Miracle-dz/UniFAR-FTUs huggingface dataset:
The NIST 2004 spring rich transcription evaluation : two-axis merging strategy in the context of multiple distance microphone based meeting speaker segmentation

This paper presents the ELISA speaker segmentation approach applied on multiple audio channel meeting recordings in the framework of NIST RT’04s meeting (spring) evaluation campaign. As done for BN data speaker segmentation, the ELISA “meeting” system involves two speaker segmentation systems developed individually by the CLIPS and LIA laboratories. The main originality consists in a “two-axis” merging strategy, proposed to deal with both multiple expert segmentation outputs and multiple microphone segmentation outputs. While expert merging strategy did not really lead to an improvement of the performance, the individual microphone segmentation merging strategy allowed to provide a global segmentation output from several audio channels (microphones) with acceptable performance. The best system obtained 22.6% of diarization error rate during the NIST RT’04s meeting evaluation.
Research Roadmap Driven by Network Benchmarking Lab (NBL): Deep Packet Inspection, Traffic Forensics, Embedded Benchmarking, Software Defined Networking and Beyond

Most researchers look for topics from the literature. But our research derived mostly from development, in turn driven by industrial projects or product testing. We spanned into the areas of cable TV networks, multi-hop cellular, Internet QoS, deep packet inspection, traffic forensics, embedded benchmarking, and software defined networking. Among them, our multi-hop cellular work was the first along this line and has a high impact on both academia and industry, with over 600 citations and standardizations in WLAN mesh (IEEE 802.11s), WiMAX (IEEE 802.16j), Bluetooth (IEEE 802.15.5), and 3GPP LTE-advanced. Side products from our research include a startup (L7 Networks Inc., in 2002), a test lab (Network Benchmarking Lab, NBL, since 2002), and a textbook Computer Networks: An Open Source Approach (McGraw-Hill, 2011). It is a perfect time to have my 20-year half-time report as we celebrate the 70th birthday of my Ph.D. thesis advisor, Prof. Mario Gerla. This report could serve as a reference for researchers in developing their own roadmap. Â
Hybrid Approach for Redundancy Optimization of Multi-State Power System

This paper presents an optimize method of the well known Redundancy Optimization Problem (ROP) using a combined ANT Colony System (ACS) and Universal Moment Generating Function (UMGF). The ACS searches for the minimum cost solution by selecting the appropriate components for a series-parallel system, given a minimum system reliability constraint. The UMGF is used to estimate the system reliability value during search. This approach is an example of a computationally efficient method to apply ACS optimization to problems for which repeated calculation of the objective function is impractical.
Use of accelerometers to characterize physical activity patterns with COPD exacerbations

Purpose To determine the feasibility of using an accelerometer to characterize physical activity patterns (PA) surrounding chronic obstructive pulmonary disease (COPD) exacerbations (AECOPD) in patients with COPD for 16 weeks. Methods Patients with COPD (n = 8) wore the RT3®, a triaxial accelerometer (Stayhealthy, Monrovia, CA) during waking hours and kept daily symptom diaries. The mean vector magnitude unit (VMU) per minute was calculated by dividing the total VMU for the day by the number of minutes the device was worn. Descriptive statistics were used and plots were made showing PA for each subject with AECOPD markers based on symptom diaries and health resource utilization. Results Sample characteristics were: age 71 ± 4; 5 Females; forced expiratory volume in one second (FEV1)% predicted: 40% ± 16%; FEV1/forced vital capacity: 45 ± 7; and Medical Research Council dyspnea scale: 2.3 ± 0.9. Overall adherence to the monitoring protocol was 97.6% (Range 92%–100%) while adherence to wearing the device for at least 10 hours per day was 91.5% (Range 75%–99%). Mean vector magnitude units per minute was 117.8 ± 47 (Range 61.4–184.1). Seven exacerbations were captured over a total of 896 person-days of monitoring. There were substantial intra-individual fluctuations in daily PA during both the stable state and with outpatient treated exacerbations. Conclusions Patients with COPD were able to adhere to a 16-week activity monitoring protocol and reported a willingness to wear such a device for an extended period of time if the data yield important and useful information for themselves and their health provider. Future work will need to focus first, on validating other promising devices that produce higher quality PA data and second, replicate this monitoring protocol with a larger sample of COPD patients over a longer period.
Minim Typing – A Rapid and Low Cost MLST Based Typing Tool for Klebsiella pneumoniae

Here we report a single nucleotide polymorphism (SNP) based genotyping method for Klebsiella pneumoniae utilising high-resolution melting (HRM) analysis of fragments within the multilocus sequence typing (MLST) loci. The approach is termed mini-MLST or Minim typing and it has previously been applied to Streptococcus pyogenes, Staphylococcus aureus and Enterococcus faecium. Six SNPs were derived from concatenated MLST sequences on the basis of maximisation of the Simpsons Index of Diversity (D). DNA fragments incorporating these SNPs and predicted to be suitable for HRM analysis were designed. Using the assumption that HRM alleles are defined by G+C content, Minim typing using six fragments was predicted to provide a D = 0.979 against known STs. The method was tested against 202 K. pneumoniae using a blinded approach in which the MLST analyses were performed after the HRM analyses. The HRM-based alleles were indeed in accordance with G+C content, and the Minim typing identified known STs and flagged new STs. The tonB MLST locus was determined to be very diverse, and the two Minim fragments located herein contribute greatly to the resolving power. However these fragments are refractory to amplification in a minority of isolates. Therefore, we assessed the performance of two additional formats: one using only the four fragments located outside the tonB gene (D = 0.929), and the other using HRM data from these four fragments in conjunction with sequencing of the tonB MLST fragment (D = 0.995). The HRM assays were developed on the Rotorgene 6000, and the method was shown to also be robust on the LightCycler 480, allowing a 384-well high through-put format. The assay provides rapid, robust and low-cost typing with fully portable results that can directly be related to current MLST data. Minim typing in combination with molecular screening for antibiotic resistance markers can be a powerful surveillance tool kit.
Development of Hand Finger Recognition System with Relative Positioning

In this paper, we propose a logical and procedural way to recognize hand finger with relat ive positioning. This relative position of hand finger will help us to identify and recognize hundreds of unique gestures bo osting the result of current state of the art approaches by the means of gesture count. The proposed method uses a color ba sed segmentation to identify skin area from image frames and connect ed component detection to detect hand region. Detecd hand regions’ palm center and angular relationship is then used t o identify relative position of hand fingers. The experimental results show that the process is able to recognize finger r elative position with a satisfactory accuracy.
Benchmarking Java Grande Applications

Increasing interest is being shown in the use of Java for large scale or Grande applications. This new use of Java places specific demands on the Java execution environments that can be tested using the Java Grande benchmark suite (Bull et al, 2000). The performance of a range of Java execution environments have been tested using the suite and the results presented.
Clustering of Lyα Emitters at z ≈ 4.5

We present the clustering properties of 151 Lyα-emitting galaxies at z ≈ 4.5 selected from the Large Area Lyman Alpha (LALA) survey. Our catalog covers an area of 36′ × 36′ observed with five narrowband filters. We assume that the angular correlation function w(θ) is well represented by a power law Awθ-β with slope β = 0.8, and we find Aw = 6.73 ± 1.80. We then calculate the correlation length r0 of the real-space two-point correlation function ξ(r) = (r/r0)-1.8 from Aw through the Limber transformation, assuming a flat, Λ-dominated universe. Neglecting contamination, we find r0 = 3.20 ± 0.42 h-1 Mpc. Taking into account a possible 28% contamination by randomly distributed sources, we find r0 = 4.61 ± 0.6 h-1 Mpc. We compare these results with the expectations for the clustering of dark matter halos at this redshift in a cold dark matter model, and find that the measured clustering strength can be reproduced if these objects reside in halos with a minimum mass of (1-2) × 1011 h-1 M☉. Our estimated correlation length implies a bias of b ~ 3.7, similar to that of Lyman break galaxies (LBGs) at z ~ 3.8-4.9. However, Lyα emitters are a factor of ~2-16 rarer than LBGs with a similar bias value and implied host halo mass. Therefore, one plausible scenario seems to be that Lyα emitters occupy host halos of roughly the same mass as LBGs, but shine with a relatively low duty cycle of 6%-50%.
Ultra low leakage synaptic scaling circuits for implementing homeostatic plasticity in neuromorphic architectures

Homeostatic plasticity is a property of biological neural circuits that stabilizes their neuronal firing rates in face of input changes or environmental variations. Synaptic scaling is a particular homeostatic mechanism that acts at the level of the single neuron over long time scales, by changing the gain of all its afferent synapses to maintain the neuron's mean firing within proper operating bounds. In this paper we present ultra low leakage analog circuits that allow the integration of compact integrated filters in multi-neuron chips, able to achieve time constants of the order of hundreds of seconds, and describe automatic gain control circuits that when interfaced to neuromorphic neuron and synapse circuits implement faithful models of biologically realistic synaptic scaling mechanisms. We present simulation results of the low leakage circuits and describe the control circuits that have been designed for a neuromorphic multi-neuron chip, fabricated using a standard 180nm CMOS process.
Distributed Memory LTL Model Checking Based on Breadth FirstSearch

We propose a parallel distributed memory on-the-fly algorithm for enumerative LTL model checking. The algorithm is designed for network of workstations communicating via MPI. The detection of cycles (faulty runs) effectively employs the so called back-level edges. In particular, a parallel level synchronized breadth first search of the graph is performed to discover all back-level edges and for each level the back-level edges are checked in parallel by a nested search procedure to confirm or refute the presence of a cycle. Several optimizations of the basic algorithm are presented and advantages and drawbacks of their application to distributed LTL model checking are discussed. Experimental evaluation of the algorithm is presented.
Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach

Numerous scientific applications across a variety of fields depend on box-constrained convex optimization. Box-constrained problems therefore continue to attract research interest. We address box-constrained (strictly convex) problems by deriving two new quasi-Newton algorithms. Our algorithms are positioned between the projected-gradient [J. B. Rosen, J. SIAM, 8 (1960), pp. 181-217] and projected-Newton [D. P. Bertsekas, SIAM J. Control Optim. , 20 (1982), pp. 221-246] methods. We also prove their convergence under a simple Armijo step-size rule. We provide experimental results for two particular box-constrained problems: nonnegative least squares (NNLS), and nonnegative Kullback-Leibler (NNKL) minimization. For both NNLS and NNKL our algorithms perform competitively as compared to well-established methods on medium-sized problems; for larger problems our approach frequently outperforms the competition.
Integrated Unified Theory of Acceptance and Use of Technology model to explore the female factors with the intention of online shopping, online shopping behavior

Information technology is changing rapidly, and gradual integration into life as the Internet, online shopping has also become a new model of consumer behavior. In this study, female consumers have used online shopping as the research object, and integrated technology acceptance model theory (Unified Theory of Acceptance and Use of Technology, UTAUT), performance expectations (Performance Expectancy, PE) expect efforts (Effort Expectancy EE), social impact (social influence, SI) of variables, combined with involvement (involvement) variables to explore whether the significant impact on female consumer online shopping intentions and online shopping behavior. The past, most people think of female bias in consumers' online shopping insights, such as impulse purchases, preferences and the impact caused by the error bias, through this project to explore the female consumer behavior, and integrated technology acceptance model theory to analyze the impact factors. The authentication method 1000 valid questionnaires were completed by purposive sampling method, and then to quantify the statistical analysis, and for the factor analysis, reliability analysis, validity analysis, the final results obtained will be available to academia and industry as a basis for reference.
SWB process: A business process management system driven by semantic technologies

Constant changes in the market force enterprises to continuously define and redefine their business processes, and the technology that supports them, in order to fulfill the organizational objectives. Business Process Management Systems (BPMS) are intensively used in organizations as a useful tool to face those changes. However, as stated in literature and practice, a BPMS still has to cope with the agility to adapt to changes and the low degree of automation of the BPM life-cycle. These issues have been faced through the integration of BPM with Semantic Technologies. Some proposals are focused in conceptual approaches while others involve tools to cover part of the BPM life-cycle. Nevertheless, there are no works that have implemented a BPMS that exploits Semantic Technologies for covering the whole BPM life-cycle. In this paper we present SWB Process, an industrial and Open Source BPMS completely driven by Semantic Technologies that uses ontologies to agilely support constant changes in the processes of organizations, increasing the degree of automation of the BPM life-cycle. Moreover, we take advantage of ontologies to quickly adapt it to new BPM needs. SWB Process has been validated through real projects in several government agencies in Mexico.
Communication on the Grassmann manifold: A geometric approach to the noncoherent multiple-antenna channel

We study the capacity of multiple-antenna fading channels. We focus on the scenario where the fading coefficients vary quickly; thus an accurate estimation of the coefficients is generally not available to either the transmitter or the receiver. We use a noncoherent block fading model proposed by Marzetta and Hochwald (see ibid. vol.45, p.139-57, 1999). The model does not assume any channel side information at the receiver or at the transmitter, but assumes that the coefficients remain constant for a coherence interval of length T symbol periods. We compute the asymptotic capacity of this channel at high signal-to-noise ratio (SNR) in terms of the coherence time T, the number of transmit antennas M, and the number of receive antennas N. While the capacity gain of the coherent multiple antenna channel is min{M, N} bits per second per Hertz for every 3-dB increase in SNR, the corresponding gain for the noncoherent channel turns out to be M* (1 - M*/T) bits per second per Hertz, where M*=min{M, N, [T/2]}. The capacity expression has a geometric interpretation as sphere packing in the Grassmann manifold.
Syllable-based probabilistic morphological analysis model of Korean

In this paper, we present a syllable-based probabilistic morphological analysis model of Korean. While the previousmorphological analyzers that regardmorpheme as a processing unit, the model exploits syllable as a processing unit in order to endure the unknown word problem. Actually, it does not use any morpheme dictionary. In contract to the previous systems that depend on manually constructed linguistic knowledge, the proposed system can fully automatically acquire the linguistic knowledge from annotated corpora. Besides, without any modification, the system can be applied to other corpus having a different tagset and annotation guidelines. We describe the model and present experimental results on two corpora.
HARDY'S INEQUALITY FROM A LOGARITHMIC CACCIOPPOLI ESTIMATE

We give a simple proof of Hardy's inequality based on the logarithmic Cacciopoli inequality for p-superharmonic func- tions. n=1 � a 1 + a2 + � � � + an n � p ≤ � p p − 1 � p ∞ X n=1 a p ,
The pathogenesis of tendinopathy. A molecular perspective.

There are many publications that discuss the aetiology, diagnosis and treatment of the various forms of tendinopathy, but few are based on conclusive scientific evidence. The pathogenesis of tendinopathy is difficult to study because tendon biopsies are rarely obtained before a tendon has ruptured. There are interesting comparisons with animal tendinopathy, particularly in the equine athlete, although many animal models do not accurately reflect the human condition—the tendon lesions usually heal. However, the application of biochemical and molecular techniques to the study of both animal and human tendinopathy has led to a greater understanding of these common and disabling conditions. This article summarizes current knowledge of the pathogenesis of tendinopathy, with particular emphasis on the molecular pathology of the tendon matrix.
Accretion-induced variability links young stellar objects, white dwarfs, and black holes

Astrophysical accretion is a universal process in objects from proto-stars to supermassive black holes. The central engines of disc-accreting stellar-mass black holes appear to be scaled down versions of the supermassive black holes that power active galactic nuclei. However, if the physics of accretion is universal, it should also be possible to extend this scaling to other types of accreting systems, irrespective of accretor mass, size, or type. We examine new observations, obtained with Kepler/K2 and ULTRACAM, regarding accreting white dwarfs and young stellar objects. Every object in the sample displays the same linear correlation between the brightness of the source and its amplitude of variability (rms-flux relation) and obeys the same quantitative scaling relation as stellar-mass black holes and active galactic nuclei. We also show that the most important parameter in this scaling relation is the physical size of the accreting object. This establishes the universality of accretion physics from proto-stars still in the star-forming process to the supermassive black holes at the centers of galaxies.
One-Dimensional, Ocean Surface Layer Modeling: A Problem and a Solution

Abstract The first part of this paper is generic; it demonstrates a problem associated with one-dimensional, ocean surface layer model comparisons with ocean observations. Unlike three-dimensional simulations or the real ocean, kinetic energy can inexorably build up in one-dimensional simulations, which artificially enhances mixing. Adding a sink term to the momentum equations counteracts this behavior. The sink term is a surrogate for energy divergence available to three-dimensional models but not to one-dimensional models. The remainder of the paper deals with the Mellor–Yamada boundary layer model. There exists prior evidence that the model’s summertime surface temperatures are too warm due to overly shallow mixed layer depths. If one adds a sink term to approximate three-dimensional model behavior, the warming problem is exacerbated, creating added incentive to seek an appropriate model change. Guided by laboratory data, a Richardson-number-dependent dissipation is introduced and this simple modificat.
Enhancing intraday trading performance of Neural Network using dynamic volatility clustering fuzzy filter

We extend Neural Network (NN) trading models with an innovative and efficient volatility filter based on fuzzy c-means clustering algorithm, where the choice for the number of clusters, a frequent problem with cluster analysis, is selected by optimizing a global risk-return performance measure. Our algorithm automatically extracts fuzzy rules from past trades by taking into account the predicted return size and intraday time varying realized volatility, the latter used as a proxy for uncertainty. The model identifies unique intraday scenarios and subsequently creates a dynamic and visually apprehensible risk-return search space to control algorithmic trading decisions. Our results show that this method can be successfully applied to support high-frequency intraday trading strategies, outperforming both standard NN and buy-and-hold models.
International Journal of Advanced Robotic Systems Rgb-d, Laser and Thermal Sensor Fusion for People following in a Mobile Robot Regular Paper

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Detecting and tracking people is a key capability for robots that operate in populated environments. In this paper, we used a multiple sensor fusion approach that combines three kinds of sensors in order to detect people using RGB-D vision, lasers and a thermal sensor mounted on a mobile platform. The Kinect sensor offers a rich data set at a significantly low cost, however, there are some limitations to its use in a mobile platform, mainly that the Kinect algorithms for people detection rely on images captured by a static camera. To cope with these limitations, this work is based on the combination of the Kinect and a Hokuyo laser and a thermopile array sensor. A real-time particle filter system merges the information provided by the sensors and calculates the position of the target, using probabilistic leg and thermal patterns, image features and optical flow to this end. Experimental results carried out with a mobile platform in a Science museum have shown that the combination of different sensory cues increases the reliability of the people following system.
Supersymmetric sigma models and 't Hooft instantons

Witten's linear sigma model for ADHM instantons possesses a natural (0, 4) supersymmetry. We study generalizations of the infrared limit of the model that are invariant under (4, 4) supersymmetry. In the case of four spacetime dimensions a background with a conformally flat metric and torsion is required. The geometry is specified by a single real scalar function satisfying Laplace's equation. It gives rise to 't Hooft instantons for the gauge group SU(2), instead of the general ADHM instantons for an SO(n) gauge group in the case (0, 4).