Miracle-dz/UniFAR-FTUs huggingface dataset:
Homo Deludens

/ This paper intends to map the possibilities as well as the dangers of using cheats in games research. It starts out from an understanding of games as entities in which the impulse to play is inextricably linked to the desire to cheat, as the close etymological kinship of the Latin terms ludo (I play) and deludo (I cheat) suggests. Therefore, it can be argued that, in order to understand a game, one must play not only by its rules but also with its rules. This will be demonstrated using examples drawn from my own games research experience, addressing the ethical, methodological and epistemological implications of this practice.
Geometrical pose and structural estimation from a single image for automatic inspection of filter components

This paper describes research on the application of machine vision techniques to a real time automatic inspection task of air filter components in a manufacturing line. A novel calibration algorithm is proposed based on a special camera setup where defective items would show a large calibration error. The algorithm makes full use of rigid constraints derived from the analysis of geometrical properties of reflected correspondence vectors which have been synthesized into a single coordinate frame and provides a closed form solution to the estimation of all parameters. For a comparative study of performance, we also developed another algorithm based on this special camera setup using epipolar geometry. A number of experiments using synthetic data have shown that the proposed algorithm is generally more accurate and robust than the epipolar geometry based algorithm and that the geometric properties of reflected correspondence vectors provide effective constraints to the calibration of rigid body transformations.
Modelling autosegmental phonology with multi-tape finite state transducers

Phonology may be briefly defined as the study of sound patterns in spoken language. One of the most well-known computational models of phonology, Koskenniemi's two-level phonology, is based on an underlying linguistic theory that has been superseded by autosegmental phonology, which began with the work of Goldsmith. There is a need for computational models that are faithful to this more recent theory. Such a model can form the basis of a computational tool that can quickly and accurately check the validity of a phonological analysis on a large amount of phonetic data, freeing the linguist from the tedious and enor-prone task of doing this by hand. This-thesis presents a new computational model of phonology that is faithful to standard autosegmental theory, that has clearly adequate expressive power, and that is suitable as the basis for a tool for phonological analysis. It follows on very recent efforts by Kornai and Bird & Ellison to model autosegmental phonology. The model is based on a view of phonology that sees phonological representations as data and phonological rules as procedures that manipulate them. It models rules using multi-tape state-labelled finite transducers (MSFTs), a natural extension of finite state transducers obtained by adding multiple input and output tapes. MSFTs are shown to be powerful enough to express a wide range of autosegmental rules. We also investigate the class of formal languages accepted by multi-tape state-labelled finite automata (MSFAs) when their input tapes are considered to encode a single word in parallel. This class is quite large, including some languages that are not context free. Given that our model is faithful to autosegmental theory, this gives an upper bound on the computational power required to model autosegmental phonological rules.
Assessing Success on the Uniform CPA Exam: A Logit Approach

Abstract In this study, the authors surveyed Indiana certified public accountant (CPA) candidates to investigate factors that may determine the likelihood of passing the Uniform CPA Exam. The authors used a logit model to test the likelihood of success in the exam as a function of factors such as undergraduate grade point average (GPA), credit hours, high school GPA, high school class size, age, high school rank, educational level, type of preparation, nature of experience, gender, and race. By and large, a full model and the models resulting from forward and backward stepwise selection indicated that undergraduate GPA, age, private accounting experience, and gender are significant determinants in success in the CPA exam.
Objective and Subjective Comparison of Audio Restoration Methods

This paper presents the results of a perceptual test to evaluate the quality of different audio restoration algorithms based on Short Time Spectral Attenuation method and on Kalman filter. The protocol by International Communication Union (ITU.R P.800) was used. A set of audio stimuli played with different instruments (i.e., different bandwidths, transients, and timbre) was selected and different impulsive and broadband noises were added. Commercial software and proprietary algorithms were used to restore the corrupted stimuli. Twelve subjects were asked to compare the restored and the noise free recordings. Statistical multivariate analysis was performed and accurate characterization of the restoration techniques used was achieved. In order to correlate perceptual results with acoustic characteristics of the different stimuli, a time-frequency analysis was performed. These results permitted to relate the esthetic judgement categories used by listeners with the main features of the restoration techniques used.
Artificial Intelligence in Civil Engineering

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.
Scalable optical switches for computing applications [Invited]

A scalable photonic interconnection network architecture is proposed whereby a Clos network is populated with broadcast-and-select stages. This enables the efficient exploitation of an emerging class of photonic integrated switch fabric. A low distortion space switch technology based on recently demonstrated quantum-dot semiconductor optical amplifier technology, which can be operated uncooled, is used as the base switch element. The viability of these switches in cascaded networks is reviewed, and predictions are made through detailed physical layer simulation to explore the potential for larger-scale network connectivity. Optical signal degradation is estimated as a function of data capacity and network size. Power efficiency and physical layer complexity are addressed for high end-to-end bandwidth, nanosecond-reconfigurable switch fabrics, to highlight the potential for scaling to several tens of connections. The proposed architecture is envisaged to facilitate high-capacity, low-latency switching suited to computing systems, backplanes, and data networks. Broadband operation through wavelength division multiplexing is studied to identify practical interconnection networks scalable to 100 Gbits/s per path and a power consumption of the order of 20 mW/(Gbits/s) for a 64×64 size interconnection network.
Advanced methods of heart rate signals processing and their usefulness in diagnosis support II. Univariate statistical techniques

(Rec. 29 February 2004) Abstract: A tentative cardiological database was established using virtual instrumentation described in the first part of presented paper. Some additional not heart rate variability parameters were added. Three selected univariate statistical techniques were used for illustration diagnosis support techniques in discrimination between healthy and coronary heart disease people. Comparison of nonparametric MannWhitney test, receiver operating characteristic ROC analysis and univariate logistic regression results was performed. In all used methods long term heart rate variability indices were most useful in prediction of patient's status. The correctness of classification was between 55 to 79 percent with ROC technique and 68 to 78 percent with logistic regression. However high number of false negative FN cases excludes univariate techniques as reliable screening test.
Phase Synchronization May Reveal Communication Pathways in Brain Activity

Employing experiments that range from studying isolated pairs of lobster neurons to looking at electrical and magnetic signals from human test subjects, physicists are applying concepts from nonlinear systems, chaos and control theory to improve our understanding of neuronal dynamics. Exemplifying this approach, a collaboration in Germany between neurologists at the University of Dusseldorf and physicists at the University of Potsdam has recently demonstrated the potential of a new nonlinear analysis technique—phase synchronization—for neuronal studies. With this tool, the researchers found evidence in magnetoencephalography (MEG) data for synchronous activity between different parts of the brain and between the brain and the muscles during the tremor of a patient with Parkinson's disease (see the figure below).
SIMSTAT with WORDSTAT: A Comprehensive Statistical Package with a Content Analysis Module

SIMSTAT is an inexpensive but full-featured Windows/DOS statistical package. Several features set it apart from its competitors in the same price range. First, SIMSTAT offers extensive bootstrapping capabilities (bootstrapping is a statistical technique that uses resampling to estimate population parameters). Second, WORDSTAT, one of several modules that can be purchased to extend the capabilities of SIMSTAT, provides a wide range of quantitative content analysis features that will be especially useful to researchers who work with relatively small text chunks. SIMSTAT and its modules are relatively easy to use, especially for users who have experience with SPSS, which SIMSTAT resembles.
Automatic recognition of USGS land use/cover categories using statistical and neural network classifiers

This report presents a description of part of an end-to-end system being developed for the automatic recognition of general land use/cover categories from digitized aerial photography. Standard USGS categories are used here and include urban, fields, trees, and water. The system consists of modules for segmentation, feature extraction, and classification. This report extends the results of our efforts on the feature extraction and classification portions of the system, which were partially described earlier. Since the data source is panchromatic, the features used are measures of texture. These include spatial gray-level co-occurrence matrix, Laws, Fourier domain rings and wedges, and a simultaneous autoregressive model. The classifiers employed include the Bayes quadratic, k-nearest neighbor, Parzen, and a multilayer perceptron neural network. Through leave-one-scene-out sampling, each classifier type is trained and tested using feature data generated by each feature extraction technique. A new, fast method of training the multilayer perceptron is described. It is expected that many of the techniques developed will be applicable to other areas of image recognition where texture is an important discriminant.
Valoración de editoriales especializadas en comunicación, biblioteconomía y documentación: encuesta a profesores e investigadores

Publishers of scholarly books about library and information science and communications are analyzed, as well as their publishing processes. The research method was a questionnaire sent to 263 Spanish researchers and teachers in these areas. The survey response rate was 35.5%. Thanks to these responses, main quality indicators for publishers were identified. Researchers’ working habits, opinions and attitudes related to the selection, editing and publishing processes of their books are also examined. Finally, as a more pragmatic result, the most prestigious Spanish and foreign publishers are identified.
A Novel Photographic and Computer Graphic Composites Detection Method

With the development of the rendering techniques, the visual difference between photographic images (PG) and computer graphics (CG) is becoming smaller. And the digital image forgery is not limited to the composite between photographic, splicing of computer graphics and photographic is also a problem to be resolved. To come up with this problem, in this paper we propose a novel hybrid classifier based on pattern noise statistics and histogram features. Experimental results show that proposed method is capable of improving the performance of the prior techniques. The proposed method also has a good performance on detection of local forgeries. Keywords-digital image forensics; computer graphics; pattern noise; histogram features
Mitigation of arsenic accumulation in rice: An agronomical, physico-chemical, and biological approach – A critical review

Abstract Human exposure to As through rice consumption is a worldwide health concern. There is an urgent need to either remediate As contaminated paddy soils, or to screen for low As accumulating rice varieties, thereby limiting the build up of As in their grains. This review presents a number of agronomic, physico-chemical, and biological approaches that may reduce the As content in paddy agroecosystems. Studies have shown that alternative water management practices significantly reduce As accumulation in rice grains. The application of Si sources into As contaminated paddy soils may limit As(III) uptake. The supplementation of redox-sensitive elements (i.e. Fe and Mn) and the incorporation of biochar (BC) may also immobilize As in the paddy environment. Inoculation of microorganisms is another in-situ method to reduce As in rice grains. Accumulation of As in rice grains can also be largely reduced through altering the expression of genes in rice plants. However, applicability of potential As mitigation approaches is dependent on the biogeochemical properties of the paddy agroecosystems, water management practices, availability of sources, and cost. This article expands on research gaps and provides future research directions to enable the production of safer rice grains with reduced As accumulation.
The control of fan speed using FPGA boards

This article describes the implementation of a DC fan controller using a field-programmable gate array (FPGA). Hardware description language (VHDL) is used to design and implement the processor of this controller. The processor is composed of a memory block that has a function of generation a Look up Table (LUT). Data saved in the memory block are used to generate a triangular signal. A carried signal can be added. This signal can be generated from digital temperature sensors. A comparator compares between the triangular signal and the carried signal to generate a PulseWidth Modulation (PWM) output that controls the fan speed. The fan speed depends on the digital temperature sensor output. When the output signal of the sensor equals the output of the triangular wave, the fan speed is maximal and the temperature is high. This design requires a FPGA board and software ISE 14.4.
The grammar of graphics

The grammar of graphics (GoG) denotes a system with seven classes embedded in a data flow. This data flow specifies a strict order in which data are transformed from a raw dataset to a statistical graphic. Each class contains multiple methods, each of which is a function executed at the step in the data flow corresponding to that class. The classes are orthogonal, in the sense that the product set of all classes (every possible sequence of class methods) defines a space of graphics which is meaningful at every point. The meaning of a statistical graphic is thus determined by the mapping produced by the function chain linking data and graphic. WIREs Comp Stat 2010 2 673–677 DOI: 10.1002/wics.118
Fast routing in wireless sensor networks using directional transmissions

In this work, we present a routing algorithm for sensor networks that utilises smart antennas to propagate information about a sensed event towards a receiving centre. The novelty of our approach lies in the fact that our protocol uses only local information and total absence of coordination between sensors. We provide a detailed experimental analysis that demonstrates the feasibility of our approach, the necessity of using smart antennas in sensor networks and the advantages that are presented to communication links due to their use. Our protocol is suited for those cases where unexpected changes to the environment (i.e. a fire, a person entering a restricted area, etc.) must be propagated quickly back to the base station without the use of complicated protocols that may deplete the network from its resources. Our protocol is very easy to implement as nodes do not have to decide whether or not to forward the message; the protocol ensures packet delivery and low energy consumption solely by the use of smart antennas on sensor nodes.
32.1: Optimal Projector Configuration Design for 300‐Mpixel Light‐Field 3D Display

To achieve an immersive natural 3D experience in a large screen, we developed a projection‐based 300‐Mpixel light‐field display that has a 100‐inch screen and a 40° viewing angle. Finding the best projector configuration is an important issue in generating a high‐quality 3D image, so we analyzed the luminance characteristics of the display and optimized the design to minimize the variation in the brightness of projected images.
Analysis of large-scale distributed knowledge sources via autonomous cooperative graph mining

In this paper, we present a model for processing distributed relational data across multiple autonomous heterogeneous computing resources in environments with limited control, resource failures, and communication bottlenecks. Our model exploits dependencies in the data to enable collaborative distributed querying in noisy data. The collaboration policy for computational resources is efficiently constructed from the belief propagation algorithm. To scale to large data sizes, we employ a combination of priority-based filtering, incremental processing, and communication compression techniques. Our solution achieved high accuracy of analysis results and orders of magnitude improvements in computation time compared to the centralized graph matching solution.
Embodied number processing

concepts become meaningful only when they refer to bodily experiences (e.g., Barsalou, 1999; Fischer & Zwaan, 2008; Glenberg, 1997; Pulvermüller, 2005; Rueschemeyer, Lindemann, van Elk, & Bekkering, 2009). Over the last two decades, research on language comprehension has provided a large amount of evidence for the idea that conceptual knowledge is grounded through such sensory-motor referencing. For instance, reading action-related sentences that imply a particular rotational motion (e.g., she opens the bottle) facilitates the execution of similar actions (e.g., rotating a knob counter-clockwise; Zwaan & Taylor, 2006; see also Glenberg & Kaschak, 2002). This functional link between the motor system and language comprehension has also been found at the neural level, reflected by motor-cortical activation through action-related language processing (e.g., Hauk, Johnsrude, & Pulvermüller, 2004). In turn, there is also evidence for the reverse referencing (in the sense of a functional link) from motor actions onto more efficient processing of action-congruent linguistic descriptions (Rueschemeyer, Lindemann, van Rooij, van Dam, & Bekkering, 2010) and memory retrieval (Pecher, Van Dantzig, Zwaan, & Zeelenberg, 2009; van Dam, Rueschemeyer, Bekkering, & Lindemann, 2013). EMBODIED NUMERICAL COGNITION With this increasing empirical evidence that activation of bodily representations contributes to conceptual knowledge, researchers began to consider the sensory-motor grounding of semantic processing also in the domain of mathematical cognition (e.g., Andres, Olivier, & Badets, 2008; Fischer, 2012; Lakoff & Núñez, 2000; Lindemann, Rueschemeyer, & Bekkering, 2009; Moeller et al., 2012). The present Special Issue presents the latest developments of this approach. The role of sensory and motor codes in number representation and mental arithmetic is important to understand because the two codes share the same class of information, namely knowledge about quantities and magnitudes. Consistent with this fact, similar parietal brain areas support magnitude processing for numbers and for grasping movements (Simon, Mangin, Cohen, Le Bihan, & Dehaene, 2002). Behavioural priming therefore works across the two domains. For example, large numbers facilitate hand opening responses (Andres, Davare, Pesenti, Olivier, & Seron, 2004) and the grasping of objects with a power grip (Lindemann, Abolafia, Girardi, & Bekkering, 2007) whereas small numbers prime hand closure and precision grip actions. In turn, number processing interferes with the timing of the duration of manual button responses (Kiesel & Vierck, 2008) and with the use of a particular response force (Krause, Lindemann, Toni, & Bekkering, 2014). Number processing also impacts judgements about © 2015 Taylor & Francis Journal of Cognitive Psychology, 2015 Vol. 27, No. 4, 381–387, http://dx.doi. org/10.1080/20445911.2015. 1032295
Visual comfort/discomfort and visual fatigue caused by stereoscopic HDTV viewing

The problems associated with watching stereoscopic HDTV have been classified into three groups, one of which is how natural/unnatural stereoscopic pictures look to viewers. It is known that the shooting and viewing conditions affect the depth of a stereoscopic image, and this depth distortion is a major factor influencing the viewer's stereoscopic perception. The second group concerns the visual comfort/discomfort. Visual discomfort is caused by the difficulty of fusing left and right images because of excessive binocular parallax and its temporal changes. We have studied how visual comfort is affected by the range of parallax distribution and temporal parallax changes. The results show that stereoscopic images are comfortable to view for an angular parallax of up to about 60 minutes and that visual comfort is achieved if discontinuous temporal changes are angle of 60 minutes or less. The third group concerns visual fatigue that a viewer experiences after viewing a stereoscopic HDTV program, which is thought to be mainly caused by the mismatch between the eyes' convergence and accommodation. We confirmed that, after observing stereoscopic images for about an hour, the fusion range diminishes and the viewer's visual functions deteriorate as a result.
Training at Lactate Threshold: Science Based Concept or Irrational Myth?

might detect exercise intensity at or close to the highest prolonged constant power with a constant BLC above resting BLC. Time invariance of BLC indicates a match between rates of glycolytic lactate generation and pyruvate respiration. The highest match between rates of glycolytic lactate generation and pyruvate respiration defines the Maximal Lactate Steady State (MLSS) detected via a series of prolonged constant power tests [5,6]. The between subject variability of both, the MLSS (1.9 to 7.5 mmol l -1