Miracle-dz/UniFAR-FTUs huggingface dataset:
Trigonometric quasi-greedy bases for L p (T;w)

Let B = {en}n∈N be a bounded Schauder basis for a Banach space X, i.e., a basis for which 0 ρ(j). Then the greedy m-term approximant to x is given by Gm(x) = ∑m j=1 e ∗ ρ(j)(x)eρ(j). The question is whether the greedy algorithm is convergent. This is clearly the case for an unconditional basis where the expansion x = ∑∞ k=1 e ∗ k(x)ek converges regardless of the ordering. However, Temlyakov and Konyagin [7] showed that the greedy algorithm may also converge for certain conditional bases. This lead them to define so-called quasi-greedy bases, see [7]. The definition of a quasi-greedy basis in [7] is slightly technical, but it was shown by Wojtaszczyk [11] to be equivalent to to the following statement which we use as definition.
An Improved Method for Extraction of Intrinsic Images from a Single Image with Integrated Measures

Intrinsic images, including reflectance and illumination images, are desirable to many vision applications. An improved method for extracting intrinsic images from a single color image with integrated measures is presented. To start with, the input image convolves with a predefined set of derivative filters. The pixels of filtered images are then classified into reflectance-related or illumination-related using a criterion measure comprising three measures of filtered pixels calculated from the input image. The three measures are denoted as chromatic measure, blur measure, and intensity measure. Finally, the intrinsic images of the input image can be computed from the classification results of the filtered images. Both synthetic and real images have been utilized in our experiments. The results demonstrated that the proposed technique can effectively extract the intrinsic images from a single image.
Algorithms for Designing Large-Scale Multimedia Servers

In this paper, we propose a novel adaptive admission control algorithm, in which a client is admitted for service by a multimediaserver only if the extrapolation from the past measurements of the storage server performance characteristics indicate that the service requirements of all the clients can be met satisfactorily. Each client may request the retrieval of a variable bit rate (VBR) encoded media stream and may require a different quality of service. We also present a disk scheduling algorithm that minimizes both seek time and rotational latency incurred while accessing a sequence of media blocks from disk. We examine the effects of a finite read-ahead on the quality of service provided to each admitted client. The effectiveness of the admission control and disk scheduling algorithms is demonstrated through extensive simulations.
Statistical Learning Algorithm for Tree Similarity

Tree edit distance is one of the most frequently used distance measures for comparing trees. When using the tree edit distance, we need to determine the cost of each operation, but this is a labor-intensive and highly skilled task. This paper proposes an algorithm for learning the costs of tree edit operations from training data consisting of pairs of similar trees. To formalize the cost learning problem, we define a probabilistic model for tree alignment that is a variant of tree edit distance. Then, the parameters of the model are estimated using the expectation maximization (EM) technique. In this paper, we develop an algorithm for parameter learning that is polynomial in time (O{mn2d6)) and space (O{n2d4)) where n, d, and m represent the size of the trees, the maximum degree of trees, and the number of training pairs of trees, respectively.
Simulating user intervention for interactive semantic place recognition with mobile devices

Recognising and learning users' semantically meaningful places is useful for personalising services and recommender systems, particularly in a mobile environment. Existing approaches that use mobile devices focus on automating place inference from underlying data, i.e. with little user interaction and intervention -- where user feedback is incorporated into the inference process. The process of intervention can be burdensome to the user but, without intervention, it is difficult to both capture personal place semantics and update places over time; resulting in a trade-off between system performance and user burden. In this paper, we present early results from a place recognition and learning approach that relies on user intervention as a form of active learning. Using simulations of user intervention generated from fine-grained ground truth, we show that good place semantic capture, classification and learning performance can feasibly be achieved in real time on mobile devices with only a small amount of user intervention.
Monetary policy in response to imported price shocks: the Israeli case

Like any other small open economy, the Israeli economy is exposed to global price shocks, which have recently presented greater challenges to the conduct of monetary policy. The high volatility of international food and energy prices during the last two years highlights the question of whether monetary policy should respond to external price shocks using the same rule it uses to respond to domestic price shocks. Israel adopted the headline (CPI) inflation target range of 1-3% in 2003. Within a flexible inflation targeting framework, the monetary policy responds to both lagged and expected price changes in order to preserve price stability while minimising output (gap) volatility and maintaining interest rate stability. Due to the fact that an external price shock leads to a trade-off between inflation and output gap, a monetary policy that focuses on headline inflation may cause a deeper recession than a policy that responds to a measure of inflation that excludes external price shocks that are highly flexible known as core inflation.
Eurographics Symposium on Geometry Processing (2007) Elastic Secondary Deformations by Vector Field Integration

We present an approach for elastic secondary deformations of shapes described as triangular meshes. The deformations are steered by the simulation of a low number of simple mass-spring sets. The result of this simulation is used to define time-dependent divergence-free vector fields whose numerical path line integration gives the new location of each vertex. This way the deformation is guaranteed to be volume-preserving and without self-intersections, giving plausible elastic deformations. Due to a GPU implementation, the deformation can be obtained in real-time for fairly complex shapes. The approach also avoids unwanted intersections in the case of collisions in the primary animation. We demonstrate its accuracy, stableness and usefulness for different kinds of primary animations/deformations.
Learning to Discriminate in the Wild : Representation-Learning Network for Nuisance-Invariant Image Comparison

We test the hypothesis that a representation-learning architecture can train away the nuisance variability present in images, owing to noise and changes of viewpoint and illumination. First, we establish the simplest possible classification task, a binary classification with no intrinsic variability, which amounts to the determination of co-visibility from different images of the same underlying scene. This is the Occlusion Detection problem and the data are typically two sequential, but not necessarily consecutive or in order, video frames. Our network, based on the Gated Restricted Boltzmann machine (Gated RBM), learns away the nuisance variability appearing on the background scene and the occluder, which are irrelevant with occlusions, and in turn is capable of discriminating between co-visible and occluded areas by thresholding a one-dimensional semi-metric. Our method, combined with Superpixels, outperforms algorithms using features specifically engineered for occlusion detection, such as optical flow, appearance, texture and boundaries. We further challenge our framework with another Computer Vision problem, Image Segmentation from a single frame. We cast it as binary classification too, but here we also have to deal with the intrinsic variability of the scene objects. We perform boundary detection according to a similarity map for all pairs of patches and finally provide a semantic image segmentation by leveraging Normalized Cuts.
Soft state in publish/subscribe

Building survivable content-based publish/subscribe systems is difficult. Every node in a distributed publish/subscribe system stores a significant amount of routing state which can be easily corrupted due to message omissions, link and node failures. In this paper, we show how to build a soft state content-based publish/subscribe system where the whole state is stored at the edge of the publish/subscribe network, at the entity which is utilizing the state. This results in a robust and resilient system, as the routing state is permanently lost or corrupted only if the endpoint entity associated with the given state permanently fails.
The Impact of the Proposed Basic Income Grant on the Western Cape

Despite that fact that South Africa is classified as a middle income country it is estimated that at least 22 million people -well over half the population -live in poverty. In 2001, the South African Council of Churches (SACC) joined a broad coalition of civil society organisations calling for the introduction of a Basic Income Grant as a key intervention in the struggle against poverty and inequality. It was envisaged that a monthly transfer of R(and)100 would provide rapid and sustained relief to all South Africans. The analyses reported in this paper seek to provide an ex ante assessment of the impact of the Basic Income Grant on the socio-economic conditions of households and industries in the Western Cape. The analyses are conducted using a computable general equilibrium model that is calibrated to a Social Accounting Matrix for the Western Cape Province. The results indicate, ceteris paribus, that when funded exogenously a BIG will achieve substantial reductions in poverty and inequality, but that the universal BIG scenario is only marginally superior to a targeted basic BIG and achieves less poverty alleviation than an enhanced but targeted BIG. If the transfers are funded by increase in tax rates the degrees of poverty alleviation achieved are greatly reduced, especially if the transfers are funded by an increase in the sales tax rate. When a BIG is funded from tax revenues the degrees of poverty alleviation from targeting increase enormously such that under some scenarios targeting can nearly double the estimated extent of poverty alleviation.
SIMBOL-X, an X-ray telescope for the 0.5-70 keV range

SIMBOL-X is a high energy "mini" satellite class mission that is proposed by a European collaboration for a launch in 2009. SIMBOL-X is making use of a classical X-ray mirror, of ~600 cm2 maximum effective area, with a 30 m focal length in order to cover energies up to several tens of keV. This focal length will be achieved through the use of two spacecrafts in a formation flying configuration. This will give to SIMBOL-X unprecedented spatial resolution (20 arcsec HEW) and sensitivity in the hard X-ray range. By its coverage, from 0.5 to 70 keV, and sensitivity, SIMBOL-X will be an excellent instrument for the study of high energy processes in a large number of sources, both compact and extended.
Assessing the Potential of DSGE Model Evaluation in a Bayesian Framework

In the recent macroeconometric literature, there has been a growing interest in using Dynamic Stochastic General Equilibrium Models (DSGE) in way of explaining macroeconomic uctuations and using the models for quantitative policy analysis. Understanding if a certain economic model can explain real data has a prominent place in the research agenda of econometricians and macroeconomists. In two inuential papers, Del Negro and Schorfheide (2004) and Del Negro, Schorfheide, Smets and Wouters (2007), an important Bayesian econometrics procedure to estimate DSGE models by using Vector Autoregressive (VAR) approach is presented. This methodology helps economists to choose the best model to represent real data among a theoretical framework from the economic literature, a statistical representation from the data and a combination between the two, a DSGE-VAR representation. The goal of this paper is to study the properties of this famous procedure and to try to highlight some of its aspects carrying out three MonteCarlo experiments which hint the possibility of improvement. JEL CODES: C11, C15, C32
Multivariable control design for fixed direction disturbances

In this paper, a blind identification method is employed to model multivariable disturbances with fixed direction. The multivariable disturbance model is used to design non- diagonal weighting filters for Hinfin control. It is demonstrated that in this way, intuitive shaping of the directions of closed loop transfer functions is facilitated, maximally exploiting design freedom that has no analogue for scalar systems.
Reliability and Validity of the Korean Version of the Childhood Trauma Questionnaire-Short Form for Psychiatric Outpatients

Objective The Childhood Trauma Questionnaire (CTQ) is perhaps the most widely used and well-studied retrospective measure of childhood abuse or neglect. This study tested the initial reliability and validity of a Korean translation of the Childhood Trauma Questionnaire (CTQ-K) among non-psychotic psychiatric outpatients. Methods The CTQ-K was administered to a total of 163 non-psychotic psychiatric outpatients at a university-affiliated training hospital. Internal consistency, four-week test-retest reliability, and validity were calculated. A portion of the participants (n=65) also completed the Trauma Assessment Questionnaire (TAQ), the Impact of Events Scale-Revised, and the Dissociative Experiences Scale-Taxon. Results Four-week test-retest reliability was high (r=0.87) and internal consistency was good (Cronbach's α=0.88). Each type of childhood trauma was significantly correlated with the corresponding subscale of the TAQ, thus confirming its concurrent validity. In addition, the CTQ-K total score was positively related to post-traumatic symptoms and pathological dissociation, demonstrating the convergent validity of the scale. The CTQ-K was also negatively correlated with the competence and safety subscale of the TAQ, confirming discriminant validity. Additionally, we confirmed the factorial validity by identifying a five-factor structure that explained 64% of the total variance. Conclusion Our study indicates that the CTQ-K is a measure of psychometric soundness that can be used to assess childhood abuse or neglect in Korean patients. It also supports the cross-cultural equivalence of the scale.
Use of Web Popularity on Entity Centric Document Filtering

Filtering pages about an entity (person, company, music band.) so that only interesting pages are kept is a real challenge. The interest can be qualified using criteria such as recency, novelty. In the last decade, we have seen classification systems trained to detect the interest for a document regarding an entity. For scalability reasons, it is not possible to consider a manual annotation of a training set for each tracked entity. Some approaches strive to build entity independent systems. These approaches obtain the state of the art performances, but we show that they can be improved. Time features differ from one entity to another, therefore no relevant statistics can be estimated out of these observations by a single classifier. Instead of having one model per entity or one model for all entities, we propose an approach that uses one model per cluster of entities based on the entity web popularity. We also introduce different strategies for automatic classification model selection. We test our approach on the Knowledge Base Acceleration (KBA) framework from TREC and we show that our approach brings significant improvements over a non-cluster-based method.
On evaluating the scalability aspect of gait-based biometric systems for larger population

The use of biometric technologies becomes ubiquitous in modern society due to the proliferating number of crimes and terror attacks as well as the vital need to provide safer environment. Gait biometrics is considered one of the emerging key research areas due to its potential use in a plethora of applications such as forensics and visual surveillance. As the evaluation of biometric-based evidence in investigation plays a pivotal role for its admissibility in court, we investigate in this research the performance of a model-based approach for people identification over an increasing population. A model-based markerless approach is described to derive the joints positions of walking subjects from uncalibrated single cameras through the use of a haar-like template matching approach. Matching of subjects is performed through posture comparison through a window of frames. Experimental results have shown that increasing the database size, the similarity scores for inter- and intra-class comparisons tend to converge to fixed values that are well separated. This suggests that for larger population, gait analysis can be still deployed and the size of the database should not be a factor impacting on the analysis.
Integrating Computers into Accounting Education: A Survey of Australian Universities and Colleges

Conflicts of ideas occur in the literature regarding the necessity and best approach in integrating computers into accounting courses in institutions of higher learning. This paper presents a report of a survey of the use of computer assisted learning in accounting curriculum in Australian universities and colleges, academics commitment to computer assisted learning and obstacles to further applications of computer assisted learning in accounting courses. The survey found that computer assisted learning has occurred mostly at an introductory level in the areas of worksheets and special purpose journals. Academics want to increase computer assisted learning in their accounting courses but are hindered by lack of financial resources, staff time, staff expertise and educationally suitable software.
Visualizations as a Basis for Agile Software Process Improvement

Software projects have usually a lot of software engineering data available in different kinds of repositories. This data can be mined and used for software process improvement purposes. In general, agile methodologies emphasize reflection, making problems visible, and learning from the past. As the human mind is powerful in interpreting visual representations, visualizations could help in recognizing problems and areas of improvement in an agile software development process. In this paper an action research approach was taken to carry out software process improvement in an industry project. The research resulted in a visualization of the issue management system's data. The visualizations were a tool to identify problems in the development process and to make them visible for all stakeholders. The results show that this kind of visual approach can be used successfully to point out problems in the process. The visualizations form a basis for communication on possible software process improvement.
Herpes simplex virus helicase-primase: the UL8 protein is not required for DNA-dependent ATPase and DNA helicase activities.

The herpes simplex virus type 1 helicase-primase complex consists of the products of the UL5, UL8 and UL52 genes. We have expressed these proteins in insect cells using baculovirus vectors and studied the requirements for enzymatic activities associated with the DNA unwinding function of the complex. In agreement with a recent report (Dodson, M.S., Crute, J.J., Bruckner, R.C. and Lehman, I.R. 1989, J. Biol. Chem. 264, 20835-20838) we find that DNA-dependent ATPase and DNA helicase activities are assembled in vivo in insect cells triply infected with viruses expressing the UL5, UL8 and UL52 proteins. Moreover, these activities were also detected in cells in which only the UL5 and UL52 products were expressed indicating that the presence of the UL8 protein is essential for neither the ATPase nor helicase activity of the complex.
Possibilistic decision trees for Intrusion Detection in IEC61850 automated substations

This paper details the use of possibilistic decision trees for a lightweight Intrusion Detection System (IDS) to be used in Intelligent Electronic Devices (IEDs) of IEC61850 automated electric substations. Traffic data is captured by performing simulated attacks on IEDs. Data is obtained for two types of genuine user activity and two types of common malicious attacks on IEDs. The genuine user activity includes, casual browsing of IED data and downloading of IED data while a Ping flood Denial of Service (DoS) and password crack attack are performed for malicious attacks. Classification is done using possibilistic decision trees for the logarithmic histogram of the time difference between the arrival of two consecutive packets. The main contribution of this paper is the use of non-specificity for obtaining a continuous valued possibilistic decision tree and its cut points. It also includes the use of mean distance metrics to obtain the possibility distribution for the real attack data.
Application of Taguchi Method in Indian Industry

The objective of the present study is to optimize the process by applying the Taguchi method with orthogonal array robust design. Taguchi Parameter Design is a powerful and efficient method for optimizing the process, quality and performance output of manufacturing processes, thus a powerful tool for meeting this challenge. Off-line quality control is considered to be an effective approach to improve product quality at a relatively low cost. The Taguchi method is one of the conventional approaches for this purpose. Analysis of variance (ANOVA) is used to study the effect of process parameters on the machining process. The approach is based on Taguchi method, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) are employed to study the performance characteristics. (121 words)
Equivalent Model of Large-Scale Synchronous Photovoltaic Power Plants

The impact that power plants employing renewable energy sources have on power systems is no longer negligible due to the ever-increasing portion of the power share that these generation systems represent. Therefore, the static and dynamic effects of these power plants on the grid must be analyzed in at least the same degree of detail as conventional generating units. For this purpose, it is necessary to develop models that are accurate and able to capture the dynamics of interest for the analysis, but also taking into account that they should be manageable and have a good computational performance. In the case of power plants based on photovoltaic (PV) or wind energy, formed by many power converters, an equivalent plant model that reduces the number of devices offers a good tradeoff between accuracy and complexity. Motivated by the analysis of an actual 100 MW PV power plant formed by 100 converters, each of them governed by a synchronous power controller, this paper presents a general method to derive a dynamic equivalent model of a group of converters that use this type of controller. The method is applied to this power plant in order to obtain several equivalent models with different degrees of detail that are compared through simulation. The results prove the accuracy of the equivalent aggregated models under different conditions and allow measuring the reduction in computation time that they achieve.