Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing and Evaluating Real Time Character Engines for Virtual Environments

As animated characters increasingly become vital parts of virtual environments, then the engines that drive these characters increasingly become vital parts of virtual environment software. This paper gives an overview of the state of the art in character engines, and proposes a taxonomy of the features that are commonly found in them. This taxonomy can be used as a tool for comparison and evaluation of different engines. In order to demonstrate this we use it to compare three engines. The first is Cal3D, the most commonly used open source engine. We also introduce two engines created by the authors, Piavca and HALCA. The paper ends with a brief discussion of some other popular engines.
Image segmentation method based on improved graph cut algorithm

Image segmentation method based on improved graph cut algorithm is proposed in this paper to improve the speed of graph cut and solve the watershed transformation over-segmentation phenomena. First, the image is segmented into a large number of small partitions making use of the watershed transformation. Then, a simplified network graph is constructed using the partition information. Finally, the graph cut algorithm is employed to realize network graph segmentation and get the segmentation results. The experimental results indicate that the proposed algorithm not only solves the watershed transformation over-segmentation phenomena, but also improves the speed of the graph cut algorithm.
Enabling Model Driven Engineering of Cloud Services by using mOSAIC Ontology

The easiness of managing and configuring resources and the low cost needed for setup and maintaining Cloud services have made Cloud Computing widespread. Several commercial vendors now offer solutions based on Cloud architectures. More and more providers offer new different services every month, following their customers needs. A way to provide a common access to Cloud services and to discover and use required services in Cloud federations is appealing. mOSAIC project addresses these problems by defining a common ontology and it aims at developing an open-source platform that enables applications to negotiate Cloud services as requested by users. Anyway the increasing complexity of services required by users in Cloud Environments usually needs the definition of composite, value added services (VAS). Usage patterns and Use Cases definitions help in defining VAS, but a way to assure that new services reach the required goals with proper qualitative and quantitative properties has to be provided in order to validate design and implementation of composite services. In this paper mOSAIC Ontology is described and the MetaMORP(h)OSY methodology and framework are introduced. The methodology uses Model Driven Engineering and Model Transformation techniques to analyse services. Due to the complexity of the systems to analyse, the mOSAIC Ontology is used in order to build modelling profiles in MetaMORP(h)OSY able to address cloud domain-related properties.
Review of Recent Research on Improving Earnings Forecasts and Evaluating Accounting‐Based Estimates of the Expected Rate of Return on Equity Capital

type="main"> We extend Easton's (2007) review of the literature on accounting-based estimates of the expected rate of return on equity capital, which we refer to as the ERR. We begin by reiterating the reasons why accounting-based estimates are used. Next, we briefly review the recent literature that focuses on improving forecasts of expected earnings by either (i) removing predictable errors from analysts’ forecasts of earnings or (ii) developing cross-sectional regression-based estimates of earnings using prior-period financial data. In the remainder of our review we discuss a recent debate on methods for evaluating estimates of the ERR. We highlight the key points in the debate so that the reader will find it easier to form an independent view of the relative merits of the proposed methods.
Does a virtual functional training induce cardiovascular responses in normotensive adults after a single session and over weeks?

Purpose. Active video games (AVG) provide an attractive alternative to sedentary behaviours and may bring some health benefits. However, single-session and chronic cardiovascular effects of AVG remain unclear. the aim of this study was to verify the impact of single-session and 4-week virtual functional training on cardiovascular responses in normotensive adults. Methods. In a pre-experimental study, 8 university students performed a 30-minute AVG session (Nike Kinect training® game) at the intensity of 64% (based on heart rate [HR]) and twice a week for 4 weeks (8 sessions). HR and systolic (SBP) and diastolic (DBP) blood pressure were measured immediately and at 10, 20, and 30 minutes after each session. A generalized estimating equation model and t-test were used to examine changes in cardiovascular responses over time (p < 0.05). Effect size was calculated by Cohen’s d. Results. A single session did not promote post-exercise hypotension (PEH). However, SBP (6.6–9.0 mm Hg) and DBP (4.5–5.5 mm Hg) decreased in 3/8 and 2/8 sessions, respectively. In pre/post-intervention comparisons at rest, small to large reduction effects were found for SBP (–3.0 mm Hg, d = 0.3), DBP (–4.7 mm Hg, d = 0.6), HR (–9 bpm, d = 0.8), and double product (–1389.3 mm Hg × bpm, d = 1.6). Conclusions. Virtual functional training reduced cardiac workload (chronic effect) and promoted PEH in some sessions among normotensive adults. these findings have practical applications for improving physical activity with attractive exercise forms, which should be recommended for healthy people.
Functional non-synonymous single nucleotide polymorphisms from the TGF-β protein interaction network

Fred A. Litwin Centre for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, M5G 1X5, Canada. Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, ON, M5G 1X5, Canada. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5G 1L5, Canada. Centre for System Biology, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, M5G 1X5, Canada. Department of Medical Genetics and Microbiology, University of Toronto, Toronto, ON, M5S 1A8, Canada.
A 165–230GHz SiGe amplifier-doubler chain with 5dBm peak output power

This paper presents the design and measurements of a 165-230 GHz SiGe BiCMOS power amplifier - frequency doubler chain, which can deliver up to 5 dBm peak output power at 204 GHz with a 3-dB bandwidth of 65 GHz. A compact high efficiency power divider is used to split the power from the input mm-wave source and convert the single ended input to two differential signals. The 3-staged transformer-coupled cascode power amplifier is optimized to deliver 14 dBm saturated output power at 110 GHz, while the frequency doubler uses a second harmonic reflector at its input to reduce the conversion loss. The chip is designed in 0. 13μm SiGe BiCMOS technology. To the authors' best knowledge, this is the highest output power above 200 GHz from silicon based amplifier-multiplier chains.
Listening to features

This work explores nonparametric methods which aim at synthesizing audio from low-dimensionnal acoustic features typically used in MIR frameworks. Several issues prevent this task to be straightforwardly achieved. Such features are designed for analysis and not for synthesis, thus favoring high-level description over easily inverted acoustic representation. Whereas some previous studies already considered the problem of synthesizing audio from features such as Mel-Frequency Cepstral Coefficients, they mainly relied on the explicit formula used to compute those features in order to inverse them. Here, we instead adopt a simple blind approach, where arbitrary sets of features can be used during synthesis and where reconstruction is exemplar-based. After testing the approach on a speech synthesis from well known features problem, we apply it to the more complex task of inverting songs from the Million Song Dataset. What makes this task harder is twofold. First, that features are irregularly spaced in the temporal domain according to an onset-based segmentation. Second the exact method used to compute these features is unknown, although the features for new audio can be computed using their API as a black-box. In this paper, we detail these difficulties and present a framework to nonetheless attempting such synthesis by concatenating audio samples from a training dataset, whose features have been computed beforehand. Samples are selected at the segment level, in the feature space with a simple nearest neighbor search. Additionnal constraints can then be defined to enhance the synthesis pertinence. Preliminary experiments are presented using RWC and GTZAN audio datasets to synthesize tracks from the Million Song Dataset.
Finite Element Approximations to the Discrete Spectrum of the Schrödinger Operator with the Coulomb Potential

In the present paper, the authors consider the Schrodinger operator H with the Coulomb potential defined in R3m, where m is a positive integer. Both bounded domain approximations to multielectron systems and finite element approximations to the helium system are analyzed. The spectrum of H becomes completely discrete when confined to bounded domains. The error estimate of the bounded domain approximation to the discrete spectrum of H is obtained. Since numerical solution is difficult for a higher-dimensional problem of dimension more than three, the finite element analyses in this paper are restricted to the S-state of the helium atom. The authors transform the six-dimensional Schrodinger equation of the helium S-state into a three-dimensional form. Optimal error estimates for the finite element approximation to the three-dimensional equation, for all eigenvalues and eigenfunctions of the three-dimensional equation, are obtained by means of local regularization. Numerical results are shown in the last section.
Robust Segmentation of Freehand Ultrasound Image Slices Using Gradient Vector Flow Fast Geometric Active Contours

We propose a new semi-automatic segmentation strategy on echocardiographic images, which combines a recently introduced gradient vector flow (GVF) fast geometric active contour (GAC) model and a modified level sets methods applied to echocardiographic data by Corsi et al. We call it adaptive GVF GAC model. We note that echocardiographic images are characterized by high levels of speckle noise, weakly-defined boundaries and severe gaps. We show that the new method, adapted for single object segmentation, can provide significantly improved performance over a competing level set method, and that was in turn shown to perform better than the original gradient vector flow method. The new method modifies the advection term in the speed function adoptively by estimating how close the propagated curve is to the target boundaries. We show both synthetic and real, freehand ultrasound image and echocardiographic image examples to illustrate the robustness and accuracy of the new segmentation method
Integrating Performance and Functional Analysis of Concurrent Systems with EMPA

An approach is proposed for modeling and analyzing concurrent systems that integrates different views (abstract vs. concrete) as well as different aspects (functional vs. performance) of their behavior. The approach is based on a stochastic process algebra, a formalism for specifying and studying concurrent systems that is characterized by the property of compositionality. The approach is instantiated to the case of Extended Markovian Process Algebra (EMPA), introduced together with the collection of its four semantics and the notion of equivalence that are required in order to implement the approach. Finally, the case study of the alternating bit protocol is presented to illustrate the approach.
Primate Social Intelligence

Abstract A computational theory of primate social intelligence is proposed in which primates represent social situations internally by discrete symbol structures, called scripts. Three well-defined computational operations on scripts are sufficient to support social learning, planning, and prediction. This gives a formal, predictive model with which to analyse how primate social knowledge is acquired, as well as how it is used. The theory is compared with primate data, such as Cheney and Seyfarth's observations of vervet monkeys. It gives simple, understandable script-based analyses of many observed phenomena—such as the recognition and use of kin relations, learning of alarm calls, habituation to calls, knowledge of rank, tactical deception, and attachment behaviour. I argue that a tight, concise theory of social cognition, such as script theory, is needed to explain the rapid learning and social guile seen in primates. It also has the benefits of simplicity and testability. The extension of scripts to incorporate a primate theory of mind is described in a subsequent paper.
Effectiveness of Psychological Preparation Program on Sport Performance of Futsal Girl Players: Mediating Role of Personality

The purpose of this research is to determine the effectiveness of the psychological preparation program in the increase of the sport performance dimensions of girls in the field of futsal with the mediator role of personality factors. The statistical population of all players in the group of youth girls of age range including 18-22 years old was in the field of futsal in Tehran province. 68 players were selected by available sampling method and randomly assigned to experimental and control groups. The research method was semi-experimental with pre-test and post-test design as well as control group. The primary level of athletic performance and personality factors of all participants were measured by questionnaire of behavioural check list and five personality factors. The psychological preparation program was implemented in 10 sessions for participants in the experimental group as well as no program was performed for participants in the control group. The performance of all participants in the post-test phase was again measured. Data were analysed using two-way analysis of variance. The results indicated that the psychological preparation program could significantly increase the dimensions of sport performance (passing the ball, ball control catching the ball) in futsal girls (p<0.01). The effect of the psychological preparation program on the dimensions of athletic performance (passing, controlling and catching the ball) depends on the moderating role of the neuroticism personality component. The results suggest that it is required to pay attention to the neuroticism personality component of the psychological preparation of girls in the field of futsal.
Towards interoperability of wireless services - a description model of service interfaces

Web services are evolving quickly in terms of standardization. Technology and additional wireless networks exact requirements upon web services used via wireless connections, such as mobile networks. The interoperability of services is essential in wireless networks because cost effective development and deployment of new wireless services for a user requires maximum utilization of service infrastructure. At the moment, constraints of service interface description models and implementation of services restrict interoperability between services. To achieve interoperability and composability, a standardized way to describe services and service interfaces is required, and for this reason standardization bodies are promoting the set of Extensible Markup Language (XML) technologies as the basis for a set of common standards. To respond to the challenges concerning service interoperability, this paper illustrates three widely known web standards that promote interoperability between web services SOAP (Simple Object Access Protocol), WSDL (Web Services Definition Language) and UDDI (Universal Description, Discovery and Integration) and proposes an interface description model for wireless Internet services. The proposed model takes into account architectural level service description in a novel way and presents its implementation using XML.
Evaluating and comparing software metrics in the software engineering laboratory

There has appeared in the literature a great number of metrics that attempt to measure the effort or complexity in developing and understanding software(1). There have also been several attempts to independently validate these measures on data from different organizations gathered by different people(2). These metrics have many purposes. They can be used to evaluate the software development process or the software product. They can be used to estimate the cost and quality of the product. They can also be used during development and evolution of the software to monitor the stability and quality of the product. Among the most popular metrics have been the software science metrics of Halstead, and the cyclomatic complexity metric of McCabe. One question is whether these metrics actually measure such things as effort and complexity. One measure of effort may be the time required to produce a product. One measure of complexity might be the number of errors made during the development of a product. A second question is how these metrics compare with standard size measures, such as the number of source lines or the number of executable statements, i.e., do they do a better job of predicting the effort or the number of errors? Lastly, how do these metrics relate to each other?
Effect of the Pre-erythrocytic Candidate Malaria Vaccine RTS,S/AS01E on Blood Stage Immunity in Young Children

(See the article by Greenhouse et al, on pages 19-26.) Background. RTS,S/AS01E is the lead candidate malaria vaccine and confers pre-erythrocytic immunity. Vaccination may therefore impact acquired immunity to blood-stage malaria parasites after natural infection. Methods. We measured, by enzyme-linked immunosorbent assay, antibodies to 4 Plasmodium falciparum merozoite antigens (AMA-1, MSP-142, EBA-175, and MSP-3) and by growth inhibitory activity (GIA) using 2 parasite clones (FV0 and 3D7) at 4 times on 860 children who were randomized to receive with RTS,S/AS01E or a control vaccine. Results. Antibody concentrations to AMA-1, EBA-175, and MSP-142 decreased with age during the first year of life, then increased to 32 months of age. Anti–MSP-3 antibody concentrations gradually increased, and GIA gradually decreased up to 32 months. Vaccination with RTS,S/AS01E resulted in modest reductions in AMA-1, EBA-175, MSP-142, and MSP-3 antibody concentrations and no significant change in GIA. Increasing anti-merozoite antibody concentrations and GIA were prospectively associated with increased risk of clinical malaria. Conclusions. Vaccination with RTS,S/AS01E reduces exposure to blood-stage parasites and, thus, reduces anti-merozoite antigen antibody concentrations. However, in this study, these antibodies were not correlates of clinical immunity to malaria. Instead, heterogeneous exposure led to confounded, positive associations between increasing antibody concentration and increasing risk of clinical malaria.
Pengaruh Motivasi, Mental dan Modal Usaha Terhadap Mahasiswa Akuntansi untuk Berwirausaha (Studi kasus pada mahasiswa akuntansi Universitas Muhammadiyah Jember )

Penelitian ini merupakan penelitian yang menguji pengaruh Motivasi, Mental dan Modal Usaha Terhadap Minat mahasiswa Akuntansi Universitas Muhammadiyah Jember untuk Berwirausaha. Penelitian ini bertujuan untuk mengetahuibagaimana pengaruh motivasi, mental dan modal usaha terhadapminat mahasiswa akuntansi Universitas Muhammadiyah Jember untuk berwirausaha. Dalam penelitian ini, menggunakan purposive sampling method dan memperoleh sampel sebanyak 83 sampel mahasiswa akuntansi Universitas Muhammadiyah Jember dari angkatan 2013-2015. Berdasarkan hasil dari uji hipotesis menyatakan bahwa motivasi berpengaruh negative terhadap minat berwirausaha, mental berpengaruh negative terhadap minat berwirausahan dan Modal Usaha berpengaruh positive terhadap minat berwirausaha pada mahasiswa Akuntansi Universitas Muhammadiyah Jember.
Branes in the Euclidean AdS_3

In this work we propose an exact microscopic description of maximally symmetric branes in a Euclidean AdS3 background. As shown by Bachas and Petropoulos, the most important such branes are localized along a Euclidean AdS2 ⊂ AdS3. We provide explicit formulas for the coupling of closed string s to such branes (boundary states) and for the spectral density of open strings. The lat ter is computed in two different ways first in terms of the open string reflection amp litude and then also from the boundary states by world-sheet duality. This gives rise to an important Cardy type consistency check. All the results are compared in detail with the geometrical picture. We also discuss a second class of branes with spherical symmetry and finally comment on some implications for D-branes in a 2D back hole geometry.
A Practical Intelligent Navigation System based on Travel Speed Prediction

This paper presents a novel intelligent navigation system capable of delivering route optimisation and guidance based on travel speed reports supplied by on the road users. The approach integrates fuzzy speed prediction models with a dynamic route optimisation engine to generate routes minimising total expected travel time using predictions on future traffic conditions across a wide road network.
2 Feature Selection and Related Work 2 . 1 Feature Selection Methods

Currently, the rapid growth of information on the Internet makes automatic text classification play an important role to help people discovering desired information on enormous resources. Text mining, feature selection and classification algorithm have effect on the classification performance directly. In this paper, the comparative study of the text classification performance is proposed. It compares between three feature selection approaches with four classification algorithms. The algorithms include C4.5, ID3, Bayes Net and Naïve Bayes. The objective is to find suitable model for restaurant dataset. The experimental results indicated that when a set of selected features was large, C4.5 and ID3 algorithms generated models with better accuracy than those induced by Bayes Net and Naïve Bayes algorithms. On the other hand, the small amount of selected features makes every algorithm yields models with almost the same accuracy. However, algorithms based on Bayes’ theorem could generally induce classification models with higher accuracy than the tree-based algorithms. Key-Words: Classification Algorithms, Feature Selection, Restaurant Classification, Text Classification
Quantifying Spillovers in Open Source Content Production : Evidence from Wikiped i a Aleksi Aaltonen

Using detailed edit-level data over eight years across a large number of articles on Wikipedia, we find evidence for a positive spillover effect in editing activity. Cumulative past contributions, embodied by the current article length, lead to significantly more editing activity, while controlling for a host of factors such as popularity of the topic and platform-level growth trends. The magnitude of the externality is significant, and growth in editing activity on the average article would have been about 50% lower in its absence. The spillover operates through an increase in the number of contributing users, whereas the length of contributions remains unchanged. Edits triggered by spillovers involve only marginally more deletion and replacement of content than the average edit, suggesting that past contributions do inspire the creation of new content rather than corrections of past mistakes. Roughly 75% of the spillover is due to new rather than returning users contributing content.