Miracle-dz/UniFAR-FTUs huggingface dataset:
Story Understanding through Semantic Analysis and Automatic Alignment of Text and Video

Stories are the pinnacle of human creativity, and yet a ubiquitous phenomenon. An important element of human communication consists of telling and listening, reading, and nowadays watching stories enacted on film. Among different means of story-telling, videos (TV series and movies) are a very powerful medium as they have the potential to engage multiple human senses. Artificial Intelligence (AI) has made large strides in the last decade, through which several advances have been achieved in both language and vision. However, these fields have been primarily studied separately, and only in the last few years do we see joint analysis rising to prominence. We argue that the ability to model, analyze, understand, and create new stories is a stepping stone for strong AI – a machine that could perform any intellectual task that a human can. Towards this grander goal of story understanding, we seek to build upon a wave of research in the joint study of vision and language. TV series and movies are perfect candidates for such a study, as they are videos produced for the specific purpose of story-telling. In this thesis, we define machine understanding of stories as the ability to perform human-like tasks upon those stories, such as indexing and searching for story events in large collections, summarizing the stories, and answering questions about them. We address the problem of story understanding from three vantage points. First, we introduce the use of novel sources of natural language text that allow to better learn the content of the videos. Next, we propose a visualization technique to obtain a big picture overview of the story conveyed in a video. Finally, we provide a means to examine machine understanding of stories by using question-answering as a surrogate task.
Catch Me If You Can: Improving the Scope and Accuracy of Fraud Prediction

We propose a parsimonious metric – the Adjusted Benford score (AB-score) – to improve the detection of financial misstatements. Based on Benford’s Law, which predicts the leading-digit distribution of naturally occurring numbers, the AB-score estimates a firm-year’s likelihood of financial statement manipulation, compared to its peers and controlling for time-series trends. The AB-score’s biggest advantage is coverage: It can be computed for about 60% more firm-years than the leading accounting-based metric (the F-score) without sacrificing accuracy. Notably, it can be computed for financial firms, which are often excluded from financial misconduct research due to data availability issues. For firm-years with all data available, combining the AB-score and F-score variables into one model yields higher accuracy in predicting misstatements. Our metric performs well out-of-sample as well as in-sample, across different misstatement databases, and for a set of notorious financial frauds. It should be especially useful to regulators and industry professionals.
A pointwise estimate for the Fourier transform and the number of maxima of a function

We show a pointwise estimate for the Fourier transform on the line involving the number of times the function changes monotonicity. The contrapositive of the theorem may be used to find a lower bound to the number of local maxima of a function. We also show two applications of the theorem. The first is the two weight problem for the Fourier transform, and the second is estimating the number of roots of the derivative of a function.
Selection of Spatial Filters for ON/OFF Based Topology Optimization of a C-Core Electromagnetic Actuator

This paper investigates different spatial filtering techniques used with ON/OFF based topology optimization and compares their performances for optimizing a C-core electromagnetic actuator. The filters’ efficacy in dealing with checkerboard patterns, perforations, and floating material pieces and their impact on the armature force and the topology’s smoothness are evaluated and discussed.
A dynamic approach to L2 development in written language

It is assumed that language is constantly changing and developing within a Dynamic Systems Theory and Complexity Theory approach. This study investigates how the developmental process works for two advanced students of English their written language productions over the course of approximately 4 years. Subsequently, the written data samples were divided into two overarching categories of writing genres, e.g. formal and informal texts. Grammatical complexity, lexical complexity, and use of formulaic sequences are analyzed by at looking at the degree of variability and patterns of change. The results were processed with scattered graphs, moving min-max graphs, and moving correlations. The results show both inter- and intra-individual variability and difference in writing genres have influenced how the learners’ language has progressed over time.
Research of Intrusion Detection System Based on Computer Network

With the rapid development of computer and network techniques, computer network security has been one of the keys to the modern computer system. Intrusion detection system (IDS) is differ from the firewall and the anti- virus software, because it can monitor the dynamic behavior character of the network or the computer system, and take active recovery measure to hold back intru- sion. Research actuality of the IDS has been detailedly discussed from concept, means and algorithm of IDS, and put forward to IDS trend in the future. At the same time, it also provides essential technology and development to farther research IDS.
Assessing Quantitative Literacy in Higher Education: An Overview of Existing Research and Assessments with Recommendations for Next-Generation Assessment. Research Report. ETS RR-14-22.

Quantitative literacy has been recognized as an important skill in the higher education and workforce communities, focusing on problem solving, reasoning, and real-world application. As a result, there is a need by various stakeholders in higher education and workforce communities to evaluate whether college students receive sufficient training on quantitative skills throughout their postsecondary education. To determine the key aspects of quantitative literacy, the first part of this report provides a comprehensive review of the existing frameworks and definitions by national and international organizations, higher education institutions, and other key stakeholders. It also examines existing assessments and discusses challenges in assessing quantitative literacy. The second part of this report proposes an approach for developing a next-generation quantitative literacy assessment in higher education with an operational definition and key assessment considerations. This report has important implications for higher education institutions currently using or planning to develop or adopt assessments of quantitative literacy.
Ultra Short Tenor Yield Curves for High-Frequency Trading and Blockchain Settlement

Blockchain, based on the distributed ledger technology, provides immediate settlement of transactions of digital assets and direct ownership. Since settlement of transactions is immediate, the blockchain system requires an ultra short tenor interest rate curve that is always up-to-date. Today, many market-quoted rates are still accrued at the end of each trading day, typically with one day as the shortest tenor available. This paper develops an interbank money market model for the equilibrium interest rate of ultra short tenor and updated at an intraday level with automated adjustment for the event of a flash crash. Apart from facilitating trades settlement on blockchain, our research findings are vital for central banks' efforts in stabilizing the currencies during flash crashes. We show that during the flash crash on 15 January 2015 when the Swiss National Bank (SNB) dropped the floor of CHF 1.2 per EUR, the ultra short CHF interest rates should have been highly negative to incentivize market makers to provide liquidity during the sharp CHF appreciation and to neutralize the arbitrage activities that aggravated the crash.
Estimating Probabilities of Patent Oppositions in a Bayesian Semiparametric Regression Framework

Most econometric analyses of patent data rely on regression methods using a parametric form of the predictor for modeling the dependence of the response in focus on given covariates. These methods often lack the capability of identifying non-linear relationships between dependent and independent variables. We present an approach based on a generalized additive model in order to avoid these shortcomings. Our method is fully Bayesian and makes use of Markov Chain Monte Carlo (MCMC) simulation techniques for estimation purposes. Using this methodology we reanalyze the determinants and the effects of patent oppositions in Europe for biotechnology/pharmaceutical and semiconductor/computer software patents. Our results largely confirm the findings of a previous parametric analysis of the same data provided by Graham, Hall, Harhoff & Mowery (2002). However, our model specification clearly verifes considerable non-linearities in the efect of various covariates on the probability of an opposition. Furthermore, our semiparametric approach shows that some categorizations of metric covariates made by Graham et al. (2002) in order to capture those non-linearities appear to be somehow ad hoc and could be optimized.
Faktor-Faktor Yang Mempengaruhi Intensi Dalam Membayar Wakaf Uang Pada Pegawai Kantor Wilayah Kementerian Agama Provinsi Dki Jakarta

Faktor-faktor yang dimaksudkan dan menjadi tujuan penelitian ini adalah pengaruh secara parsial dari sikap, norma subyektif dan kepercayaan pada niat dalam membayar uang tunai-waqf pada karyawan. Metode yang digunakan dalam penelitian ini adalah metode survei dengan pendekatan korelasi. Pengumpulan data menggunakan kuesioner dengan Proportionate Stratified Random Sampling, dengan sampel adalah 136 yang beragama Islam. Analisis data teknis menggunakan analisis persyaratan analisis, analisis uji asumsi, analisis regresi, analisis korelasi dan penentuan. Dari uji persyaratan analisis, data dinyatakan normal dan linier dengan hasil persamaan regresi berganda Ỹ = 8,268 + 0,157X1 + 0,170 X2 + 0,261X3. Dari analisis data, diperoleh nilai T untuk sikap 3,206, norma subyektif 3,552, dan kepercayaan 6,989> 1,978 (T Tabel). Oleh karena itu, hasil penelitian ini menunjukkan bahwa secara parsial, sikap, norma dan kepercayaan subjektif memiliki pengaruh positif dan signifikan terhadap niat membayar uang tunai-wakaf. Studi ini menyimpulkan secara parsial bahwa sikap yang lebih baik, tingkat norma dan kepercayaan subjektif yang lebih tinggi, akan meningkatkan niat mereka dalam membayar wakaf tunai. Cara lain, sikap yang kurang baik, tingkat norma dan kepercayaan subjektif yang lebih rendah, akan mengurangi niat mereka dalam membayar wakaf tunai.
Minimum Spanning Tree Co-registration Approach for Time-Series Sentinel-1 TOPS Data

Synthetic aperture radar (SAR) image co-registration is one of the essential steps for interferometric SAR processing and the following multitemporal analysis. All acquisitions from time-series images with the Sentinel-1 Terrain Observation by Progressive Scans (TOPS) model should be co-registrated to a common reference geometry with an accuracy of approximately 0.001 pixels. Such a high accuracy can be achieved by correcting the residual azimuth mis-registration using the Enhanced Spectral Diversity (ESD) technique. However, the performance of the ESD depends on the coherence of image pairs, especially over fast decorrelation areas. To improve the coherence between acquisitions, we develop a joint co-registration procedure based on the minimum-spanning-tree algorithm and iterative reweighted least squares. In order to further improve the accuracy of the azimuth mis-registration over low-coherence scenes, we present a coherence estimator by combining two consecutive bursts of SLC samples to reduce both bias and variance. The proposed method is tested over two low-coherence scenes and compared to the network-based ESD approach. The results from both synthetic and real data demonstrated the advantages of our method.
Conformal Killing 2-forms on 4-dimensional manifolds

We study 4-dimensional simply connected Lie groups $G$ with left-invariant Riemannian metric $g$ admitting non-trivial conformal Killing 2-forms. We show that either the real line defined by such a form is invariant under the group action, or the metric is half conformally flat. In the first case, the problem reduces to the study of invariant conformally K\"ahler structures, whereas in the second case, the Lie algebra of $G$ belongs (up to homothety) to a finite list of families of metric Lie algebras.
Minimax Filtering via Relations between Information and Estimation

We investigate the problem of continuous-time causal estimation under a minimax criterion. Let $X^T = \{X_t,0\leq t\leq T\}$ be governed by the probability law $P_{\theta}$ from a class of possible laws indexed by $\theta \in \Lambda$, and $Y^T$ be the noise corrupted observations of $X^T$ available to the estimator. We characterize the estimator minimizing the worst case regret, where regret is the difference between the causal estimation loss of the estimator and that of the optimum estimator. One of the main contributions of this paper is characterizing the minimax estimator, showing that it is in fact a Bayesian estimator. We then relate minimax regret to the channel capacity when the channel is either Gaussian or Poisson. In this case, we characterize the minimax regret and the minimax estimator more explicitly. If we further assume that the uncertainty set consists of deterministic signals, the worst case regret is exactly equal to the corresponding channel capacity, namely the maximal mutual information attainable across the channel among all possible distributions on the uncertainty set of signals. The corresponding minimax estimator is the Bayesian estimator assuming the capacity-achieving prior. Using this relation, we also show that the capacity achieving prior coincides with the least favorable input. Moreover, we show that this minimax estimator is not only minimizing the worst case regret but also essentially minimizing regret for "most" of the other sources in the uncertainty set. We present a couple of examples for the construction of an minimax filter via an approximation of the associated capacity achieving distribution.
ECAR Study of Undergraduate Students and Information Technology, 2014.

Technology is a critical part of undergraduate students’ experiences in higher education. This study explores technology ownership, use patterns, and expectations as they relate to the student experience. Colleges and universities can use the results of this study to better engage students in the learning process. Furthermore, institutions can use the data to improve information technology (IT) services, increase technology-enabled productivity, prioritize strategic contributions of IT to higher education, plan for technology shifts that impact students, and become more technologically competitive among peer institutions.
Decision Making under Uncertainty: An Experimental Study in Market Settings

We design and implement a novel experimental test of subjective expected utility theory and its generalizations. Our experiments are implemented in the laboratory with a student population and pushed out through a large-scale panel to a general sample of the U.S.\ population. We find that a majority of subjects' choices are consistent with the maximization of {\em some} utility function, but not with subjective utility theory. The theory is tested by gauging how subjects respond to price changes. A majority of subjects respond to price changes in the direction predicted by the theory, but not to a degree that makes them fully consistent with subjective expected utility. Surprisingly, maxmin expected utility adds no explanatory power to subjective expected utility. Our findings remain the same regardless of whether we look at laboratory data or the panel survey, even though the two subject populations are very different. The degree of violations of subjective expected utility theory is not affected by age nor cognitive ability, but it is correlated with financial literacy.
Simulation of sensory-evoked signal flow in anatomically realistic models of neural networks

English In this thesis, a new concept for development and simulation of anatomically and functionally constrained models of signal flow in neural networks is described. This approach consists of the following tools: 1. A standardized anatomical reference frame of the brain region studied and registration methods to integrate anatomical data from different experiments with the highest precision possible. 2. A method for determining morphological neuron types to allow correlation between measurements of the morphology and functional responses of individual neurons. 3. A tool to build an average three-dimensional (3D) statistical model of the neural networks in a brain region based on a representative sparse sample of all neuron types present in the brain region. This model contains 3D morphological models for every neuron in the brain region, as well as the total number and 3D distribution of synaptic contacts between them. 4. A method to activate the network based on measured responses of different neuron types, and to simulate the response of individual neurons representative of different cell types within this network model. The feasibility and validity of this process is demonstrated on the example of rat vibrissal cortex. The 3D model of this primary sensory area in cortex contains ∼ 530, 000 neurons of 16 different types and ∼ 6×10 thalamocortical and intracortical synapses. Activation of this model with functional responses measured after whisker touch and simulation of the responses of different neuron types shows that the simulated model responses match experimental measurements. This allowed investigating how robust sensory-evoked responses after different sensory stimuli are formed in different neuron types using computer simulations, and to make predictions to experimentally test these hypotheses.
Calibration Method of Accelerometer’s High-Order Error Model Coefficients on Precision Centrifuge

This paper presents a new calibration method of the accelerometer tested on a precision centrifuge to further enhance the calibration accuracy of the high-order error model coefficients. To eliminate the influence of dynamic and static error sources of precision centrifuge on calibration accuracy, nine coordinate systems are established considering the errors of a centrifuge, which are propagated by homogeneous transformation, and the accurate specific forces acting on three axes of the tested accelerometer are obtained. Based on the error model and the accurately computed input specific forces of the accelerometer, the indicated outputs of the tested accelerometer are derived, and with the combinations of indicated outputs of six calibration position pairs, a calibration model of the accelerometer is established. By designing a test plan of 12 positions under three mounting modes and using the least-squares method, all the high-order error model coefficients of the tested accelerometer are calibrated accurately. In the calibration method, the dynamic errors of precision centrifuge are introduced into the observation vectors, and the static errors are introduced into the vectors to be identified; the influence of centrifuge errors is automatically eliminated. Error analysis implies that the calibration accuracy is improved greatly.
Avaliação da secagem de metformina 850mg em leito fluidizado industrial

A administracao de farmacos para efeitos sistemicos por via oral e a forma mais comum dentre os medicamentos. Dentre estes, os medicamentos na forma de comprimidos sao os mais empregados. A granulacao e um processo que visa melhorar o transporte do po na maquina compressora por meio da aglomeracao de particulas. A secagem em leito fluidizado acoplado a tecnica de spray dryer e a tecnica comumente empregada para a formacao de grânulos que atendam as caracteristicas necessarias de granulometria uniforme, com controle rigoroso da umidade final do granulado e tempo relativamente curto de processo quando comparado a outras tecnicas para producao de medicamentos. A metformina e um farmaco, apresentado na forma de cloridrato, e administrado como comprimidos revestidos por via oral. E indicado no tratamento de diabetes, mais especificamente diabetes mellitus tipo 2. Com o objetivo de aprimorar a produtividade em um leito fluidizado industrial utilizado na granulacao e secagem de metformina, faz-se necessario avaliar os efeitos das condicoes operacionais utilizadas no processo referentes a qualidade material particulado e o processo de producao propriamente dito. Para tanto, realizou-se o estudo fluidodinâmico da granulacao e secagem de metformina em leito fluidizado investigando assim a velocidade minima de fluidizacao para o processamento deste farmaco. A influencia da temperatura e da velocidade do ar de secagem no tempo de processamento da formula e no tamanho medio da particula tambem foram avaliados. Os experimentos foram elaborados a partir da teoria da Operacao Evolutiva, proposta por Box (1957). A modelagem da etapa de secagem tambem foi realizada. Por meio dos experimentos realizados conseguiu-se reduzir a zero os reprocessos de bateladas por formacao de canais preferenciais, onde poderia ocorrer deposicao de solucao polimerica sobre o material particulado. Foi possivel tambem reduzir o tempo medio de processamento em 8 minutos, agregando maior produtividade e economia para a empresa na qual este trabalho foi desenvolvido. Os resultados obtidos mostram que houve ganhos em relacao a produtividade, e norteiam para onde os esforcos devem ser direcionados para continuidade do melhoramento de produtividade, fornecendo uma metodologia pratica para aplicacao da tecnica que podera ser aplicada na producao de outros farmacos que utilizam o processo de granulacao por via umida em leito fluidizado.