Miracle-dz/UniFAR-FTUs huggingface dataset:
WLSI-OIAF4HLT 2016 Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies

We present Kathaa, an Open Source web-based Visual Programming Framework for Natural Language Processing (NLP) Systems. Kathaa supports the design, execution and analysis of complex NLP systems by visually connecting NLP components from an easily extensible Module Library. It models NLP systems an edge-labeled Directed Acyclic MultiGraph, and lets the user use publicly co-created modules in their own NLP applications irrespective of their technical proficiency in Natural Language Processing. Kathaa exposes an intuitive web based Interface for the users to interact with and modify complex NLP Systems; and a precise Module definition API to allow easy integration of new state of the art NLP components. Kathaa enables researchers to publish their services in a standardized format to enable the masses to use their services out of the box. The vision of this work is to pave the way for a system like Kathaa, to be the Lego blocks of NLP Research and Applications. As a practical use case we use Kathaa to visually implement the Sampark Hindi-Panjabi Machine Translation Pipeline and the Sampark Hindi-Urdu Machine Translation Pipeline, to demonstrate the fact that Kathaa can handle really complex NLP systems while still being intuitive for the end user.
Dealing with crosscutting concerns in existing software

This paper provides a roadmap for dealing with crosscutting concerns while trying to understand, maintain, and evolve existing software systems. We describe an integrated, systematic, approach that helps a software engineer with identifying, documenting and migrating crosscutting concerns in the source code of a software system, and discuss the integration considerations. We conclude with a number of lessons learned and directions for future research.
Short- and long-term consequences in decision-making under risk: immediate feedback about long-term prospects benefits people tending to impulsive processing

ABSTRACT Many decisions in everyday life involve weighing up immediate and expected future outcomes that may be conflictive. Yet, it is still unclear which cognitive functions may affect decision-making in such situations. We examined 150 healthy subjects using a new decision-making task that measures people’s ability at handling short- and long-term consequences under objective risk. Two task versions were developed to investigate the effects of feedback about long-term consequences on decision-making. One version includes feedback about changes in long-term prospects while the other does not. Both groups revealed that advantageous decision-making correlated with reasoning and working-memory abilities, however, no correlations with executive functions were found. The effect of feedback on decision-making performance was moderated by impulsivity and need for cognition. Our findings contribute to recent dual-system approaches for risky decision-making by showing that individuals with predispositions towards impulsive rather than reflective information processing could profit from feedback about long-term prospects.
Duetting as a Collective Behavior

Mated birds of many species vocalize together, producing duets. Duetting behavior occurs at two levels of organization: the individual level and the pair level. Individuals initiate vocalizations, answer their mates’ vocalizations, and control the structure and timing of their own vocalizations. Pairs produce duets that vary with respect to duration, temporal coordination, and phrase-type combinations, among other properties. To make sense of this hierarchical structure, organize duetting research, and identify new avenues of investigation, we advocate a “collective behavior” approach to the study of duets. We critically review key terminology in the duetting literature in light of this approach, and elucidate six insights that emerge from the collective behavior approach: (1) Individual-level behaviors describe pair-level behaviors, but the opposite is not true; (2) The level of organization informs how we test for the rules that govern behavior; (3) Functional hypotheses about duetting must distinguish individual from group characters; (4) Stimulus-response, cybernetics, and entrainment offer alternative hypotheses for the cognitive control of duetting behavior; (5) Avian duetting has the potential to be a model system for the ontogeny of vocal interaction; and (6) The collective behavior approach suggests new avenues of research. Ultimately, we argue that nearly every aspect of duetting research stands to benefit from adopting a collective behavior approach. This approach also has applications to other forms of interactive vocal communication in birds and primates, including humans.
Combining PGMs and Discriminative Models for Upper Body Pose Detection

In this project, I utilized probabilistic graphical models together with discriminative models such as SVM to perform upper body pose estimation. Figure 1 illustrates the definition of a problem in terms of input and output. Pose estimation is an important problem that has a wide array of applications such as pedestrian detection, sports video analysis, action recognition, etc. The entire human body can be seen as a graph where each body part is the node in the graph and two adjacent body parts are connected via an edge. Therefore, it is natural to utilize probabilistic graphical models to solve pose detection related problems. Additionally, the idea of incorporating discriminative models has been shown to be very successful as well, specifically in [1] [2]. Intuitively it makes sense that combination of generative and discriminative models should produce a model that is more powerful than each of these individually. Therefore, my hope is that combining these two techniques will produce solid results for this challenging problem.
High morale is associated with increased survival in the very old.

BACKGROUND high morale is defined as future-oriented optimism. Previous research suggests that a high morale independently predicts increased survival among old people, though very old people have not been specifically studied. OBJECTIVE to investigate whether high morale is associated with increased survival among very old people. SUBJECTS the Umeå 85+/GErontological Regional DAtabase-study (GERDA) recruited participants aged 85 years and older in northern Sweden and western Finland during 2000-02 and 2005-07, of whom 646 were included in this study. METHODS demographic, functional- and health-related data were collected in this population-based study through structured interviews and assessments carried out during home visits and from reviews of medical records. The 17-item Philadelphia Geriatric Center Morale Scale (PGCMS) was used to assess morale. RESULTS the 5-year survival rate was 31.9% for participants with low morale, 39.4% for moderate and 55.6% for those with high morale. In an unadjusted Cox model, the relative risk (RR) of mortality was higher among participants with low morale (RR = 1.86, P < 0.001) and moderate morale (RR = 1.59, P < 0.001) compared with participants with high morale. Similar results were found after adjustment for age and gender. In a Cox model adjusted for several demographic, health- and function-related confounders, including age and gender, mortality was higher among participants with low morale (RR = 1.36, P = 0.032) than those with high morale. There was a similar but non-significant pattern towards increased mortality in participants with moderate morale (RR = 1.21, P value = 0.136). CONCLUSION high morale is independently associated with increased survival among very old people.
Comparison of real-time industrial process control solutions: Glass melting case study

Two solutions supporting advanced control algorithms in real-time are described and compared in the paper: a SCADA-based system and a custom QNX-based system. The control of the glass melting and conditioning process, which is considered to be difficult and demanding for control applications in the glass industry, is provided as an implementation example in the paper.
Multi-category SVMs-based Image Categorization

Automatic image categorization, which maps lowlevel visual features to high-level semantics, is the crucial basis for effective understanding, annotation, retrieval, and management of digital visual information. In this paper, we present a multicategory SVMs-based (Support Vector Machines) image categorization system by exclusively using global low-level features. Images are represented by the MPEG-7 SCD (Scalable Color Descriptor) and the modified MPEG-7 EHD (Edge Histogram Descriptor), which are verified by the K-Means algorithm to be effective. The K-Means algorithm is also applied to select training images. Multi-category SVMs using the Gaussian RBF (Radial Basis Function) kernels are further evaluated on the categorization of the image database with general-purpose images from COREL. The empirical results demonstrate that the proposed categorization method outperforms the peer approaches in the literature in terms of both efficiency and accuracy. In addition, each test image is labeled by a set of confidence values for each possible category.
Enhancer- A Time Commit Protocol

This paper contains content with the investigating the performance implications of providing transaction atomicity for a deadline real time applications operating on distributed data. Considering all the commit protocols and discussing all phases of the commit protocols and examine their working model over different aspects of distributed database. Implementing distributed real time database system(DRTDBS) content which must be design on all level of database architecture to support timely execution of request. The enormous progress in applications of distributed database systems necessitates formulation of an efficient atomic commitment protocol. The efficiency of these protocols is vital when higher transaction throughput is to be supported. The existing blocking commit protocols affect over the capacity of system resources, which worsens in distributed database system Many existing real time commit protocols try to enhance system performance by allowing a committing participant to share its data to an executing participant, thus it reduces data inaccessibility.
Do rich teens get richer? Facebook use and the link between offline and online social capital among Palestinian youth in Israel

ABSTRACT Studies have shown that using social networking sites contributes to social capital. This study investigated the association between specific features of Facebook and online social capital. Two contrasting hypothesis were tested. The first posits that the rich get richer, meaning that the creation of social capital online reflects the stock of offline resources already available. In contrast, the compensation hypothesis argues that disadvantaged ethnic minorities are more likely to use social media to compensate for their lack of social capital offline. We tested these two theories among a representative sample of Palestinian teenagers (N = 567). While we found no gender differences in the use of Facebook’s features, our results highlight the positive correlation between the use of active and passive communication features and perceived social capital online. Moreover, the results support the rich-get-richer model; in that, even among this socially disadvantaged group, the youngsters who already had a store of social capital offline benefitted more from using Facebook.
Active automata learning for real life applications

Acknowledgements I want to thank Bernhard Steffen for guiding me during the past five years. Clearly, this dis-sertation is a result of having being challenged, motivated, and supported in a truly unique environment, created by the persons that gathered at the Chair of Programming Systems to create and cooperate. Thus I would also like to thank my colleagues, and in particular Falk Howar, with whom I had the pleasure of sharing an office for three years. Hilarity sure ensued, as did pleasant traveling and countless hours of fruitful discussion. Last but not least, thanks also go to my family, which was both supportive and patient.
Distributed Sensor Particles for Remote Fluorescence Detection of Trace Analytes: UXO/CW

This report summarizes the development of sensor particles for remote detection of trace chemical analytes over broad areas, e.g residual trinitrotoluene from buried landmines or other unexploded ordnance (UXO). We also describe the potential of the sensor particle approach for the detection of chemical warfare (CW) agents. The primary goal of this work has been the development of sensor particles that incorporate sample preconcentration, analyte molecular recognition, chemical signal amplification, and fluorescence signal transduction within a ''grain of sand''. Two approaches for particle-based chemical-to-fluorescence signal transduction are described: (1) enzyme-amplified immunoassays using biocompatible inorganic encapsulants, and (2) oxidative quenching of a unique fluorescent polymer by TNT.
An Adaptive Robust Guaranteed Cost Controller Design and Its Application to the Yaw Control of Helicopter

This paper discusses the adaptive robust guaranteed cost tracking control problem of linear systems, with time-varying uncertainties. The bounds of varying uncertainty ellipsoidal are obtained by set membership identification method. The proposed adaptive robust controller consists of a constant gain determined by the nominal system and a variable gain tuned by the designed adaptive laws. The application of this approach to the yaw control of a small-scale helicopter mounted on an experiment platform shows the effectiveness
Nuclear Factor I/Thyroid Transcription Factor 1 Interactions Modulate Surfactant Protein C Transcription

ABSTRACT Surfactant protein C (SP-C; Sftpc) gene expression is restricted to pulmonary type II epithelial cells. The proximal SP-C promoter region contains critical binding sites for nuclear factor I (NFI) and thyroid transcription factor 1 (TTF-1; also called Nkx2.1). To test the hypothesis that NFI isoforms interact with TTF-1 to differentially regulate SP-C transcription, we performed transient transfection assays in JEG-3 cells, a choriocarcinoma cell line with negligible endogenous NFI or TTF-1 activity. Cotransfection of NFI family members with TTF-1 induced synergistic activation of the SP-C promoter that was further enhanced by p300. TTF-1 directly interacts with the conserved DNA binding and dimerization domain of all NFI family members in coimmunoprecipitation and mammalian two-hybrid experiments. To determine whether SP-C expression is regulated by NFI in vivo, a chimeric fusion protein containing the DNA binding and dimerization domain of NFI-A and the Drosophila engrailed transcriptional repression domain (NFIen) was conditionally expressed in mice under control of a doxycycline-inducible transgene. Induction of NFIen in a subset of type II cells inhibited SP-C gene expression without affecting expression of TTF-1 in doxycycline-treated double-transgenic mice. Taken together, these findings support the hypothesis that NFI family members interact with TTF-1 to regulate type II cell function.
XI: A Simple Prolog-based Language for Cross-Classification and Inheritance

This paper describes a simple Prolog-based knowledge representation language called XI ‐ X for cross-classification and I for inheritance ‐ which is designed to represent knowledge about individuals, about classes of individuals, and about inclusion relations between classes of individuals. XI allows for str aightforward definitions of cross-classification hierarchies and for the associatio n of arbitrary attribute-value information with classes or with individuals. XI also provi des a simple inheritance mechanism which allows attribute values to be inherited by classes or individuals lower in the hierarchy. XI is simple, flexible, theoreticall y well-founded, and fully implemented. The utility of the language is demonstrated by discussing how it has been motivated by, and used in, a natural language processing system to represent the conceptual and world knowledge needed to perform co-reference resolution.
The dynamics of permanence

This dissertation is a simulated-robotics study of the development of the A-not-B behavior and object permanence capacity in infancy. Drawing from recent empirical, theoretical, and modeling work as well as earlier work of Poincare and Piaget, I argue, through a series of theoretical discussions and computer simulations, (i) that the body rotation of infants, which no extant model of the A-not- B behavior explicitly takes into account, shall be taken into account because it causes the occluded target to change egocentric location without direct visual feedback, and can be taken into account in a simulated robotic model that extends Thelen and colleagues' dynamic systems model via introducing kinesthesis-based updating of spatial working memory that compensates for body rotation; (ii) that the notion of attractor stability underwriting analysis of behavior from the dynamic systems perspective, needs to be extended to a notion of “relational stability” so as to account for infants' compensatory memory activity in relation to relative target shifting, an extension that suggests a way of explicating the representational character of cognition; (iii) that underwriting representation of location is a developmentally more primary achievement of a capacity for localization, a point that is corroborated by findings from researchers such as Acredolo and Newcombe and in agreement with challenges raised by Newcombe, Smith and Scheier to models, such as that from Munakata, in which locations are modeled by units labeled with location names such as ‘A’ or ‘B’; (iv) that the spatial working memory dynamics and the associated kinesthesis-based compensation mechanism can be learned by neuroscience-inspired unsupervised learning, which provides a way to concretize the well-documented correlation between the development of object permanence and the development of locomotion; and (v) that both successful tracking of an occluded target and the development of such tracking mechanism in the presence of incessant bodily movements require that the metric detail of relative target displacements be available.
Free-Riding Analysis of BitTorrent-Like Peer-to-Peer Networks

BitTorrent is a very popular P2P file sharing system. It has been successful at distributing large files quickly and efficiently. Embedded in BitTorrent is a set of incentive mechanisms to encourage sharing and contribute, and prevent systematic free-riding. In this paper, a fluid model with two classes of peers is used to capture the effect of free-riding in a BitTorrent system. With the model, we explore how does free-riding influenced the BitTorrent system. From results, it is shown that BitTorrent mechanism is successful to guard against free-riding. Finally, we discuss the dying process of a BitTorrent system and the probability of system dead that is induced by free-riding
Memory and Neuropsychology in Down Syndrome.

This paper outlines the strengths and weaknesses in both short-term and long-term memory in Down syndrome, and the implications of these patterns for both other aspects of cognitive development and underlying neural pathology. There is clear evidence that Down syndrome is associated with particularly poor verbal short-term memory performance, and a deficit in verbal short-term memory would be expected to negatively affect aspects of language acquisition, particularly vocabulary development. Individuals with Down syndrome also show impaired explicit long-term memory for verbal information, and may also have particular problems in explicit long-term memory for visual-object associations. However, implicit memory appears to be less affected in Down syndrome, and may therefore provide an important basis for intervention approaches. These findings are consistent with the suggestion of dysfunction within the hippocampal system in Down syndrome, and problems in verbal memory may be linked to impaired functioning of pre-frontal brain regions.
On the efficient traversal of the itemset lattice: A literature review

The mining of itemsets passes thorugh an efficient traversal of lattice traversal. In this paper we point out some findings regarding the exploration of lattice itemsets which should drive the design of efficient data mining algorithms. This paper attempts to outline some findings for an efficient traversal of the itemset inclusion lattice, by looking at different problems investigated in literature, and to draw directions for the implementation of efficient search algorithms.
Textual and stylistic error detection and correction: Categorization, annotation and correction strategies

In this paper we present an analysis of the most frequently encountered style and text structure errors produced by a variety of types of authors when producing texts. We then show how such errors can be annotated together with their correction(s). From these annotations, via generalizations, correction rules can be induced. Since correcting errors is a complex process, with several solutions and possibilities, we finally show how an argumentation system can be used so that the user can get arguments for or against a certain correction.
Dual Regulation of c-Myc by p300 via Acetylation-Dependent Control of Myc Protein Turnover and Coactivation of Myc-Induced Transcription

ABSTRACT The c-Myc oncoprotein (Myc) controls cell fate by regulating gene transcription in association with a DNA-binding partner, Max. While Max lacks a transcription regulatory domain, the N terminus of Myc contains a transcription activation domain (TAD) that recruits cofactor complexes containing the histone acetyltransferases (HATs) GCN5 and Tip60. Here, we report a novel functional interaction between Myc TAD and the p300 coactivator-acetyltransferase. We show that p300 associates with Myc in mammalian cells and in vitro through direct interactions with Myc TAD residues 1 to 110 and acetylates Myc in a TAD-dependent manner in vivo at several lysine residues located between the TAD and DNA-binding domain. Moreover, the Myc:Max complex is differentially acetylated by p300 and GCN5 and is not acetylated by Tip60 in vitro, suggesting distinct functions for these acetyltransferases. Whereas p300 and CBP can stabilize Myc independently of acetylation, p300-mediated acetylation results in increased Myc turnover. In addition, p300 functions as a coactivator that is recruited by Myc to the promoter of the human telomerase reverse transcriptase gene, and p300/CBP stimulates Myc TAD-dependent transcription in a HAT domain-dependent manner. Our results suggest dual roles for p300/CBP in Myc regulation: as a Myc coactivator that stabilizes Myc and as an inducer of Myc instability via direct Myc acetylation.
New relevance feedback method based on dynamic weight updating

In content-based image retrieval systems using relevance feedback are often considered relevant images but ignored irrelevant images. This paper proposes an approach of updating corresponding weight by combining the proportion of relevant and irrelevant images. According the proportion, using the standard deviation adjust the feature value. To avoid the state of sub-optimal, a disturbing factor has been used to get the best feature weights. Experiments show the better result.