Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Reality Mining Dataset for Human Behavior Analysis -- A Survey

Recent advancements in mobile technologies have designed a new kind of device: the smart phone. Smart phones have become quintessential for a large fraction of people in developed as well as developing countries in their day to day life. The device integrates a number of sensor technologies for automatic observation which can provide data with high accuracy & precision, can be programmed to interact with the user, and can have communication with remote researchers. This allows relentless and cost-effective access to erstwhile inaccessible history of data on everyday social behavior, such as intimacy of people, phone calls, and movement patterns. In this paper, the concept and applications of reality mining are summarized and its significance towards human behavior analysis is illustrated. The sensor data collected from smart phones is experimented with survey data by applying machine learning algorithms to predict human behavior in social networks. This survey conjointly highlights reality mining applications, future issues and challenges.
Joint upsampling and noise reduction for real-time depth map enhancement

An efficient system that upsamples depth map captured by Microsoft Kinect while jointly reducing the effect of noise is presented. The upsampling is carried by detecting and exploiting the piecewise locally planar structures of the downsampled depth map, based on corresponding high-resolution RGB image. The amount of noise is reduced by accumulating the downsampled data simultaneously. By benefiting from massively parallel computing capability of modern commodity GPUs, the system is able to maintain high frame rate. Our system is observed to produce the upsampled depth map that is very close to the original depth map both visually and mathematically.
Evolution and modulation of intracellular calcium release during long‐lasting, depleting depolarization in mouse muscle

Intracellular calcium signals regulate multiple cellular functions. They depend on release of Ca2+ from cellular stores into the cytosol, a process that in many types of cells appears to be tightly controlled by changes in [Ca2+] within the store. In contrast with cardiac muscle, where depletion of Ca2+ in the sarcoplasmic reticulum is a crucial determinant of termination of Ca2+ release, in skeletal muscle there is no agreement regarding the sign, or even the existence of an effect of SR Ca2+ level on Ca2+ release. To address this issue we measured Ca2+ transients in mouse flexor digitorum brevis (FDB) skeletal muscle fibres under voltage clamp, using confocal microscopy and the Ca2+ monitor rhod‐2. The evolution of Ca2+ release flux was quantified during long‐lasting depolarizations that reduced severely the Ca2+ content of the SR. As in all previous determinations in mammals and non‐mammals, release flux consisted of an early peak, relaxing to a lower level from which it continued to decay more slowly. Decay of flux in this second stage, which has been attributed largely to depletion of SR Ca2+, was studied in detail. A simple depletion mechanism without change in release permeability predicts an exponential decay with time. In contrast, flux decreased non‐exponentially, to a finite, measurable level that could be maintained for the longest pulses applied (1.8 s). An algorithm on the flux record allowed us to define a quantitative index, the normalized flux rate of change (NFRC), which was shown to be proportional to the ratio of release permeability P and inversely proportional to Ca2+ buffering power B of the SR, thus quantifying the ‘evacuability’ or ability of the SR to empty its content. When P and B were constant, flux then decayed exponentially, and NFRC was equal to the exponential rate constant. Instead, in most cases NFRC increased during the pulse, from a minimum reached immediately after the early peak in flux, to a time between 200 and 250 ms, when the index was no longer defined. NFRC increased by 111% on average (in 27 images from 18 cells), reaching 300% in some cases. The increase may reflect an increase in P, a decrease in B, or both. On experimental and theoretical grounds, both changes are to be expected upon SR depletion. A variable evacuability helps maintain a constant Ca2+ output under conditions of diminishing store Ca2+ load.
Self-Reported Benefits and Costs of Research Participation by Sexual Minority and Heterosexual Youth

Decision making about the balance of costs and harms experienced by research participants should be based on empirical data and not on subjective points of view. These data are scarce for young people in general and virtually nonexistent for sexual minority youth. The current study examines the effects of research participation on sexual minority and heterosexual youth and the explanations for potential differences in effects. Participants (N = 447, 16–20 years old) completed an online questionnaire about their well-being (psychological distress, loneliness, and suicidality) and self-perceived effects of research participation. Sexual minority youth reported significantly higher levels of perceived benefits and perceived costs than heterosexual participants. Participants who reported higher levels of psychological distress and loneliness experienced more costs from their research participation. When controlling for the aspects of well-being and sociodemographics, sexual minority youth still reported elevated levels of benefits from their participation, while the differences in the experienced costs disappeared. Implications for policymakers and researchers are discussed in addition to the limitations of the current study. Beslissingen over of de baten voor deelnemers aan studies groter zijn dan de kosten moeten gebaseerd zijn op empirische data en niet op subjectieve oordelen. Helaas zijn data van deelname effecten op jongeren schaars en ontbreken data voor seksuele minderheidsjongeren. De huidige studie brengt de effecten van deelname seksuele minderheids- en heteroseksuele jongeren en kaart en zoekt verklaringen voor mogelijke verschillen. Jongeren (N = 447, 16-20 jaar oud) vulden een online vragenlijst in over minderheidsstress, psychisch welbevinden, middelengebruik, sociaal welzijn en de effecten die het invullen van deze vragen op hen had. Gemiddeld genomen rapporteerden seksuele minderheidsjongeren en heteroseksuele deelnemers meer voor- dan nadelen van hun deelname aan het onderzoek. Seksuele minderheden rapporteerden meer voor- en nadelen van deelname dan heteroseksuele deelnemers. Als we controleren voor sociaal-demografische kenmerken en welzijn, dan blijven de verschillen in ervaren voordelen bestaan, maar zien we geen verschillen meer voor wat betreft de ervaren nadelen. Implicaties voor beleidsmakers en onderzoekers worden besproken alsmede de beperkingen van het huidige onderzoek.
EFFICIENT DESIGN OF EDDR CIRCUIT FOR ADVANCED VIDEO CODING/H.264

Advanced video coding/H.264 is the video compression standard introduced by ISO/IEC. Motion Estimation (ME) has a critical role in the video coder. The main objective of Motion Estimation is to exploit temporal correlation among adjacent frames in a video sequence to reduce redundancy. Testing such a module is of priority concern. Processing Equipments (PEs) are the key components of Motion Estimation (ME). An error in PE affects the visual quality and PSNR (peak signal to noise ratio) of the high definition video. The error can be detected and recovered effectively by using proposed Error Detection and Data Recovery (EDDR) design based on Residue and Quotient (RQ) code. The proposed EDDR have acceptable area overhead and time penalty. Thus the reliability and throughput of Motion Estimation will be improved.
High-redshift galaxies and low-mass stars

The sensitivity available to near-infrared surveys has recently allowed us to probe the galaxy population at z ≈ 7 and beyond. The existing Hubble Wide Field Camera 3 (WFC3) and Visible and Infrared Survey Telescope for Astronomy (VISTA) Infrared Camera (VIRCam) instruments allow deep surveys to be undertaken well beyond 1 μm – a capability that will be further extended with the launch and commissioning of the James Webb Space Telescope (JWST). As new regions of parameter space in both colour and depth are probed, new challenges for distant galaxy surveys are identified. In this paper, we present an analysis of the colours of L- and T-dwarf stars in widely used photometric systems. We also consider the implications of the newly identified Y-dwarf population – stars that are still cooler and less massive than T-dwarfs for both the photometric selection and spectroscopic follow-up of faint and distant galaxies. We highlight the dangers of working in the low-signal-to-noise regime, and the potential contamination of existing and future samples. We find that Hubble/WFC3 and VISTA/VIRCam Y-drop selections targeting galaxies at z ∼ 7.5 are vulnerable to contamination from T- and Y-class stars. Future observations using JWST, targeting the z ∼ 7 galaxy population, are also likely to prove difficult without deep medium-band observations. We demonstrate that single emission line detections in typical low-signal-to-noise spectroscopic observations may also be suspect, due to the unusual spectral characteristics of the cool dwarf star population.
ERF silences extra-synaptic utrophin by N-box mediated repression in skeletal muscle

Utrophin is the autosomal homologue of dystrophin, the protein product of the Duchenne’s muscular dystrophy (DMD) locus. Utrophin expression is temporally and spatially regulated being developmentally down-regulated perinatally and enriched at neuromuscular junctions (NMJs) in adult muscle. Synaptic localization of utrophin occurs in part by heregulin-mediated ERKphosphorylation, leading to binding of GABPα/β to the N-box/EBS and activation of the major utrophin promoter-A expressed in myofibers. However, molecular mechanisms contributing to concurrent extra-synaptic silencing that must occur to achieve NMJ localization are unknown. We demonstrate that the Ets-2 repressor factor (ERF) represses extra-synaptic utrophin-A in muscle. Gel-shift and chromatin immunoprecipitation studies demonstrated physical association of ERF with the utrophin-A promoter N-Box/EBS site. ERF overexpression repressed utrophin-A promoter activity: conversely, siRNA-mediated ERF knockdown enhanced promoter activity as well as endogenous utrophin mRNA levels in cultured muscle cells in vitro. Laser-capture microscopy of tibialis anterior NMJ and extra-synaptic transcriptomes and gene transfer studies provide spatial and direct evidence respectively, for ERF-mediated utrophin repression in vivo. Together, these studies suggest “repressing repressors” as a potential strategy for achieving utrophin upregulation in DMD and provide a model for utrophin-A regulation in muscle.
Topological Analysis of Urban Street Networks

The authors propose a topological analysis of large urban street networks based on a computational and functional graph representation. This representation gives a functional view in which vertices represent named streets and edges represent street intersections. A range of graph measures, including street connectivity, average path length, and clustering coefficient, are computed for structural analysis. In order to characterise different clustering degrees of streets in a street network they generalise the clustering coefficient to a k-clustering coefficient that takes into account k neighbours. Based on validations applied to three cities, the authors show that large urban street networks form small-world networks but exhibit no scale-free property.
Blind equalization technique base on the initialization of constant modulus algorithm

The constant modulus algorithm is a widely used blind equalization algorithm. But it has a disadvantage for its initialization. Its convergence characteristics depends on its preliminary tap gains. The paper introduced the method of optimization and the technology of small swatch repetition to overcome the initializationpsilas effect and accelerate the convergence. Computer simulation is implemented with QAM system. The algorithm achieves the goal and is proved successful.
A Class of Large-and Small-update Primal-dual Interior-point Algorithms for Linear Optimization ∗

In this paper we present a class of polynomial primal-dual interior-point algorithms for linear optimization based on a new class of kernel functions. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel functions as special cases. The analysis of the algorithms in the paper follows the same line of arguments as in [4], where a variety of non-self-regular kernel functions were considered including the ones with linear and quadratic growth terms. However, the important case when the growth term is between linear and quadratic was not considered. The goal of this paper is to introduce such class of kernel functions and to show that the interior-point methods based on these functions have favorable complexity results. In order to achieve these complexity results, several new arguments had to be used. We obtain iteration bounds of O ( qn p+q q(p+1) log n 2 ) for large-update methods and O ( q √ n log n 2 ) for small-update methods, where p ∈ [0, 1] and q ≥ 1 are the growth and barrier parameters of the new class of kernel functions, respectively. These iteration bounds match the currently best known iteration bounds. Examples are the prototype self-regular function with quadratic growth term (when p = 1, q > 1), a simple non-self-regular function with linear growth term (when p = 0, q = 2), and the classical logarithmic kernel function (when p = 1, q = 1).
A Method for Quality Inspection of Motors by Detecting Abnormal Sound

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system. Keywords—Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation
Correction of multiple frequency offsets and detection in V-BLAST OFDM systems with distributed transmit antennas

This paper addresses the correction of multiple carrier frequency offsets (CFO) and detection in vertical Bell Labs layered space-time (V-BLAST) orthogonal frequency division multiplexing (OFDM) systems with distributed transmit antennas. We first propose a low-complexity CFO correction method suitable for low delay spread channels by exploiting the underlying characteristics of zero-forcing (ZF) detection, and then propose a ZF based detection method involving two CFO correction processes to further improve its performance in the high delay spread case. Simulation results show that the proposed CFO correction method can effectively correct multiple CFOs in low delay spread channels, while for the high delay spread case the proposed detection method with two CFO correction processes can further improve the detection performance.
Monte Carlo Local Likelihood for Estimating Generalized Linear Mixed Models

We propose the Monte Carlo local likelihood (MCLL) method for estimating generalized linear mixed models (GLMMs) with crossed random e ects. MCLL initially treats model parameters as random variables, sampling them from the posterior distribution in a Bayesian model. The likelihood function is then approximated up to a constant by tting a density to the posterior samples and dividing it by the prior. In the MCLL algorithm, the posterior density is approximated using local likelihood density estimation (Loader, 1996), in which the log-density is locally approximated by a polynomial function. In his Monte Carlo kernel likelihood (MCKL) method, De Valpine (2004) proposed a similar approach using kernel density estimation instead of local likelihood density estimation. We also develop a novel method to compute standard errors and the Bayes factor. Using empirical and simulation examples, we show that our proposed method outperforms existing methods such as the Laplace approximation and Monte Carlo maximum likelihood estimation (MCMLE).
A Multilevel Approach for Overlapping Community Detection

Many real world complex networks have an a overlapping community structure, in which a vertex belongs to one or more communities. Numerous approaches for crisp overlapping community detection were proposed in the literature, most of them have a good accuracy but their computational costs are considerably high and infeasible for large-scale networks. Since the multilevel approach has not been previously applied to deal with overlapping communities detection problem, in this paper we propose an adaptation of this approach to tackle the detection problem to overlapping communities case. The goal is to analyze the time impact and the quality of solution of our multilevel strategy regarding to traditional algorithms. Our experiments show that our proposal consistently produces good performance compared to single-level algorithms and in less time.
The Overbot: An Off-Road Autonomous Ground Vehicle Testbed

The Overbot, originally designed to run the DARPA Grand Challenge, has been retasked as an off-road autonomous vehicle testbed. The base chassis is a Polaris Ranger 6x6 gasoline powered off-road vehicle. It has a single cylinder 30 HP engine capable of propelling the vehicle to over 40 mph. In addition to the chassis, the Overbot is equipped with a SiCK LiDAR on a custom gimbaled mount, a color firewire camera in a waterproof housing, a Crossbow AHRS, a Novatel differential GPS system and several modified 802.11. b wireless hubs. In terms of actuation, there are five Galil Motion Controllers which drive servomotors that handle shifting (H-L-N-R), braking, throttle, steering and the vision angle. Software which performs obstacle detection, path planning and low-level control is implemented in a Real Time Operating System (RTOS) on a standard Pentium class PC. The original incarnation of the Overbot was selected to run in the National Qualifying Events (NQE) of the Grand Challenge in both 2004 and 2005, but failed to proceed to actual competition. The Overbot is a very agile off-road platform, capable of passing over obstacles as high as 15 inches. Demonstration of new path following control shows crosstrack errors that are less than 1 meter and a new heading correction implementation is discussed.
Multi step ahead forecasting of wind power by different class of neural networks

This paper presents a comparison of three different classes of artificial neural networks (ANN) for multi-step ahead time series forecasting of wind power. The neural network needs past wind generation measurement as an input. For time series prediction, the time lag data pattern is required & for this purpose the statistical tool called autocorrelation function (ACF) facilitates to work out on the input variables of neural networks. The three models which have been used are: linear neural network with time delay (LNNTD), feed forward neural network (FFNN) and Elman recurrent neural network (ERNN). The performance comparisons of the models are on the basis of mean absolute error (MAE) & mean absolute percentage error (MAPE). Data of wind power from Ontario Electricity Market for the year 2011-2012 has been considered for the case study and tested for a period of one week for twelve multi-steps ahead forecasting. It is observed that all class of neural networks shows almost equal results.
An efficient shift-invariant model for polyphonic music transcription

In this paper, we propose an efficient model for automatic transcription of polyphonic music. The model extends the shift-invariant probabilistic latent component analysis method and uses pre-extracted and pre-shifted note templates from multiple instruments. Thus, the proposed system can efficiently transcribe polyphonic music, while taking into account tuning deviations and frequency modulations. Additional system improvements utilising massive parallel computations with GPUs result in a system performing much faster than real-time. Experimental results using several datasets show that the proposed system can successfully transcribe polyphonic music, outperforming several state-of-the-art approaches, and is over 140 times faster compared to a standard shiftinvariant transcription model.
Analysis and design of a hardware/software trusted platform module for embedded systems

Trusted platforms have been proposed as a promising approach to enhance the security of general-purpose computing systems. However, for many resource-constrained embedded systems, the size and cost overheads of a separate Trusted Platform Module (TPM) chip are not acceptable. One alternative is to use a software-based TPM, which implements TPM functions using software that executes in a protected execution domain on the embedded processor itself. However, since many embedded systems have limited processing capabilities and are battery-powered, it is also important to ensure that the computational and energy requirements for SW-TPMs are acceptable. In this article, we perform an evaluation of the energy and execution time overheads for a SW-TPM implementation on a handheld appliance (Sharp Zaurus PDA). We characterize the execution time and energy required by each TPM command through actual measurements on the target platform. We observe that for most commands, overheads are primarily due to the use of 2,048-bit RSA operations that are performed within the SW-TPM. In order to alleviate SW-TPM overheads, we evaluate the use of Elliptic Curve Cryptography (ECC) as a replacement for the RSA algorithm specified in the Trusted Computing Group (TCG) standards. In addition, we also evaluate the overheads of using the SW-TPM in the context of various end applications, including trusted boot of the Linux operating system (OS), a secure VoIP client, and a secure Web browser. Furthermore, we analyze the computational workload involved in running SW-TPM commands using ECC. We then present a suite of hardware and software enhancements to accelerate these commands—generic custom instructions and exploitation of parallel processing capabilities in multiprocessor systems-on-chip (SoCs). We report results of evaluating the proposed architectures on a commercial embedded processor (Xtensa from Tensilica). Through uniprocessor and multiprocessor optimizations, we could achieve speed-ups of up to 5.71X for individual TPM commands.
What Does “Flexibility” Mean for Children's Services?

Abstract Advocates from a range of political perspectives now argue that social services intended to help children and their families don't work. They have converged upon a vision of reform in which notions of “flexibility” are featured. The authors argue that maintaining a critical perspective on social service reform requires paying attention to the possibilities and limits of flexibility. Drawing from an ethnographic study conducted at a demonstration site of one prototypical model of reform, “wraparound services,” the authors discuss the meaning of flexibility for the reform of children's services and highlight unresolved tensions that are embedded within the design of reform itself.