Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Natural Language Requirements Quality Using Workflow Patterns

Natural language (NL) requirements are usually humancentric and therefore error-prone and inaccurate. In order to improve the 3Cs of natural language requirements, namely Consistency, Correctness and Completeness, in this paper we propose a systematic pattern matching approach supporting both NL requirements modeling and inconsistency, incorrectness and incompleteness analysis among requirements. We first use business process modeling language to model NL requirements and then develop a formal language — Workflow Patterns-based Process Language (WPPL) — to formalize NL requirements. We leverage workflow patterns to perform two-level 3Cs checking on the formal representation based on a coherent set of checking rules. Our approach is illustrated through a real world financial service example — Global Equity Trading System (GETS). key words: requirements analysis, correctness, consistency, workflow patterns, pattern matching
TVSum: Summarizing web videos using titles

Video summarization is a challenging problem in part because knowing which part of a video is important requires prior knowledge about its main topic. We present TVSum, an unsupervised video summarization framework that uses title-based image search results to find visually important shots. We observe that a video title is often carefully chosen to be maximally descriptive of its main topic, and hence images related to the title can serve as a proxy for important visual concepts of the main topic. However, because titles are free-formed, unconstrained, and often written ambiguously, images searched using the title can contain noise (images irrelevant to video content) and variance (images of different topics). To deal with this challenge, we developed a novel co-archetypal analysis technique that learns canonical visual concepts shared between video and images, but not in either alone, by finding a joint-factorial representation of two data sets. We introduce a new benchmark dataset, TVSum50, that contains 50 videos and their shot-level importance scores annotated via crowdsourcing. Experimental results on two datasets, SumMe and TVSum50, suggest our approach produces superior quality summaries compared to several recently proposed approaches.
Automatic image annotation by incorporating feature hierarchy and boosting to scale up SVM classifiers

The performance of image classifiers largely depends on two inter-related issues:(1)suitable frameworks for image content representation and automatic feature extraction;(2) effective algorithms for image classifier training and feature subset selection. To address the first issue, a multiresolution grid-based framework is proposed for image content representation and feature extraction to bypass the time-consuming and erroneous process for image segmentation. To address the second issue, a hierarchical boosting algorithm is proposed by incorporating feature hierarchy and boosting to scale up SVM image classifier training in high-dimensional feature space. The high-dimensional multi-modal heterogeneous visual features are partitioned into multiple low-dimensional single-modal homogeneous feature subsets and each of them characterizes certain visual property of images. For each homogeneous feature subset, principal component analysis (PCA)is performed to exploit the feature correlations and a weak classifier is learned simultaneously. After the weak classifiers for different feature subsets and grid sizes are available, they are combined to boost an optimal classifier for the given object class or image concept, and the most representative feature subsets and grid sizes are selected. Our experiments on a specific domain of natural images have obtained very positive results.
Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system. Dominant terms in the Koopman expansion are typically computed using dynamic mode decomposition (DMD). DMD uses linear measurements of the state variables, and it has recently been shown that this may be too restrictive for nonlinear systems. Choosing the right nonlinear observable functions to form an invariant subspace where it is possible to obtain linear reduced-order models, especially those that are useful for control, is an open challenge. Here, we investigate the choice of observable functions for Koopman analysis that enable the use of optimal linear control techniques on nonlinear problems. First, to include a cost on the state of the system, as in linear quadratic regulator (LQR) control, it is helpful to include these states in the observable subspace, as in DMD. However, we find that this is only possible when there is a single isolated fixed point, as systems with multiple fixed points or more complicated attractors are not globally topologically conjugate to a finite-dimensional linear system, and cannot be represented by a finite-dimensional linear Koopman subspace that includes the state. We then present a data-driven strategy to identify relevant observable functions for Koopman analysis by leveraging a new algorithm to determine relevant terms in a dynamical system by ℓ1-regularized regression of the data in a nonlinear function space; we also show how this algorithm is related to DMD. Finally, we demonstrate the usefulness of nonlinear observable subspaces in the design of Koopman operator optimal control laws for fully nonlinear systems using techniques from linear optimal control.
Atoms embedded in an electron gas: Beyond the local-density approximation.

Etude des proprietes de la liaison chimique des atomes appartenant aux trois premieres lignes du tableau periodique des elements, dans le cadre du modele de l'atome plonge dans le jellium. Les structures electroniques sont resolues de facon auto-coherente en utilisant la theorie de la fonctionnelle de la densite. L'extraction des proprietes de la liaison est effectuee dans le cadre de la theorie du milieu effectif. On insiste sur la recherche systematique des tendances le long des series 2p, 3P, et 3d et sur les effets dus aux differents types d'approximations pour l'echange electronique et la correlation. Les resultats donnent un apercu de la raison pour laquelle l'approximation de la densite locale pour les solides sur-evalue les energies de cohesion, mais donne d'assez bonnes valeurs des constantes de reseau et des modules elastiques
Fuzzy-Model-Based Robust Fault Detection With Stochastic Mixed Time Delays and Successive Packet Dropouts

This paper is concerned with the network-based robust fault detection problem for a class of uncertain discrete-time Takagi-Sugeno fuzzy systems with stochastic mixed time delays and successive packet dropouts. The mixed time delays comprise both the multiple discrete time delays and the infinite distributed delays. A sequence of stochastic variables is introduced to govern the random occurrences of the discrete time delays, distributed time delays, and successive packet dropouts, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fuzzy fault detection filter such that the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fuzzy fault detection filters, and then, the corresponding solvability conditions for the desired filter gains are established. In addition, the optimal performance index for the addressed robust fuzzy fault detection problem is obtained by solving an auxiliary convex optimization problem. An illustrative example is provided to show the usefulness and effectiveness of the proposed design method.
Horizontal eye movement networks in primates as revealed by retrograde transneuronal transfer of rabies virus: Differences in monosynaptic input to “slow” and “fast” abducens motoneurons

The sources of monosynaptic input to “fast” and “slow” abducens motoneurons (MNs) were revealed in primates by retrograde transneuronal tracing with rabies virus after injection either into the distal or central portions of the lateral rectus (LR) muscle, containing, respectively, “en grappe” endplates innervating slow muscle fibers or “en plaque” motor endplates innervating fast fibers. Rabies uptake involved exclusively motor endplates within the injected portion of the muscle. At 2.5 days after injections, remarkable differences of innervation of slow and fast MNs were demonstrated. Premotor connectivity of slow MNs, revealed here for the first time, involves mainly the supraoculomotor area, central mesencephalic reticular formation, and portions of medial vestibular and prepositus hypoglossi nuclei carrying eye position and smooth pursuit signals. Results suggest that slow MNs are involved exclusively in slow eye movements (vergence and possibly smooth pursuit), muscle length stabilization and gaze holding (fixation), and rule out their participation in fast eye movements (saccades, vestibulo‐ocular reflex). By contrast, all known monosynaptic pathways to LR MNs innervate fast MNs, showing their participation in the entire horizontal eye movements repertoire. Hitherto unknown monosynaptic connections were also revealed, such as those derived from the central mesencephalic reticular formation and vertical eye movements pathways (Y group, interstitial nucleus of Cajal, rostral interstitial nucleus of the medial longitudinal fasciculus). The different connectivity of fast and slow MNs parallel differences in properties of muscle fibers that they innervate, suggesting that muscle fibers properties, rather than being self‐determined, are the result of differences of their premotor innervation. J. Comp. Neurol. 498:762–785, 2006. © 2006 Wiley‐Liss, Inc.
Genetic Diversity of Brazilian Bovine Pestiviruses Detected Between 1995 and 2014

Pestivirus infections in ruminants result in significant economic losses worldwide. The aetiological agents are three species from the genus Pestivirus, family Flaviviridae, including bovine viral diarrhoea virus type 1 (BVDV-1), BVDV-2, border disease virus (BDV), and an atypical pestivirus named HoBi-like pestivirus. In this study, eighty-nine pestivirus isolates that were collected in Brazil between 1995 and 2014 and that originated from either cattle, fetal bovine serum (FBS) or as cell culture contaminants were genotyped based on a comparison of gene sequences from their 5' untranslated regions (5'UTR), N-terminal autoprotease (Npro ) and envelope glycoprotein 2 (E2). Of these isolates, 53.9% of the sequences were genotyped as BVDV-1, 33.7% as BVDV-2 and 12.4% as HoBi-like pestivirus. The prevalence of subgenotypes within the species was as follows: BVDV-1a (35.9%), BVDV-2b (31.4%), BVDV-1b (10.1%), BVDV-1d (6.7%), BVDV-2c (2.2%) and BVDV-1e (1.1%). BVDV-2c and BVDV-1e were detected for the first time in Brazil. This study revealed extensive genetic diversity among Brazilian pestivirus isolates, and the combination of pestiviruses that was detected is unique to Brazil. This information may serve as a foundation for designing and evaluating diagnostic tools and in the development of more effective vaccines; therefore, it may potentially contribute to pestivirus control and eradication.
Systematic Review of the Association between Dairy Product Consumption and Risk of Cardiovascular-Related Clinical Outcomes

The objective of this systematic review was to determine if dairy product consumption is detrimental, neutral, or beneficial to cardiovascular health and if the recommendation to consume reduced-fat as opposed to regular-fat dairy is evidence-based. A systematic review of meta-analyses of prospective population studies associating dairy consumption with cardiovascular disease (CVD), coronary artery disease (CAD), stroke, hypertension, metabolic syndrome (MetS), and type 2 diabetes (T2D) was conducted on the basis of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Quality of evidence was rated by using the Grading of Recommendations Assessment, Development, and Evaluation scale. High-quality evidence supports favorable associations between total dairy intake and hypertension risk and between low-fat dairy and yogurt intake and the risk of T2D. Moderate-quality evidence suggests favorable associations between intakes of total dairy, low-fat dairy, cheese, and fermented dairy and the risk of stroke; intakes of low-fat dairy and milk and the risk of hypertension; total dairy and milk consumption and the risk of MetS; and total dairy and cheese and the risk of T2D. High- to moderate-quality evidence supports neutral associations between the consumption of total dairy, cheese, and yogurt and CVD risk; the consumption of any form of dairy, except for fermented, and CAD risk; the consumption of regular- and high-fat dairy, milk, and yogurt and stroke risk; the consumption of regular- and high-fat dairy, cheese, yogurt, and fermented dairy and hypertension risk; and the consumption of regular- and high-fat dairy, milk, and fermented dairy and T2D risk. Data from this systematic review indicate that the consumption of various forms of dairy products shows either favorable or neutral associations with cardiovascular-related clinical outcomes. The review also emphasizes that further research is urgently needed to compare the impact of low-fat with regular- and high-fat dairy on cardiovascular-related clinical outcomes in light of current recommendations to consume low-fat dairy.
Real-time BTF Rendering

The Bidirectional Texture Function (BTF) is a suitable representation for the appearance of highly detailed surface structures under varying illumination and viewing conditions. Since real-time rendering of the full BTF data via linear interpolation is not feasible on current graphics hardware due to its huge size, suitable approximations are required in order to reduce the amount of data and to exploit the features of current graphics hardware. In this paper we exploit the recently proposed Local Principal Component Analysis (LPCA) compression which provides a reasonable trade-off between visualquality, rendering speed and size of the representation and present a new rendering method which is approximately three times faster than the originally proposed method. This is achieved by reparameterizing and rearranging the BTF-data appropriately so that built-in hardware interpolation between the values of the discrete LPCA representation can be exploited.
Scalable state replication with weak consistency

Initial work on peer-to-peer systems has focused on findinginformation in large-scale decentralized systems. Morerecently, the focus has shifted to sharing information in suchcontexts. Meeting this goal in environments in which manydata replicas change their state frequently is very challenging.The objectives of the work described in this paper is two-fold:designing mechanisms that allow information lookupbased not only on unique data keys, but also on meta data,and enabling efficient and scalable implementation of datasharing by providing a notion of consistency weaker than existentproposals. The paper formalizes the notion of weakconsistency in peer-to-peer environments, and presents detailedimplementations of our information lookup and datasharing mechanisms.
Extended ASP Tableaux and rule redundancy in normal logic programs1

Abstract We introduce an extended tableau calculus for answer set programming (ASP). The proof system is based on the ASP tableaux defined in the work by Gebser and Schaub (Tableau calculi for answer set programming. In Proceedings of the 22nd International Conference on Logic Programming (ICLP 2006), S. Etalle and M. Truszczynski, Eds. Lecture Notes in Computer Science, vol. 4079. Springer, 11–25) with an added extension rule. We investigate the power of Extended ASP Tableaux both theoretically and empirically. We study the relationship of Extended ASP Tableaux with the Extended Resolution proof system defined by Tseitin for sets of clauses, and separate Extended ASP Tableaux from ASP Tableaux by giving a polynomial-length proof for a family of normal logic programs {Φn} for which ASP Tableaux has exponential-length minimal proofs with respect to n. Additionally, Extended ASP Tableaux imply interesting insight into the effect of program simplification on the lengths of proofs in ASP. Closely related to Extended ASP Tableaux, we empirically investigate the effect of redundant rules on the efficiency of ASP solving.
Mechanisms of Sentence Processing: Assigning Roles to Constituents of Sentences

Abstract : How do we assign nouns correctly to their underlying case roles in English, and how do we select an appropriate verb frame to assign these nouns to? How do we know whether a noun phrase is a modifier of a preceding noun phrase or an argument of the verb? How do we select the correct meaning of each noun in the sentence, and how do we allow content to modulate its meaning? How do we know how to handle these new nouns and verbs? In this article we describe a simulation model that addresses these questions from a perspective quite different from the conventional perspective found in Computational Linguistics. Words are treated as patterns of activation, and knowledge about them is stored in distributed form, in the connections in a large network of simple neutron-like processing units. The model exhibits considerable facility in dealing with the problems of frame selection, role assignment, disambiguation, etc, and suggests a natural way to resolve unappealing aspects of the idea that there is a fixed set of individuated case roles. So far, our simulation model can only process one clause sentences. Possible extensions to multi-clause sentences are described.
Drawing the betweenness of place

This research explores the practice of creativity as a means to illuminating the significant yet under explored concept of betweenness. It consists of a theoretical interpretation of the concept and its intersection with related concepts, augmented by interview material drawn from participants experiencing the betweenness of everyday journeying. Research participants were drawn from the Tasmanian arts community and included practitioners of visual arts, music, dance, literature, architecture, poetry and film. Creative production itself involves crossings-over; attempts to transcend the mundane by entering emotional and intellectual terrain that is unfamiliar and of unknown status – between what is known and what is yet to be known. For this reason, art practitioners were deemed to be particularly suited to the research needs of the project. The thesis explores participants’ descriptions of their everyday journeys between two places in order to answer the following questions. Is the inchoate experience, the numinous sensation that seems to characterise commonly undertaken journeys between two places, the emotional essence of betweenness? Given that the inchoate and numinous that qualify betweenness reside at the limits of representation, how might one represent these experiences? This might be described as ‘representing the unrepresentable – without representing it’. The device that I use is the practice of drawing. Rather than representing the betweenness, I use the practice of drawing as a device to ‘give presence’ to the betweenness. The research uses a phenomenological approach to elucidate individuals’ perceptions of their journeys between two places, and then gathers observations into groups which, together with a review of the literature and autoethnographic explorations, reveal several of many possible components of betweenness. Taken together these comprise a drawing of the betweenness of place. The responses are visual and evocative while also affective in the more discursive sense of the term. Stress is on the process, then, and no ‘hard, definitive’ conclusion as to the nature of betweenness is reached.
Political Speech Generation

In this report we present a system that can generate political speeches for a desired political party. Furthermore, the system allows to specify whether a speech should hold a supportive or opposing opinion. The system relies on a combination of several state-of-the-art NLP methods which are discussed in this report. These include n-grams, Justeson & Katz POS tag filter, recurrent neural networks, and latent Dirichlet allocation. Sequences of words are generated based on probabilities obtained from two underlying models: A language model takes care of the grammatical correctness while a topic model aims for textual consistency. Both models were trained on the Convote dataset which contains transcripts from US congressional floor debates. Furthermore, we present a manual and an automated approach to evaluate the quality of generated speeches. In an experimental evaluation generated speeches have shown very high quality in terms of grammatical correctness and sentence transitions.
Evaluating the evaluations of code recommender systems: A reality check

While researchers develop many new exciting code recommender systems, such as method-call completion, code-snippet completion, or code search, an accurate evaluation of such systems is always a challenge. We analyzed the current literature and found that most of the current evaluations rely on artificial queries extracted from released code, which begs the question: Do such evaluations reflect real-life usages? To answer this question, we capture 6,189 fine-grained development histories from real IDE interactions. We use them as a ground truth and extract 7,157 real queries for a specific method-call recommender system. We compare the results of such real queries with different artificial evaluation strategies and check several assumptions that are repeatedly used in research, but never empirically evaluated. We find that an evolving context that is often observed in practice has a major effect on the prediction quality of recommender systems, but is not commonly reflected in artificial evaluations.
Architectural solution for virtualized processing of big earth data

The Earth Observation data repositories are increasing each day by several terabytes. There is a need to provide efficient techniques to store and process this huge amount of data in order to provide end-users with valuable information and knowledge. The architectural solution proposed in this paper is based on cloud virtualization and aims to provide a flexible and adaptive method to extract and highlight knowledge from the huge data of Earth Observation images. The problem of data processing is solved by virtualizing algorithm objects which are placed in key positions on the hardware level. The users could describe and experiment complex use cases and take advantage of the improvement on execution performance provided by the flexible description and the adaptive processing on high performance computing platforms.