Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Practical Facial Feature Detection

Localizing facial features is a critical component in many computer vision applications such as expression recognition, face recognition, face tracking, animation, and red-eye correction. Practical applications require detectors that operate reliably under a wide range of conditions, including variations in illumination, pose, ethnicity, gender and age. One challenge for the development of such detectors is the inherent trade-off between robustness and precision. Robust detectors tend to provide poor localization and detectors sensitive to small changes in local structure, which are needed for precise localization, generate a large number of false alarms. Here we present an approach to this trade-off based on context dependent inference. First, robust detectors are used to detect contexts in which target features occur, then precise detectors are trained to localize the features given the detected context. This paper describes the approach and presents a thorough empirical examination of the parameters needed to achieve practical levels of performance, including the size of the training database, size of the detector's receptive fields and methods for information integration. The approach operates in real time and achieves, to our knowledge, the most accurate localization performance to date.
Audio emotion recognition by perceptual features

A 9-D perceptual feature set has been used for audio emotion recognition. Performance tests have been performed on well known EMO-DB and VAM databases and the results are reported for different classifiers. Support Vector Machines, Gaussian Mixture Models and Learning Vector Quantization have been used in classification. Audio emotion recognition performance achieved by the perceptual visual features are compared to openEar and GerDa which are cited as state of the art audio emotion recognition systems. It is shown that the 9-D perceptual feature vectors are highly discriminative in continuous emotional space. It is concluded that the learning Vector Quantization increases the performance for natural records, while the Support Vector Machines provide the highest recognition rate for the acted records.
Optimising Up*/Down* Routing By Minimal Paths

Networks of workstations (NOWs) often uses irregular interconnection patterns. Up*/down* is the most popular routing scheme currently used in NOWs with irregular topologies. One of the main problem with up*/down* routing is difficult to route all packets through minimal paths. Several solutions have been proposed in order to improve the up*/down* routing scheme. In this paper we discussed those solutions which provide minimal paths to route most the packets to improve the performance of the up*/down* routing.
Complexity − Effective Design Workshop on

We consider processor core complexity and its implications for the power-performance efficiency of SMT and CMP architectures, exploring fundamental trade-offs between the efficiency of multi-core architectures and the complexity of their cores from a power-performance perspective. Taking pipeline depth and width as proxies for core complexity, we conduct power-performance simulations of several SMT and CMP architectures employing cores of varying complexity. Our analyses identify efficient pipeline dimensions and outline the implications of using a powerperformance efficiency metric for core complexity. Collectively, our results suggest SMT architectures enable efficient increases in pipeline dimensions and core complexity. Furthermore, reducing pipeline dimensions in CMP cores is inefficient, assuming ideal power-performance scaling from voltage/frequency scaling and circuit re-tuning. Given these conclusions, we formulate guidelines for complexity effective design.
An estimate of the cost of acute health effects from food-and water-borne marine pathogens and toxins in the USA

Large and growing segments of the United States population consume seafood or engage in marine recreation. These activities provide significant benefits but also bring risk of exposure to marineborne illness. To manage these risks, it is important to understand the incidence and cost of marineborne disease. We review the literature and surveillance/monitoring data to determine the annual incidence of disease and health consequences due to marine-borne pathogens from seafood consumption and beach recreation in the USA. Using this data, we employ a cost-of-illness model to estimate economic impacts. Our results suggest that health consequences due to marine-borne pathogens in the USA have annual costs on the order of US$900 million. This includes US$350 million due to pathogens and marine toxins specifically identified as causing food-borne disease, an estimated US$300 million due to seafood-borne disease with unknown etiology, US$30 million from direct exposure to the Vibrio species, and US$300 million due to gastrointestinal illness from beach recreation. Although there is considerable uncertainty about the degree of underreporting of certain pathogen-specific acute marine-related illnesses, the conservative assumptions we have used in constructing our estimate suggest that it should be considered a lower bound on true costs. doi: 10.2166/wh.2011. 157 Erin P. Ralston (corresponding author) Hauke Kite-Powell Andrew Beet Marine Policy Center, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA E-mail: eralston@whoi.edu
An empirical evaluation of zero resource acoustic unit discovery

Acoustic unit discovery (AUD) is a process of automatically identifying a categorical acoustic unit inventory from speech and producing corresponding acoustic unit tokenizations. AUD provides an important avenue for unsupervised acoustic model training in a zero resource setting where expert-provided linguistic knowledge and transcribed speech are unavailable. Therefore, to further facilitate zero-resource AUD process, in this paper, we demonstrate acoustic feature representations can be significantly improved by (i) performing linear discriminant analysis (LDA) in an unsupervised self-trained fashion, and (ii) leveraging resources of other languages through building a multilingual bottleneck (BN) feature extractor to give effective cross-lingual generalization. Moreover, we perform comprehensive evaluations of AUD efficacy on multiple downstream speech applications, and their correlated performance suggests that AUD evaluations are feasible using different alternative language resources when only a subset of these evaluation resources can be available in typical zero resource applications.
Behaviors of concrete filled square steel tubes confined by carbon fiber sheets (CFS) under compression and cyclic loads

The existing CFT columns present the deterioration in confining effect after the yield of steel tube, local buckling and the deterioration in load capacity. If lateral load such as earthquake load is applied to CFT columns, strong shearing force and moment are generated at the lower part of the columns and local buckling appears at the column. In this study, axial compression test and beam-column test were conducted for existing CFT square column specimens and those reinforced with carbon fiber sheets (CFS). The variables for axial compression test were width-thickness ratio and the number of CFS layers and those for beamcolumn test were concrete strength and the number of CFS layers. The results of the compression test showed that local buckling was delayed and maximum load capacity improved slightly as the number of layers increased. The specimens` ductility capacity improved due to the additional confinement by carbon fiber sheets which delayed local buckling. In the beam-column test, maximum load capacity improved slightly as the number of CFS layers increased. However, ductility capacity improved greatly as the increased number of CFS layers delayed the local buckling at the lower part of the columns. It was observed that the CFT structure reinforced with carbon fiber sheets controlled the local buckling at columns and thus improved seismic performance. Consequently, it was deduced that the confinement of CFT columns by carbon fiber sheets suggested in this study would be widely used for reinforcing CFT columns.
Effects of compliant ankles on bipedal locomotion

The influence of ankle compliance on bipedal robot locomotion is investigated in this paper. The focus is on reduction of energy consumption. The concept of hybrid zero dynamics is adapted to design walking gaits with three phases: underactuated heel roll, full actuation and underactuated toe roll. Ankle springs work in parallel with the ankle actuators. Stiffness and offset of the linear torsional springs at the ankle and gait parameters are optimized simultaneously. It is shown that simultaneous optimization of spring properties and gait is superior to optimizing the spring after the gait. Optimal spring stiffness and offset lead to a major reduction in energy consumption. Furthermore, a more human-like gait is observed for simultaneous optimization of gait and spring parameters compared to gait optimization with zero stiffness.
Unscented kalman filtering of line spectral frequencies

We propose a new method for estimating Line Spectral Frequency (LSF) trajectories that uses unscented Kalman filtering (UKF). This method is based upon an iterative Expectation Maximisation (EM) approach in which LSF estimates are generated during a forward pass and then smoothed during a backward pass. The EM approach also provides re-estimated Kalman filter parameters for further forward-backward passes that improve estimation. This approach exploits the non-independence of neighbouring spectra. We estimate LSFs as they have good interpolation and quantization properties. This allows us to estimate LSF trajectories that are guaranteed to result in stable filters. We analyse noisy synthetic speech using this technique. The results compare favourably with other methods.
Egocentric Information Abstraction for Heterogeneous Social Networks

Social network is a powerful data structure that allows the depiction of relationship information between entities. However, real-world social networks are sometimes too complex for human to pursue further analysis. In this work, an unsupervised mechanism is proposed for egocentric information abstraction in heterogeneous social networks. To achieve this goal, we propose a vector space representation for heterogeneous social networks to identify linear combination of relations as features and compute statistical dependencies as feature values. Then we design several abstraction criteria to distill representative and important information to construct the abstracted graphs for visualization. The evaluations conducted on a real world movie dataset and an artificial crime dataset demonstrate that the abstractions can indeed retain important information and facilitate more accurate and efficient human analysis.
Fastest Mixing Markov Chain on a Path

We consider the problem of assigning transition probabilities to the edges of a path in such a way that the resulting Markov chain or random walk mixes as rapidly as possible. In this note we prove that fastest mixing is obtained when each edge has a transition probability of 1/2. Although this result is intuitive (it was conjectured in [6]) and can be found numerically using convex optimization methods [2], [3], we give a self-contained proof here. Consider a path with n (≥ 2) nodes, labeled 1, 2, . , n, with n − 1 edges connecting pairs of adjacent nodes and with a loop at each node, as shown in Figure 1. We consider a Markov chain (or random walk) on this path, with transition probability from node i to node j denoted Pi j . The requirement that transitions can occur only along an edge or loop of the path is equivalent to Pi j = 0 when |i − j | > 1 (i.e., P is a tridiagonal matrix). Since the Pi j are transition probabilities, we have Pi j ≥ 0 and ∑ j Pi j = 1 (i.e., P is a stochastic matrix). This can be expressed as P1 = 1, where 1 is the vector with all components one. We consider symmetric transition probabilities, meaning those that satisfy Pi j = Pji . Thus, P is a symmetric, (doubly) stochastic, tridiagonal matrix. Since P1 = 1, we have (1/n)T P = 1T /n, which means that the uniform distribution, given by 1T /n, is stationary.
IRES: An integrated software and hardware interface framework for reconfigurable embedded system

Hardware/software co-design is an interesting topic for most embedded system architects. However, designers find integrating hardware and software communications interface challenging. A framework for integrating the software and hardware communication interface for computing in reconfigurable embedded systems, called IRES, is proposed. The framework supports reconfigurable computing architectures, based on traditional central processing unit and the reconfigurable field programmable gate array, and composed of the integration linker, the boot loader, small task-oriented operating objects and the hardware management unit. The integration linker enables the IRES to link hardware net-list files and tasks into one execution file, called the executor, constructed with the boot loader, the task-oriented operating kernel, the application tasks and the accelerating hardware functions. Task and hardware functions are segregated by program segment prefixes, designed to record interaction information of hardware and software resources. When the executor operates on the target-embedded environment, the implicit hardwire-call will be supported to invoke hardware functions in the task codes. The IRES successfully implements in the realised hardware platform, and this work verifies communication effectiveness between hardware and software through video compression applications.
Which resemblance is useful to predict phrase boundary rise labels for Japanese expressive text-to-speech synthesis, numerically-expressed stylistic or distribution-based semantic?

To establish Expressive Text-to-speech synthesis, current research studies both the processing of input text and the rendering of natural expressive speech. Focusing on the former as a front-end task in the production of synthetic speech, this paper investigates a novel feature for predicting phrase boundary tone labels which transcribe local fundamental frequency (F0) changes frequently appearing at phrase end positions in expressive speech. To this end, we examined a kind of distribution-based semantic features consisting of i) word surface strings, ii) their part-of-speech tags taken from a phrase and iii) the pause existence/non-existence at the ﬁnal position of the phrase, which are different from conventional numerically-expressed stylistic features such as positions and lengths and distances of the phrase. Through experiments on Japanese expressive speech such as conversational speech and advertisement speech, we conﬁrmed that the proposed features attain performance equal to or better than conventional features. These results suggest that the distribution-based semantic features might be useful to predict phrase boundary rise labels for conversational speech and might be useful equal to conventional numerically-expressed stylistic feature for advertisement speech.
Multi-VPN Optimization for Scalable Routing via Relaying

Enterprise networks are increasingly adopting Layer-3 multiprotocol label switching (MPLS) virtual private network (VPN) technology to connect geographically disparate locations. The any-to-any direct connectivity model of this technology is causing routing tables in the service provider's routers to grow very large. The concept of relaying was proposed earlier to separately minimize the routing table memory footprint of individual VPNs by selecting a small number of hub routers to maintain complete reachability information for each VPN and enabling nonhub spoke routers with reduced routing tables to reach others by routing traffic via a hub. A large service provider network typically hosts thousands of different VPNs. In this paper, we generalize relaying to the multi-VPN environment and consider new constraints on resources shared across VPNs, such as router uplink bandwidth and memory. The hub selection problem involves complex tradeoffs along multiple dimensions including these shared resources and the additional distance traversed by traffic. We formulate the hub selection as a constraint optimization problem and develop an algorithm with provable guarantees to approximate this NP-complete problem. Evaluations using traces and configurations from a large provider indicate that the resulting relaying solution reduces the total router memory requirement by 85% while smoothing out the utilization on each router and requiring only a small increase in the end-to-end path for the relayed traffic.
Discriminant Analysis: A Case Study of a War Data Set

Mathematical models are applied in war theories as these of Richarson and Lanchester. In this paper discriminant analysis is used for the most famous battles of the Second World War. The linear function of Fisher classifies the opposite sides in two groups (the one of the winners and the one of the losers). That function can be used in order to predict the winner of a battle and to evaluate the difficulty of a win. Mathematics Subject Classification : 62-07
Incorporating gene networks into statistical tests for genomic data via a spatially correlated mixture model

MOTIVATION It is a common task in genomic studies to identify a subset of the genes satisfying certain conditions, such as differentially expressed genes or regulatory target genes of a transcription factor (TF). This can be formulated as a statistical hypothesis testing problem. Most existing approaches treat the genes as having an identical and independent distribution a priori, testing each gene independently or testing some subsets of the genes one by one. On the other hand, it is known that the genes work coordinately as dictated by gene networks. Treating genes equally and independently ignores the important information contained in gene networks, leading to inefficient analysis and reduced power. RESULTS We propose incorporating gene network information into statistical analysis of genomic data. Specifically, rather than treating the genes equally and independently a priori in a standard mixture model, we assume that gene-specific prior probabilities are correlated as induced by a gene network: while the genes are allowed to have different prior probabilities, those neighboring ones in the network have similar prior probabilities, reflecting their shared biological functions. We applied the two approaches to a real ChIP-chip dataset (and simulated data) to identify the transcriptional target genes of TF GCN4. The new method was found to be more powerful in discovering the target genes.
Characterization of Polyurethane Coated Railroad Ballast Behavior

This paper focuses on the applicability and potential benefits of polyurethane coating technology to railroad ballast studied at the University of Illinois in a controlled laboratory environment. The effectiveness of two chemically different elastomer polyurethanes and polyurethane with catalyst were evaluated for their ability to reduce aggregate breakage and resulting ballast fouling. AREMA No.4 aggregate, along with the urethane coated particles, were subjected to realistic field loading conditions in a large shear box test apparatus used for strength testing of ballast at full gradation. The urethane coated ballast was allowed to set for 1, 3, 7, and 14 days prior to subjecting the samples up to 10 shear passes. The polyurethane-catalyst coated ballast was allowed to set for 1, 3, 6, 24, and 72 hours prior to subjecting the samples to a single direct shear pass. Shear and normal stress data were gathered during testing; and the fines generated by all powdering test samples were collected and analyzed. Results show a major increase in the shear strength gained with one of the polyurethane coatings, as well as a modest increase using the polyurethane-catalyst applicable to field maintenance applications. A decrease in the breakdown of the coated ballast, and a decrease in particle reorientation which could lead to a reduction in ballast settlement were also observed. The two polyurethanes tested, 63020R and 63004R, were designed with specific goals in mind. 63020R was designed to achieve a higher strength while 63004R was designed to have a higher displacement before failure.
Recent advances in pediatric gastroenterology, hepatology and nutrition

Pediatric gastroenterology, hepatology and nutrition are rapidly evolving, exciting and diverse disciplines. Because the field is so expansive, this commentary highlights important trends, rather than narrowly focusing on specific advances. Examples of advances in the highest impact and rapidly moving areas of pediatric gastroenterology are reviewed, including the intestinal microbiome, biomedical genomics, the biology of unique gastrointestinal cell types, and microRNAs (miRNAs).
Statistics of Wavelength Division Multiplexed Channels in Fiber-Optical Parametric Amplification

The amplification of wavelength division multiplexed (WDM) data in fiber-optical parametric amplifiers give rise to cross-gain saturation and four-wave mixing crosstalk. This crosstalk affects the data quality, especially at higher input powers. The statistics in this regime are nontrivial to obtain and we present, for the first time, a model based on a combination of theory and numerics that gives accurate statistics at a highly reduced computational cost. This model is obtained from an exact solution of WDM data being amplified in the strictly nonlinear regime which is derived in this paper. Using this model, predictions of the bit-error rate (BER) can be obtained even at very low rates impossible to reach by numerical methods alone. We show that there exists no trivial relationship between the BER and the commonly used quality measure, the Q-value. We also study how different amplifier parameters affect the statistics and suggest design rules to reduce channel crosstalk.
Strategies for Improving Survival After In-Hospital Cardiac Arrest in the United States: 2013 Consensus Recommendations A Consensus Statement From the American Heart Association

The goal of this statement is to develop consensus recommendations aimed at measuring and optimizing outcomes after in-hospital cardiac arrest (IHCA). For the purposes of this statement, IHCA is defined as a cardiac arrest that occurs in a hospital (whether the patient is admitted or not) and for which resuscitation is attempted with chest compressions, defibrillation, or both. Members of the writing group were selected for their expertise in cardiac resuscitation and post–cardiac arrest care. Monthly telephone conferences and “webinars” over a 10-month period were used to define the scope of the statement and to assign writing teams for each section. The first draft of each section was discussed and sent to the chair to be compiled into a single document. Revised versions were then sent to all writing group members until consensus was achieved. The final draft underwent 3 sets of independent peer review before publication. The American Heart Association (AHA) is committed to the highest ethical standards. The AHA believes that having experts who have a relationship with industry or other relevant relationships on writing groups can strengthen the writing group effort when these relationships are transparent and managed. The AHA conflict of interest policy requires each member to declare relevant and current conflicts of interest. The chair may not have any relationship with industry relevant to the topic. The majority of writing group members (defined as>50% +1) must be free of relevant relationships with industry. Every writing group member agrees to maintain his or her current status with respect to relationships with industry throughout the development of the manuscript to publication. In addition, each member formally declares his or her conflict of interest or relationship with industry at the time of publication. All members of this writing group were compliant with this policy (“Writing Group Disclosures”). IHCA …