Miracle-dz/UniFAR-FTUs huggingface dataset:
Sifting signal from noise: A new perspective on the meaning of tweets about the “big game”

A good deal of Twitter research focuses on event-detection using algorithms that rely on keywords and tweet density. We present an alternative analysis of tweets, filtering by hashtags related to the 2012 Superbowl and validated against the 2013 baseball World Series. We analyze low-volume, topically similar tweets which reference specific plays (sub-contexts) within the game at the time they occur. These communications are not explicitly linked; they pivot on keywords and do not correlate with spikes in tweets-per-minute. Such phenomena are not readily identified by current event-detection algorithms, which rely on volume to drive the analytic engine. We propose to demonstrate the effectiveness of empirically and theoretically informed approaches and use qualitative analysis and theory to inform the design of future event-detection algorithms. Specifically, we propose theories of Information Grounds and “third places” to explain sub-contexts that emerge. Conceptualizing sub-contexts as a socio-technical place advances the framing of Twitter event-detection from principally computational to deeply contextual.
Meshless Approximation Methods and Applications in Physics Based Modeling and Animation

With growing computing power, physical simulations have become increasingly important in computer graphics. Content creation for movies and interactive computer games relies heavily on physical models, and physically-inspired interactions have proven to be a great metaphor for shape modeling. This tutorial will acquaint the reader with meshless methods for simulation and modeling. These methods differ from the more common grid or mesh-based methods in that they require less constraints on the spatial discretiza-tion.Since the algorithmic structure of simulation algorithms so critically depends on the underlying discretization, we will ﬁrst treat methods for function approximation from discrete, irregular samples: smoothed particle hydrodynamics and moving least squares. This discussion will include numerical properties as well as complexity considerations.Inthesecondpart of this tutorial, we will then treat a number of applications for these approximation schemes. The smoothed particle hydrodynamics framework is used in ﬂuid dynamics and has proven particularly popular in real-time applications. Moving least squares approximations provide higher order consistency, and are therefore suited for the simulation of elastic solids. We will cover both basic elasticity and applications in modeling.
The influence of online store characteristics on consumer impulsive decision-making: A model and empirical application

This study is one of the first to provide insight into the relationships between the online store and consumer impulsive decision-making. We develop a model and show how online store merchandise, ease of use (high task-relevant cues), enjoyment and style (low task relevant cues) relate to online impulse buying. The model is tested using survey data from 532 customers of a Dutch online store. The results show significant effects of merchandise, enjoyment and online store style, mediated by consumers’ emotions and browsing behavior. The study adds to the literature by enhancing our understanding of online impulse buying and by assessing the impact of the online store beyond rational decision-making settings.
High-Order Methods for the Numerical Simulation of Vortical and Turbulent Flows Control of three-dimensional wakes using evolution strategie

We investigate three-dimensional cylinder wakes of incompressible fully developed flows at Re= 300, resulting from contro induced by tangential motions of the cylinder surface. The motion of the cylinder surface, in two dimensions, is optimize evolution strategies, resulting in significant drag reduction and drastic modification of the wake as compared to the unc flow. The quasi-optimal velocity profile obtained in 2D is modified by spanwise harmonics and applied to 3D flows. The indicate important differences in the flow physics induced by two and three dimensional control strategies. To cite this article: P. Poncet et al., C. R. Mecanique 333 (2005).  2004 Académie des sciences. Published by Elsevier SAS. All rights reserved. Résumé Stratégies évolutionnaires pour le contrôle des sillages tridimensionnels. On s’intéresse aux sillages de cylindres compressibles dont la tridimensi onnalité est totalement développée à Re= 300, obtenus suite à un contrôle exercé par mouvements tangentiels à la surface du corps. Les mouvements de surface sont optimisées par des stratégies évolut ont pour conséquence une réduction subtantielle du coefficient de tr aînée et une modification im portante du sillage par rappo à l’écoulement non contrôlé. Le profil de vitesse quasi-optimal obtenu en 2D est modifié par des harmoniques dans la axiale, et appliqué à un écoulement 3D. Les résultats indiquent d’importantes différences dans la physique de l’éc selon la nature 2D ou 3D du contrôle. Pour citer cet article : P. Poncet et al., C. R. Mecanique 333 (2005).  2004 Académie des sciences. Published by Elsevier SAS. All rights reserved.
A Linear Non-Gaussian Acyclic Model for Causal Discovery

In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data. Such methods make various assumptions on the data generating process to facilitate its identification from purely observational data. Continuing this line of research, we show how to discover the complete causal structure of continuous-valued data, under the assumptions that (a) the data generating process is linear, (b) there are no unobserved confounders, and (c) disturbance variables have non-Gaussian distributions of non-zero variances. The solution relies on the use of the statistical method known as independent component analysis, and does not require any pre-specified time-ordering of the variables. We provide a complete Matlab package for performing this LiNGAM analysis (short for Linear Non-Gaussian Acyclic Model), and demonstrate the effectiveness of the method using artificially generated data and real-world data.
A Novel Rotor and Stator Magnetic Fields Direct-Orthogonalized Vector Control Scheme for the PMSM Servo System

Permanent Magnet Synchronous motor (PMSM) has received widespread acceptance in recent years. In this paper, a new rotor and stator Magnetic Fields Direct-Orthogonalized Vector Control (MFDOVC) scheme is proposed for PMSM servo system. This method simplified the complex calculation of traditional vector control, a part of the system resource is economized. At the same time, through the simulation illustration validation, the performance of PMSM servo system with the proposed MFDOVC scheme can achieve the same with the complex traditional vector control method, but much simpler calculation is implemented using the proposed method. Copyright © 2014 IFSA Publishing, S. L.
Kinect-based framework for enhanced learning of disabled students

Educating students with disabilities is different from those without disabilities. Students with disabilities would require modifications and different methods of teaching thin the traditional method. Current learning methods in Malaysia make use of the traditional pencil-and-paper method, which is a hassle. Furthermore, the different styles of learning are often neglected. Although there are attempts to use other learning tools to assist these students, they are often costly. This paper proposes an alternative learning method via Microsoft Kinect. An overview of the research framework and proposed system will be detailed. The expected main outcome from this project is the design of the proposed cost effective framework using Kinect. The framework would include new alternative method of delivering subjects to physically disabled students rather than the current method. The proposed framework also contributes to the motivation factors that drive the students to perform, and the suitability of multiple learning styles utilizing the same classroom tool.
Urbanization, Trace Metal Pollution, and Malaria Prevalence in the House Sparrow

Anthropogenic pollution poses a threat for the environment and wildlife. Trace metals (TMs) are known to have negative effects on haematological status, oxidative balance, and reproductive success in birds. These pollutants particularly increase in concentration in industrialized, urbanized and intensive agricultural areas. Pollutants can also interfere with the normal functioning of the immune system and, as such, alter the dynamics of host-parasite interactions. Nevertheless, the impact of pollution on infectious diseases has been largely neglected in natural populations of vertebrates. Here, we used a large spatial scale monitoring of 16 house sparrow (Passer domesticus) populations to identify environmental variables likely to explain variation in TMs (lead, cadmium, zinc) concentrations in the feathers. In five of these populations, we also studied the potential link between TMs, prevalence of infection with one species of avian malaria, Plasmodium relictum, and body condition. Our results show that lead concentration is associated with heavily urbanized habitats and that areas with large woodland coverage have higher cadmium and zinc feather concentrations. Our results suggest that lead concentration in the feathers positively correlates with P. relictum prevalence, and that a complex relationship links TM concentrations, infection status, and body condition. This is one of the first studies showing that environmental pollutants are associated with prevalence of an infectious disease in wildlife. The mechanisms underlying this effect are still unknown even though it is tempting to suggest that lead could interfere with the normal functioning of the immune system, as shown in other species. We suggest that more effort should be devoted to elucidate the link between pollution and the dynamics of infectious diseases.
Generalized Proximity and Projection with Norms and Mixed-norms

We discuss generalized proximity operators (GPO) and their associated generalized projection problems. On inputs of size n, we show how to efficiently apply GPOs and generalized projections for separable norms and distance-like functions to accuracy in O(n log(1/ )) time. We also derive projection algorithms that run theoretically in O(n log n log(1/ )) time but can for suitable parameter ranges empirically outperform the O(n log(1/ )) projection method. The proximity and projection tasks are either separable, and solved directly, or are reduced to a single root-finding step. We highlight that as a byproduct, our analysis also yields anO(n log(1/ )) (weakly linear-time) procedure for Euclidean projections onto the `1,∞-norm ball; previously only an O(n log n) method was known. We provide empirical evaluation to illustrate the performance of our methods, noting that for the `1,∞-norm projection, our implementation is more than two orders of magnitude faster than the previously known method.
Boosted Edge Orientation Histograms for Grasping Point Detection

In this paper, we describe a novel algorithm for the detection of grasping points in images of previously unseen objects. A basic building block of our approach is the use of a newly devised descriptor, representing semi-local grasping point shape by the use edge orientation histograms. Combined with boosting, our method learns discriminative grasp point models for new objects from a set of annotated real-world images. The method has been extensively evaluated on challenging images of real scenes, exhibiting largely varying characteristics concerning illumination conditions, scene complexity, and viewpoint. Our experiments show that the method works in a stable manner and that its performance compares favorably to the state-of-the-art.
Unit Testing and Action-Level Security Solution of Struts Web Applications Based on MVC

The MVC design pattern is very useful for architecting Web applications, which encourages developers to partition the applications as early as in the design phase. Nowadays, Struts Web applications based on MVC have become more and more popular in various fields, the unit testing and action-level security are the most important method for guaranteeing the applications quality.In this paper, we present a systematic solution for unit testing and action-level security of Struts Web applications. In the solution, we test the applications from model-view-controller (MVC) respectively, and secure Struts applications by different access control implementations. Lastly, an actual applied example is employed to illustrate the testing solution, verifies the effectiveness of the solution.
Writing and Achievement at University as Individualistic or Social Practices: Two Latino Undergraduates’ Contrasting Approaches to Academic Success

ABSTRACT Although Latino enrollment has increased at postsecondary institutions, this minority population is not graduating at the same rate as others. The current study looks at the intersection of educational success stories and writing practices of two upper division Latino students, Martin and Raquel, at a large public U.S. university. Using Bourdieu’s (1977, 1991) theories of symbolic capital and agency, the study addresses how the students’ stories reflect their approach to academics, specifically during the writing process. The study found that despite similar demographic backgrounds, the students greatly differed in their approaches to academic success and the writing process. While Martin adopted an individualistic approach, Raquel relied on social structures to help with the academic and linguistic capital needed to succeed in college. Moreover, while Raquel graduated from university, Martin did not. The study concludes with discussing which approach might be more useful for academic achievement at the postsecondary level.
Reflectance properties of selected arctic-boreal land cover types: field measurements and their application in remote sensing

Abstract. We developed a mobile remote sensing measurement facility for spectral and anisotropic reflectance measurements. We measured reflection properties (BRF) of over 100 samples from most common land cover types in boreal and subarctic regions. This extensive data set serves as a unique reference opportunity for developing interpretation algorithms for remotely sensed materials as well as for modelling climatic effects in the boreal and subarctic zones. Our goniometric measurements show that the reflectances of the most common land cover types in the boreal and subarctic region can differ from each other by a factor of 100. Some types are strong forward scatterers, some backward scatterers, some reflect specularly, some have strong colours, some are bright in visual, some in infrared. We noted that spatial variations in reflectance, even among the same type of vegetation, can be well over 20%, diurnal variations of the same order and seasonal variation often over a factor of 10. This has significant consequences on the interpretation of satellite and airborne images and on the development of radiation regime models in both optical remote sensing and climate change research. We propose that the accuracy of optical remote sensing can be improved by an order of magnitude, if better physical reflectance models can be introduced. Further improvements can be reached by more optimised design of sensors and orbits/flight lines, by the effective combining of several data sources and better processing of atmospheric effects. We conclude that more extensive and systematic laboratory experiments and field measurements are needed, with more modelling effort.
Interpretation of Chinese Discourse Connectives for Explicit Discourse Relation Recognition

This paper addresses the specific features of Chinese discourse connectives, including types (word-pair and single-word), linking directions (forward and backward linking), positions and ambiguous degrees, and discusses how they affect the discourse relation recognition. A semisupervised learning method is proposed to learn the probability distributions of discourse functions of connectives from a small labeled dataset and a big unlabeled dataset. The statistics learned from the dataset demonstrates some interesting linguistic phenomena such as connective synonyms sharing similar distributions, multiple discourse functions of connectives, and couple-linking elements providing strong clues for discourse relation resolution.
Iapr Workshop on Machine Vision Applications. 13-1 3 Model-based 3d Motion Analysis via Robust Estimation

Within a human motion analysis system, body parts are modeled by simple virtual 3D rigid objects. Its position and orientation parameters at frame t + 1 are estimated based on the parameters at frame t and the image intensity variation from frame t to t + 1, under kinematic constraints. An optimization procedure calculates the 3D parameters that make a goal function that measures the intensity change minimum. The goal function is robust, so that outliers located especially near the virtual object projection borders have less effect on the estimation. Since the object's parameters are relative to the reference system, they are the same from different cameras, so more cameras are easily added, increasing the constraints over the same number of variables. A successful experiment is presented for an arm motion of three parts seen from two cameras.
Fuzzy based clustering method on yeast dataset with different fuzzification methods

Clustering is a process for classifying objects or patterns in such a way that samples of the same group are more similar to one another than samples belonging to different groups. In this paper, we introduce the clustering method called soft clustering and its type Fuzzy C-Means. The clustering algorithms are improved by implementing the two different membership functions. The Fuzzy C-Means algorithm can be improved by implementing the Fuzzification parameter values from 1.25 to 2.0 and compared with different datasets using Davis Bouldin Index. The Fuzzification parameter 2.0 is most suitable for Fuzzy C-Means clustering algorithm than other Fuzzification parameter. The Fuzzy C-Means and K-Means clustering algorithms are implemented and executed in Matlab and compared with Execution speed and Iteration Count Methods. The Fuzzy C-Means clustering method achieve better results and obtain minimum DB index for all the different cluster values from different datasets. The experimental results shows that the Fuzzy C-Means method performs well when compare with the K-Means clustering.
Growth: With or Without Scale Effects?

December 15, 1998 -- Version 1.0 The property that ideas are nonrivalrous leads to a tight link between idea-based growth models and increasing returns to scale. In particular, changes in the size of an economy's population generally affect either the long-run growth rate or the long-run level of income in such models. This paper provides a partial review of the expanding literature on idea-based models and scale effects. It presents simple versions of various recent idea-based growth models and analyzes their implications for the relationship between scale and growth. Prepared for the AEA Meetings, January 3, 1999. Forthcoming in the AER Papers and Proceedings, May 1999. (This abstract was borrowed from another version of this item.)
Comparison of Harris Detector and Ridge Bifurcation Points in the Process of Fingerprint Registration using Supervised Contactless Biometric System

Most of the matching or verification phases of the contact based fingerprint verification systems utilize minutiae to find the matched pairs from the input and template fingerprints. Unfortunately, due to some non-linear distortions, like excessive pressure and twisting of fingers during enrollment, this process can cause the minutiae features to be distorted from the original. Contact-based fingerprint systems have some drawbacks due to skin elasticity, inconsistent finger placement, contact pressure, small sensing area, environment conditions and sensor noise. In this paper, we present two fingerprint registration algorithms based on Harris Detector and Minutiae matching for a Contactless Biometric system approach. The performances of the algorithms are evaluated using statistical mean and variance. Based on the above measures, the most efficient registration algorithm is pointed out.
A Privacy-by-Design Contextual Suggestion System for Tourism

We focus on personal data generated by the sensors and through the everyday usage of smart devices and take advantage of these data to build a non-invasive contextual suggestion system for tourism. The system, which we call Pythia, exploits the computational capabilities of modern smart devices to offer high quality personalized POI (point of interest) recommendations. To protect user privacy, we apply a privacy by design approach within all of the steps of creating Pythia. The outcome is a system that comprises important architectural and operational innovations. The system is designed to process sensitive personal data, such as location traces, browsing history and web searches (query logs), to automatically infer user preferences and build corresponding POI-based user profiles. These profiles are then used by a contextual suggestion engine to anticipate user choices and make POI recommendations for tourists. Privacy leaks are minimized by implementing an important part of the system functionality at the user side, either as a mobile app or as a client-side web application, and by taking additional precautions, like data generalization, wherever necessary. As a proof of concept, we present a prototype that implements the aforementioned mechanisms on the Android platform accompanied with certain web applications. Even though the current prototype focuses only on location data, the results from the evaluation of the contextual suggestion algorithms and the user experience feedback from volunteers who used the prototype are very positive.
Developing a 'profile' of emergent personality disorder among adolescents : the effect on treatment outcomes in the IMPACT adolescent depression study

PART I is a systematic review of existing research investigating the relationship between peer victimisation in childhood and subsequent emergence of personality disorder (PD) in adolescence or adulthood. The quality of current evidence and key outcomes are considered, while potential mechanisms that could account for a peer victimisation-PD relationship are explored by drawing on theoretical models of PD development. PART II comprises of an empirical study involving secondary analysis of data from the IMPACT Trial (Goodyer et al, 2016). The study focuses on the development of an emergent Personality Disorder ‘profile’ among adolescents with a diagnosis of major depression, and subsequently exploring whether this profile predicts depression treatment outcomes for young people in terms of depression severity, rates of recovery and withdrawal from treatment. PART III is a critical appraisal of the research process overall. The experience of conducting the research is reflected upon, including how the project developed in the context of the author’s professional, intellectual and personal interests. Strengths and limitations of the research are considered as well as ideas for how it could be expanded in future.