Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependency-based Semantic Analysis of Natural-language Text

Semantic roles, logical relations such as Agent or Instrument that hold between events and their participants and circumstances, need to be determined automatically by several types of applications in natural language processing. This process is referred to as semantic role labeling. This dissertation describes how to construct statistical models for semantic role labeling of English text, and how role semantics is related to surface syntax. It is generally agreed that the problem of semantic role labeling is closely tied to syntactic analysis. Most previous implementations of semantic role labelers have used constituents as the syntactic input, while dependency representations, in which the syntactic structure is viewed as a graph of labeled word-to-word relations, has received very little attention in comparison. Contrary to previous claims, this work demonstrates empirically that dependency representations can serve as the input for semantic role labelers and achieve similar results. This is important theoretically since it makes the syntactic-semantic interface conceptually simpler and more intuitive, but also has practical significance since there are languages for which constituent annotation is infeasible. The dissertation devotes considerable effort to investigating the relation between syntactic representation and semantic role labeling performance. Apart from the main result that dependency-based semantic role labeling rivals its constituent-based counterpart, the empirical experiments support two findings: First, that the dependency-syntactic representation has to be well-designed in order to achieve a good performance in semantic role labeling. Secondly, that the choice of syntactic representation affects the substages of the semantic role labeling task differently; above all, the role classification task, which relies strongly on lexical features, is shown to benefit from dependency representations. The systems presented in this work have been evaluated in two international open evaluations, in both of which they achieved the top result. (Less)
Towards Inferring Web Page Relevance — An Eye-Tracking Study

We present initial results from a project, in which we examined feasibility of inferring web page relevance from eye-tracking data. We conduced a controlled, lab-based Web search experiment, in which participants conducted assigned information search tasks on Wikipedia. We performed analyses of variance as well as employed classification algorithms in order to predict user perceived Web page relevance. Our findings demonstrate that it is feasible to infer document relevance from eye-tracking data on Web pages. The results indicate that eye fixation duration, pupil size and the probability of continuing reading are good predictors of Web page relevance. Our work extends results from previous studies of text document search that were conducted under more constrained human-information interaction.
Isbell Duality for Refinement Types

Any refinement system (= functor) has a full and faithful embedding into the refinement system of presheaves over categories, by a simultaneous generalization of the Yoneda embedding and of the slice representation of a category. Motivated by an analogy between side-effects in programming and "context effects" in proof theory, we study logical aspects of this embedding, as well as of an associated "opposite embedding" (= embedding of the opposite functor). We expose a duality between these two embeddings mediated by negation into a "universal refinement" (a presheaf associated with the original refinement system), and use this to derive two interesting formulas for the embedding of a pushforward, which decompose it either as the negation of a pullback of a negation, or as the double-negation of a pushforward.
An overview of Altera SDK for OpenCL: A user perspective

In recent years there has been a great interest in High Level Synthesis (HLS) CAD tools to raise the level of design abstraction, reduce design time, rapidly explore the design space and fully exploit the multi-million gate heterogeneous hardware platforms provided by dramatic improvements in integrated circuits. Open Computing Language (OpenCL) is a well-known standard for heterogeneous computing. The Altera SDK for OpenCL is used to convert OpenCL code to kernels that can be run on an FPGA accelerator card. It is a recently introduced HLS CAD tool that allows for the potential to convert existing, or create new C/C++ programs that utilize dedicated hardware to execute specific applications much faster and more efficient than current computer systems, whether single core or multi-core. This can all be done without the knowledge of FPGAs, VHDL, or Verilog as the SDK converts the OpenCL files into Verilog models that are then compiled into FPGA hardware. This paper presents a user-centric overview of Altera SDK for OpenCL. As a first step to achieve the best speedup, the candidate algorithm for acceleration must be analyzed to check if it is inherently parallelizable. The key features such as designing appropriate OpenCL kernels and host program, their compilation, execution and testing are summarized. A working example for accelerating a simple matrix multiplication algorithm is described. Our motivation is to provide the novice users with a useful tutorial that will enable them to quickly become proficient in using this important HLS CAD tool. To our knowledge, such a user-centric tutorial has not been presented so far in the literature.
The cost of privacy: destruction of data-mining utility in anonymized data publishing

Re-identification is a major privacy threat to public datasets containing individual records. Many privacy protection algorithms rely on generalization and suppression of "quasi-identifier" attributes such as ZIP code and birthdate. Their objective is usually syntactic sanitization: for example, k-anonymity requires that each "quasi-identifier" tuple appear in at least k records, while l-diversity requires that the distribution of sensitive attributes for each quasi-identifier have high entropy. The utility of sanitized data is also measured syntactically, by the number of generalization steps applied or the number of records with the same quasi-identifier. In this paper, we ask whether generalization and suppression of quasi-identifiers offer any benefits over trivial sanitization which simply separates quasi-identifiers from sensitive attributes. Previous work showed that k-anonymous databases can be useful for data mining, but k-anonymization does not guarantee any privacy. By contrast, we measure the tradeoff between privacy (how much can the adversary learn from the sanitized records? ) and utility, measured as accuracy of data-mining algorithms executed on the same sanitized records. For our experimental evaluation, we use the same datasets from the UCI machine learning repository as were used in previous research on generalization and suppression. Our results demonstrate that even modest privacy gains require almost complete destruction of the data-mining utility. In most cases, trivial sanitization provides equivalent utility and better privacy than k-anonymity, l-diversity, and similar methods based on generalization and suppression.
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods

This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.
Mobilizing the TV ecosystem Making mobile TV viable by involving external stakeholders in prototype testing

In order to bring mobile TV applications to the market, service providers have to deal with a large set of external stakeholders, such as broadcasters, media houses an d operators. Such external stakeholders should be involved early in the design cycle in order to get their commitment for commerci alization. In this paper, we describe a case in which external st akeholders are involved half-way through the design cycle, that is , while testing the prototype of a mobile TV application. We explor e whether greater satisfaction and adoption levels of stakeho lders during prototype testing increase their willingness to be involved in commercializing the service concept. We analyze sur vey data, but also log data on adoption levels. While reported sa tisfaction and adoption levels from the survey are positively corr elated with the intention to be involved in commercialization and expected market success, this is not the case for the log da ta on adoption levels. Our results contribute to academic discussi on on how to involve stakeholders in design research. Keywords-mobile services; mobile TV; stakeholder analysis; business models; design science; design research
Using Brain Stimulation to Enhance Working Memory: A Charged Topic

Although working memory (WM) training programs consistently result in improvement on the trained task, benefit is typically short-lived and extends only to tasks very similar to the trained task. Pairing repeated performance of a WM task with brain stimulation may encourage plasticity in brain networks involved in WM task performance, thereby improving the training benefit. In the current study, transcranial direct current stimulation (tDCS) was paired with performance of a WM task. In Experiment 1, participants performed a spatial locationmonitoring n-back during stimulation, while Experiment 2 used a verbal identity-monitoring nback. In each experiment, participants received either active (2.0 mA) or sham (0.1 mA) stimulation with the anode placed over either the right or the left dorsolateral prefrontal cortex (DLPFC) and the cathode placed extracephalically. In Experiment 1, only participants receiving active stimulation with the anode placed over the right DLPFC showed marginal improvement on the trained spatial n-back, which did not extend to a near transfer (verbal n-back) or far transfer (fluid intelligence) task. In Experiment 2, both left and right anode placements led to improvement, and right DLPFC stimulation resulted in numerical (though not sham-adjusted) improvement on the near transfer (spatial n-back) and far transfer (fluid intelligence) task.
Traffic Engineering an Operational Network with the TOTEM Toolbox

We explain how the TOTEM toolbox can be used to engineer an operational network. TOTEM is an open source TOolbox for Traffic Engineering Methods which covers IP- based and MPLS-based intradomain traffic engineering (TE) algorithms, but also interdomain TE. In this paper, we use the toolbox as an off-line simulator to optimise the traffic of an operational network. To help an operator choose between an IP-based or MPLS-based solution, or find the best way to load- balance a network for a given traffic, our case study compares several IP and MPLS routing algorithms, evaluates the impact of hot-potato routing on the intradomain traffic matrix, and analyses the worst-case link failure. This study reveals the power of a toolbox that federates many traffic engineering algorithms.
Nonlinear Liquidity Adjustments in the Euro Area Overnight Money Market

The market-oriented approach promoted by the European Central Bank in the design of its refinancing operations creates incentives to credit insitutions to use actively the interbank market to manage their liquidity needs. In this context, we examine the ability of the overnight segment to guarantee the timely provision of unsecured funds to banks to smoothly absorb their liquidity shocks. This paper specifically focuses on the speed of reversion of transaction costs and available depth to their equilibrium levels in this market for overnight unsecured funds from 4 September 2000 to 31 December 2007. The reported evidence points to time-varying liquidity adjustments and identifies liquidity, market activity and the institutional setting of the ECB’s refinancing operations as significant determinants of the observed resiliency regimes. Our analysis also shows how the speed of mean reversion of market liquidity, by affecting the level and the volatility of the overnight market rate, also affects the anchoring of the yield curve in the euro area. JEL Classification: C22, C25, G01, G10, G21, E52
Complex networks : Models and dynamics

This report is a brief introduction to complex networks. It describes the most important models for random, small world, and scale-free networks, and discusses their properties. Measures such as the clustering coefficient and the local efficiency are defined, and dynamical properties such as network searchability and synchronization are briefly discussed. The report provides necessary background material for further studies on how the networks in a network-based defence should be designed in order to facilitate information spreading and synchronization.
Robust structure from motion using motion parallax

An efficient and geometrically intuitive algorithm for reliably interpreting the image velocities of moving objects in 3-D is presented. It is well known that under a weak perspective the image motion of points on a plane can be characterized by an affine transformation. It is shown that the relative image motion of a nearby non-coplanar point and its projection on the plane is equivalent to motion parallax, and because it is independent of view rotations it is a reliable geometric cue to 3-D shape and viewer/object motion. The authors summarize why structure from motion algorithms are often very sensitive to errors in the measured image velocities and then show how to efficiently and reliably extract an incomplete qualitative solution. They also show how to augment this into a complete solution if additional constraints or views are available. A real-time example is presented in which the 3-D visual interpretation of hand gestures or a hand-held object is used as part of a man-machine interface. This is an alternative to the Polhemus coil instrumented Dataglove commonly used in sensing manual gestures. <<ETX>>
The hyperdyadic index and generalized indexing and query with PIQUE

Many scientists rely on indexing and query to identify trends and anomalies within extreme-scale scientific data. Compressed bitmap indexing (e.g., FastBit) is the go-to indexing method for many scientific datasets and query workloads. Recently, the ALACRITY compressed inverted index was shown as a viable alternative approach. Notably, though FastBit and ALACRITY employ very different data structures (inverted list vs. bitmap) and binning methods (bit-wise vs. decimal-precision), close examination reveals marked similarities in index structure. Motivated by this observation, we ask two questions. First, "Can we generalize FastBit and ALACRITY to an index model encompassing both? " And second, if so, "Can such a generalized framework enable other, new indexing methods? " This paper answers both questions in the affrmative. First, we present PIQUE, a Parallel Indexing and Query Unified Engine, based on formal mathematical decomposition of the indexing process. PIQUE factors out commonalities in indexing, employing algorithmic/data structure "plugins" to mix orthogonal indexing concepts such as FastBit compressed bitmaps with ALACRITY binning, all within one framework. Second, we define the hyperdyadic tree index, distinct from both bitmap and inverted indexes, demonstrating good index compression while maintaining high query performance. We implement the hyperdyadic tree index within PIQUE, reinforcing our unified indexing model. We conduct a performance study of the hyperdyadic tree index vs. WAH compressed bitmaps, both within PIQUE and compared to FastBit, a state-of-the-art bitmap index system. The hyperdyadic tree index shows a 1.14-1.90x storage reduction vs. compressed bitmaps, with comparable or better query performance under most scenarios tested.
Ethics, Political Perspective Taking, and Digital Games

Ethics, Political Perspective Taking, and Digital Games Colin Fitzpatrick, Alexis Hope, Salwa Barhumi, Yanna Krupnikov and Matthew W. Easterday Northwestern University Author Note Colin Fitzpatrick, School of Communication, Northwestern University; Alexis Hope, School of Communication, Northwestern University; Salwa Barhumi, School of Education and Social Policy, Northwestern University; Matthew W. Easterday, School of Education and Social Policy, Northwestern University; Yanna Krupnikov, Department of Political Science, Northwestern University Correspondence concerning this article should be addressed to: Colin Fitzpatrick, School of Communication, Frances Searle, 2240 Campus Drive, Northwestern University, Evanston, Illinois 60208 Email: fitzcn@u.northwestern. edu
Recent Progress in Learning Decision Lists by Prepending Inferred Rules

This paper describes a new algorithm for learning decision lists that operates by prepending successive rules to the front of the list under construction. By contrast, the classic algorithm operates by appending successive rules to the end of the decision list under construction. The new algorithm is demonstrated in the majority of cases to produce smaller classifiers that provide improved predictive accuracy in less time than the classic algorithm.
The Research of the Raptor Fountain Code in Shortwave Communication System

Compared with the traditional communication equipment, short wave communication equipment has strong anti-destroying ability. It can greatly reduce the complexity during the data transfer process. However, by the time-variation characteristic and the influence of the multipath interference, short wave communication system has some deficiencies in transmission. Therefore, it will be of great significance if we study the problems with great efforts and find a solution. The fountain code in the short wave broadband OFDM (Orthogonal Frequency Division Multiplexing) communication system will be introduced. And an excellent concatenated code composed of the Turbo and LDPC (Low Density Parity Check Code) codes will be used to run a pre-coding stage in this paper. The simulation results show that the concatenated codes are the mirror in the realization of long codes and hold the outstanding correction capability for random errors.
Finite-rate feedback of input covariance matrices in MIMO systems

We analyze feedback of the optimal input covariance matrix Q from a channel-aware multi-antenna receiver to a multi-antenna transmitter using Nf bits per block. The matrix Q is allowed to have real or complex entries and its rank is allowed to be either fixed or variable. By unravelling the geometry of the quantization spaces involved, we obtain the normalized volume of geodesic balls and use these to evaluate the distortion suffered in quantizing information using different code books. The difference in ergodic capacity between the finite and infinite rate feedback cases is bounded as O(2− Nf over N) where N is the dimension of the quantization manifold. The results apply to both the MIMO link and the MIMO MAC channels, and do not depend on the specific distribution of the channel matrix.
Learner Corpora and the Acquisition of Word Order : A Study of the Production of Verb-Subject Structures in L 2 English 1

Though there is a long tradition of research into word order phenomena in Second Language (L2) acquisition, this area of enquiry has recently been given a new impetus both from theoretical developments on the form-function interplay and, crucially, from the emergence of learner corpora This paper focuses on a particular phenomenon which has received considerable attention in the literature: the production of postverbal subjects in L2 English by L1 speakers of languages characterised as allowing ‘free inversion’ of the subject in V(erb) S(ubject) structures, such as Spanish and Italian. In previous research emphasis has been placed on the learners’ production of ungrammatical VS order (see for instance Rutherford, 1989 Zobl, 1989 and, more recently, Oshita, 2004). Our approach, however, seeks to identify the syntactic, semantic and pragmatic conditions, as well as conditions deriving from processing mechanisms, under which learners produce inverted subjects, regardless of errors resulting from the syntactic encoding of those notions. We analyse VS vs. SV structures in the Italian and Spanish subcorpus of ICLE (Grange et al., 2002) and we compare our results with preliminary results obtained from a similar native English corpus (LOCNESS). Thus, we incorporate some of the fundamental tenets of what is known as Contrastive Interlanguage Approach (see, e.g. Granger ,1996 and Gilquin, 2001), which establishes comparisons between: (a) native and non-native data, and (b) different non-native data. Our main purpose is to see if the properties that govern the occurrence of postverbal Ss in native English, as currently analysed in the theoretical and descriptive literature, are the same as those operating in the non-native grammars of Spanish and Italian speakers We first examine the properties of VS order in English vs. Spanish/Italian (Section 2). In Section 3, we review previous L2 studies on postverbal Ss. Our hypotheses are presented in Section 4. Section 5 describes the method used to extract and code data from the corpus and their statistical treatment. Results are presented and
Background Segmentation Using Spatial-Temporal Multi-Resolution MRF

Robust and accurate background segmentation is crucial for surveillance applications and is a key element in visual tracking, layer-based compression, and silhouette-based 3D reconstruction. In this paper, we present a novel spatial-temporal model that describes the appearance and dynamics of background scenes at multiple resolutions. We propose a time-dependent Markov Random Field (MRF) to represent the state of foreground and background at each pixel in the spatial-temporal pyramid. Pixels are linked spatially and temporally across frames. The probability of adding/deleting a foreground object is calculated by online learning algorithm and is used as prior information in computing foreground label. We use Gibbs Sampling to solve the MRF in a Maximum A Posterior (MAP) framework. Experimental results show that this real-time algorithm is able to segment the foreground object accurately from videos and more resilient to distractions such as imaging noise, illumination changes, camera shakes, and random motion in the scene.
Some Observations from the Scrutiny of Different Methods used for Iris Recognition

The objective of this work is to determine the ability of methods that are used for iris recognition. Because of unique characteristics of iris recognition have mesmerize more attention of researchers, which make iris identification system development rapidly. In whole process of iris identification various methods are available. Since the techniques which we are considering is the first step of iris image processing, the accuracy and quality of location will directly affect the ultimate results of iris recognition. This paper will summarize the ideas of the existed iris techniques; finally, there is a discussion on some of the challenges encountered by better techniques when operating in a real-world environment and some of the methods used to address these challenges.