Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Study habits using a Behaviour Change Framework Incorporating Social Motivation and Gamification

Students entering into their first year of university studies are subject to a jarring difference between the learning experiences of high school and university. High schools typically take a very structured approach to teaching whereas university expects students to take ownership of their learning. This dramatic shift often means students are not adequately prepared to form positive study habits on their own, or existing habits are likely to break down. Further complicating this issue is the rising popularity of video games and social networking amongst students. These two areas provide fun and engaging experiences for their users where traditional learning environments struggle to do so. In this research-in-progress paper, we propose a framework that can be used by instructors to improve learning environments so that their students are better engaged and encouraged to form positive study habits. The framework utilises a hybrid of the Transtheoretical model of behaviour change (TTM) and the SNAP model of motivation. Social networking and gamification are used as triggers that enable the process to occur. It is envisaged that this research will lead to instructors creating more effective learning environments with less effort, and making academic learning a more enjoyable pursuit for students.
Airborne determination of the temporo-spatial distribution of benzene, toluene, nitrogen oxides and ozone in the boundary layer across Greater London, UK

Abstract. Highly spatially resolved mixing ratios of benzene and toluene, nitrogen oxides (NOx) and ozone (O3) were measured in the atmospheric boundary layer above Greater London during the period 24 June to 9 July 2013 using a Dornier 228 aircraft. Toluene and benzene were determined in situ using a proton transfer reaction mass spectrometer (PTR-MS), NOx by dual-channel NOx chemiluminescence and O3 mixing ratios by UV absorption. Average mixing ratios observed over inner London at 360 ± 10 m a.g. l. were 0.20 ± 0.05, 0.28 ± 0.07, 13.2 ± 8.6, 21.0 ± 7.3 and 34.3 ± 15.2 ppbv for benzene, toluene, NO, NO2 and NOx respectively. Linear regression analysis between NO2, benzene and toluene mixing ratios yields a strong covariance, indicating that these compounds predominantly share the same or co-located sources within the city. Average mixing ratios measured at 360 ± 10 m a.g. l. over outer London were always lower than over inner London. Where traffic densities were highest, the toluene / benzene (T / B) concentration ratios were highest (average of 1.8 ± 0.5 ppbv ppbv-1), indicative of strong local sources. Daytime maxima in NOx, benzene and toluene mixing ratios were observed in the morning (~ 40 ppbv NOx, ~ 350 pptv toluene and ~ 200 pptv benzene) and in the mid-afternoon for ozone (~ 40 ppbv O3), all at 360 ± 10 m a.g. l.
Emerging Chemicals and Analytical Methods

Emerging contaminants in the water environment continues to be a strong research focus, as evidenced by the abundance of material published during 2004. This review summarizes peer-reviewed literature pertinent to the field of environmental engineering and science and related to analysis, occurrence, and fate of emerging chemical contaminants in the water environment, focusing on the following broad categories of emerging organic contaminants: antibiotics and pharmaceuticals; personal care products ingredients (PCPIs), endocrine disrupting compounds (EDCs), halogenated compounds (particularly brominated and fluorinated compounds), and disinfection byproducts (DBPs). To maintain this focus, articles pertaining specifically to human and ecological toxicity, bioconcentration or bioaccumulation, risk assessments, and innovative treatment and destruction methods are not included in this review. Additionally, summaries of literature covering organometallic compounds are not included in this review as in past years. Because of the sheer volume of literature covered by this topic, this review should not be considered to be comprehensive. Acronyms that are used in this review for chemical species and analytical methods are summarized in Tables 1 and 2, respectively.
Search Result Diversification Methods to Assist Lexicographers

We show how the lexicographic task of finding informative and diverse example sentences can be cast as a search result diversification problem, where an objective based on relevance and diversity is maximized. This problem has been studied intensively in the information retrieval community during recent years, and efficient algorithms have been devised. We finally show how the approach has been implemented in a lexicographic project, and describe the relevance and diversity functions used in that context.
Convex Optimization-Based Parameter Estimation and Experiment Design for Pauli Channels

In this technical note, we study the problem of parameter estimation for quantum channels, which are (completely positive) maps acting on quantum states. We focus on an important subclass of channels called Pauli channels which are characterized by a certain set of vectors (directions) and a number of scalar parameters. For the case where the directions are known, a special parametrization turns the parameter estimation problem into a convex optimization problem. For the case of unknown directions we give a simple algorithm to estimate the directions for qubit Pauli channels. These results assume that the identification experiment configuration is given, namely, a set of quantum states are given on which the channel acts, and a set of positive measurement (operator)s are fixed from which information is gathered. In the second part of the technical note we consider the problem of determining the experiment design, namely, determining states and measurements for optimal parameter identification of the channels. We formalize this problem as a maximization problem for Fisher information and, assuming known channel directions, prove that this problem is convex. We also prove that the optimal states to be used in experiments are pure and the optimal measurements are extremal. For qubit Pauli channels we prove that both the optimal pure input states and projective measurements should be directed towards the channel directions. We illustrate the results of the technical note with numerical examples and simulations.
XMM-Newton light curves of the low-mass X-ray binary EXO 0748–676: Dips, eclipses, and bursts

We present an analysis of XMM-Newton light curves of the dipping, bursting, and eclipsing low-mass X-ray binary EXO 0748-676, focusing on the variability on time scales of seconds to hours. The observed variability can be roughly divided in three types: dips, eclipses and bursts. We find that the appearance of the latter two, depends strongly on the strength of the first. We show that the absorption dips change from spectrally hard to spectrally soft as they become deeper, which supports suggestions that the source is composed of a spectrally hard compact source and a spectrally soft extended source. The fast variability in the soft light curve indicates that the large structures causing the dips are made up of smaller absorption cores. We present the first clear detection with XMM-Newton of eclipses below 2 keV in this source, and show that dipping activity is apparently unrelated to the source luminosity. We also test several proposed models for the spectral evolution during dips and confirm the presence of a scatter/reflection component in the eclipse spectrum.
Instantaneous power control of D-STATCOM with consideration of power factor correction

This paper presents a modified instantaneous power control scheme of D-STATCOM for power factor and harmonic compensation. The proposed control strategy has been introduced in order to enhance some steady-state performances besides its functional elimination of power quality disturbances. Power factor and harmonic current of a controlled feeder section are two vital roles in steady-state power distribution system operation. Utilizing an already installed D-STATCOM to achieve these additional control objectives can help system operators maximize overall system performances. In this paper, a control scheme with constant power and sinusoidal current compensation [1,2] is exploited. In order to correct the power factor, a power factor control loop is required and therefore included in the control block. To verify its use, a 22-kV power distribution feeder with a three-phase rectifier load was tested. Results showed that integration of the proposed reactive power control loop can correct the power factor of the controlled feeder to be unity power factor.
2005 7 th International Conference on Information Fusion ( FUSION ) Color Segmentation Using an Eigen Color Representation

In real images, color segmentation is a challenging problem because of natural variations in light and shadows. Most existing color models have limitations in distinctive representation of colors in real scenes. Color segmentation approaches are highly dependent on the robustness of the used color model to these variations. In this paper, we present a novel color representation for color segmentation. The proposed model is a fusion of classical color representations. It is calculated using a closed form linear transformation from a high dimensional classical feature space to a lower dimensional new space. We prove the high performance of the proposed model in terms of robustness to natural variations and distinction between different colors, when compared with classical color models. Through color segmentation of real images, we provide a quantitative and qualitative comparison between the proposed model and classical models. The experimental results support the potential of the proposed model. '.
Evaluation of Stereoscopic Images: Beyond 2D Quality

Perceived image quality is a standard evaluation concept for 2D imaging systems. When applied to stereoscopic 3D imaging systems, however, it does not incorporate the added value of stereoscopic depth. Higher level evaluation concepts (naturalness and viewing experience) are proposed that are sensitive to both image quality and stereoscopic depth. A 3D Quality Model is constructed in which such higher level evaluation concepts are expressed as a weighted sum of image quality and perceived depth. This model is validated by means of three experiments, in which stereoscopic depth (camera base distances and screen disparity) and image quality (white Gaussian noise and Gaussian blur) are varied. The resulting stimuli are evaluated in terms of naturalness, viewing experience, image quality and depth percept. Analysis revealed that viewing experience and naturalness incorporated variations in image quality to a similar extent, yet the added value of stereoscopic depth is incorporated significantly more by naturalness. This result classifies naturalness as the most appropriate concept to evaluate 3D quality of stereoscopic stills. The 3D Quality Model based on naturalness as evaluation concept is validly applicable to stereoscopic stills and the naturalness score is determined for approximately 75% by image quality and for approximately 25% by the added value of stereoscopic depth.
Caffe Framework on the Jetson TK1: Using Deep Learning for Real Time Object Detection

— Deep Neural Networks are an approach to using state-of-the-art machine learning algorithms in order to improve the applications of the computer vision field. These neural networks are complex mathematical models which can be trained to identify certain objects within a frame, and some of them are also able to identify where on the image is the object that they identified. This technical report focuses on presenting the implementation of a deep neural network on a low-power embedded computer system, specifically the NVIDIA Jetson TK1, in order to run convolutions in real-time for object detection. This can be achieved by implementing Fast R-CNN–a state-of-the-art model for convolutions–in the machine learning framework called Caffe.
Identifying Nonlinear Wave Interactions in Plasmas Using Two-point Measurements: a Case Study of Slams

Two fundamental quantities for characterizing nonlinear wave phenomena in plasmas are the spectral energy transfer associated with the energy redistribution between Fourier modes, and the linear growth rate. It is shown how these quantities can be estimated simultaneously from dual spacecraft data using Volterra series models. We consider magnetic eld data gathered upstream the Earth's quasiparallel bow shock, in which Short Large Amplitude Magnetic Structures (SLAMS) supposedly play a leading role. The analysis attests the dynamic evolution of the SLAMS and reveals an energy cascade toward high frequency waves. These results put constraints on possible mechanisms for the shock front formation. 3
Firms formation and growth in the model with heterogeneous agents and monitoring

In this article we extend the agent-based model of firms' formation and growth proposed in [4]. In [4] the firms creation, expansion or contraction results from the interaction of heterogeneous utility maximizers. While the original model was able to replicate the power law distribution in the firms' sizes agents in the model set their utility maximizing effort levels completely freely and undetected. This led to the emergence of free riding and influenced the overall dynamics of the model. Therefore we decided to extend the original model by introducing the monitoring which is seen in the economic literature, besides for example the proper incentive scheme ([18]), as a possible way how to make employees work harder. Our motivation is to compare the extended model with both to the original case without monitoring and empirical data about firms sizes distribution.
Object Detection Using Hausdorff Distance and Multiclass Discriminative Field

In this paper, we present a novel object detection scheme using only local contour fragments. A sample fragment extraction method decomposes a whole contour into several parts. Then, the candidate locations of corresponding fragments in test images are detected by a modified Hausdorff distance with punishment on clutter edge regions. The most probable locations are selected by Multiclass Discriminative Field (MDF). Finally, contours of the objects can be drawn with these locations and sample fragments. Our major contributions are simplifying the MDF by an undirected graph constructed by the candidate locations and directly selecting the fragment locations by this MDF. The results on our postmark database and the ETHZ database from internet show that the proposed scheme is practicable.
Stochastic Volatility: Likelihood Inference And Comparison With Arch Models

In this paper, Markov chain Monte Carlo sampling methods are exploited to provide a unified, practical likelihood-based framework for the analysis of stochastic volatility models. A highly effective method is developed that samples all the unobserved volatilities at once using an approximating offset mixture model, followed by an importance reweighting procedure. This approach is compared with several alternative methods using real data. The paper also develops simulation- based methods for filtering, likelihood evaluation and model failure diagnostics. The issue of model choice using non-nested likelihood ratios and Bayes factors is also investigated. These methods are used to compare the fit of stochastic volatility and GARCH models. All the procedures are illustrated in detail.
A low-cost parallel computing platform for power engineering applications

This paper develops and evaluates a low-cost parallel computing platform for the implementation of parallel algorithms in Power Engineering applications. The proposed approach utilises an existing local area network without incurring any additional hardware costs. Application of computational intelligence techniques based on the developed computing platform to the economic dispatch problem is outlined. The performance of genetic algorithms in parallel and cluster structures and their abilities in coping time constraint applications are also demonstrated. It is found that when the workload is large, a parallel computing structure should be exploited for cost-effectiveness purpose.
World Bank and Urban Development: From Projects to Policy

Introduction 1. Theorizing the World Bank and Development 2. Toward Social Lending - Shifts in the World Bank's Development Thinking 3. The Search for an Urban Agenda at The World Bank 4. The Fall of Poverty Alleviation: The Politics of Urban Lending at The World Bank 5. Beyond Global and Local: A Critical Analysis of The World Bank Urban Programs In Zimbabwe 6. Globalization, Neo-Liberalism and The Politics of The Bank's Current Urban Agenda 7. Conclusion. Bibliography
A Eulerlan-Lagrangian Model to Simulate Two-Phase/Particulate Flows

Abstract : Figure 1 shows a snapshot of liquid fuel spray coming out of an injector nozzle in a realistic gas-turbine combustor. Here the spray atomization was simulated using a stochastic secondary breakup model (Apte et al. 2003a) with point-particle approximation for the droplets. Very close to the injector, it is observed that the spray density is large and the droplets cannot be treated as point-particles. The volume displaced by the liquid in this region is significant and can alter the gas-phase flow and spray evolution. In order to address this issue, one can compute the dense spray regime by an Eulerian- Eulerian technique using advanced interface tracking/level-set methods (Sussman et al. 1994; Tryggvason et al. 2001; Herrmann 2003). This, however, is computationally intensive and may not be viable in realistic complex configurations. We therefore plan to develop a methodology based on Eulerian-Lagrangian technique which will allow us to capture the essential features of primary atomization using models to capture interactions between the fluid and droplets and which can be directly applied to the standard atomization models used in practice. The numerical scheme for unstructured grids developed by Mahesh et al. (2003) for incompressible flows is modified to take into account the droplet volume fraction. The numerical framework is directly applicable to realistic combustor geometries. Our main objectives in this work are: * Develop a numerical formulation based on Eulerian-Lagrangian techniques with models for interaction terms between the fluid and particles to capture the Kelvin- Helmholtz type instabilities observed during primary atomization. * Validate this technique for various two-phase and particulate flows. * Assess its applicability to capture primary atomization of liquid jets in conjunction with secondary atomization models.
Nonlinear MIMO communication systems : channel estimation and information recovery using Volterra models. (Systèmes de communication MIMO non-linéaires : estimation de canal et récupération d'information en utilisant des modèles de Volterra)

Due to the presence of nonlinear devices such as power amplifiers (PA) and optical instruments, the communication signals are sometimes corrupted by nonlinear distortions. In such cases, nonlinear models are used to provide an accurate signal representation, allowing the development of efficient signal processing techniques capable of eliminating or reducing these nonlinear distortions. In this context, the choice of the nonlinear system model plays a fundamental role. The Volterra model has since longtime been used to represent communication systems in presence of nonlinear distortions, with applications for modeling satellite communication links, orthogonal frequency division multiplexing (OFDM) systems and radio over fiber (ROF) channels. The main objective of this thesis is to propose techniques for channel estimation and information recovery in multiple-input-multiple-output (MIMO) Volterra communication systems. This kind of MIMO model is able of modeling nonlinear communication channels with multiple transmit and receive antennas, as well as multi-user channels with a single transmit antenna for each user and multiple receive antennas. Channel estimation and equalization techniques are developed for three types of nonlinear MIMO communication systems: OFDM, ROF and Code division multiple access (CDMA)-ROF systems. According to the considered communication systems, different kinds of MIMO Volterra models are used. In the case of OFDM systems, we develop receivers that exploit the diversity provided by a proposed transmission scheme. In the case of time and space division multiple access (TDMA-SDMA) systems, a set of orthonormal polynomials is developed for increasing the convergence speed of a supervised adaptive MIMO Volterra estimation algorithm. Moreover, in order to develop signal processing techniques for MIMO Volterra communication channels in a blind scenario, we make use of tensor decompositions. By exploiting the fact that Volterra models are linear with respect to their coefficients, blind estimation and equalization of MIMO Volterra channels are carried out by means of the Parallel Factor (PARAFAC) tensor decomposition, considering TDMA-SDMA and CDMA communication systems.
k-POD: A Method for k-Means Clustering of Missing Data

The k-means algorithm is often used in clustering applications but its usage requires a complete data matrix. Missing data, however, are common in many applications. Mainstream approaches to clustering missing data reduce the missing data problem to a complete data formulation through either deletion or imputation but these solutions may incur significant costs. Our k-POD method presents a simple extension of k-means clustering for missing data that works even when the missingness mechanism is unknown, when external information is unavailable, and when there is significant missingness in the data. [Received November 2014. Revised August 2015. ]
Vitamin A Transport and the Transmembrane Pore in the Cell-Surface Receptor for Plasma Retinol Binding Protein

Vitamin A and its derivatives (retinoids) play diverse and crucial functions from embryogenesis to adulthood and are used as therapeutic agents in human medicine for eye and skin diseases, infections and cancer. Plasma retinol binding protein (RBP) is the principal and specific vitamin A carrier in the blood and binds vitamin A at 1∶1 ratio. STRA6 is the high-affinity membrane receptor for RBP and mediates cellular vitamin A uptake. STRA6 null mice have severely depleted vitamin A reserves for vision and consequently have vision loss, even under vitamin A sufficient conditions. STRA6 null humans have a wide range of severe pathological phenotypes in many organs including the eye, brain, heart and lung. Known membrane transport mechanisms involve transmembrane pores that regulate the transport of the substrate (e.g., the gating of ion channels). STRA6 represents a new type of membrane receptor. How this receptor interacts with its transport substrate vitamin A and the functions of its nine transmembrane domains are still completely unknown. These questions are critical to understanding the molecular basis of STRA6′s activities and its regulation. We employ acute chemical modification to introduce chemical side chains to STRA6 in a site-specific manner. We found that modifications with specific chemicals at specific positions in or near the transmembrane domains of this receptor can almost completely suppress its vitamin A transport activity. These experiments provide the first evidence for the existence of a transmembrane pore, analogous to the pore of ion channels, for this new type of cell-surface receptor.