Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-linguistic structural priming in bilinguals: priming of the subject-to-object raising construction between English and Korean

A cross-linguistic structural priming experiment explores the issue of whether parallel syntactic constructions of the two languages in bilinguals share a representation when the surface word orders of the constructions differ. The target population was early balanced bilinguals of Korean and English; the tested constructions were structures relevant to the subject-to-object raising (STOR) operation, which until this study have not been used for structural priming research in cross-linguistic contexts (e.g., STOR: Mary believes Jerry to be trustworthy; non-STOR: Mary believes that Jerry is trustworthy). These syntactic structures exist in both English and Korean, but with different surface word orders. The results show that cross-linguistic priming of the STOR construction occurred, suggesting that parallel syntactic constructions of the languages in bilinguals can share a representation independent of surface word order.
Narrative and interactivity in computer games

Contents: Foreword. Preface. P. Vorderer, J. Bryant, K.M. Pieper, R. Weber, Playing Video Games as Entertainment. M. Sellers, Designing the Experience of Interactive Play. Part I: The Product. H. Lowood, A Brief Biography of Computer Games. B.P. Smith, The (Computer) Games People Play. S. Smith, Perps, Pimps, and Provocative Clothing: Examining Negative Content Patterns in Video Games. E. Chan, P. Vorderer, Massively Multiplayer Online Games. Part II: Motivation and Selection. G.C. Klug, J. Schell, Why People Play Games: An Industry Perspective. P. Ohler, G. Nieding, Why Play? An Evolutionary Perspective. T. Hartmann, C. Klimmt, The Influence of Personality Factors on Computer Game Choice. C. Klimmt, T. Hartmann, Effectance, Self-Efficacy, and the Motivation to Play Video Games. M. von Salisch, C. Oppl, A. Kristen, What Attracts Children? A.A. Raney, J.K. Smith, K. Baker, Adolescents and the Appeal of Video Games. J. Bryant, J. Davies, Selective Exposure to Video Games. Part III: Reception and Reaction Processes. D. Williams, A Brief Social History of Game Play. J.L. Sherry, K. Lucas, B.S. Greenberg, K. Lachlan, Video Game Uses and Gratifications as Predicators of Use and Game Preference. R. Tamborini, P. Skalski, The Role of Presence in the Experience of Electronic Games. S.M. Zehnder, S.D. Lipscomb, The Role of Music in Video Games. K.M. Lee, N. Park, S-A. Jin, Narrative and Interactivity in Computer Games. M.A. Shapiro, J. Pea-Herborn, J.T. Hancock, Realism, Imagination, and Narrative Video Games. A-S. Axelsson, T. Regan, Playing Online. F.F. Steen, P.M. Greenfield, M.S. Davies, B. Tynes, What Went Wrong With The Sims Online: Cultural Learning and Barriers to Identification in a Massively Multiplayer Online Role-Playing Game. Part IV: Effects and Consequences. K.M. Lee, W. Peng, What Do We Know About Social and Psychological Effects of Computer Games? A Comprehensive Review of the Current Literature. R. Weber, U. Ritterfeld, A. Kostygina, Aggression and Violence as Effects of Playing Violent Video Games? K.E. Buckley, C.A. Anderson, A Theoretical Model of the Effects and Consequences of Playing Video Games. D.A. Lieberman, What Can We Learn From Playing Interactive Games? U. Ritterfeld, R. Weber, Video Games for Entertainment and Education. K. Durkin, Game Playing and Adolescents' Development.
Developmental Cognitive Neuroscience Neural Processing of Amplitude and Formant Rise Time in Dyslexia

Keywords: Dyslexia Amplitude rise time Formant rise time Mismatch response a b s t r a c t This study aimed to investigate how children with dyslexia weight amplitude rise time (ART) and for-mant rise time (FRT) cues in phonetic discrimination. Passive mismatch responses (MMR) were recorded for a/ba/-/wa/contrast in a multiple deviant odd-ball paradigm to identify the neural response to cue weighting in 17 children with dyslexia and 17 age-matched control children. The deviant stimuli had either partial or full ART or FRT cues. The results showed that ART did not generate an MMR in either group, whereas both partial and full FRT cues generated MMR in control children while only full FRT cues generated MMR in children with dyslexia. These findings suggest that children, both controls and those with dyslexia, discriminate speech based on FRT cues and not ART cues. However, control children have greater sensitivity to FRT cues in speech compared to children with dyslexia.
Accurate image noise level estimation by high order polynomial local surface approximation and statistical inference

Image noise level estimation is an important step in many image processing tasks such as denoising, compression and segmentation. Although recently proposed SVD and PCA approaches have produced the most accurate estimates so far, these linear subspace-based methods still suffer from signal contamination from the clean signal content, especially in the low noise situation. In addition, the common performance evaluation procedure currently in use treats test images as noise-free. This omits the noise already in those test images and invariably incurs a bias. In this paper we make two contributions. First, we propose a new noise level estimation method using nonlinear local surface approximation. In this method, we first approximate image noise-free content in each block using a high degree polynomial. Then the block residual variances, which follow chi squared distribution, are sorted and the upper quantile of a carefully chosen size is used for estimation. Secondly, we propose a new performance evaluation procedure that is free from the influence of the noise already present in the test images. Experimental results show that it has much improved performance than typical state-of-the-art methods in terms of both estimation accuracy and stability.
Self-organizing autonomic computing systems

Recently a great deal of research has been under-taken in the area of automating the enterprise IT Infrastructure. For enterprises with a large number of computers the IT Infrastructure operation represents a considerable amount of the enterprise budget. Autonomic Computing Systems are systems which were created for minimizing this budget component. They were meant to correct and optimize the IT infrastructure's own self-functioning by executing corrective operations without any need for human interventions. In most cases, where autonomic computing systems have been developed, this was achieved by the addition of external global controllers monitoring the sub-systems of the enterprise IT Infrastructure, determining where changes should be made and applying appropriate commands to implement these changes. Self-Organizing systems on the other hand are systems which reach a global desired state without the use of a central authority which in certain case is the human operator. This paper introduces a general architecture and appropriate algorithms for a self-organizing system which automates a cluster of servers and which maintains an equal desired response time across all the servers. The self-organizing control applies either in the case of homogeneous servers or heterogeneous ones. Furthermore, a simple controller can be built to add or remove servers from the cluster where the controller is itself a peer in the self-organizing system. Simulation data for an autonomic computing system made out of a few cluster servers which are controlled by a self-organizing controller is presented.
Malware Detection via Classifying with Compression

The proliferation of malware has been causing great harm to computer and information systems. Traditional signature-based approaches fail to detect obfuscated malware and unknown malware. We present a preliminary study on classifying with compression of program instructions for malware detection. The code structure information was utilized to compress. The disassembled code is converted to its intermediate representation. We extract the opcode to form the stream for prediction by partial matching (PPM). The binaries are classified with this statistical compression algorithm. The preliminary experiment shows that our method can efficiently detect malware with high accuracy and low false positive rate.
Achilles and the Astronaut: What Heroism Humanities Can Teach Heroism Science

In its ambition to become a “transdisciplinary” field of study, heroism science should leverage the expertise of the “heroism humanities. ” This article uses humanistic knowledge to address one of the thorniest issues in the field: Who counts as a hero? After summarizing the “subjective” versus “objective” approach to defining heroism, I suggest the problem exists because we conflate two distinct conceptual categories: “Heroes,” or the ascription of heroic status to persons and “heroism,” or the ascription of heroic status to behavior. “Hero,” with deep roots in classical antiquity, generates a far more diverse web of associations than “heroism,” a modern construction. Using four examples from a recent news cycle of persons deemed “heroes” (a dictator, an astronaut, a victim of abuse, and an athlete), I demonstrate that a deeper appreciation of the Greek heroic tradition reveals that contemporary ascription of “hero” status is often a continuation, rather than a “diminution” of the word’s historic meanings. Finally, I suggest that heroism science shift its focus from the study of heroic actors as natural objects to the study of how heroes function, discursively and symbolically, within their communities.
Extracting topographic structure from digital elevation data for geographic information-system analysis

Software tools have been developed at the U.S. Geological Survey's EROS Data Center to extract topographic structure and to delineate watersheds and overland flow paths from digital elevation models. The tools are special purpose FORTRAN programs interfaced with general-purpose raster and vector spatial analysis and relational data base management packages. The first phase of analysis is a conditioning phase that generates three data sets: the original DEM with depressions filled, a data set indicating the flow direction for each cell, and a flow accumulation data set in which each cell receives a value equal to the number of cells that drain to it. The original DEM and these three derivative data sets can then be processed in a variety of ways to optionally delineate drainage networks, overland paths, watersheds for user-specified locations, sub-watersheds for the major tributaries of a drainage network, or pour point linkages between watersheds. The computer-generated drainage lines and watershed polygons and the pour point linkage information can be transferred to vector-based geographic information systems for further analysis. Comparisons between these computer generated features and their manually delineated counterparts generally show close agreement, indicating that these software tools will save analyst time spent in manual interpretation and digitizing.
Complexity of Inexact Proximal Newton methods

Recently several methods were proposed for sparse optimization which make careful use of second-order information [10, 28, 16, 3] to improve local convergence rates. These methods construct a composite quadratic approximation using Hessian information, optimize this approximation using a first-order method, such as coordinate descent and employ a line search to ensure sufficient descent. Here we propose a general framework, which includes slightly modified versions of existing algorithms and also a new algorithm, and provide a global convergence rate analysis in the spirit of proximal gradient methods, which includes analysis of method based on coordinate descent.
Extensive RPA2 hyperphosphorylation promotes apoptosis in response to DNA replication stress in CHK1 inhibited cells

The replication protein A (RPA)–ssDNA complex formed at arrested replication forks recruits key proteins to activate the ATR-CHK1 signalling cascade. When CHK1 is inhibited during DNA replication stress, RPA2 is extensively hyperphosphorylated. Here, we investigated the role of RPA2 hyperphosphorylation in the fate of cells when CHK1 is inhibited. We show that proteins normally involved in DNA repair (RAD51) or control of RPA phosphorylation (the PP4 protein phosphatase complex) are not recruited to the genome after treatment with CHK1 and DNA synthesis inhibitors. This is not due to RPA2 hyperphosphorylation as suppression of this response does not restore loading suggesting that recruitment requires active CHK1. To determine whether RPA2 hyperphosphorylation protects stalled forks from collapse or induction of apoptosis in CHK1 inhibited cells during replication stress, cells expressing RPA2 genes mutated at key phosphorylation sites were characterized. Mutant RPA2 rescued cells from RPA2 depletion and reduced the level of apoptosis induced by treatment with CHK1 and replication inhibitors however the incidence of double strand breaks was not affected. Our data indicate that RPA2 hyperphosphorylation promotes cell death during replication stress when CHK1 function is compromised but does not appear to be essential for replication fork integrity.
IMPACT ANALYSIS OF BLACK HOLE ATTACKS ON MOBILE AD HOC NETWORKS PERFORMANCE

A Mobile Ad hoc Network (MANET) is a collection of mobile stations with wireless interfaces which form a temporary network without using any central administration. MANETs are more vulnerable to attacks because they have some specific characteristics as complexity of wireless communication and lack of infrastructure. Hence security is an important requirement in mobile ad hoc networks. One of the attacks against network integrity in MANETs is the Black Hole Attack. In this type of attack all data packets are absorbed by malicious node, hence data loss occurs. In this paper we investigated the impacts of Black Hole attacks on the network performance. We have simulated black hole attacks using Network Simulator 2 (NS-2) and have measured the packet loss in the network without and with a black hole attacks. Also, we measured the packet loss when the number of black hole attacks increases.
Design Optimization Model for an Automotive Electric Water Pump

A non-volatile memory includes a single transistor having a semiconductor substrate, source and drain diffusion layers formed on a surface of the semiconductor substrate, and a gate electrode provided on the semiconductor substrate with a gate insulating film interposed between them. The non-volatile memory further includes a programmable insulating film provided in self-alignment between the gate electrode and at least one of the source and drain diffusion layers and the programmable insulating film is broken down by a voltage applied to the gate electrode so as to execute programming.
Joint Structured Sparsity Regularized Multiview Dimension Reduction for Video-Based Facial Expression Recognition

Video-based facial expression recognition (FER) has recently received increased attention as a result of its widespread application. Using only one type of feature to describe facial expression in video sequences is often inadequate, because the information available is very complex. With the emergence of different features to represent different properties of facial expressions in videos, an appropriate combination of these features becomes an important, yet challenging, problem. Considering that the dimensionality of these features is usually high, we thus introduce multiview dimension reduction (MVDR) into video-based FER. In MVDR, it is critical to explore the relationships between and within different feature views. To achieve this goal, we propose a novel framework of MVDR by enforcing joint structured sparsity at both inter- and intraview levels. In this way, correlations on and between the feature spaces of different views tend to be well-exploited. In addition, a transformation matrix is learned for each view to discover the patterns contained in the original features, so that the different views are comparable in finding a common representation. The model can be not only performed in an unsupervised manner, but also easily extended to a semisupervised setting by incorporating some domain knowledge. An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging video-based FER datasets demonstrate the effectiveness of the proposed framework.
Automatic feature selection with applications to script identification of degraded documents

Current approaches to script identification rely onhand-selected features and often require processing a significantpart of the document to achieve reliable identification.We present an approach that applies a large pool ofimage features to a small training sample and uses subsetfeature selection techniques to automatically select a subsetwith the most discriminating power. At run time we usea classifier coupled with an evidence accumulation engineto report a script label once a preset likelihood thresholdhas been reached. We apply the system to a diverse corpusof printed Russian and English documents that suffer fromcommon degradation problems. Our validation studyshows promising results both in terms of the script identificationaccuracy and the ability to identify script on thescale of individual words and text lines.
Data Web house to support Web intelligence in e-learning environments

The amazing usage of Internet as a communication channel has changed the very structure of companies activities, being education a clear example of this situation. Though data mining has been successfully used to improve the 1-to-1 relationship in e-commerce sites, when applied to e-learning environments the results are often limited to provide the educator with access summary information or primitive patterns. In any case, information being obtained is not being used pro-actively. For environments to profit from the information obtained it has to be integrated in a global infrastructure. This paper presents the design of a data e-learning Web-house as supporting structure for future e-learning personalized systems.
SimiHawk at SemEval-2016 Task 1: A Deep Ensemble System for Semantic Textual Similarity

This paper describes the SimiHawk system submission from UMass Lowell for the core Semantic Textual Similarity task at SemEval-2016. We built four systems: a small feature-based system that leverages word alignment and machine translation quality evaluation metrics, two end-to-end LSTM-based systems, and an ensemble system. The LSTM-based systems used either a simple LSTM architecture or a Tree-LSTM structure. We found that of the three base systems, the feature-based model obtained the best results, outperforming each LSTM-based model’s correlation by . 06. Ultimately, the ensemble system was able to outperform the base systems substantially, obtaining a weighted Pearson correlation of 0.738, and placing 7th out of 115 participating systems. We ﬁnd that the ensemble system’s success comes largely from its ability to form a consensus and eliminate complementary noise from its base systems’ predictions.
A Hybrid DVS Scheme for Interactive 3D Games

Interactive 3D games are now widely available on a variety of mobile devices for which battery-life is a major concern. Many of these devices support voltage/frequency-scalable processors and dynamic voltage scaling (DVS) has emerged as a powerful technique for energy management in such devices. Although DVS algorithms have been very successfully applied to video encoding/decoding applications, their use in interactive computer games has not been sufficiently explored so far. In this paper we propose a novel DVS scheme that is specifically directed towards interactive 3D game applications running on battery-operated portable devices. The key to this DVS scheme lies in an accurate prediction of the rendering workload of a current game scene. We have applied this scheme to first person shooter games (e.g. Quake II) and obtained significant power savings while maintaining high frame rates. Based on the observation that there exist two types of workload variations in such games, we compute the voltage/frequency setting for any game scene using a hybrid combination of two different techniques: (i) adjusting the workload prediction using a control-theoretical feedback mechanism, and (ii) analyzing the graphical objects in the current game scene by parsing the corresponding frame. Our scheme is significantly different from those commonly applied to video decoding applications (where only technique (i) is used) and has shown very encouraging results when evaluated with different setups (e.g. laptop running Windows, PDA running Windows Mobile and a configurable simulation platform).
Population structure of the hydrocoral Millepora platyphylla in habitats experiencing different flow regimes in Moorea, French Polynesia

While the fire coral Millepora platyphylla is an important component of Indo-Pacific reefs, where it thrives in a wide range of environments, the ecological and biological processes driving its distribution and population structure are not well understood. Here, we quantified this species’ population structure in five habitats with contrasting hydrodynamic regimes in Moorea, French Polynesia; two in the fore reef: mid and upper slopes, and three in the lagoon: back, fringing and patch reefs. A total of 3651 colonies of fire corals were mapped and measured over 45,000 m2 of surveyed reef. Due to the species’ sensitivity to fragmentation in response to strong water movement, hydrodynamic conditions (e.g. waves, pass and lagoonal circulation) corresponded to marked differences in colony size distributions, morphology and recruitment dynamics among habitats. The size structure varied among reef habitats with higher proportions of larger colonies in calm nearshore reefs (fringing and patch reefs), while populations were dominated by smaller colonies in the exposed fore reefs. The highest densities of fire corals were recorded in fore reef habitats (0.12–0.20 n.m-2) where the proportion of recruits and juveniles was higher at mid slope populations (49.3%) than on the upper slope near where waves break (29.0%). In the latter habitat, most colonies grew as vertical sheets on encrusting bases making them more vulnerable to colony fragmentation, whereas fire corals were encrusting or massive in all other habitats. The lowest densities of M. platyphylla occurred in lagoonal habitats (0.02–0.04 n.m-2) characterized by a combination of low water movement and other physical and biological stressors. This study reports the first evidence of population structure of fire corals in two common reef environments and illustrates the importance of water flow in driving population dynamic processes of these reef-building species.
SLIDING MODE CONTROL OF UNCERTAIN LINEAR SYSTEMS BASED ON A HIGH GAIN OBSERVER FREE OF PEAKING

Abstract A model-reference variable structure controller based on a high gain observer (HGO) is proposed and analyzed. For single-input-single-output (SISO) linear plants with relative degree larger than one, the switching law is generated using the HGO state while the modulation function in the control law is generated using signals from state variable filters free of high gains. This scheme achieves global exponential stability with respect to a small residual set and does not generate the peaking phenomena.