Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Statement: Dipanjan Das 1 Natural Language Processing

I design computationally intensive statistical methods for the discovery of syntactic and semantic structure in natural language text. A major focus of my research is on the use of both linguistically annotated as well as unannotated textual data, from which the aforementioned statistical models are estimated. My work has resulted in significant improvements in shallow semantic parsing of text [9, 6, 7], recognition of semantic equivalence of utterances [8], and the learning of linguistic structure from unannotated data with indirect supervision [5, 1]. I am also interested in developing practical systems that are open-source and useful to the human language technologies community.1
Hyperbolic surface subgroups of one‐ended doubles of free groups

Gromov asked whether every one‐ended word‐hyperbolic group contains a hyperbolic surface group. We prove that every one‐ended double of a free group has a hyperbolic surface subgroup if (1) the free group has rank 2 or (2) every generator is used the same number of times in a minimal automorphic image of the amalgamating words. To prove this, we formulate a stronger statement on Whitehead graphs and prove its specialization by combinatorial induction for (1) and the characterization of perfect matching polytopes by Edmonds for (2).
Error estimates for mixed methods

Abstract : This paper presents abstract error estimates for mixed methods for the approximate solution of elliptic boundary value problems. These estimates are then applied to obtain quasi-optimal error estimates in the usual Sobolev norms for four examples: three mixed methods for the biharmonic problem and a mixed method for 2nd order elliptic problems. (Author)
GIRTH AND CHROMATIC NUMBER OF GRAPHS

This paper will look at the relationship between high girth and high chromatic number in both its finite and transfinite incarnations. On the one hand, we will demonstrate that it is possible to construct graphs with high oddgirth and high chromatic number in all cases. We will then look at a theorem which tells us why, at least in the transfinite case, it is impossible to generalize this to include even cycles. Finally, we will use the probabilistic method to show why it is possible to construct graphs of any given finite girth and finite chromatic number.
Recognition of Historical Records Using Gabor and Zonal Features

The paper addresses the automation of the task of an epigraphist in reading and deciphering inscriptions. The automation steps include Pre-processing, Segmentation, Feature Extraction and Recognition. Preprocessing involves, enhancement of degraded ancient document images which is achieved through Spatial filtering methods, followed by binarization of the enhanced image. Segmentation is carried out using Drop Fall and Water Reservoir approaches, to obtain sampled characters. Next Gabor and Zonal features are extracted for the sampled characters, and stored as feature vectors for training. Artificial Neural Network (ANN) is trained with these feature vectors and later used for classification of new test characters. Finally the classified characters are mapped to characters of modern form. The system showed good results when tested on the nearly 150 samples of ancient Kannada epigraphs from Ashoka and Hoysala periods. An average Recognition accuracy of 80.2% for Ashoka period and 75.6% for Hoysala period is achieved.
Probabilistic Methods for Adaptive Background Subtraction

Visual surveillance applications such as object identification, movement tracking, and activity monitoring require reliable moving object detection as an initial processing step. The process that segments moving objects from the stationary scene is termed background subtraction. In the past, the most effective background subtraction methods have been those that employ probabilistic modeling of the background. In this thesis, we present three adaptive detection modalities that apply generally to any pixel-based probabilistic background model. Formulated within the classical binary hypothesis framework, a method for explicit foreground modeling is proposed, which refines the decision process wherever moving objects are present and reduces the miss rate. Also, by modeling the detection mask as a Markov random field, we present a method that adapts spatially to impose continuity on the detection result. In addition, we apply a multiple comparisons procedure known as false discovery rate control. The result is a temporally variable thresholding strategy that adapts to object sparsity. The new methods offer a clear qualitative improvement in real scenarios as well as a measurable performance gain over non-adaptive techniques when tested on synthetic sequences.
CoCos: A Primer

Contingent convertible capital instruments (CoCos) are hybrid capital securities that absorb losses when the capital of the issuing bank falls below a certain level. In this article, we go over the structure of CoCos, trace the evolution of their issuance, and examine their pricing in primary and secondary markets. CoCo issuance is primarily driven by their potential to satisfy regulatory capital requirements. The bulk of the demand for CoCos has come from small investors, while institutional investors have been relatively restrained so far. The spreads of CoCos over other subordinated debt greatly depend on their two main design characteristics - the trigger level and the loss absorption mechanism. CoCo spreads are more correlated with the spreads of other subordinated debt than with CDS spreads and equity prices.
Architecture of malware tracker visualization for malware analysis

Malware is a man-made malicious code designed for computer destructive purposes. The early destructive programs were developed either for pranks or experimental purposes. However, in this day and age, malware are created mainly for financial gain. Since years ago, the use of malware attack tools, such as keylogger, screen capture software, and trojan were rapidly used to commit cybercrimes. The figures are expected to increase significantly and the attack tools are becoming more sophisticated in order to evade the detection of current security tools. The malware debugger analysis process is an essential part of analyzing and comprehending the purpose and the destructive part of the malware. It is an exhausting and time consuming task; moreover, in-depth computer knowledge is required. With the popularity and variety of malware attacks over the Internet, the number of virus needed to be analyzed by computer security experts are rapidly increasing and has bottlenecked the effectiveness of the analysis process. In this paper, we present a method to visually explore the reverse engineering of a binary executable flow over time to aid in the identification and detection of malicious program on x86-32 platform. We first achieve the preexecution analysis for a sketch of a program’s behavior by combining static analysis and graphical visualization to construct a control flow graph (CFG) as an interface for the analyzed code. Each node in the CFG graph which represents a basic block allows analysts to be selective in the components they monitor. All nodes in the CFG express the complex relationships and causalities of the analyzed code. As the binary executes, those codes that are dynamically generated will be monitored and captured; thus, a fuller understanding of the execution’s behavior will be provided. The backward track approach which allows analysts to restudy the changes of the executed instructions’ memory during dynamic analysis provides a chance for analysts to restudy the execution behavior of the executed instructions. The overall architecture of the visualization debugger, both statically and dynamically will be explained in this paper. To the end of the paper, we analyze a malware test case; W32/NGVCK.dr.gen virus with our malware tracker visualization toolkit and the analysis results proves that our visualization malware tracker tool can simplify the analysis process by displaying the analyzed code in basic block approach. This work is a substantial step towards providing high-quality tool support for effective and efficient visualization malware analysis.
F3-C,E: Machine Learning & Sensor Management for High Throughput Screening

This project is investigating the development of automated explosive detection and classification algorithms for high throughput screening. This is critical both in portal systems, where high throughput requires significant automated decision support, and in stand-off systems where the proliferation of multimodal data can overwhelm human interpretation. The project’s fundamental assumption is that it is too slow or costly to collect full sensor data on every object of interest, either for training, or during real-time operation. As a consequence, there are several important problems to address. In training, one needs to select which data will be used to train the decision algorithms in order to achieve robust performance. This is a problem known as active learning. In the real-time phase, one needs to use a hierarchy of sensing and classification strategies, based on relatively inexpensive early warning sensors, and adaptively select subsequent sensor measurements in order to arrive rapidly at an accurate classification decision. The longrange impact of this research will be the development of adaptive, high throughput screening algorithms for different combinations of sensing modalities that exhibit improved sensitivity/specificity.
Adaptive covariance matrix estimation through block thresholding

Estimation of large covariance matrices has drawn considerable recent attention, and the theoretical focus so far has mainly been on developing a minimax theory over a fixed parameter space. In this paper, we consider adaptive covariance matrix estimation where the goal is to construct a single procedure which is minimax rate optimal simultaneously over each parameter space in a large collection. A fully data-driven block thresholding estimator is proposed. The estimator is constructed by carefully dividing the sample covariance matrix into blocks and then simultaneously estimating the entries in a block by thresholding. The estimator is shown to be optimally rate adaptive over a wide range of bandable covariance matrices. A simulation study is carried out and shows that the block thresholding estimator performs well numerically. Some of the technical tools developed in this paper can also be of independent interest.
Design and Application on Calculating Iron Ores Matching Model

Based on the status of iron ores matching at present,the structure of the calculating iron ores matching has been put forward.During the calculating iron ores matching model,the chemistry index,granularity composition of raw materials,as well as the economy index were considered.One calculating iron ores matching software has been developed using Visual C++ 6.0. Using this software,consumers can carry out the mixing iron ores matching neatly by fixed matching method or linear programming method in response to the practicality.In addition,rapidly matching raw materials can also be realized using this software by fixed matching method or simplified theory matching method.This software has been successfully applied in the sintering experiments.
Infinitesimal Structure of Differentiability Spaces, and Metric Differentiation

Abstract We prove metric differentiation for differentiability spaces in the sense of Cheeger [10, 14, 27]. As corollarieswe give a new proof of one of the main results of [14], a proof that the Lip-lip constant of any Lip-lip space in the sense of Keith [27] is equal to 1, and new nonembeddability results.
Residual Circulation and Tropopause Structure

The effect of large-scale dynamics as represented by the residual mean meridional circulation in the transformed Eulerian sense, in particular its stratospheric part, on lower stratospheric static stability and tropopause structure is studied using a comprehensive chemistry–climate model (CCM), reanalysis data, and simple idealized modeling. Dynamical forcing of static stability as associated with the vertical structure of the residual circulation results in a dominant dipole forcing structure with negative static stability forcing just below the tropopause and positive static stability forcing just above the tropopause. This dipole forcing structure effectively sharpens the tropopause, especially during winter. Furthermore, the strong positive lowermost stratospheric static stability forcing causes a layer of strongly enhanced static stability just above the extratropical tropopause—a tropopause inversion layer (TIL)—especially in the winter midlatitudes. The strong positive static stability forcing is shown to be mainly due to the strong vertical gradient of the vertical residual velocity found just above the tropopause in the winter midlatitudes. Stratospheric radiative equilibrium (SRE) solutions are obtained using offline radiative transfer calculations for a given tropospheric climate as simulated by the CCM. The resulting tropopause height in SRE is reduced by several kilometers in the tropics but is increased by 1–2 km in the extratropics, strongly reducing the equator-to-pole contrast in tropopause height. Moreover, the TIL in winter midlatitudes disappears in the SRE solution in contrast to the polar summer TIL, which stays intact. When the SRE solution is modified to include the effect of stratospheric dynamics as represented by the stratospheric residual circulation, the TIL in winter midlatitudes is recovered, suggesting that the static stability forcing associated with the stratospheric residual circulation represents the main cause for the TIL in the winter midlatitudes whereas radiation seems dominant in causing the polar summer TIL.
Robustness in Interdependent Networks Mmath Cd Dissertation

The field of network science has seen massive growth in the last 15 years. Tools have been developed to study the properties of abstract networks, as well as problems involving real-world systems. One such problem concerns the robustness of a network: how well the network continues to function when parts of its structure are destroyed. A rapidly emerging area of network science is the study of multilayer networks. We investigate the robustness of one type of multilayer network: interdependent networks. We use probability generating functions, along with computer simulations, to analyse the behaviour of interdependent networks under random failure and targeted attacks. Using Erdős-Rényi networks and scale-free networks as examples, we find that the same network can react quite differently, depending on the type of attack. Moreover, for scale-free networks, the interdependent system sometimes displays very different behaviour to the equivalent non-interdependent network.
K-theory for semigroup C*-algebras

We compute K-theory for semigroup C*-algebras. First, we prove a general theorem which covers a large class of cancellative semigroups. Our result describes the K-theory of reduced semigroup C*-algebras in terms of the K-theory for the reduced group C*-algebras of certain groups which are typically easier to handle. Then we apply our result to specific semigroups from algebraic number theory.
CONSTRUCTION OF BOUNDARY LAYER ELEMENTS FOR SINGULARLY PERTURBED CONVECTION-DIFFUSION EQUATIONS AND L- STABILITY ANALYSIS

It has been demonstrated that the ordinary boundary layer elements play an essential role in the finite element approximations for singularly perturbed problems producing ordinary boundary layers. Here we revise the element so that it has a small compact support and hence the resulting linear system becomes sparse, more precisely, block tridiagonal. We prove the validity of the revised element for some singularly perturbed convection-diffusion equations via numerical simulations and via the H1approximation error analysis. Furthermore due to the compact structure of the boundary layer we are able to prove the L2stability analysis of the scheme and derive the L2error approximations.
BAYESIAN ANALYSIS OF METAPOPULATION DATA

A Bayesian approach is used to develop a method for fitting a metapopulation model (the incidence function model) to data on habitat patch occupancy, providing esti- mates of the five model parameters. Parameter estimation is carried out using a Markov chain Monte Carlo sampler, and data augmentation is used to include the effect of missing data in the analysis. The Bayesian approach allows us to take into account uncertainty about the parameter estimates when making predictions with the model. We demonstrate the methods of parameter estimation and prediction with simulated data. We first simulated metapopulation dynamics in real habitat patch networks with given parameter values and sampled the simulated data. Parameters were estimated both from full data sets, and from data sets with data for many years treated as missing. These estimates were then used to predict the distribution of time to extinction in modified networks, where patch areas had been reduced so that the real parameter values led to metapopulation extinction within ;30 yr. We were successfully able to fit the model and found that, in some cases, the predictions can be sensitive to one of the parameters.
Name of the Project: Delving Deeper: Lexicographic Description of Syntactic and Semantic Properties of Czech Verbs

Information on syntactic and semantic properties of verbs, which are traditionally considered to be the center of a sentence, plays a key role in many rule-based NLP tasks such as information retrieval, text summarization, question answering, machine translation, etc. Moreover, theoretical aspects of valency and its adequate lexicographic representation are also challenging. The proposed project focuses on a theoretically adequate description of advanced language phenomena related to the valency behavior of verbs. Changes in valency structure of verbs belong to such phenomena – whereas various types of changes in valency structure of verbs, based on different language means (grammatical, syntactic or semantic), attract the attention of linguists for decades (see Section 1), their adequate lexicographic representation is still missing. For studying such verbal properties, a concept of a (type) situation – consisting of a set of participants that are characterized by particular semantic properties and connected by particular relations – plays a key role. Thus, mapping participants onto valency complementations and their semantic characteristics are crucial for a lexicographic processing of language data. The project takes advantage of an existing Valency lexicon of Czech verbs VALLEX. VALLEX provides the core valency information, i.e. information on the combinatorial potential of verbs in their particular senses. The goals of the project are two fold. It aims at the deepening of the theoretical insight into various phenomena at the syntax-semantics interface (including the contrastive perspective). Moreover, it attempts to substantially qualitatively and quantitatively enhance the publicly available electronic language resource.
Heavy traffic limit for processor sharing queue with soft deadlines

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Topological dynamics and group theory

We prove, using notions and techniques of topological dynamics, that a nonamenable group contains a finitely-generated subgroup of exponential growth. We also show that a group which belongs to a certain class, defined by means of topological dynamical properties, always contains a free subgroup on two generators. Topological dynamics can be viewed as a theory of representations of groups as homeomorphism groups. In this paper we want to emphasize this point of view and to show that information about the structure of a group can be obtained by studying such representations. One illustration of this method is the characterization obtained in [7] of amenable groups as groups which admit no nontrivial strongly proximal flow. (See definitions below.) Furthermore this method yields results which do not explicitly involve notions from topological dynamics, for example using the above characterization of amenable groups we prove the theorem that a nonamenable group has a finitely generated subgroup of exponential growth. (This last result also follows from the main theorem in [8, p. 150] and Lemma 5 in [9].) The paper is arranged as follows. In § 1 we define the necessary notions from topological dynamics. In particular strongly proximal, totally proximal and extremely proximal flows are defined. In the second section we prove, using the notion of a strongly proximal flow, that a nonamenable group contains a finitely generated subgroup of exponential growth [9]. In the third section we show that an extremely proximal flow is both strongly proximal and totally proximal. We show that a group which has a nontrivial extremely proximal flow contains a free subgroup on two generators. Finally we show by means of examples that strong proximality does not imply total proximality nor does total proximality imply strong proximality. I wish to thank Professor H. Furstenberg for his help and advice. 1. Definitions. A flow is a pair (T, X) consisting of a locally compact topolog-ical group T and a compact Hausdorff space X, equipped with a continuous function T x X —» X, denoted it, x) —► tx, which satisfies the following conditions: Fot all s, t eT and for all x e X, ist)x = sitx) and for all x e X ex = x,
Örgütsel Vatandaşlık Davranışı Çalışmaları Üzerine Eleştirel Bir Çözümleme: Teleolojik ve Epistemolojik Kaygılar

Calisanlarin islerindeki rollerinin otesinde sergiledikleri yardim etme davranislari ve kolaylastirici cabalar orgutsel davranis yazininda orgutsel vatandaslik davranisi olarak adlandirilmaktadir. Orgutsel vatandaslik davranisi konusu ozellikle son on bes-yirmi yillik donemde bircok arastirmacinin ilgisini cekmis, bu konunun onculleri ve sonuclari uzerine bircok arastirma yapilmistir. Ancak yapilan arastirmalarin sonuclari incelendiginde, kavramin genel gecer bazi kabuller uzerine oturtuldugu, kuramsal, kavramsal ya da felsefi temelde tartisilmadigi gorulmektedir. Bu acigi bir olcude kapatabilmek amaciyla yapilan bu arastirmanin bulgulari teleolojik ve epistemolojik temelde orgutsel vatandaslik davranisi konusunda bazi kaygilarin olabilecegini gostermektedir