Miracle-dz/UniFAR-FTUs huggingface dataset:
Continuous Time Bayesian Networks for Reasoning and Decision Making in Finance

The analysis of the huge amount of financial data, made available by electronic markets, calls for new models and techniques to effectively extract knowledge to be exploited in an informed decision-making process. The aim of this thesis is to introduce probabilistic graphical models that can be used to reason and to perform actions in such a context. In the first part of this thesis, we present a framework which exploits Bayesian networks to perform portfolio analysis and optimization in a holistic way. It leverages on the compact and efficient representation of high dimensional probability distributions offered by Bayesian networks and their ability to perform evidential reasoning in order to optimize the portfolio according to different economic scenarios. In many cases, we would like to reason about the market change, i.e. we would like to express queries as probability distributions over time. Continuous time Bayesian networks can be used to address this issue. In the second part of the thesis, we show how it is possible to use this model to tackle real financial problems and we describe two notable extensions. The first one concerns classification, where we introduce an algorithm for learning these classifiers from Big Data, and we describe their straightforward application to the foreign exchange prediction problem in the high frequency domain. The second one is related to non-stationary domains, where we explicitly model the presence of statistical dependencies in multivariate time-series while allowing them to change over time. In the third part of the thesis, we describe the use of continuous time Bayesian networks within the Markov decision process framework, which provides a model for sequential decision-making under uncertainty. We introduce a method to control continuous time dynamic systems, based on this framework, that relies on additive and context-specific features to scale up to large state spaces. Finally, we show the performances of our method in a simplified, but meaningful trading domain.
An Approach to Detect Polarity Variation Rules for Sentiment Analysis

: Sentiment Analysis is a discipline that aims at identifying and extract the subjectivity expressed by authors of information sources. Sentiment Analysis can be applied at different level of granularity and each of them still has open issues. In this paper we propose a completely unsupervised approach aimed at inducing a set of words patterns that change the polarity of subjective terms. This is a very important task because, while sentiment lexicons are valid tools that can be used to identify the polarity at word level, working at different level of granularity they are no longer sufﬁcient, because of the various aspects to consider like the context, the use of negations and so on that can change the polarity of subjective terms.
Interactive Ray Tracing of Arbitrary Implicits with SIMD Interval Arithmetic

We present a practical and efficient algorithm for interactively ray tracing arbitrary implicit surfaces. We use interval arithmetic (IA) both for robust root computation and guaranteed detection of topological features. In conjunction with ray tracing, this allows for rendering literally any programmable implicit function simply from its definition. Our method requires neither special hardware, nor preprocessing or storage of any data structure. Efficiency is achieved through SIMD optimization of both the interval arithmetic computation and coherent ray traversal algorithm, delivering interactive results even for complex implicit functions.
A BPM-based solution for inter-domain circuit management

In the last few years, network middleware solutions have been proposed to deal with Quality of Service (QoS) demands of end-user network applications. Usually, such solutions employ virtual circuits, with end-points often located in different administrative domains. However, these middleware solutions still do not support online human decisions. The human-centered support is specially important when pre-installed rules do not suffice to evaluate virtual circuit requests. In this paper, we present a middleware for dynamic circuit networks (DCNs) based on the Business Process Management (BPM) approach to support human administrator decisions in virtual circuits provisioning. A set of experiments have been conducted in the Brazilian National Education and Research Network (RNP) backbone, and the findings in performance and flexibility are presented.
Multifunctional microstrip transmission lines integrated with defected ground structure for RF front-end application

This paper presents multifunctional microstrip transmission lines for designing a high port-isolation dual-frequency orthogonally polarized rectangular patch antenna and the antenna-integrated power amplifier. The proposed lines were realized through the integration of defected ground structures (DGSs) with conventional microstrip lines. A spiral-shaped DGS-integrated microstrip line enhances the port isolation of the antenna, while feeding the 2.0-GHz excitation to the antenna and filtering out the 2.5-GHz receiving signal from the other port. High-order harmonic signal suppression of the power amplifier at the 2.5-GHz port was accomplished by the dumbbell-shaped DGS, thereby improving the efficiency of the amplifier. Measurements show an improvement of 20 dB in port isolation and 3% in power-added efficiency relative to an identical RF front-end, but integrated with a conventional patch antenna. An image impedance of the DGS-integrated microstrip lines can be controlled by the integrated DGS geometries. Relatively high-impedances lines, i.e., 150 and 100 /spl Omega/, are effectively implemented using microstrip lines with 75- and 50-/spl Omega/ linewidths by incorporating the spiral- and dumbbell-shaped DGSs, respectively.
iPod Touch® to Increase Functional Communication of Adults With Autism Spectrum Disorder and Significant Intellectual Disability

Adults with autism spectrum disorder (ASD) and significant intellectual disability (ID) often have limited speech communication abilities. Abundant research supports use of augmentative and alternative communication (AAC) to enhance skills of children with ASD and ID, but less research has examined efficacy of AAC with non-speaking adults. In this study, three adults with ASD and significant ID were taught basic functional communication using the iPod Touch® with MyTalk Mobile® software within a single-case, multiple-probe across-subjects design. The iPod Touch® taught with most-to-least prompting increased participants’ independent manding, participants were able to discriminate between picture symbols, and participants’ manding generalized to a naturalistic setting with typically available preferred items. Implementation of AAC coincided with increases in speech for one participant. Results illustrate how an applied behavior analysis approach incorporating a speech generating device is effective in teaching communication to adults with ASD and significant ID.
Description of Embryogenesis of Atlantic Cod Gadus Morhua

This paper presents a description of the embryonic development of Atlantic cod Gadus morhua. In addition, an equation describing the effect of temperature on developmental rate was developed. The whole period of embryogenesis was divided into 6 subperiods and 75 specific stages based on the distinctive characteristics. Temperature effects on the developmental rate of Atlantic cod embryos were studied at 5 different regimes of constant temperature in the range 1.912. 25C. During somitogenesis no less than 46 somites from a total number of 52-53 appear at equal time intervals. Embryos within single temperature batches showed very high synchronism of development: the deviation was no more than 1% from fertilization till hatching. In order to unify the developmental time under different temperature regimes, the age of embryos was measured in the relative units of S (“tau somite”), which correspond to the time of formation of a single somite pair. The empirical S values determined at different temperature regimes were used to define an equation describing the dependence of the developmental rate on temperature in Atlantic cod embryos. This dependence was expressed as: log S (t) = 2.62025-0.06803t + 0.00087t , where t is the temperature.
Efficient multi-task feature learning with calibration

Multi-task feature learning has been proposed to improve the generalization performance by learning the shared features among multiple related tasks and it has been successfully applied to many real-world problems in machine learning, data mining, computer vision and bioinformatics. Most existing multi-task feature learning models simply assume a common noise level for all tasks, which may not be the case in real applications. Recently, a Calibrated Multivariate Regression (CMR) model has been proposed, which calibrates different tasks with respect to their noise levels and achieves superior prediction performance over the non-calibrated one. A major challenge is how to solve the CMR model efficiently as it is formulated as a composite optimization problem consisting of two non-smooth terms. In this paper, we propose a variant of the calibrated multi-task feature learning formulation by including a squared norm regularizer. We show that the dual problem of the proposed formulation is a smooth optimization problem with a piecewise sphere constraint. The simplicity of the dual problem enables us to develop fast dual optimization algorithms with low per-iteration cost. We also provide a detailed convergence analysis for the proposed dual optimization algorithm. Empirical studies demonstrate that, the dual optimization algorithm quickly converges and it is much more efficient than the primal optimization algorithm. Moreover, the calibrated multi-task feature learning algorithms with and without the squared norm regularizer achieve similar prediction performance and both outperform the non-calibrated ones. Thus, the proposed variant not only enables us to develop fast optimization algorithms, but also keeps the superior prediction performance of the calibrated multi-task feature learning over the non-calibrated one.
Stable and High-Order Finite Difference Methods for Multiphysics Flow Problems

Partial differential equations (PDEs) are used to model various phenomena in nature and society, ranging from the motion of fluids and electromagnetic waves to the stock market and traffic jams. There are many methods for numerically approximating solutions to PDEs. Some of the most commonly used ones are the finite volume method, the finite element method, and the finite difference method. All methods have their strengths and weaknesses, and it is the problem at hand that determines which method that is suitable. In this thesis, we focus on the finite difference method which is conceptually easy to understand, has high-order accuracy, and can be efficiently implemented in computer software.We use the finite difference method on summation-by-parts (SBP) form, together with a weak implementation of the boundary conditions called the simultaneous approximation term (SAT). Together, SBP and SAT provide a technique for overcoming most of the drawbacks of the finite difference method. The SBP-SAT technique can be used to derive energy stable schemes for any linearly well-posed initial boundary value problem. The stability is not restricted by the order of accuracy, as long as the numerical scheme can be written in SBP form. The weak boundary conditions can be extended to interfaces which are used either in domain decomposition for geometric flexibility, or for coupling of different physics models.The contributions in this thesis are twofold. The first part, papers I-IV, develops stable boundary and interface procedures for computational fluid dynamics problems, in particular for problems related to the Navier-Stokes equations and conjugate heat transfer. The second part, papers V-VI, utilizes duality to construct numerical schemes which are not only energy stable, but also dual consistent. Dual consistency alone ensures superconvergence of linear integral functionals from the solutions of SBP-SAT discretizations. By simultaneously considering well-posedness of the primal and dual problems, new advanced boundary conditions can be derived. The new duality based boundary conditions are imposed by SATs, which by construction of the continuous boundary conditions ensure energy stability, dual consistency, and functional superconvergence of the SBP-SAT schemes.
Combined link dimensioning and weight assignment of minimum weight routing networks

MPLS (multi-protocol label switching) technology provides the flexibility required for managing the way the traffic is routed through the network. However, label switched path (LSP) configuring is a hard task in a growing network, as more and more routes need configuring and monitoring. A viable alternative may be to rely on an IGP (interior gateway protocol) routing protocol to determine the paths to be used by the LSPs, thus freeing the operator from the manual configuring of all LSP paths. Here, we address the procedure of dimensioning a MPLS network where a minimum weight routing protocol (as OSPF or IS-IS) is used to determine the paths of the LSPs. We start by presenting the complete minimum weight routing network design problem (MWRNDP) with explicit minimum weight routing constraints. Then, we propose a two-step approach based on two ILP models which are a decomposition of the complete model in two separate optimization problems: first, we determine the physical network configuration and the traffic flow routing with the network design problem (NDP); then, we determine the link weights required to achieve the determined traffic routing with the link weight assignment problem (LWA). Because in the first problem the traffic routing is destination based, there may be instances where a minimum weight routing solution is not found. In these cases, an additional constraint is added to the first problem and the two-step approach is repeated. An important observation is that this methodology obtains the optimal solutions and the computational results show that it requires much lower computational times than the original global MWRNDP model. Using the two-step approach, a set of computational tests is presented to determine the cost penalty in MPLS network design when using minimum weight routing as opposed to source based routing.
Establishing the Spokes-Character in Academic Inquiry: Historical Overview and Framework For Definition

ABSTRACT A growing interest in advertising spokes-characters as product presenters suggests the need to establish a foundation for serious academic inquiry in this topic area. The issues that emerge most often when considering how to direct research efforts in this topic area are related to character definition, i.e., how a character looks and acts in an advertisement. This paper briefly documents the history and evolution of advertising spokes-characters, and outlines two criteria that separate these images from other advertising trademark symbols. A multi-dimensional framework for spokes-character definition is then presented, which provides for definition along four parameters: the physical Appearance of the character, the Medium it appears in, advertising or non-advertising Origin, and spokes-character Promotion of the product (AMOP). Topics for future research are discussed.
Hit it!: an apparatus for upscaling mobile HCI studies

Mobile HCI studies are often conducted in a highly controlled environment and with a small convenient sample. Such common studies can have a high internal validity but often lack external validity. The findings cannot always be generalized to the behaviour of real users in real contexts. In contrast, researchers recently started to use apps as an apparatus for mobile HCI research. Publishing apps in mobile application stores enables to study large samples in their 'natural habitat'. We present the game Hit It! that has been installed 427,255 times and, more importantly, served as a tool to conduct a number of HCI studies. The amount of collected data enabled us to study users' touch behaviour, approaches to ask for consent, the best time to deploy games, and approaches for providing tactile feedback. We discuss advantages of the approach and argue that Hit It! enabled findings that would be impossible to obtain using traditional studies.
The INTERSPEECH 2009 emotion challenge

The last decade has seen a substantial body of literature on the recognition of emotion from speech. However, in comparison to related speech processing tasks such as Automatic Speech and Speaker Recognition, practically no standardised corpora and test-conditions exist to compare performances under exactly the same conditions. Instead a multiplicity of evaluation strategies employed – such as cross-validation or percentage splits without proper instance definition – prevents exact reproducibility. Further, in order to face more realistic scenarios, the community is in desperate need of more spontaneous and less prototypical data. This INTERSPEECH 2009 Emotion Challenge aims at bridging such gaps between excellent research on human emotion recognition from speech and low compatibility of results. The FAU Aibo Emotion Corpus [1] serves as basis with clearly defined test and training partitions incorporating speaker independence and different room acoustics as needed in most reallife settings. This paper introduces the challenge, the corpus, the features, and benchmark results of two popular approaches towards emotion recognition from speech. Index Terms: emotion, challenge, feature types, classification
Reinforcement learning based algorithm with Safety Handling and Risk Perception

Navigation in an unknown or uncertain environment is a challenging task for an autonomous agent. The agent is expected to behave independently and to learn the suitable action to take for a given situation. Reinforcement Learning could be used to help the agent adapt to an unknown environment and learn the right actions to take. This paper presents the setup and the results of a reinforcement learning problem utilizing Q-learning and a Safety Handling Exploration with Risk Perception Algorithm (SHERPA) for safe exploration in an unknown environment. The agent has to explore its environment safely and must learn the optimal action for a given situation from the feedback received from the environment. The results show that the agent can learn a value function converged to within 10% of the optimal values after 5000 iterations. The simulation results show that the proposed approach ensures that the agent explores an unknown environment safely and learns the desirable actions for a given situation.
T-FUSE IMPROVING HADOOP THROUGH FUSIONFS

Hadoop is an open-source software framework for distributed storage and distributed processing of massive data sets on large computer clusters [1]. Hadoop stores all the files on Hadoop Distributed File System (HDFS [2]). The major drawback of HDFS is that it stores all the metadata of its files on a single node called Name Node. When we have large number of small files the size of metadata might increase in such a way that it may not fit on a single node. And also if there are thousands of meta-data requests from the user, then the server might not be able to handle all of them. So HDFS cannot be used for many modern scientific applications like climatology, astronomy [3] are becoming metadata intensive and requires more support from the storage subsystem [4]. Therefore we use FusionFs [5], a Distributed File System which was designed to handle metadata intensive workloads efficiently. In this paper we are going to use FusionFS as our distributed storage engine and implement Toy Hadoop a MapReduce framework to process small files efficiently.
Economic Reforms and Constitutional Transition

This paper investigates the relationship between economic reforms and constitutional transition, which has been neglected by many transition economists. It is argued that assessment of reform performance might be very misleading if it is not recognized that economic reforms are just a small part of large scale of constitutional transition. Rivalry and competition between states and between political forces within each country are the driving forces for constitutional transition. We use Russia as an example of economic reforms associated with constitutional transition and China as an example of economic reforms in the absence of constitutional transition to examine features and problems in the two patterns of transition. It is concluded that under political monopoly of the ruling party, economic transition will be hijacked by state opportunism. Dual track approach to economic transition may generate very high long-term cost of constitutional transition that might outweigh its short-term benefit of buying out the vested interests.
Adipokines and Obesity Are Associated with Colorectal Polyps in Adult Males: A Cross-Sectional Study

Background Obesity increases the risk of colon cancer. It is also known that most colorectal cancers develop from adenomatous polyps. However, the effects of obesity and adipokines on colonic polyp formation are unknown. Methods To determine if BMI, waist circumference or adipokines are associated with colon polyps in males, 126 asymptomatic men (48–65 yr) were recruited at time of colonoscopy, and anthropometric measures as well as blood were collected. Odds ratios were determined using polytomous logistic regression for polyp number (0 or ≥3) and polyp type (no polyp, hyperplastic polyp, tubular adenoma). Results 41% of the men in our study were obese (BMI ≥30). The odds of an obese individual having ≥3 polyps was 6.5 (CI: 1.3–33.0) times greater than those of a lean (BMI<25) individual. Additionally, relative to lean individuals, obese individuals were 7.8 (CI: 2.0–30.8) times more likely to have a tubular adenoma than no polyp. As BMI category increased, participants were 2.9 (CI: 1.5–5.4) times more likely to have a tubular adenoma than no polyps. Serum leptin, IP-10 and TNF-α were significantly associated with tubular adenoma presence. Serum leptin and IP-10 were significantly associated with increased likelihood of ≥3 polyps, and TNF-α showed a trend (p = 0.09). Conclusions Obese men are more likely to have at least three polyps and adenomas. This cross-sectional study provides evidence that colonoscopy should be recommended for obese, white males.
Thermodynamics of model prions and its implications for the problem of prion protein folding.

Prion disease is caused by the propagation of a particle containing PrPSc, a misfolded form of the normal cellular prion protein (PrPC). PrPC can re-fold to form PrPSc with loss of alpha-helical structure and formation of extensive beta-sheet structure. Here, we model this prion folding problem with a simple, low-resolution lattice model of protein folding. If model proteins are allowed to re-fold upon dimerization, a minor proportion of them (up to approximately 17%) encrypts an alternative native state as a homodimer. The structures in this homodimeric native state re-arrange so that they are very different in conformation from the monomeric native state. We find that model proteins that are relatively less stable as monomers are more susceptible to the formation of alternative native states as homodimers. These results suggest that less-stable proteins have a greater need for a well-designed energy landscape for protein folding to overcome an increased chance of encrypting substantially different native conformations stabilized by multimeric interactions. This conceptual framework for aberrant folding should be relevant in Alzheimer's disease and other disorders associated with protein aggregation.