Miracle-dz/UniFAR-FTUs huggingface dataset:
The visitor pattern as a reusable, generic, type-safe component

The VISITOR design pattern shows how to separate the structure of an object hierarchy from the behaviour of traversals over that hierarchy. The pattern is very flexible; this very flexibility makes it difficult to capture the pattern as anything more formal than prose, pictures and prototypes. We show how to capture the essence of the VISITOR pattern as a reusable software library, by using advanced type system features appearing in modern object-oriented languages such as Scala. We preserve type-safety statically and modularly: no reflection or similar mechanisms are used and modules can be independently compiled. The library is generic, in two senses: not only is it parametrised by both the return type and the shape of the object hierarchy, but also it allows a number of implementation choices (internal versus external control, imperative versus functional behaviour, orthogonal aspects such as tracing and memoisation) to be specified by parameters rather than fixed in early design decisions. Finally, we propose a generalised datatype-like notation,on top of our visitor library: this provides a convenient functional decomposition style in object-oriented languages.
Can Audio Enhance Visual Perception and Performance in a Virtual Environment?

Does the addition of audio enhance visual perception and performance within a virtual environment? To address this issue we used both a questionnaire and an experimental test of the effect of audio on recall and recognition of visual objects within different rooms of a virtual environment. We tested 60 college-aged students who had normal visual acuity, color vision, and hearing. The between-participants factor was audio condition (none, low fidelity, and high fidelity). The questionnaire results showed that ambient sounds enhanced the sense of presence (or “being there”) and the subjective 3D quality of the visual display, but not the subjective dynamic interaction with the display. We also showed that audio can enhance recall and recognition of visual objects and their spatial locations within the virtual environment. These results have implications for the design and use of virtual environments, where audio sometimes can be used to compensate for the quality of the visual display.
A secure mobile payment system using QR code

Mobile phones have become an inseparable companion for many users, serving much more than just communication tools. In developing countries, the number of mobile phone users exceeds the number of those having bank accounts. Besides, the low banking service penetration and the large migrant communities are another factor to utilize mobile phones for payment purposes. Therefore, mobile payment may find the success it is targeting easily and much faster than in developed countries. There are a lot of variables involved related to Mobile Payments. In this paper, the various models used for Mobile payments are first discussed. Then, the paper will propose a scenario for mobile payment that tackles both concerns of the process, namely: speed of transaction and security, without complicating the process or making it undesirable to users.
Prediction of All-Cause Mortality From Global Longitudinal Speckle Strain: Comparison With Ejection Fraction and Wall Motion Scoring

Background—Although global left ventricular systolic function is an important determinant of mortality, standard measures such as ejection fraction (EF) and wall motion score index (WMSI) have important technical limitations. The aim of this study was to compare global longitudinal speckle strain (GLS), an automated technique for measurement of long-axis function, with EF and WMSI for the prediction of mortality. Methods and Results—Of 546 consecutive individuals undergoing echocardiography for assessment of resting left ventricular function, 91 died over a period of 5.2±1.5 years. In addition to Simpson biplane EF, WMSI was determined by 2 experienced readers and GLS was calculated from 3 standard apical views using 2D speckle tracking. The incremental value of EF, WMSI, and GLS to significant clinical variables was assessed in nested Cox models. Clinical factors associated with outcome (model &khgr;2=20.2) were age (hazard ratio [HR], 1.46; P<0.01), diabetes (HR, 1.88; P=0.01), and hypertension (HR, 1.59; P<0.05). Although addition of EF (HR, 1.23; P=0.03) or WMSI (HR, 1.28; P<0.01) added to the predictive power of clinical variables, the addition of GLS (HR, 1.45; P<0.001) caused the greatest increment in model power (&khgr;2=34.9, P<0.001). GLS also provided incremental value in subgroups with EF >35% and those with and without wall motion abnormalities. A GLS ≥−12% was found to be equivalent to an EF ≤35% for the prediction of prognosis. Intraobserver and interobserver variations for EF and GLS were similar. Conclusions—GLS is a superior predictor of outcome to either EF or WMSI and may become the optimal method for assessment of global left ventricular systolic function.
on D-branes

This is an introduction to the physics of D-branes. Topics covered include Polchinski’s original calculation, a critical assessment of some duality checks, D-brane scattering, and effective worldvolume actions. Based on lectures given in 1997 at the Isaac Newton Institute, Cambridge, at the Trieste Spring School on String Theory, and at the 31rst International Symposium Ahrenshoop in Buckow.
Dynamic model-based augmented extended Kalman filter for real time simulation of mobile robots

This paper presents a new design of augmented extended Kalman filter (AEKF) based on the dynamic model for real-time simulation of mobile robots. The dynamic model is composed of two consecutive parts; kinematic model and equations of linear and angular torques. A Simulink® model is developed for simultaneous localization and odometry calibration of mobile robots in real time manner. Assuming an absolute measurement available, the AEKF provides the local reconstruction of mobile robots position and orientation with an on-line odometry calibration. Furthermore, it gives estimations for the linear and angular velocities of the robot that can be used for control strategy. The simulation results verify the effectiveness of the proposed method and suggest it as a promising way for real time control of mobile robots.
The Thermal X-Ray Spectra of Centaurus X-4, Aquila X-1 , and 4U 1608-522 in Quiescence

We reanalyze the available X-ray spectral data of the type I bursting neutron star transients Aql X-1, Cen X-4, and 4U 1608-522 using realistic hydrogen atmosphere models. Previous spectral fits assumed a blackbody spectrum; because the free-free-dominated photospheric opacity decreases with increasing frequency, blackbody spectral fits overestimate the effective temperature and underestimate, by as much as 2 orders of magnitude, the emitting area. Hydrogen atmosphere spectral models, when fit to the available observational data, imply systematically larger emission area radii, consistent with the canonical 10 km radius of a neutron star. This suggests that a substantial fraction of the quiescent luminosity is thermal emission from the surface of the neutron star. The magnitude of the equivalent hydrogen column density toward these systems, however, presents a considerable systematic uncertainty, which can be eliminated only by high signal-to-noise X-ray spectral measurements (e.g., with AXAF or XMM) that would permit simultaneous determination of the equivalent hydrogen column density, emission area, and thermal temperature.
Independent Tasks Scheduling Based on Genetic Algorithm in Cloud Computing

Task scheduling algorithm, which is an NP-completeness problem, plays a key role in cloud computing systems. In this paper, we propose an optimized algorithm based on genetic algorithm to schedule independent and divisible tasks adapting to different computation and memory requirements. We prompt the algorithm in heterogeneous systems, where resources (including CPUs) are of computational and communication heterogeneity. Dynamic scheduling is also in consideration. Though GA is designed to solve combinatorial optimization problem, it's inefficient for global optimization. So we conclude with further researches in optimized genetic algorithm.
Why Do We Move Our Head to Look at an Object in Our Peripheral Region? Lateral Viewing Interferes with Attentive Search

Why do we frequently fixate an object of interest presented peripherally by moving our head as well as our eyes, even when we are capable of fixating the object with an eye movement alone (lateral viewing)? Studies of eye-head coordination for gaze shifts have suggested that the degree of eye-head coupling could be determined by an unconscious weighing of the motor costs and benefits of executing a head movement. The present study investigated visual perceptual effects of head direction as an additional factor impacting on a cost-benefit organization of eye-head control. Three experiments using visual search tasks were conducted, manipulating eye direction relative to head orientation (front or lateral viewing). Results show that lateral viewing increased the time required to detect a target in a search for the letter T among letter L distractors, a serial attentive search task, but not in a search for T among letter O distractors, a parallel preattentive search task (Experiment 1). The interference could not be attributed to either a deleterious effect of lateral gaze on the accuracy of saccadic eye movements, nor to potentially problematic optical effects of binocular lateral viewing, because effect of head directions was obtained under conditions in which the task was accomplished without saccades (Experiment 2), and during monocular viewing (Experiment 3). These results suggest that a difference between the head and eye directions interferes with visual processing, and that the interference can be explained by the modulation of attention by the relative positions of the eyes and head (or head direction).
A 6.5Mb/s to 11.3Gb/s continuous-rate clock and data recovery

A continuous-rate CDR based upon a digital dual delay/phase locked loop is reported. This CDR is implemented in 0. 13μm CMOS and operates from 6.5Mb/s to 11.3Gb/s. It exceeds all SONET jitter specifications from OC-3 to OC-192, with random jitter of 452fs at 9.95Gb/s. The die area is 2×2mm2, and is implemented in a 24-pin LFCSP.
d=5 operators in SUSY GUT: fermion masses versus proton decay

In the minimal SU(5) SUSY GUT $d =5$ operators lead to $p\to K^+ \nu$ decay with the proton life time of the order of $10^{28}$ years for the natural choice of the parameters of the theory. This value is in strong contradiction with experimental bound $\tau_{p\to K\nu} > 10^{32}$ years. $d=5$ operators are induced by colored Higgsino exchanges and are closely (through SU(5) and super symmetry) related to another wrong prediction of SU(5) SUSY GUT: $m_d /m_s = m_e /m_{\mu}$. We demonstrate how in the model where reasonable pattern of quark and lepton masses and CKM mixing angles are obtained proton decay can be suppressed and proton life time can be close to the present experimental bound.
Efficient and Comprehensive Representation of Uniqueness for Next-Generation Sequencing by Minimum Unique Length Analyses

As next generation sequencing technologies are getting more efficient and less expensive, RNA-Seq is becoming a widely used technique for transcriptome studies. Computational analysis of RNA-Seq data often starts with the mapping of millions of short reads back to the genome or transcriptome, a process in which some reads are found to map equally well to multiple genomic locations (multimapping reads). We have developed the Minimum Unique Length Tool (MULTo), a framework for efficient and comprehensive representation of mappability information, through identification of the shortest possible length required for each genomic coordinate to become unique in the genome and transcriptome. Using the minimum unique length information, we have compared different uniqueness compensation approaches for transcript expression level quantification and demonstrate that the best compensation is achieved by discarding multimapping reads and correctly adjusting gene model lengths. We have also explored uniqueness within specific regions of the mouse genome and enhancer mapping experiments. Finally, by making MULTo available to the community we hope to facilitate the use of uniqueness compensation in RNA-Seq analysis and to eliminate the need to make additional mappability files.
Multi-mode saliency dynamics model for analyzing gaze and attention

We present a method to analyze a relationship between eye movements and saliency dynamics in videos for estimating attentive states of users while they watch the videos. The multi-mode saliency-dynamics model (MMSDM) is introduced to segment spatio-temporal patterns of the saliency dynamics into multiple sequences of primitive modes underlying the saliency patterns. The MMSDM enables us to describe the relationship by the local saliency dynamics around gaze points, which is modeled by a set of distances between gaze points and salient regions characterized by the extracted modes. Experimental results show the effectiveness of the proposed model to classify the attentive states of users by learning the statistical difference of the local saliency dynamics on gaze-paths at each level of attentiveness.
Communication Schemes with Constrained Reordering of Resources

This paper introduces a communication model inspired by two practical scenarios. The first scenario is related to the concept of protocol coding, where information is encoded in the actions taken by an existing communication protocol. We investigate strategies for protocol coding via combinatorial reordering of the labelled user resources (packets, channels) in an existing, primary system. However, the degrees of freedom of the reordering are constrained by the operation of the primary system. The second scenario is related to communication systems with energy harvesting, where the transmitted signals are constrained by the energy that is available through the harvesting process. We have introduced a communication model that covers both scenarios and elicits their key feature, namely the constraints of the primary system or the harvesting process. We have shown how to compute the capacity of the channels pertaining to the communication model when the resources that can be reordered have binary values. The capacity result is valid under arbitrary error model in which errors in each resource (packet) occur independently. Inspired by the information-theoretic analysis, we have shown how to design practical error-correcting codes suited for the communication model. It turns out that the information-theoretic insights are instrumental for devising superior design of error-control codes.
Title: Faster: Fully Automated Statistical Thresholding for Eeg Artifact Rejection Affiliation

Electroencephalogram (EEG) data are typically contaminated with artifacts (e.g., by eye movements). The effect of artifacts can be attenuated by deleting data with amplitudes over a certain value, for example. Independent component analysis (ICA) separates EEG data into neural activity and artifact; once identified, artifactual components can be deleted from the data. Often, artifact rejection algorithms require supervision (e.g., training using canonical artifacts). Many artifact rejection methods are time consuming when applied to high density EEG data. We describe FASTER (Fully Automated Statistical Thresholding for EEG artifact Rejection). Parameters were estimated for various aspects of data (e.g., channel variance) in both the EEG time-series and in the independent components of the EEG: outliers were detected and removed. FASTER was tested on both simulated EEG (n=47) and real EEG (n=47) data on 128-, 64-, and 32-scalp electrode arrays. Faster was compared to supervised artifact detection by experts and to a variant of the Statistical Control for Dense Arrays of Sensors (SCADS) method. FASTER had > 90% sensitivity and specificity for detection of contaminated channels, eye movement and EMG artifacts, linear trends and white noise. FASTER generally had > 60% sensitivity and specificity for detection of contaminated epochs, vs. 0.15% for SCADS. The variance in the ERP baseline, a measure of noise, was significantly lower for FASTER than either the supervised or SCADS methods. ERP amplitude did not differ significantly between FASTER and the supervised approach.
Cancer, Computers and Complexity: Decision Making for the Patient

In health care, a trend may be noted to fundamentally question some of today’s assumptions about the traditional roles of medical disciplines, the doctor–patient relationship, the feasibility of medical studies, and about the role of computers as an aid or replacement of doctors. Diagnostics and therapy decision-making become more complex, and no end is in sight. Amounts of health-related data are being collected individually, and through the health care systems. On the example of breast cancer care, technological advances and societal changes can be observed as they take place concurrently, and patterns and hypotheses emerge that will be the focus of this article. In particular, three key changes are to be considered: (1) the growing appreciation of the uniqueness of diseases and the impact of this notion on the future of evidence-based medicine; (2) the acknowledgment of a ‘big data’ problem in today’s medical practice and science, and the role of computers; and (3) the societal demand for ‘P4 medicine’ (predictive, preventive, participatory, personalized), and its impact on the roles of doctors and patients.
A novel Fibonacci windows model for finding emerging patterns over online data stream

Patterns i.e. the itemsets whose frequency increased significantly from one class to another are called emerging patterns (EP). Finding EP in a massive online data streaming is a tough yet complex task. On one hand the emergence of patterns must be examined at different time stamps since no one knows when the patterns may be emerging; on another hand, EP must be found in a given limited time and memory resources. In this work a novel method to accomplish such task is proposed. The history of itemsets and their support is kept in a novel data window model, called Fibonacci windows model, which shrinks a big number of data historical windows into a considerable much smaller number of windows. The emergence of itemsets being extracted from online transactions is examined directly with respect to the Fibonacci windows. Furthermore, as the historical windows are recorded, EP can be found both in online and offline mode.
Offline handwritten character recognition using neural network

Character Recognition (CR) has been an active area of research in the past and due to its diverse applications it continues to be a challenging research topic. In this paper, we focus especially on offline recognition of handwritten English words by first detecting individual characters. The main approaches for offline handwritten word recognition can be divided into two classes, holistic and segmentation based. The holistic approach is used in recognition of limited size vocabulary where global features extracted from the entire word image are considered. As the size of the vocabulary increases, the complexity of holistic based algorithms also increases and correspondingly the recognition rate decreases rapidly. The segmentation based strategies, on the other hand, employ bottom-up approaches, starting from the stroke or the character level and going towards producing a meaningful word. After segmentation the problem gets reduced to the recognition of simple isolated characters or strokes and hence the system can be employed for unlimited vocabulary. We here adopt segmentation based handwritten word recognition where neural networks are used to identify individual characters. A number of techniques are available for feature extraction and training of CR systems in the literature, each with its own superiorities and weaknesses.We explore these techniques to design an optimal offline handwritten English word recognition system based on character recognition. Post processing technique that uses lexicon is employed to improve the overall recognition accuracy.
Multimodal Interaction with Co-located Drones for Search and Rescue

We present a multimodal interaction framework that allows a human operator to interact with co-located drones during search and rescue missions. In contrast with usual human-multidrones interaction scenarios, in this case the operator is not fully dedicated to the control of the robots, but directly involved in search and rescue tasks, hence only able to provide fast, although high-value, instructions to the robots. This scenario requires a framework that supports intuitive multimodal communication along with an effective and natural mixed-initiative interaction between the human and the robots. In this work, we describe the domain along with the designed multimodal interaction framework.
Passenger traffic forecast based on the Grey-Markov method

Passenger traffic forecast is significant for the study of the change of passenger transport capacity. Forecasting passenger traffic scientifically is very important for decision-making of transportation development strategies. This paper analyzes the factors of passenger traffic, and describes the principle of the grey-Markov chain. Then we divide these factors into two categories: supply factors and affecting factors. Based on the characters of passenger traffic and the advantages of grey model and Markov chain, this paper gives grey-Markov chain model for forecasting passenger traffic. Grey model forecasting curve shows the developing of passenger traffic. Markov model reflects the volatility law and then optimizes the result. Through the empirical research of the data of passenger turnover from 1990 to 2007, the following conclusions are drawn: the Markov Chain method may help to modify the forecast accuracy to a great extent; Passenger traffic development is known from the GM (1, 1) forecast values and the maximum Markov state transition probability. Forecasting the fluctuations and random passenger traffic by the Grey-Markov model can have a higher rate of accuracy.
Implementation of a Model-Tracing-Based Learning Diagnosis System to Promote Elementary Students' Learning in Mathematics

Of all teaching methods, one-to-one human tutoring is the most powerful method for promoting learning. To achieve this aim and reduce teaching load, researchers developed intelligent tutoring systems (ITSs) to employ one-to-one tutoring (Aleven, McLaren, & Sewall, 2009; Aleven, McLaren, Sewall, & Koedinger, 2009; Anderson, Corbett, Koedinger, & Pelletier, 1995; Anderson & Reiser, 1985; Blessing, Gilbert, Ourada, & Ritter, 2009; Mitrovic et al., 2009; Mitrovic & Ohlsson, 1999; Suraweera, Mitrovic, & Martin, 2007; VanLehn et al., 2005). However, most ITSs have restricted user interfaces, which confine reasoning strategies of students during problem solving, thus ignoring the fact that students could use dissimilar strategies to solve a given question. Furthermore, student learning problems could be diagnosed from the derivation of their answers. In order to interpret students' mathematical problem-solving behaviors, this study developed a Model-tracing Intelligent Tutor (MIT) to diagnose students' learning problems and provide learning feedback for individual students. A quasi-experiment was conducted in an elementary school to evaluate the effectiveness of the proposed approach, in which 124 fifth graders participated. The experimental results show that the model-tracing-based learning diagnosis system is significantly more helpful to the students in learning mathematics than the conventional web-based test in terms of learning achievements.