similar rates (as assessed through flow cytometry by the decrease in forward angle light‐scatter and externalization of phosphatidylserine (PS; as detected by Annexin V‐FITC) that occur as neutrophils undergo apoptosis). Fas expression was down‐regulated on apoptotic neutrophils in conjunction with maximal PS externalization and decreased forward angle light‐scatter. Collectively, these findings suggest that FasL/Fas‐mediated apoptosis is not essential in regulating the lifespan of neutrophils during an acute inflammatory response. The abbreviated inflammatory response observed in FasL/Fas‐deficient mice is likely to be a secondary effect of the gld/lpr autoimmune/lymphoproliferative syndrome, and not a direct effect of FasL/Fas on the ability of inflammatory neutrophils to undergo apoptosis. J. Leukoc. Biol. 64: 373–383; 1998.
CONTACT, CONTEXT, AND COLLOCATION

This study uses a mixed-effects model to examine the acquisition of targetlike patterns of phonological variation by 17 English-speaking learners of French during study abroad in France. Naturalistic speech data provide evidence for the incipient acquisition of a phonological variable showing sociostylistic variation in native speaker speech: the elision of /l/ in third-person subject clitic pronouns (il vient [il vjɛ̃] ∼ [i vjɛ̃] “he is coming”). Speech data are compared and correlated with the results of a social network strength scale designed for the study abroad learning context. Results demonstrate that phonological variation patterns are acquired in a predictable order based on token type and collocation and that social networks with native speakers are statistically significant predictors of phonological variation patterns.
Protection against Autoimmunity in Nonlymphopenic Hosts by CD4+CD25+ Regulatory T Cells Is Antigen-Specific and Requires IL-10 and TGF-β1

CD4+CD25+ regulatory T cells (TReg) play a critical role in the control of autoimmunity. However, little is known about how TReg suppress self-reactive T cells in vivo, thus limiting the development of TReg-based therapy for treating autoimmune diseases. This is in large part due to the dependency on a state of lymphopenia to demonstrate TReg-mediated suppression in vivo and the unknown Ag specificity of TReg in most experimental models. Using a nonlymphopenic model of autoimmune pneumonitis and TReg with known Ag specificity, in this study we demonstrated that these TReg can actively suppress activation of self-reactive T cells and protect mice from fatal autoimmune pneumonitis. The protection required TReg with the same Ag specificity as the self-reactive T cells and depended on IL-10 and TGF-β. These results suggest that suppression of autoimmunity by TReg in vivo consists of multiple layers of regulation and advocate for a strategy involving Ag-specific TReg for treating organ-specific autoimmunity, because they do not cause generalized immune suppression.
A lower bound for disconnection by random interlacements

We consider the vacant set of random interlacements on $\mathbb{Z}^d$, with $d$ bigger or equal to 3, in the percolative regime. Motivated by the large deviation principles obtained in our recent work arXiv:1304.7477, we investigate the asymptotic behavior of the probability that a large body gets disconnected from infinity by the random interlacements. We derive an asymptotic lower bound, which brings into play tilted interlacements, and relates the problem to some of the large deviations of the occupation-time profile considered in arXiv:1304.7477.
Factors Influencing Bangkokian Adults’ Decision-Making in Choosing an English Language School

The purpose of this study was to determine the factors influencing Bangkokian adults aged 18 – 60 years old on decision-making in choosing an English language school. This study applied non-probability sampling as a sampling procedure. The questionnaires were distributed to by snowballing sampling. 400 questionnaires from both offline and online platforms were distributed. This study applied four statistical models including descriptive analysis, One-Way ANOVA, Pearson’s Correlation and multiple regression models. Most of the respondents were female. The majority of the respondents were aged between 29 - 39 years old. 76.8% of the respondents worked as private company employees and 60.5% of them worked at the operational level. Most of respondents have incomes between 15,001 baht and 40,000 baht per month. The results from multiple linear regressions analysis showed that product, promotion, people and process have positive influence on adult’s decision-making in choosing an English language school while age, occupation, job level, income, price, place, physical evidence do not have a positive influence on adults’ decision-making in choosing an English language school .
Dynamic Virtual Network Allocation for OpenFlow Based Cloud Resident Data Center

SUMMARY Dynamic virtual network allocation is a promising traffic control model for cloud resident data center which offers virtual data centers for customers from the provider’s substrate cloud. Unfortunately, dynamic virtual network allocation designed in the past was aimed to the Internet so it needs distributed control methods to scale with such a large network. The price for the scalability of the completely distributed control method at both virtual layer and substrate layer is the slow convergence of algorithm and the less stability of traffic. In this paper, we argue that the distributed controls in both virtual and substrate networks are not necessary for the cloud resident data center environment, because cloud resident data center uses centralized controller as the way to give network control features to customers. In fact, we can use the centralized algorithm in each virtual data center which is not very large network and the distributed algorithm is only needed in substrate network. Based on the specific properties of this model, we have used optimization theory to re-design the substrate algorithm for periodically re-adjusting virtual link capacity. Results from theoretical analysis, simulations, and experiments show that our algorithm has faster convergence time, simpler calculation and can make better use of the feedback information from virtual networks than the previous algorithm.
Post-fault operation of fault-tolerant inverters for PMSM drives

This paper considers post-fault operation of permanent-magnet synchronous motor drives equipped with a fault-tolerant inverter. In post-fault mode, the faulted phase is isolated and the neutral point is connected either to an additional inverter leg or to the midpoint of the DC bus. Different methods of controlling the neutral point voltage are presented and compared. Furthermore, operation without a position sensor (i.e., sensorless control) is considered and a modification to an estimator previously reported in the literature is proposed in order to take into account the effect of the asymmetry introduced due to the isolation of the faulted phase in post-fault mode. Simulations and experimental results are provided to support the theory and demonstrate the practical impact of the modifications proposed
Classification of Relapse Ovarian Cancer on MALDI-TOF Mass Spectrometry Data

Ovarian cancer recurs at the rate of 75% within a few months or several years later after therapy. Early recurrence, though responding better to treatment, is difficult to detect. Recently, high-resolution MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry has shown promise as a screening tool for detecting discriminatory protein patterns. The major computational obstacle in analyzing MALDI-TOF data is a large number of mass/charge peaks (a.k.a. features, data points). To tackle this problem, we have developed a multi-step strategy for data preprocessing and afterwards feature selection. The preprocessing is composed of binning, baseline correction, and normalization. For the preprocessed data, we propose a new feature subset selection method. Our scheme is applied to the analysis of ovarian cancer dataset to predict early relapse in ovarian cancer. To validate the performance of the proposed algorithm, experiments are performed in comparison with other feature selection and classification methods. We show that our proposed approach outperforms other algorithms
Fully integrated distributed power amplifier in CMOS technology, optimized for UWB transmitters

A power amplifier (PA) using the distributed amplifier technique for the ultra wideband (UWB) standard is presented. The amplifier is fabricated in a standard 0.13 /spl mu/m CMOS technology and comes with on-chip biasing circuitry and a non-distributed input stage. Measurement results are given for a chip-on-board module to take any influence of product assembly into account. It achieves a transmission coefficient S/sub 21/ = 17 dB, a corner frequency of f/sub c/ = 8 GHz and a 1 dB compression point of A/sub 1dB/ = 3.5 dBm. The output impedance is matched to 50 /spl Omega/ so that external matching circuitry can be omitted. With these features, it is customized to be integrated with other building blocks to a fully integrated CMOS UWB transmitter product.