Miracle-dz/UniFAR-FTUs huggingface dataset:
Delivering stable high-quality video: an SDN architecture with DASH assisting network elements

Dynamic adaptive streaming over HTTP (DASH) is a simple, but effective, technology for video streaming over the Internet. It provides adaptive streaming while being highly scalable at the side of the content providers. However, the mismatch between TCP and the adaptive bursty nature of DASH traffic results in underperformance of DASH streams in busy networks. This paper describes a networking architecture based on the Software Defined Networking (SDN) paradigm. Controllers in the network with a broad overview on the network activity provide two mechanisms for adaptation assistance: explicitly signaling target bitrates to DASH players and dynamic traffic control in the network. We evaluate how each of these mechanisms can contribute to the delivery of a stable and high quality stream. It shows that our architecture improves the quality of experience by doubling the video bitrate and reducing disturbing quality switches. As such, this paper contributes insights on how to implement DASH-aware networking that also enables internet service providers, network administrators, and end-users to configure their networks to their requirements.
Effects of China's Pharmaceutical Price Regulation between 1997 and 2008

This paper uses macro-level data between 1997 and 2008 to evaluate the effects of China’s pharmaceutical price regulations. We find that these regulations had short-run effects on medicine price indices, reducing them by less than 0.5 percentage points. The effects could have been slightly reinforced when these regulations were imposed on more medicines. However, these regulations failed to reduce household health expenditures and the average profitability of the pharmaceutical industry, and firms on the break-even edge were worse off. Finally, although these regulations had no significant effect on the price of substitute or complementary medicines, they increased expensive medicine imports.
Immersive Learning Support System based on Kinect Sensor for Children to Learn About Paleontological Environments

Abstract This paper proposes a simulation-based environmental learning support system, based on Kinect sensors, which is currently under development. Our system animates paleontological animals and their habitats on a display in synchronization with learners’ actions, immersing learners in a real- life paleontological environment. We evaluated the system by recording real-time measurements of learners’ movements, and controlled the animation based on sensor output. Participants were subsequently interviewed to assess their sense of immersion. The system was found to provide a nearreal experience of a defunct environment and the results confirmed that learners felt a sense of immersion and experienced an enhanced interest.
Handle identification by keypoint extraction

Door identification is a key problem to be solved during mobile robot navigation. Doors give access to many locations that are defined as goals for the robot. This paper presents an approach to door identification by means of recognition of the door handle. Rather than using the lines defined by the door blades, the region of interest of an image is extracted by means of the Hough transform and afterwards keypoints are obtained and matched against a database in order to positively recognize the door. The keypoint extraction is performed using three different methods, SIFT, SURF and its upright variant USURF, that are compared in terms of different performance measures. The approach is evaluated and tested on a real PeopleBot robot.
On the calculation of generalized Reed-Muller canonical expansions from disjoint cube representation of Boolean functions

An algorithm that converts disjoint cube representation of Boolean functions into fixed-polarity generalized Reed-Muller expansions (GRME) is presented. Since the known fast algorithm that generates the GRME based on the factorization of the Reed-Muller transform matrix always start from the truth table (minterm) of Boolean function, then the described method has an advantage due to smaller required computer memory. Moreover, for the Boolean functions described by only a few disjoint cubes the method is much more efficient than the fast algorithm. <<ETX>>
Short-Term Fidelity, Habitat Use and Vertical Movement Behavior of the Black Rockfish Sebastes schlegelii as Determined by Acoustic Telemetry

The recent miniaturization of acoustic tracking devices has allowed fishery managers and scientists to collect spatial and temporal data for sustainable fishery management. The spatial and temporal dimensions of fish behavior (movement and/or vertical migrations) are particularly relevant for rockfishes (Sebastes spp.) because most rockfish species are long-lived and have high site fidelity, increasing their vulnerability to overexploitation. In this study, we describe the short-term (with a tracking period of up to 46 d) spatial behavior, as determined by acoustic tracking, of the black rockfish Sebastes schlegelii, a species subject to overexploitation in the Yellow Sea of China. The average residence index (the ratio of detected days to the total period from release to the last detection) in the study area was 0.92 ± 0.13, and most of the tagged fish were detected by only one region of the acoustic receiver array, suggesting relatively high site fidelity to the study area. Acoustic tracking also suggested that this species is more frequently detected during the day than at night in our study area. However, the diel detection periodicity (24 h) was only evident for certain periods of the tracking time, as revealed by a continuous wavelet transform. The habitat selection index of tagged S. schlegelii suggested that S. schlegelii preferred natural reefs, mixed sand/artificial reef bottoms and mixed bottoms of boulder, cobble, gravel and artificial reefs. The preference of this species for the artificial reefs that were recently deployed in the study area suggests that artificial seascapes may be effective management tools to attract individuals. The vertical movement of tagged S. schlegelii was mostly characterized by bottom dwelling behavior, and there was high individual variability in the vertical migration pattern. Our results have important implications for S. schlegelii catchability, the implementation of marine protected areas, and the identification of key species habitats, and our study provides novel information for future studies on the sustainability of this important marine resource in eastern China.
On improving the efficiency of complex-valued ELM

The Paper proposes new complex-valued ELM. The main emphasis in designing the new Complex-valued ELM is to improve the classification accuracy and also to remove the drawbacks present in other complex-valued ELMs. A novel method of converting the input to complex domain has been proposed in which the real-valued feature is considered as a projection of complex number. Two random complex valued input-hidden weights are generated which project the complex-valued input on two random hyper-planes. The ratio of two random projections of input is used as aggregation function. An algebraic function has been used as the activation function. Comparative performance evaluation of proposed complex-valued ELM with the well-known CC-ELM [1] and SVM demonstrates the superiority of proposed complex-valued ELM.
To be published in: International Journal of Industrial Organization QUANTITATIVE NOTES ON THE EXTENT OF GOVERNMENTAL REGULATIONS IN VARIOUS OECD NATIONS*

This essay attempts a quantitative evaluation of the extent of governmental regulation of industry in 21 OECD nations, using several business surveys as a data base. Employing this experimental measure, the essay then explores quantitatively three questions: Is government ownership complementary or a substitute to regulation? What are the determinants of the extent of government regulation? And what is the relationship between governmental effectiveness and the extent of governmental regulation. JEL Classifications: L50, L51, P52
Quantum Mechanical Actuation of Microelectromechanical Systems by the Casimir Force

The Casimir force is the attraction between uncharged metallic surfaces as a result of quantum mechanical vacuum fluctuations of the electromagnetic field. We demonstrate the Casimir effect in microelectromechanical systems using a micromachined torsional device. Attraction between a polysilicon plate and a spherical metallic surface results in a torque that rotates the plate about two thin torsional rods. The dependence of the rotation angle on the separation between the surfaces is in agreement with calculations of the Casimir force. Our results show that quantum electrodynamical effects play a significant role in such microelectromechanical systems when the separation between components is in the nanometer range.
Parallel simulation of cloth on distributed memory architectures

The physically based simulation of clothes in virtual environments is a highly demanding problem. It involves both modeling the internal material properties of the textile and the interaction with the surrounding scene. We present a parallel cloth simulation approach designed for distributed memory parallel architectures, in particular clusters built of commodity components. In this paper, we focus on the parallelization of the collision handling phase. In order to cope with the high irregularity of this problem we employ a task parallel approach with fully dynamic problem decomposition. This leads to a robust algorithm, regardless of the complexity of the scene. We report on initial performance measurements indicating the usefulness of our approach.
Family Illness History, Obstetric Complications and Age of Onset in Bipolar Patients

The study examined the relationship between obstetric complications, genetic risk and age of illness onset in bipolar disorder. Thirty DSM-IV bipolar I patients in remission (ages 21-39yr, mean 30.7 + 6.1yr.) and twenty seven healthy controls (ages 19-39yr, mean 27.7 + 7.0yr.) were investigated using structured interview, life chart and pregnancy and birth complica- tions questionnaire. Family history, pregnancy and birth complications and age of illness onset were collected. Compari- sons were made between patients and controls and also between patient groups with age of illness onset before and after the age of 21 years. Obstetric complications were more common in patients (effect size= 0.48) than controls but this was not significant statis- tically (Fisher's exact test, p=0.13). There was a non-significant excess in early onset patients. Family histories of mood disorder were found in 22 out of 30 bipolar subjects, but rates in early and late onset groups did not differ (p=0.35). The study failed to find evidence of either increased rates of obstetric complications in bipolar disorder patients or of a link between age of illness onset and a family history of mood disorders. The power of the study was limited by a sample size and difficulties in obtaining unequivocal obstetric data. The finding is in agreement with a recent metanalysis. The large effect size indicates that larger study of obstetric complications in bipolar disorder subjects is justified, looking par- ticularly for subgroups for which there may be an association between complications and clinical variables.
Modified stepped-frequency train of LFM pulses

A new modified signal - the stepped-frequency train of LFM pulses with modulation of MPS (minimum peak sidelobe) biphasic coding and Costas frequency coding is proposed, whose spectrum function and ambiguity function are deduced respectively. Then the processing measure of the ranging system is illustrated in detail and the principle of the measure is analyzed. Range and velocity estimation of the target are resolved and how to form HRRP (high-resolution range profile) is exhibited. Finally, the resolution and ambiguity characteristics are studied. Research shows that the new modified ranging system is feasible and has advantageous performance.
Two level time synchronization scheme for wireless sensor networks

Continuous surveillance of a remote field is one of the applications of wireless sensor networks (WSNs). Acoustic target localization is one of the methods that are used in surveillance application. Accuracy of acoustic target localization is one of the most important quality of service (QoS) metrics that greatly depends on the accuracy of time synchronization. Power saving is another important requirement of WSNs. In this paper a new time synchronization method is proposed that is specific for acoustic target localization in surveillance application and is combination of two known existing time synchronization methods. Simulation results show that proposed method with regard of time synchronization accuracy do more power saving in comparison with most of the commonly used time synchronization methods.
A knowledge-level analysis of explanation-based learning

Although Explanation-Based Learning (EBL) has up to now been used only for deductive learning that improves execution speed, chunking in Soar, which is closely related to EBL, was demonstrated to acquire new knowledge. We first analyze such knowledge level learning in EBL, by showing that a rule set is specialized when rules in it are replaced by their composition, and is generalized when a rule is replaced by its decomposition. Counting on this discussion, we propose a method to learn generalized rules by making a decomposition of instances. Since this method acquires knowledge that is deduced from domain theory and induced from instances, it is a natural method for combining empirical and explanation-based learning. We demonstrate deductive and inductive aspects of our method by examples of logic circuit design and geometric analogy.
A fractional order variational model for tracking the motion of objects in the applications of video surveillance

Motion tracking of moving objects from a sequence of images is an active research area devoted to the applications of video surveillance. The motion estimation is performed by means of optical flow. In this paper, a fractional order variational model is presented for motion estimation. In particular, the proposed model generalizes the existing variational models from integer order to fractional order. More specific, the fractional order derivative describes discontinuous information about texture and edges, whereas integer order unable to do so, and therefore, a more suitable in estimating the optical flow. The Grünwald-Letnikov derivative is used as a discretization scheme to discretize the complex fractional order partial differential equations corresponding to the Euler-Lagrange equations. The resulting system of equations is solved by using the conjugate gradient method. Experimental results on various datasets verify the validity of the proposed model.
Coordinating regulation and demand response in electric power grids using multirate model predictive control

We propose a framework for reducing demand-supply imbalances in the grid, by jointly controlling both the supply-side electric power regulation together with the demand-side energy consumption by residential and commercial consumers demand response. We focus on performance improvements that arise from the complementary dynamics: regulation allows for frequent control updates but suffers from slower dynamics; demand response has faster dynamics but does not allow as frequent control updates. We propose a multirate model predictive control (MPC) approach for coordinating the two services, and we refer to this coordinator as an aggregator. Multirate MPC captures the varying dynamics and update rates, and nonlinearities due to saturation and ramp rate limits, and a total variation constraint limits the switching of the demand response signal. Our approach can operate with both direct reference or indirect market price based imbalance signal. Numerical examples are presented to show the efficacy of this joint control approach.
A LCMS Rendering Intelligent Tutoring Modules for the Provision of Study Skills Training

It is recognized that students in higher education need to acquire and develop effective and transferable skills in order to be successful in their study and after graduation. In this paper a new custom built LCMS, called the 'skills superstore', which renders intelligent tutoring modules for the provision of study and transferable skills training, is presented and its performance evaluated. The proposed system has two principal units, administrator unit and student user unit. The administrator unit enables administrators with no knowledge of Web application design and development to create and modify highly dynamic and engaging multimedia modules to be offered by the system. The student user unit delivers highly interactive and customized modules for the provision of skills training to students in higher education. The system's features, functionality and architecture were defined based on the findings of a viability study conducted at our institution. The system was developed using an iterative software prototyping
An Antidote to the Imager's Fallacy, or How to Identify Brain Areas That Are in Limbo

Traditionally, fMRI data are analyzed using statistical parametric mapping approaches. Regardless of the precise thresholding procedure, these approaches ultimately divide the brain in regions that do or do not differ significantly across experimental conditions. This binary classification scheme fosters the so-called imager's fallacy, where researchers prematurely conclude that region A is selectively involved in a certain cognitive task because activity in that region reaches statistical significance and activity in region B does not. For such a conclusion to be statistically valid, however, a test on the differences in activation across these two regions is required. Here we propose a simple GLM-based method that defines an “in-between” category of brain regions that are neither significantly active nor inactive, but rather “in limbo”. For regions that are in limbo, the activation pattern is inconclusive: it does not differ significantly from baseline, but neither does it differ significantly from regions that do show significant changes from baseline. This pattern indicates that measurement was insufficiently precise. By directly testing differences in activation, our procedure helps reduce the impact of the imager's fallacy. The method is illustrated using concrete examples.
Generating ternary stock trading signals using fuzzy genetic network programming

In this paper, an expert system is developed using fuzzy genetic network programming with reinforcement learning (GNP-RL) in order to generate stock trading signals based on technical indices of the stock prices. In order to increase the accuracy and reliability of results, we applied Wavelet Transform to eliminate noises and irregularities in prices. Since choosing the most appropriate wavelet base is an important decision, the Energy to Shannon Entropy Ratio, as an objective method, is used in order to address this concern. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. The proposed model has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in testing time period shows that the developed system has more favorable performance in comparison with the simple GNP-RL with binary signals and Buy and Hold strategy.
Progressive Gender Attitudes, Time to First Birth and Sex Selection in Delhi

Statistical evidence shows that the sex ratio of India's total population is unnaturally male biased (Jha et al. (2011)). There is however disagreement on whether sex selective abortions are practiced for the first birth (Jha et al. (2006), Retherford and Roy (2003)). Using data from the NFHS-3 this paper first finds out that sex ratios for firstborns in Delhi, Punjab and Rajasthan do have significantly less females than the biologically normal ratio and creates an index of women's progressivism using a multilevel latent factor model. Progressivism is defined in terms of attitudes and perceptions favouring the advancement of women towards better conditions in society. Delhi is then taken as a case study and the effect of progressivism on the firstborn's gender and the first birth interval is assessed using competing risk models. The main findings are: (i) A one-standard deviation increase in the progressivism index increases the likelihood of a firstborn girl by 5.8 percentage points compared to women who have not yet given birth. This effect is robust to the set of covariates used to create the index and increases for different subsamples; (ii) More progressive women do not experience longer first birth intervals which, consistent with the first result, may indicate that they are less inclined to sex-select their firstborn. These results imply that women should be taught about their human rights and gender equality. More generally, regional governments should introduce interventions aimed at subsidizing and empowering girls.
Emotion regulation strategies and later externalizing behavior among European American and African American children

Abstract Children's early emotion regulation strategies (ERS) have been related to externalizing problems; however, most studies have included predominantly European American, middle-class children. The current study explores whether ERS use may have differential outcomes as a function of the mother's ethnic culture. The study utilizes two diverse samples of low-income male toddlers to examine observed ERS during a delay of gratification task in relation to maternal and teacher reports of children's externalizing behavior 2 to 6 years later. Although the frequencies of ERS were comparable between ethnic groups in both samples, the use of physical comfort seeking and self-soothing was positively related to African American children's later externalizing behavior but negatively related to externalizing behavior for European American children in Sample 1. Data from Sample 2 appear to support this pattern for self-soothing in maternal, but not teacher, report of externalizing behavior. Within group differences by income were examined as a possible explanatory factor accounting for the ethnic differences, but it was not supported. Alternative explanations are discussed to explain the pattern of findings.
On the Adams spectral sequence for R–modules

We discuss the Adams Spectral Sequence for R-modules based on commutative localized regular quotient ring spectra over a commutative S -algebra R in the sense of Elmendorf, Kriz, Mandell, May and Strickland. The formulation of this spectral sequence is similar to the classical case and the calculation of its E2 -term involves the cohomology of certain 'brave new Hopf algebroids' E R E. In working out the details we resurrect Adams' original approach to Universal Coecient Spectral Sequences for modules over an R ring spectrum. We show that the Adams Spectral Sequence for SR based on a commutative localized regular quotient R ring spectrum E = R=I(X 1 ) converges to the