Miracle-dz/UniFAR-FTUs huggingface dataset:
Tobacco Use and Lower Accuracy in a Novel Facial Detection Task

The aim of the present study was to investigate the ways in which tobacco addiction affects a person’s ability to recognize facial patterns. Facial detection was assessed in 16 individuals with tobacco use disorder and 16 healthy nonsmokers. Facial stimuli were taken from the Ignatian Educational Foundation (FEI) database, from which 12 male and 12 female faces were randomly selected. In the facial detection task, the subjects’ task was to detect the location of a face when it was presented with a face/nonface pair on the screen. The order of stimulus presentation was randomized within sessions. Bayesian adaptive estimation was used for stimulus presentation. Presentation times varied between 16.7 and 3,006 ms. Lower response accuracy was associated with worse discrimination. No predictive effects of the cognitive tests on facial detection were found. A person’s ability of facial detection can be applied to provide initial descriptions of impairments in the visual processing system. Early stage visual processing is impaired by chronic smoking, and subjects are able to recognize this. Therefore, there is a possibility of reversing this effect and promoting a better prognosis. The present task has biopsychosocial applications and may improve smokers’ health by detecting subtle initial changes in visual processing.
Esophageal ECG: The challenge of electrode design

Two commercially available electrode catheters are examined for their suitability in esophageal long-term ECG recordings. Both, electrical sensing characteristics as well as clinical acceptance were investigated in a clinical study including inpatients with cardiovascular diseases. In total, 31 esophageal ECG were obtained in 36 patients. Results showed that esophageal electrodes were well tolerated by the patients. Hemispherical electrodes with higher diameter required more insertion attempts and were associated with increased failure rates as compared to cylindrical electrodes. In contrast, the higher surface area of hemispherical electrodes resulted in significantly higher signal-to-noise ratio. Contact impedance was equal for both electrode types, but esophageal electrodes had lower impedance if compared with skin electrodes.
Image-based path following for nonholonomic mobile robot

This paper presents an image-based path following task for a nonholonomic mobile robot using visual line features. To perform this task, the robot has to keep the features in his field of view. For this purpose, an image-based visual servo controller using task function formalism is developed to control the robot motion. The proposed controller is implemented on carlike robot and evaluated through real experiments.
Understanding users' continued usage of IP-based personal communication applications

Internet Protocol (IP)-based communication technology, such as Voice over IP (VoIP) in particular, is widely used for personal communication. Previous research focused on developing applications to achieve good Quality of Service (QoS), but were less focused on the quality perception and application adoption. This study proposed a model with Perceived Quality as an extension to the Expectation Confirmation Model (ECM). Data were collected from 125 participants who had previously used IP applications. The results revealed that Confirmation, Perceived Usefulness and Perceived Quality have a direct effect on Satisfaction. Based on the findings, VoIP providers should avoid creating overly-high expectations in their customers, as this would negatively affect satisfaction.
A framework for valuing derivative securities

This paper develops a general framework for valuing a wide range of derivative securities. Rather than focusing on the stochastic process of the underlying security and developing an instantaneously-riskless hedge portfolio, we focus on the terminal distribution of the underlying security. This enables the derivative security to be valued as the weighted sum of a number of component pieces. The component pieces are simply the different payoffs that the security generates in different states of the world, and they are weighted by the probability of the particular state of the world occurring. A full set of derivations is provided. To illustrate its use, the valuation framework is applied to plain-vanilla call and put options, as well as a range of derivatives including caps, floors, collars, supershares, and digital options.
The Russian Option: Reduced Regret

We propose a new put option where the option buyer receives the maximum price (discounted) that the option has ever traded at during the time period (which may be indefinitely long) between the purchase time and the exercise time, so that the buyer need look at the fluctuations only occasionally and enjoys having little or no regret that he did not exercise the option at an earlier time (except for the discounting). We give an exact simple formula for the optimal expected present value (fair price) that can be derived from the option and the (unique) optimal exercise strategy that achieves the optimum value under the assumption that the asset fluctuations follow the Black-Scholes exponential Brownian motion model, which is widely accepted. It is important to note that the discounting is necessary: If it is omitted or even if it is less than the Black-Scholes drift, then the value to the buyer under optimum performance isinfinite. We also solve the same problem under a different model: the original Bachelier linear Brownian market with linear discounting. This model is no longer accepted, but of course the mathematics is consistent. To our knowledge no such regretless option is currently traded in any existing market despite its evident appeal. We call it the Russian option, partly to distinguish it from the American and European options, where the term of the option is prescribed in advance and where no exact formula for the value has been given.
A method for finding word clusters in spoken language

At the Department of Linguistics in Gothenburg, a research group led by Jens Allwood has been working with spontaneous spoken language since the late 70's. The authors of this paper are currently a part of this group. We think that it is important to be aware that spoken language is different from written language, and that methods and theories developed for written language are not necessarily suited for spoken language. For a description of the differences between spoken and written language, see e.g. (Allwood 1996).
Solving Lattice Protein Folding Problems by Discrete Particle Swarm Optimization

Using computer programs to predict protein structures from a mass of protein sequences is promising for discovering the relationship between the protein construction and their functions. In the area of computational protein structure analysis, the hydrophobic-polar (HP) model is one of the most commonly applied models. The protein folding problem based on HP model has been shown as NP-hard, to handle such an NP-hard problem, this paper proposes a discrete particle swarm optimization algorithm (DPSO HP ) to solve various 2D and 3D HP lattice models-based protein folding problems. The discrete particle swarm optimization method used in DPSO HP is based on the set concept and the possibility theory from a set-based PSO (S-PSO). A selection strategy incorporating heuristic information and possibilities is adopted in DPSO HP . A particle’s positions in the algorithm are defined as a set of elements and the velocities of a particle are defined as a set of elements associated with possibilities. The experimental results on a series of 2D and 3D protein sequences show that DPSO HP is promising and performs better than various competitive state-of-the-art evolutionary algorithms.
Elastic imaging with OBS receiver-side multiples

Receiver-side water-column multiples acquired with ocean-bottom seismic sensors can be used for elastic imaging of the subsurface, which can provide additional information relative to more conventional acoustic imaging. These multiples can be separated from primaries contained in ocean-bottom seismic data using techniques such as up/down decomposition. In elastic imaging, the down-going wavefield consists of only P-waves because multiples propagate through the water-column. Receiver-side water-column multiples can be imaged by backpropagation from virtual receivers located at symmetric positions relative to the ocean surface, thereby increasing the imaging aperture. We perform imaging in the angle domain, which enables us to reverse the reflection polarity change at normal incidence. In addition to physical reflections, a strong solid/liquid interface at the ocean bottom generates unwanted mode conversions which are present in the images in the form of cross-talk between physical and non-physical events. However, this cross-talk can be easily identified in shot-domain or image-domain commonimage gathers, and can therefore be removed after imaging. In the end, our procedure leads to a collection of images accounting for different combinations of incident and reflected P and S waves. These images exploit surface-related multiples, and are therefore the expression of different subsurface illumination relative to the analogous reflections using primary reflections only. Such elastic images can be used to infer accurate lithological information about the subsurface using angle-dependent reflectivity for different combinations of incident and reflected waves.
Upgrading a large oil refinery electric power system

This paper describes the activities developed in Amuay Refinery of Petroleos de Venezuela, to upgrade its 182 MW electric power system, through the interconnection with an external independent power producer and major modifications in the electrical distribution system, in order to restore the system reliability, operational flexibility and equipment maintainability. Design criteria, power system analysis, power distribution installations and automation for generation, distribution and control room developed during the upgrading project are reviewed.
A Generic Task Model Using Timed Automata to Design and Analyze Real-Time Applications

In this work, we propose an approach for automated analysis of real-time scheduling problems based on timed automata. Tasks are modeled using timed automata while schedulers correspond to feasible runs computed using model checking algorithms. Using this model, we present a method to prove on one hand the feasibility of a scheduling problem and to compute, on the other hand, an hybrid off-line/on-line scheduling policy. We expose how to use it to re-demonstrate well known results, to produce efficient schedule regarding of various properties such as minimal preemption number, and to address the problem of scheduling real-time task set composed by possibly self-suspending tasks which is known to be NP-hard.
Hardware-level thread migration in a 110-core shared-memory multiprocessor

Advantages - significantly reduces traffic on high-locality workloads up to 14x reduction in traffic in some benchmarks - simple to implement and verify (indep. of core count, no transient states) - decentralized & trivially scalable (only # core ID bits, addr ↔ core mapping) Challenges - workloads should be optimized with memory model in mind (like allocating data on cache line boundaries but more coarse-grained) - automatically mapping allocation over cores not a trivial problem Opportunities - fine-grained migration is an enabling technology - since it's cheap and responsive, can be used for almost anything - e.g., if only some cores have FPUs, migrate to access FPU.
Differences between running activity in tennis training and match-play

ABSTRACT The aim of this study was to compare the running activity between training and match-play for young high-level tennis players. Ten female and ten male young high-level tennis players took part in the study (13.80 age ±2.08 years). Twelve Portable GPS devices operating at10 Hz were used to collect velocity data. Match-play analysis was carried out by Aragon Tennis Master on hard court and training analysis was carried out by High Level Performance Centre of the Aragon Tennis Federation. The distance covered per minute (DCmin) by players in match-play was higher than in training (Match-play = 50.4 ± 6.0 m· min−1 vs. Training = 34.5 ± 6.2 m· min−1; F(1, 76) = 163.9; p < 0.001; ὴ2p = 0.64, moderate effect). The acceleration distance covered per minute (DCAmin), was higher in match-play than in training (Match-play = 45.0 ± 3.0 m· min−1 vs. Training = 28.6 ± 6.2 m· min−1; F(1, 76) = 267.6; p < 0.001; ὴ2p = 0.7, moderate effect). The results showed that match-play was characterised by demanding to players a great number of accelerating efforts, whereas in training, players do not replicate these actions, predominating movements at high average speed than in match-play.
Simply recycled selection and incrementally reinforced selection methods applicable for semi-supervised learning algorithms

This paper presents an empirical study on selecting a small amount useful unlabeled data with which the classification accuracy of semi-supervised learning (SSL) algorithms can be improved. In particular, two selection strategies, named simply recycled selection and incrementally reinforced selection, are considered and empirically compared. The experimental results, obtained with well-known benchmark data sets, demonstrate that the latter works better than the former does in terms of classification accuracy.
Generating Concept Ontologies through Text Mining

Designing mechanisms for creating concept ontologies automatically is an important research problem. In this work we have proposed a rough-set based mechanism to generate concept ontologies with concepts mined from documents. When the concept ontology is mined from preclassified documents, the output signifies the core set of domain concepts and their inter-relationships that define the categories, as well as the inter-category relationships. When the ontology is mined from a heterogeneous collection, the documents are first clustered into homogeneous groups and then mined for concepts. Rough set based lower and upper approximations have been used to identify core concepts and associated concepts for a domain or a group. The scheme has been tested over multiple domains
Compliance control for standing maintenance of humanoid robots under unknown external disturbances

For stable motions of position controlled humanoid robots, ZMP (Zero Moment Point) control is widely adopted, but needs to be integrated with other controllers due to its relatively slow response and the execution error of robots. While CoM (Center of Mass) control is much more directly than ZMP feedback control in the view of rejecting unknown external disturbance. In the meanwhile, we hope the position-based humanoid robot can have the whole body compliance in standing maintenance. So we proposes a CoM compliance controller to achieve stable standing of position controlled humanoid robot under unknown disturbance. The controller uses the concept of force control and integrates virtual model control with admittance control, where an AMPM (Angular Momentum including inverted Pendulum Model)-based virtual model with variable gain is designed to not only generate desired recovery force but also take the GRF (Grand Reaction Force) constraints into account, while an admittance controller is employed to transform the desired force to expected CoM position and body attitude. The experiments were conducted on the humanoid robot `Kong' by exerting external force disturbance and changing the slope of the ground to demonstrate the effectiveness and robustness of our method.
The O I Line Emission in Active Galactic Nuclei Revisited

UV, visible, and near-infrared spectroscopy is used to study the transitions of neutral oxygen leading to the emission of broad O I λ8446, λ11287, and λ1304 in active galactic nuclei. From the strength of the former two lines, contrary to the general belief, we found that in six of seven galaxies, Lyβ fluorescence is not the only mechanism responsible for the formation of these three lines. Because O I λ13165 is almost reduced to noise level, continuum fluorescence is ruled out as an additional excitation mechanism, but the presence of O I λ7774 in one of the objects suggests that collisional ionization may have an important role in the formation of O I λ8446. The usefulness of the O I lines as a reliable reddening indicator for the broad-line region is discussed. The values of E(B-V) derived from the λ1304/λ8446 ratio agree with those obtained using other reddening indicators. The observations point toward a break in the one-to-one photon relation between λ8446 and λ1304, attributable to several destruction mechanisms that may affect the latter line.
Appears in Symbolic , Connectionist , and Statistical Approaches to Learning for Natural Language Processing

This paper presents results from recent experiments with Chill, a corpus-based parser acquisition system. Chill treats language acquisition as the learning of search-control rules within a logic program. Unlike many current corpus-based approaches that use statistical learning algorithms, Chill uses techniques from inductive logic programming (ILP) to learn relational representations. Chill is a very exible system and has been used to learn parsers that produce syntactic parse trees, case-role analyses, and executable database queries. The reported experiments compare Chill's performance to that of a more naive application of ILP to parser acquisition. The results show that ILP techniques, as employed in Chill, are a viable alternative to statistical methods and that the control-rule framework is fundamental to Chill's success.
Identifying the tunnel surrounding rock parameters based on particle swarm optimization arithmetic

Because numerical model complexity of tunnel, the paper induces a swarm intelligence optimization algorithm — improved particle swarm optimization, constructs the surrounding rock parameters identification method. Based on orthogonal design and uniformity design, the numerical tests of underground engineering are carried out, so as to produce data set to gain the regress model relating rock mechanical parameters and monitoring displacements. Begin from the random values of parameters, take error between calculation values and monitoring data as fitness value, iterating according to the PSO rule, then the parameters adaptive identification realized. True tunnel engineering calculation states that the mean has good global optimization ability, the recognition accuracy is satisfied.
Temporal/spatial model-based fault diagnosis vs. Hidden Markov models change detection method: Application to the Barcelona water network

This paper deals with a comparison of two different fault diagnosis frameworks. The first method is based on a temporal/spatial model-based analysis by exploiting a-priori information about the system under study, so fault detection is based on monitoring the residuals of combined spatial and time series models obtained from the network. The second method aims at characterizing and detecting changes in the probabilistic pattern sequence of data coming from the network. Relationships between data streams are modelled through sequences of linear dynamic time-invariant models whose trained coefficients are used to feed a Hidden Markov Model (HMM). When the pattern structure of incoming data cannot be explained by the trained HMM, a change is detected. Here, the performance obtained from this two distinct approaches is examined by using a dataset coming from the Barcelona water transport network.
Geometric Crossover for Permutations with Repetitions : Applications to Graph Partitioning Technical Report CSM-448

Geometric crossover is a representation-independent generalization of the traditional crossover defined using the distance of the solution space. By choosing a distance firmly rooted in the syntax of the solution representation as basis for geometric crossover, one can design new crossovers for any representation. In previous work we have applied geometric crossover to simple permutations. In this paper we design a new geometric crossover for permutations with repetitions that naturally suits partition problems and test it on the graph partitioning problem. Our new crossover outperforms all previous ones.
Health Insurance and Relational Contracts in Small American Firms

This paper studies the provision of health insurance in small private American …rms. Using unique data covering about 15,000 …rms over the period 2006-2011, we …nd that health insurance provision is strongly associated with relational contracts, speci…cally with wage shielding. The sensitivity of average wages to local housing prices during the 2008 housing crisis is high for …rms with no health
Steady-state distributions for human decisions in two-alternative choice tasks

In human-in-the-loop systems, humans are often faced with making repeated choices among finite alternatives in response to observations of the evolving system performance. In order to design humans into such systems, it is important to develop a systematic description of human decision making in this context. We examine a commonly used, drift-diffusion, decision-making model that has been fit to human neural and behavioral data in sequential, two-alternative, forced-choice tasks. We show how this model and type of task together can be regarded as a Markov process, and we derive the steady-state probability distribution for choice sequences. Using the analytic expression for this distribution, we prove matching behavior for tasks that exhibit a matching point and we compute the sensitivity of steady-state choices to a model parameter that measures the decision maker's “exploratory” tendency.
IN-SAMPLE ASYMPTOTICS AND ACROSS-SAMPLE EFFICIENCY GAINS FOR HIGH FREQUENCY DATA STATISTICS

We revisit in-sample asymptotic analysis extensively used in the realized volatility literature. We show that there are gains to be made in estimating current realized volatility from considering realizations in prior periods. The weighting schemes also relate to Kalman-Bucy filters, although our approach is non-Gaussian and model-free. We derive theoretical results for a broad class of processes pertaining to volatility, higher moments, and leverage. The paper also contains a Monte Carlo simulation study showing the benefits of across-sample combinations.
Strategy Description and Modelling for Multi-agent Systems (Invited Paper)

The field of robot soccer provides numerous opportunities for the application of AI methods for game strategy development. Robot soccer is a part of standard applications of distributed system control in real time. The software part of a distributed control system is realized by decision making and executive agents. The algorithm of agents’ cooperation was proposed with the control agent on a higher level. The algorithms for agents realized in robots are the same. Real-time dynamic simple strategy description and strategy learning possibility based on game observation is important for discovering opponents strategies and searching for tactical group movements, simulation and synthesis of suitable counter-strategies. For the improvement of game strategy, we are developing an abstract description of the game and propose ways to use this description (e.g. for learning rules and adapting team strategies to every single opponent).