Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracting Tabular Information From Text Files

This paper presents work done in locating and extracting tables and their contents from document images. While most research in the area of table analysis and recognition has focused on analyzing the raster image, our approach builds upon the advances in optical character recognition (OCR) software to preserve the layout of tabular data by means of white space. By using methods to analyze the geometry, syntax, and the semantics of the character data, as well as utilizing some well-known image processing techniques, we are able to 1) isolate embedded tables from documents, and 2) identify table components uch as title blocks, table entries, and footer blocks. Furthermore, the table analysis techniques presented in this paper can also be applied when analyzing blocks of text isolated by traditional methods such as connected component analysis[1] or bounding box [2].
Monetary Policy Rules, Total Factor Productivity Growth and Uncertainty:An empirical Assessment

This dissertation explores how uncertainty a�ffects diff�erent facets of an economy through three empirical essays. First, we presents an analytical framework to examine the policy reaction function of a central bank in an open economy context while allowing for asymmetric preferences. This implies that the policy makers can weigh negative and positive deviations of target variables (inflation and output gap) from their corresponding targets di�fferently. We use an open economy New-Keynesian forward looking model where aggregate demand and supply depend on real exchange rate. Using quarterly data ranging from 1979q1-2007q4 for Canada, Japan, the UK and the US, the empirical evaluation is drawn through generalized methods of moments. The results strongly favor the presence of asymmetries in the response of monetary policy towards both inflation rate and output gap for all sample countries. The estimates show that central banks follow an active monetary policy. Also, there is evidence that changes in foreign interest rate and exchange rate �significantly aff�ects the domestic monetary policy formation. Second, we examine the role of various sources of uncertainty on total factor productivity growth. Specifi�cally, this essay estimates the role of of uncertainty emanating from global, country, and industry level on TFP growth in manufacturing industries of sixteen emerging economies. For this purpose, we use annual data covering the period from 1971-2008. Our fi�ndings suggest a signifi�cant impact of each source of uncertainty on TFP growth. Particularly, we observe that industry and country specifi�c uncertainty have a positive impact on TFP growth of manufacturing industries. However, global uncertainty has statistically signifi�cant and negative impact on TFP growth. We also provide evidence that the impact of industry speci�fic uncertainty strengthens as the size of industry increases whereas the reverse holds for both country specifi�c and global uncertainty. In addition, we observe that the positive impact of both industry and country speci�fic uncertainty gets stronger at higher levels of factor intensity. Third, we examine the role of of uncertainty of technology diff�usion in TFP convergence of manufacturing industries of frontier and non-frontier countries. For this purpose, we use annual data covering the time period from 1981-2008, eighteen manufacturing industries of fi�ve emerging economies. We employ superlative index number approach to compute the TFP level and growth in manufacturing industries of these countries. Our �findings suggest a signi�ficant evidence of TFP convergence in manufacturing industries of non-frontier and frontier countries. Moreover, technology diff�usion not only pertains a positive impact on TFP growth of manufacturing industries of non-frontier countries but also facilitates the process of TFP convergence. More importantly, we report a signi�ficant negative impact of uncertainty of technology diff�usion on the TFP growth.
Bounds on MMSE multiuser detection for CDMA

Minimum-mean-square-error (MMSE) linear multiuser detector considers multiple access interference (MAI) and background noise asymptotically Gaussian for large number of users in asynchronous code division multiple access (CDMA) system. For this asymptotic condition, the available results in literature have been derived for two-user case. In this paper, we have proposed a general formula to calculate upper bound on normalized cross-correlation (NCC) for arbitrary number of users. Under near-far situation, Chernoff upper bound on error probability of MMSE multiuser detector is presented. Its proof based on divergence theorem and study of leakage coefficients imposes minimum bound on signal-to-noise ratio of desired user (SNRD).
Using suffix arrays as language models: Scaling the n-gram

In this article, we propose the use of suffix arrays to implement n-gram language models with practically unlimited size n. These unbounded n-grams are called ∞-grams. This approach allows us to use large contexts efficiently to distinguish between different alternative sequences while applying synchronous back-off. From a practical point of view, the approach has been applied within the context of spelling confusibles, verb and noun agreement and prenominal adjective ordering. These initial experiments show promising results and we relate the performance to the size of the n-grams used for disambiguation.
The Role of Intraseasonal Variability in the Nature of Asian Monsoon Precipitation

Abstract The structure of the mean precipitation of the south Asian monsoon is spatially complex. Embedded in a broad precipitation maximum extending eastward from 70°E to the northwest tropical Pacific Ocean are strong local maxima to the west of the Western Ghats mountain range of India, in Cambodia extending into the eastern China Sea, and over the eastern tropical Indian Ocean and the Bay of Bengal (BoB), where the strongest large-scale global maximum in precipitation is located. In general, the maximum precipitation occurs over the oceans and not over the land regions. Distinct temporal variability also exists with time scales ranging from days to decades. Neither the spatial nor temporal variability of the monsoon can be explained simply as the response to the cross-equatorial pressure gradient force between the continental regions of Asia and the oceans of the Southern Hemisphere, as suggested in classical descriptions of the monsoon. Monthly (1979–2005) and daily (1997–present) rainfall estimates .
Applying Matrix Decompositions to Counterterrorism

Governments collect data in which they hope to flnd patterns of terrorist activity. It is hard to know what such patterns look like and, in any case, terrorists are actively trying to avoid leaving any distinctive traces. However, if they work as a group, it is impossible to avoid some correlation among their attributes and actions. We show that such correlation can be detected, partly because it is likely to be qualitatively difierent from the correlations among groups with more innocent purpose. We show that matrix decompositions, in particular singular value decomposition and semidiscrete decomposition, have several useful properties for this problem. In many cases it is possible to identify a terrorist group with few false positives.
Human face processing techniques with application to large scale video indexing

Human faces play an important role in efficiently indexing and accessing video contents, especially in large scale broadcasting news video databases. It is due to faces are associated to people who are related to key events and key activities happening from all over the world. There are many applications using face information as the key ingredient, for example, video mining, video indexing and retrieval, person identification and so on. However, face appearance in real environments exhibits many variations such as pose changes, facial expressions, aging, illumination changes, low resolution and occlusion, making it difficult for current state of the art face processing techniques to obtain reasonable retrieval results. This thesis studies human face processing techniques whose target is to efficiently apply to a general framework for large scale video mining and indexing. In this framework, faces firstly are extracted, filtered and normalized from video sequences by using a fast and robust face detector. Next, similar faces are grouped into clusters. Then, these face clusters are labeled by the person names extracted from the video transcripts. To extract faces from video, we propose a multi-stage approach that uses cascades of classifiers to yield a coarse-to-fine strategy to reduce significantly detection time while maintaining a high detection rate. This approach is distinguished from previous work by two features. First, we use a cascade of AdaBoost classifiers that is trained to be invariant to translation up to 25% of the original window size to detect quickly face candidate regions. Second, we use SVM classifiers which reuse the features selected by AdaBoost in the previous stage for robust classification and simple training. Reusing these features brings to two advantages: (i) These features do not need to be re-evaluated because they have already
An Assessment of Changeability of Open Source Software

Among the maintainability sub-characteristics, changeability plays a critical role in analyzing the maintainability of software. Changeability is highly influenced by the dependencies that exist between the components of a system. Therefore, we need to have measurement mechanisms that can take into account the dependencies between components so as to determine the ease which modifications can be made to given software. This paper attempts to investigate the usefulness of three coupling metrics (CBO, Ce, and Ca) and one size/complexity metric (WMC) as predictors of changeability. The assessment is based on a case study of open source software known as OpenBravoPOS which is commonly used in the retail business and developed in Java. The results show that some of the coupling metrics can be used as good predictors of changeability.
Two SVDs produce more focal deep learning representations

A key characteristic of work on deep learning and neural networks in general is that it relies on representations of the input that support generalization, robust inference, domain adaptation and other desirable functionalities. Much recent progress in the field has focused on efficient and effective methods for computing representations. In this paper, we propose an alternative method that is more efficient than prior work and produces representations that have a property we call focality -- a property we hypothesize to be important for neural network representations. The method consists of a simple application of two consecutive SVDs and is inspired by Anandkumar (2012).
Spontaneous Formation of Nucleic Acid-based Nanoparticles Is Responsible for High Interferon-α Induction by CpG-A in Plasmacytoid Dendritic Cells*

Plasmacytoid dendritic cells (PDC) represent a highly specialized immune cell subset that produces large quantities of the anti-viral cytokines type I interferons (IFN-α and IFN-β) upon viral infection. PDC employ a member of the family of toll-like receptors, TLR9, to detect CpG motifs (unmethylated CG dinucleotides in certain base context) present in viral DNA. A certain group of CpG motif-containing oligodeoxynucleotides (CpG ODN), CpG-A, was the first synthetic stimulus available that induced large amounts of interferon-α (IFN-α) in PDC. However, the mechanism responsible for this activity remained elusive. CpG-A is characterized by a central palindrome and poly(G) at the 5′ and 3′ end. Here we demonstrate that CpG-A self-assembles to higher order tertiary structures via G-tetrad formation of their poly(G) motifs. Spontaneous G-tetrad formation of CpG-A required the palindrome sequence allowing structure formation in a physiological environment. Once formed, G-tetrad-linked structures were stable even under denaturing conditions. Atomic force microscopy revealed that the tertiary structures formed by CpG-A represent nucleic acid-based nanoparticles in the size range of viruses. Similarly sized preformed polystyrene nanoparticles loaded with a CpG ODN that is otherwise weak at inducing IFN-α (CpG-B) gained the potency of CpG-A to induce IFN-α. Higher ODN uptake in PDC was not responsible for the higher IFN-α-inducing activity of CpG-A or of CpG-B-coated nanoparticles as compared with CpG-B. Based on these results we propose a model in which the spatial configuration of CpG motifs as particle is responsible for the virus-like potency of CpG-A to induce IFN-α in PDC.
Solution Synthesis Approach to Colloidal Cesium Lead Halide Perovskite Nanoplatelets with Monolayer-Level Thickness Control

We report a colloidal synthesis approach to CsPbBr3 nanoplatelets (NPLs). The nucleation and growth of the platelets, which takes place at room temperature, is triggered by the injection of acetone in a mixture of precursors that would remain unreactive otherwise. The low growth temperature enables the control of the plate thickness, which can be precisely tuned from 3 to 5 monolayers. The strong two-dimensional confinement of the carriers at such small vertical sizes is responsible for a narrow PL, strong excitonic absorption, and a blue shift of the optical band gap by more than 0.47 eV compared to that of bulk CsPbBr3. We also show that the composition of the NPLs can be varied all the way to CsPbBr3 or CsPbI3 by anion exchange, with preservation of the size and shape of the starting particles. The blue fluorescent CsPbCl3 NPLs represent a new member of the scarcely populated group of blue-emitting colloidal nanocrystals. The exciton dynamics were found to be independent of the extent of 2D confinement in these platelets, and this was supported by band structure calculations.
Coupling fine root dynamics with ecosystem carbon cycling in black spruce forests of interior Alaska

Fine root processes play a prominent role in the carbon and nutrient cycling of boreal ecosystems due to the high proportion of biomass allocated belowground and the rapid decomposition of fine roots relative to aboveground tissues. To examine these issues in detail, major components of ecosystem carbon flux were studied in three mature black spruce forests in interior Alaska, where fine root production, respiration, mortality and decomposition, and aboveground production of trees, shrubs, and mosses were measured relative to soil CO2 fluxes. Fine root production, measured over a two-year period using minirhizotrons, varied from 0.004 ± 0.001 mm·cm–2·d–1 over winter, to 0.051 ± 0.015 mm·cm–2·d–1 during July, with peak growing season values comparable to those reported for many temperate forests using similar methods. On average, 84% of this production occurred within 20 cm of the moss surface, although the proportion occurring in deeper profiles increased as soils gradually warmed throughout the summer. M.
Evaluation of a commercial enzyme‐linked immunosorbent assay for detection of antibodies against the H5 subtype of Influenza A virus in waterfowl

The ID Screen Influenza H5 Antibody Competition enzyme‐linked immunosorbent assay was tested for the detection of antibodies to the H5 subtype of influenza A (IA) virus in waterfowl. Assays were conducted with sera obtained from Mallards (Anas platyrhynchos) and Pekin Ducks (Anas platyrhynchos domestica), experimentally infected with eight low pathogenic (LP) and nine highly pathogenic (HP) H5N1 IA viral strains. Three incubation periods (1, 4 and 18 hours) and two dilutions (1:2 and 1:5) were tested. All serum samples from LP H5‐infected birds tested positive; however, improved detection rates were observed for viruses belonging to the HP H5N1 clade 2.2.1 as compared with those belonging to clade 2.1. 3.
The Long-Run Role of the Media: Evidence from Initial Public Offerings

The unique characteristics of the U.S. initial public offering IPO process, particularly the strict quiet period regulations, allow us to explore the effects of media coverage when the coverage does not contain genuine news i.e., hard information that was previously unknown. We show that a simple, objective measure of pre-IPO media coverage is positively related to the stock's long-term value, liquidity, analyst coverage, and institutional investor ownership. Our results are robust to additional controls for size, to using abnormal or excess media, and to an instrumental variable approach. We also find that pre-IPO media coverage is negatively related to future expected returns, measured by the implied cost of capital. In all, we find a long-term role for media coverage, consistent with Merton's attention or investor recognition hypothesis. This paper was accepted by Brad Barber, finance.
COMPARISON OF SERUM ADIPONECTIN AND INTERLEUKIN 6 CONCENTRATIONS IN NONDIABETIC HYPERTENSIVE AND DIABETIC HYPERTENSIVE PATIENTS WHO DEVELOPED CEREBRAL INFARCT

Stroke is the second leading cause of death and a major cause of morbidity and mortality in western as well as developing countries. Adiponectin is a fat-derived plasma protein that has beneficial actions on cerebrovascular disorders. A low level of plasma adiponectin is associated with increased mortality after ischemic stroke. Interleukin 6 is a cytokine, which is elevated in inflammatory, traumatic and ischemic injuries. The objective of this study was to compare serum adiponectin and interleukin-6 levels in diabetic hypertensive and nondiabetic hypertensive patients and to measure the size of cerebral infarct. 89 patients (30 controls, 30 nondiabetic hypertensive and 29 diabetic hypertensive) were recruited in the study according to inclusion criteria of Ziauddin University Hospital. Serum adiponectin and interleukin 6 concentrations were measured by ELISA. Blood glucose and lipid profile was done by standard kit methods. Serum adiponectin concentration was significantly lower (P<0.05) in both study groups and interleukin 6 concentration was significantly higher (P<0.05) in diabetic hypertensive group as compared with controls. The mean serum interleukin 6 in diabetic hypertensive patients with cerebral infarct was significantly higher than that of nondiabetic hypertensive patients with cerebral infarct (P < 0.001). Serum adiponectin concentration was decreased while the infarct size was larger in diabetic hypertensive group as compared to nondiabetic hypertensive group but the difference in these parameters was statistically non significant. Hence the study supports to the evidence of involvement of adiponectin and interleukin 6 in patients of stroke.
A new approach to object recognition for multi viewed objects

In this paper, we proposed a new method for object recognition for multi viewed object based on shape space. Here we extract the similar features of all the objects of different classes and identified in a single point in a high dimensional manifold which is known as shape space. Object recognition is achieved by measuring the Euclidian distance between an observed object and a model in the shape space. The problem of image retrieval is much more challenging than that of text retrieval since significant features for representing and searching an arbitrary image vary with the image content. So, we focus on landmarks of processing images which are easily recognisable by human users.
Class-pinning: A Novel Approach for Hop-by-Hop QoS Routing

The need for Quality of Service (QoS) on the Internet is increasing everyday due to the wide dissemination of new communication services with more stringent demands from the network. There have been several proposals for QoS provisioning, particularly, the Integrated Services and Differentiated Services frameworks developed on the Internet Engineering Task Force (IETF). As the deployment of Differentiated Services on the Internet becomes a reality, it urges for its combination with QoS aware routing protocols. Among other proposals, at the Laboratory of Communications and Telematics of the University of Coimbra is being developed an intra-domain QoS routing protocol (UCQoSR). In this paper a mechanism of class-pinning to integrate the UC-QoSR strategy is proposed and evaluated. This mechanism addresses the stability problem associated with congestion based routing by controlling the instant when a traffic class shifts to a new path. A traffic class is moved to a new path only if it is considerably better than the current path. Results show that with the use of classpinning it is possible to maintain a adequate path for each traffic class and to avoid the instability due to frequent path shifts.
A measurement-based model of energy consumption for PLC modems

In this paper a detailed measurements-based analysis of the energy consumption of commercial broadband PLC modems is reported. Energy consumption measurements are carried out on the basis of pairs of many commercial PLC modems. Ethernet frames with variable sizes and bit/frame rates are sent on a modem, and received on the other modem. An analytic linear model that quantifies the energy consumption associated to Ethernet frames and PLC Physical Blocks (PBs) processing is proposed for a pair of PLC modems.
Stability and Bifurcation Analysis for an Improved HIV Model with Time Delay and Cure Rate

In this paper, a modified delayed mathematical model for the dynamics of HIV with cure rate is consid- ered. By regarding the time delay as bifurcation parameter, stability and existence of local Hopf bifurcation are studied by analyzing the transcendental characteristic equation. Then the global existence of bifurcating periodic solutions is established with the assistance of global Hopf bifurcation theory. Finally, some numerical examples are given.
Comparison of sampling methods for hard-to-reach francophone populations: yield and adequacy of advertisement and respondent-driven sampling

Background: Francophones who live outside the primarily French-speaking province of Quebec, Canada, risk being excluded from research by lack of a sampling frame. We examined the adequacy of random sampling, advertising, and respondent-driven sampling for recruitment of francophones for survey research. Methods: We recruited francophones residing in the city of Calgary, Alberta, through advertising and respondentdriven sampling. These 2 samples were then compared with a random subsample of Calgary francophones derived from the 2006 Canadian Community Health Survey (CCHS). We assessed the effectiveness of advertising and respondent-driven sampling in relation to the CCHS sample by comparing demographic characteristics and selected items from the CCHS (specifically self-reported general health status, perceived weight, and having a family doctor). Results: We recruited 120 francophones through advertising and 145 through respondent-driven sampling; the random sample from the CCHS consisted of 259 records. The samples derived from advertising and respondentdriven sampling differed from the CCHS in terms of age (mean ages 41.0, 37.6, and 42.5 years, respectively), sex (proportion of males 26.1%, 40.6%, and 56.6%, respectively), education (college or higher 86.7% , 77.9% , and 59.1%, respectively), place of birth (immigrants accounting for 45.8%, 55.2%, and 3.7%, respectively), and not having a regular medical doctor (16.7%, 34.5%, and 16.6%, respectively). Differences were not tested statistically because of limitations on the analysis of CCHS data imposed by Statistics Canada. Interpretation: The samples generated exclusively through advertising and respondent-driven sampling were not representative of the gold standard sample from the CCHS. Use of such biased samples for research studies could generate misleading results.