Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the Usefulness of Generalized Word Representations in SMT

We investigate the use of generalized representations (POS, morphological analysis and word clusters) in phrase-based models and the N-gram-based Operation Sequence Model (OSM). Our integration enables these models to learn richer lexical and reordering patterns, consider wider contextual information and generalize better in sparse data conditions. When interpolating generalized OSM models on the standard IWSLT and WMT tasks we observed improvements of up to +1.35 on the English-to-German task and +0.63 for the German-to-English task. Using automatically generated word classes in standard phrase-based models and the OSM models yields an average improvement of +0.80 across 8 language pairs on the IWSLT shared task.
Efficient extraction of human motion volumes by tracking

We present an automatic and efficient method to extract spatio-temporal human volumes from video, which combines top-down model-based and bottom-up appearance-based approaches. From the top-down perspective, our algorithm applies shape priors probabilistically to candidate image regions obtained by pedestrian detection, and provides accurate estimates of the human body areas which serve as important constraints for bottom-up processing. Temporal propagation of the identified region is performed with bottom-up cues in an efficient level-set framework, which takes advantage of the sparse top-down information that is available. Our formulation also optimizes the extracted human volume across frames through belief propagation and provides temporally coherent human regions. We demonstrate the ability of our method to extract human body regions efficiently and automatically from a large, challenging dataset collected from YouTube.
Convergence of the Mass-Transport Steepest Descent Scheme for the Subcritical Patlak-Keller-Segel Model

Variational steepest descent approximation schemes for the modified Patlak-Keller-Segel equation with a logarithmic interaction kernel in any dimension are considered. We prove the convergence of the suitably interpolated in time implicit Euler scheme, defined in terms of the Euclidean Wasserstein distance, associated with this equation for subcritical masses. As a consequence, we recover the recent result about the global in time existence of weak solutions to the modified Patlak-Keller-Segel equation for the logarithmic interaction kernel in any dimension in the subcritical case. Moreover, we show how this method performs numerically in dimension one. In this particular case, this numerical scheme corresponds to a standard implicit Euler method for the pseudoinverse of the cumulative distribution function. We demonstrate its capabilities to reproduce the blow-up of solutions for supercritical masses easily without the need of mesh-refinement.
Study & Analysis Of Cloud Erp Solutions Dr

Cloud Computing is a buzzword in computer science it has gained momentum in the last decade. Research work shows that many software companies is evaluating the promised advantages and considering making use of cloud services. It is based on rent and sharing model. In this paper I present my view and analysis for cloud computing and its importance for the operation of ERP systems and SMBE (Small and Medium Business Enterprises). As per my opinion the phenomenon of cloud computing could lead to a decisive change in the way business software is deployed in companies. My reference outline contains the three basic levels (IaaS, PaaS, SaaS) and explains the meaning of public, private and hybrid clouds. The three levels of cloud computing and their impact on ERP systems operation are discussed. From the analysis I identify areas for further research and sketch a research agenda.
Interactive surveillance event detection at TRECVid2012

This demonstration shows the integration of video analysis and search tools to facilitate the interactive retrieval of video segments depicting specific activities from surveillance footage. The implementation was developed by members of the SAVASA project for participation in the interactive surveillance event detection (SED) task of TRECVid 2012. This year, for the first time, the purpose of the interactive SED task was to evaluate systems' ability to support users in identifying video segments that depict a specific activity (event) in a large collection of surveillance video footage. Project partners worked together to analyse video and provide a query interface enabling users to search and identify matching video segments. The collaborative integration of components from multiple partners and the participation of end user partners in evaluating the system are the novel aspects of this work.
Finite Data Performance Analysis of Lcmv Antenna Array Beamformers with and Without Signal Blocking

A linearly constrained minimum variance (LCMV) antenna array beamformer using flnite data samples sufiers from slow convergence when the received array data contain the desired signal. It has been reported that signal blocking techniques speed up the convergence rate and increase the robustness of LCMV antenna array beamformers. However, the reason of this improvement has not been explored in the literature. Moreover, the existing formulas for the output signal-to-interference-plus-noise ratio (SINR) are too rough to realize the in∞uence of signal blocking techniques on the performance. In this paper, we show that the correlation due to flnite samples causes the redundant component (termed as the cross weight) embedded in the weight vector of a LCMV beamformer even if the signal sources and noise are independent. The cross power results from the cross weight degrades the performance when the sample size is small. In contrast, the cross weight and cross power can be fully eliminated when a signal blocking technique is used. The theoretical results presented in this paper provide a comprehensive description on the efiectiveness and the price of using signal blocking for antenna array beamforming. Simulation results are also given for conflrming the validity of the theoretical results.
EJTCP: Enhanced Jitter-based TCP for Wireless Broadband Networks

TCP is one of the most important and widely adopted transport protocols at present. With the advent of advanced wireless broadband technologies, TCP must be properly tuned and enhanced from traditional networks made up of purely wired links to wiredcum-wireless networks. As a result of high bit error rate (BER) in wireless links, TCP halves down its congestion window unnecessarily caused by random packet loss event continuously, and the performance is significantly degraded in wireless networks. The problem about differentiating congestion loss and random loss has been investigated recently by a number of wireless TCP solutions, such as JTCP (jitter-based TCP). While the existing solutions are accomplishing fundamental efforts to distinguish packet losses, some unavoidable events may occur to make TCP timeout frequently. Hence, we amend JTCP scheme to design a smooth transmission scheme to increase the correctness of loss distinction and avoid burst transmission. Besides, a novel channel aware scheme is designed to deal with dynamic modulation changing in 802.16 Wireless MAN. The experimental results show that our scheme, enhanced JTCP (EJTCP), unrolls significantly better performance than other algorithms over wired-cum-wireless network.
Language independent rule based classification of printed & handwritten text

Handwriting in data entry forms/documents usually indicates user's filled information that should be treated differently from the printed text. In Arab world, these filled information are normally in English or Arabic. Secondly, classification approaches are quite different for machine printed and script. Therefore, prior to segmentation & classification, text distinction into Printed & script entries is mandatory. In this research, the dilemma of the language independent text distinction in multilingual data entry forms is addressed. Our main focus is to distinguish the machine printed text and script in multilingual data entry forms that are language independent. The proposed approach explore new statistical and structural features of text lines to classify them into separate categories. Accordingly a set of classification rules is derived to explicitly differentiate machine printed and handwritten entries, written in any language. Additional, novelty of the proposed approach is that no training/training data is required rather text is discriminated on basis of simple rules. Promising experimental results with 90 % accuracy exhibit that proposed approach is simple and robust. Finally, the scheme is independent of language, style, size, and fonts that commonly co-exist in multilingual data entry forms.
Relation between modifiable lifestyle factors and lifetime risk of heart failure.

CONTEXT The lifetime risk of heart failure at age 40 years is approximately 1 in 5 in the general population; however, little is known about the association between modifiable lifestyle factors and the remaining lifetime risk of heart failure. OBJECTIVE To examine the association between modifiable lifestyle factors and the lifetime risk of heart failure in a large cohort of men. DESIGN, SETTING, AND PARTICIPANTS Prospective cohort study using data from 20,900 men (mean age at baseline, 53.6 years) from the Physicians' Health Study I (1982-2008) who were apparently healthy at baseline. Six modifiable lifestyle factors were assessed: body weight, smoking, exercise, alcohol intake, consumption of breakfast cereals, and consumption of fruits and vegetables. MAIN OUTCOME MEASURE Lifetime risk of heart failure. RESULTS During a mean follow-up of 22.4 years, 1200 men developed heart failure. Overall, the lifetime risk of heart failure was 13.8% (95% confidence interval [CI], 12.9%-14.7%) at age 40 years. Lifetime risk remained constant in men who survived free of heart failure through age 70 years and reached 10.6% (95% CI, 9.4%-11.7%) at age 80 years. Lifetime risk of heart failure was higher in men with hypertension than in those without hypertension. Healthy lifestyle habits (normal body weight, not smoking, regular exercise, moderate alcohol intake, consumption of breakfast cereals, and consumption of fruits and vegetables) were individually and jointly associated with a lower lifetime risk of heart failure, with the highest risk in men adhering to none of the 6 lifestyle factors (21.2%; 95% CI, 16.8%-25.6%) and the lowest risk in men adhering to 4 or more desirable factors (10.1%; 95% CI, 7.9%-12.3%). CONCLUSION In this cohort of apparently healthy men, adherence to healthy lifestyle factors is associated with a lower lifetime risk of heart failure.
The WRKY70 Transcription Factor: A Node of Convergence for Jasmonate-Mediated and Salicylate-Mediated Signals in Plant Defense On-line version contains Web-only data.

Cross talk between salicylic acid (SA)– and jasmonic acid (JA)–dependent defense signaling has been well documented in plants, but how this cross talk is executed and the components involved remain to be elucidated. We demonstrate that the plant-specific transcription factor WRKY70 is a common component in SA- and JA-mediated signal pathways. Expression of WRKY70 is activated by SA and repressed by JA. The early induction of WRKY70 by SA is NPR1-independent, but functional NPR1 is required for full-scale induction. Epistasis analysis suggested that WRKY70 is downstream of NPR1 in an SA-dependent signal pathway. Modulation of WRKY70 transcript levels by constitutive overexpression increases resistance to virulent pathogens and results in constitutive expression of SA-induced pathogenesis-related genes. Conversely, antisense suppression of WRKY70 activates JA-responsive/COI1-dependent genes. The effect of WRKY70 is not caused by subsequent changes in SA or JA levels. We suggest that WRKY70 acts as an activator of SA-induced genes and a repressor of JA-responsive genes, integrating signals from these mutually antagonistic pathways.
Exact coherent structures in pipe flow: travelling wave solutions

Three-dimensional travelling wave solutions are found for pressure-driven fluid flow through a circular pipe. They consist of three well-defined flow features – streamwise rolls and streaks which dominate and streamwise-dependent wavy structures. The travelling waves can be classified by the $m$-fold rotational symmetry they possess about the pipe axis with $m\,{=}\,1,2,3,4,5$ and $6$ solutions identified. All are born out of saddle-node bifurcations with the lowest corresponding to $m\,{=}\,3$ and traceable down to a Reynolds number (based on the mean velocity) of 1251. The new solutions are found using a constructive continuation procedure based upon key physical mechanisms thought generic to wall-bounded shear flows. It is believed that the appearance of these new alternative solutions to the governing equations as the Reynolds number is increased is a necessary precursor to the turbulent transition observed in experiments.
Bounding the extrapolated correlation energy using Padé approximants

We present a rigorous strategy, based on Stieltjes series and Pade approximants, to obtain suitable bounds for extrapolation of the quantum chemical correlation energy. Computational tests are performed for the second-order Moller-Plesset (MP2) correlation energy, and the bounds obtained are tight enough for practical calculational purposes: The associated error in most cases is much less than 1 kcal/mol. The bounds presented here are also shown to be rigorous for functional forms that represent a wide variety of methods in quantum chemistry and hence may be used in extrapolating a wide range of expressions, some of them yielding significant computational advantages compared to traditional techniques. c 2000 John Wiley & Sons, Inc. Int J Quantum Chem 79: 222-234, 2000
Extension of the critical path tracing algorithm

Critical path tracing (CPT) is an approximate algorithm used for fast fault simulation, as part of test generation algorithms. It partitions the circuit to be simulated into fanout free regions in order to simplify decisions regarding the propagation of logic signal changes through the circuit. Presented are concepts that result in faster decision making than in CPT for many combinations of input changes. After true value simulation, improved critical path tracing (ICPT) does a more extensive classification of lines than CPT does. This finer classification determines propagation of fault effects without fault simulation in many cases where CPT may require fault simulation. The increase in execution time to incorporate the improvements is insignificant compared to the savings in simulation time for many input vectors. <<ETX>>
Gps-Copilot: Real-Time Location Based Adaptive Cruise Control System Involving Driver Health And Head Distraction Analysis

Adaptive Cruise Control (ACC) is an electronic system that allows the vehicle to slow while approaching another vehicle and accelerate again to the preset speed when traffic is cleared. It also warns the driver and/or applies brake support if there is a high risk of a collision. The project aim is to design a GPS equipped ACC system that (apart from performing normal ACC functions) slows down the vehicle intelligently when it enters speed restricted zones such as schools and colleges. It is also capable of detecting the speed breakers ahead and controls the vehicle dynamically according to the speed limit set for that part of the road. The system also continuously monitors driver distraction and driver health condition and brings the vehicle under ACC control if the need arises. There are a variety of ways in which drivers can get distracted while driving, for example looking sideways, talking over a mobile phone etc. Driver head movement indicates if he is distracted or not. Our system is capable of sensing this. Another major issue is drivers in city buses or cars who are aged above 40 are at a higher risk of heart attack or similar heart related problems. A heart attack for a city bus driver while driving is fatal not only to him but also for the passengers. Heart rate is a vital symptom for identifying this condition. Our system senses the heart rate of the driver. In real-world scenario this system should need to perform the operation within some timing deadline and must be extremely responsive or the result is fatal. Hence the system utilizes the services of a RTOS (Real-Time Operating System). GPS aided ACC with Driver Status Monitoring can be implemented in all types of vehicles where safety will be given first priority and has the potential to become a standard part of any future vehicle.
Alcoholism and other socio-demographic risk factors for adverse TB-drug reactions and unsuccessful tuberculosis treatment – data from ten years’ observation at the Regional Centre of Pulmonology, Bydgoszcz, Poland

Background Tuberculosis (TB) is one of the most dangerous infectious diseases and has one of the highest mortality rates. For decades a strong association has been evident between certain socio-economic factors and TB adverse events and failure of treatment, yet there is a limited quantity of literature available on this subject, especially in the Polish literature. Material/Methods We examined epidemiological data from 2025 TB patients treated at the Regional Centre of Pulmonology in Bydgoszcz, Poland between 2001 and 2010. This article focuses on the association between all forms of unsuccessful TB treatment outcomes or adverse drug reaction (ADR) and socio-demographic characteristics, condition on admission, and other biological, clinical, social, and healthcare access factors. Results The rate of TB-ADR during hospitalization was 38.9%. Multivariate logistic regression analysis showed that age (P<0.001) and alcohol abuse (P=0.007) were independently associated with the occurrence of TB-ADR. The rate of unsuccessful TB treatment was 10.5%. After adjusting for confounding variables, age (P<0.001), alcohol abuse (P=0.002), and education (P=0.01) were significantly associated with unsuccessful treatment. Smoking did not have any significant influence on occurrence of either TB-ADR during hospitalization or unsuccessful treatment. Conclusions Among our TB patients treated between 2001 and 2010, alcohol abuse significantly worsened the treatment outcome. This information will be crucial in developing strategies targeted at this demographic group.
Women's organisations, maternal knowledge, and social capital to reduce prevalence of stunted children: Evidence from rural Nepal

Abstract This study analyses behaviour of women's community-based organisations in rural Nepal in reducing prevalence of child malnutrition in member households drawing upon the survey data collected in 2000. The induced institutional innovation hypothesis is tested: are capabilities of women organisations reflecting ‘structured social capital’ positively associated with improved child nutritional status? The effectiveness of outside interventions is also tested. Econometric results based on 2SLS show that higher capabilities of the autonomous group are associated with lower underweight. We also demonstrate that enhanced knowledge diffusion, combined with growth promotion, represents an effective instrument for empowering rural women in acting to reduce the prevalence of chronic malnutrition.
Support Vector Machines

Support Vector Machines -SVMs -are learning machines, originally designed for bi-classification problems, implementing the well-known Structural Risk Minimization (SRM) inductive principle to obtain good generalization on a limited number of learning patterns (Vapnik, 1998). The optimization criterion for these machines is maximizing the margin between two classes, i.e. the distance between two parallel hyperplanes that split the vectors of each one of the two classes, since larger is the margin separating classes, smaller is the VC dimension of the learning machine, which theoretically ensures a good generalization performance (Vapnik, 1998), as it has been demonstrated in a number of real applications (Cristianini, 2000). In its formulation is applicable the kernel trick, which improves the capacity of these algorithms, learning not being directly performed in the original space of data but in a new space called feature space; for this reason this algorithm is one of the most representative of the called Kernel Machines (KMs). Main theory was originally developed on the sixties and seventies by V. Vapnik and A. Chervonenkis (Vapnik et al., 1963, Vapnik et al., 1971, Vapnik, 1995, Vapnik, 1998), on the basis of a separable binary classification problem, however generalization in the use of these learning algorithms did not take place until the nineties (Boser et al., 1992). SVMs has been used thoroughly in any kind of learning problems, mainly in classification problems, although also in other problems like regression (Scholkopf et al., 2004) or clustering (Ben-Hur et al., 2001). The fields of Optic Character Recognition (Cortes et al., 1995) and Text Categorization (Sebastiani, 2002) were the most important initial applications where SVMs were used. With the extended application of new kernels, novel applications have taken place in the field of Bioinformatics, concretely many works are related with the classification of data in Genetic Expression (Microarray Gene Expression) (Brown et al., 1997) and detecting structures between proteins and their relationship with the chains of DNA (Jaakkola et al., 2000). Other applications include image identification, voice recognition, prediction in time series, etc. A more extensive list of applications can be found in (Guyon, 2006).
Hamilton-Jacobi solutions for strongly coupled gravity and matter

A Green function method is developed for solving strongly coupled gravity and matter in the semiclassical limit. In the strong-coupling limit, one assumes that Newton's constant approaches infinity, . As a result, one may neglect second-order spatial gradients, and each spatial point evolves like a homogeneous universe. After constructing the Green function solution to the Hamiltonian constraint, the momentum constraint is solved using functional methods in conjunction with the superposition principle for Hamilton-Jacobi theory. Exact and approximate solutions are given for a dust field or a scalar field interacting with gravity.