Miracle-dz/UniFAR-FTUs huggingface dataset:
A blind channel identification-based two-stage approach to separation and dereverberation of speech signals in a reverberant environment

Blind separation of independent speech sources from their convolutive mixtures in a reverberant acoustic environment is a difficult problem and the state-of-the-art blind source separation techniques are still unsatisfactory. The challenge lies in the coexistence of spatial interference from competing sources and temporal echoes due to room reverberation in the observed mixtures. Focusing only on optimizing the signal-to-interference ratio is inadequate for most if not all speech processing systems. In this paper, we deduce that spatial interference and temporal echoes can be separated and an M/spl times/N MIMO system will be converted into M SIMO systems that are free of spatial interference. Furthermore we show that the channel matrices of these SIMO systems are irreducible if the channels from the same source in the MIMO system do not share common zeros. Thereafter we can apply the Bezout theorem to remove reverberation in those SIMO systems. Such a two-stage procedure leads to a novel sequential source separation and speech dereverberation algorithm based on blind multichannel identification. Simulations with measurements obtained in the varechoic chamber at Bell Labs demonstrate the success and robustness of the proposed algorithm in highly reverberant acoustic environments.
Business Rules Separation and Reuse Using MDA, OWL and AspectJ

Two important challenges for MDA designers are to make business rules independent of the specific platform model and to ensure the resulting implementation does not violate the specified properties in the application domain. In this paper we present an approach that allows developers to both describe and corroborate domain properties at run time. In our approach, an ontology specifies domain properties and translates it to aspect-oriented code. The implementation code could be automatically merged. As a result, we will be able to perform approval tests at runtime and to create business rules reused in other MDA specific models. This novel approach shall be evaluates in a toolkit for reengineering an industrial furnace management application.
Simplification of scattered point cloud based on feature extraction

Simplification of scattered point cloud is one of the key preprocessing technologies in reverse engineering. Most simplification algorithms always lose geometric feature excessively in the process. On the basis of feature extraction, a new algorithm is proposed for the simplification of scattered point cloud with unit normal vectors. First, points in point cloud are distributed into uniform cubes. Next, bounding spheres are constructed with their centers at each point; accordingly K-nearest neighbors are searched in the relevant sphere. Later, a specified function is defined to measure the curvature of each point so that feature points can be extracted. Finally, feature points and non-feature points are simplified according to the radius of bounding sphere and the threshold of normal vectors' inner product. The experiments show that the proposed algorithm has the advantages of fast speed and high reservation of the geometric feature of point cloud.
The Hot Intergalactic Medium-Galaxy Connection: Two Strong O VI Absorbers in the Sight Line toward PG 1211+143

We present Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) and Far Ultraviolet Spectroscopic Explorer (FUSE) spectra of the QSO PG 1211+143 (zem = 0.081) and a galaxy survey of the surrounding field. This sight line shows two strong intergalactic absorption systems at cz ≃ 15,300 and 19,300 km s-1. This sight line addresses the nature and origin of the O VI absorbers and their connection to galaxies. We explore the relationship of these absorbers to the nearby galaxies and compare them to other O VI-bearing absorbers in diverse environments. At 15,300 km s-1, we find four distinct H I components and associated C II, C III, C IV, Si II, Si III, Si IV, N V, and O VI, lying near a spiral-dominated galaxy group with a bright member galaxy 137 h kpc from the sight line. The observed ions of C, Si, and N are likely to be photoionized, but the O VI is more consistent with collisional ionization. The ion ratios in this absorber resemble the highly ionized Galactic high-velocity clouds (HVCs); it may also trace the hot intragroup medium gas or the unbound wind of an undiscovered dwarf galaxy. At 19,300 km s-1, we find five H I components and associated C III, Si III, and collisionally ionized O VI lying 146 h kpc from an isolated galaxy. The properties of the O VI-bearing gas are consistent with an origin in strong shocks between low-metallicity gas (≥2%-6% solar) and one or more of the warm photoionized components. It is likely that these absorbers are related to the nearby galaxies, perhaps by outflows or gas stripped from unseen satellite galaxies by interactions. However, we cannot reject completely the hypothesis that they reside in the same large-scale structure in which the galaxies are embedded but are otherwise not directly related.
Recent Advances in Creep Modelling of the Nickel Base Superalloy, Alloy 720Li

Recent work in the creep field has indicated that the traditional methodologies involving power law equations are not sufficient to describe wide ranging creep behaviour. More recent approaches such as the Wilshire equations however, have shown promise in a wide range of materials, particularly in extrapolation of short term results to long term predictions. In the aerospace industry however, long term creep behaviour is not critical and more focus is required on the prediction of times to specific creep strains. The current paper illustrates the capability of the Wilshire equations to recreate full creep curves in a modern nickel superalloy. Furthermore, a finite-element model based on this method has been shown to accurately predict stress relaxation behaviour allowing more accurate component lifing.
Author's Personal Copy Behavioural Brain Research the Effects of Working Memory Resource Depletion and Training on Sensorimotor Adaptation

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t We have recently demonstrated that visuospatial working memory performance predicts the rate of motor skill learning, particularly during the early phase of visuomotor adaptation. Here, we follow up these correlational findings with direct manipulations of working memory resources to determine the impact on visuomotor adaptation, a form of motor learning. We conducted two separate experiments. In the first one, we used a resource depletion strategy to investigate whether the rate of early visuomotor adaptation would be negatively affected by fatigue of spatial working memory resources. In the second study, we employed a dual n-back task training paradigm that has been shown to result in transfer effects [1] over five weeks to determine whether training-related improvements would boost the rate of early visuomotor adaptation. The depletion of spatial working memory resources negatively affected the rate of early visuomotor adaptation. However, enhancing working memory capacity via training did not lead to improved rates of visuomotor adaptation, suggesting that working memory capacity may not be the factor limiting maximal rate of visuomotor adaptation in young adults. These findings are discussed from a resource limitation/capacity framework with respect to current views of motor learning.
Joint complex diversity coding and channel coding over space, time and frequency

This study provides a general diversity analysis for joint complex diversity coding (CDC) and channel coding-based space-time-frequency codeing is provided. The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This study provides and proves a sufficient condition of full diversity construction with joint three-dimensional CDC and channel coding, bit-interleaved coded complex diversity coding and symbol-interleaved coded complex diversity coding. Both non-iterative and iterative detections of joint channel code and CDC transmission are investigated. The proposed minimum mean-square error-based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity.
Exploring Rated Datasets with Rating Maps

Online rated datasets have become a source for large-scale population studies for analysts and a means for end-users to achieve routine tasks such as finding a book club. Existing systems however only provide limited insights into the opinions of different segments of the rater population. In this paper, we develop a framework for finding and exploring population segments and their opinions. We propose rating maps, a collection of (population segment, rating distribution) pairs, where a segment, e.g., {18-29 year old males in CA} has a rating distribution in the form of a histogram that aggregates its ratings for a set of items (e.g., movies starring Russel Crowe). We formalize the problem of building rating maps dynamically given desired input distributions. Our problem raises two challenges: (i) the choice of an appropriate measure for comparing rating distributions, and (ii) the design of efficient algorithms to find segments. We show that the Earth Mover's Distance (EMD) is well-adapted to comparing rating distributions and prove that finding segments whose rating distribution is close to input ones is NP-complete. We propose an efficient algorithm for building Partition Decision Trees and heuristics for combining the resulting partitions to further improve their quality. Our experiments on real and synthetic datasets validate the utility of rating maps for both analysts and end-users.
Hyperspectral endmember class extraction using clustering and validity indexes

A set of spectral endmembers can be used to model the spectral variability of an endmember in a hyperspectral image. Clustering analysis is used to group similar spectral endmember signatures into endmember classes. The resulting clusters are used to model the endmember variability in the image. In this paper, hierarchical, partitional and spectral clustering techniques are compared for endmember class extraction. Experimental results with test data and a full hyperspectral image are presented. Hierarchical clustering with complete and average linkage outperforms partitional and spectral clustering results. Validity indexes are compared for the estimation of the number of endmember classes. The Davies and Bouldin index, and the Kim index presented the best results for the estimation of the number of spectral endmember classes in the experiments presented.
Gifted from the “Inside out”

In this pilot study, 24 gifted, elementary students in second to fifth grade enrolled in a large, diverse, urban public school were introduced to 10 mindfulness-based techniques that the students practiced in school. The students practiced the techniques for 10 weeks once per week for 30 minutes in the school’s media center under the guidance of the researchers and certified mindfulness instructors. Using qualitative data (interviews and observations), quantitative percentages of qualitative findings are reported. Results include increased enjoyment, calmness, heightened awareness, creativity, and minor discomfort and a gain in mindfulness competency. The need for further research and plans to proceed are discussed.
Meditative Movement Therapies and Health-Related Quality-of-Life in Adults: A Systematic Review of Meta-Analyses

Poor health-related quality-of-life (HRQOL) is a significant public health issue while the use of meditative movement therapies has been increasing. The purpose of this investigation was to carry out a systematic review of previous meta-analyses that examined the effects of meditative movement therapies (yoga, tai chi and qigong) on HRQOL in adults. Previous meta-analyses of randomized controlled trials published up through February, 2014 were included by searching nine electronic databases and cross-referencing. Dual-selection and data abstraction occurred. The Assessment of Multiple Systematic Reviews Instrument (AMSTAR) was used to assess methodological quality. Standardized mean differences that were pooled using random-effects models were included. In addition, 95% prediction intervals were calculated as well as the number needed-to-treat and percentile improvements. Of the 510 citations screened, 10 meta-analyses representing a median of 3 standardized mean differences in 82 to 528 participants (median = 270) with breast cancer, schizophrenia, low back pain, heart failure and diabetes, were included. Median methodological quality was 70%. Median length, frequency and duration of the meditative movement therapies were 12 weeks, 3 times per week, for 71 minutes per session. The majority of results (78.9%) favored statistically significant improvements (non-overlapping 95% confidence intervals) in HRQOL, with standardized mean differences ranging from 0.18 to 2.28. More than half of the results yielded statistically significant heterogeneity (Q ≤ 0.10) and large or very large inconsistency (I2 ≥ 50%). All 95% prediction intervals included zero. The number-needed-to-treat ranged from 2 to 10 while percentile improvements ranged from 9.9 to 48.9. The results of this study suggest that meditative movement therapies may improve HRQOL in adults with selected conditions. However, a need exists for a large, more inclusive meta-analysis (PROSPERO Registration #CRD42014014576).
k-NN graph construction based on markov random walk

k-nearest-neighbors (k-NN) graphs are widely used in image retrieval, machine learning and other research fields. Selecting its neighbors is a core for constructing the k-NN graph. However, existing selection methods usually encounter some unreliable neighbors in the k-NN graph. This paper proposes an efficient Markov random walk (MRW) based method for selecting more reliable neighbors for constructing the k-NN graph. The MRW model is defined on the raw k-NN graph. The k-NN of a sample is determined by the probability of the MRW. Since the high order transition probabilities reflects complex relationships among data, the neighbors in the graph obtained by our proposed method are more reliable than those of existing methods. Also, our proposed method can improve the performances of some applications with k-NN graph. Experiments are performed on the synthetic and real datasets for comparison. The results show that the graph obtained by our proposed method better correspond to the structure of the data compared to those of the state-of-the-art methods.
Improved reconstruction of quantized CT scans via genetic algorithms

Cost-effective storage and timely transmission of medical images are very difficult technical challenges. Compression and reconstruction techniques must guarantee no significant loss of clinical information. This paper presents a convenient technique for improving the quality of reconstructed computed tomography (CT) images previously subjected to specified levels of lossy compression. Our genetic algorithm (GA) evolves novel transforms that consistently outperform state-of-the-art wavelet-based schemes supported by the Digital Imaging and Communication in Medicine (DICOM) standard.
Word-level Dependency-structure Annotation to Corpus of Spontaneous Japanese and its Application

In Japanese, the syntactic structure of a sentence is generally represented by the relationship between phrasal units, bunsetsus in Japanese, based on a dependency grammar. In many cases, the syntactic structure of a bunsetsu is not considered in syntactic structure annotation. This paper gives the criteria and definitions of dependency relationships between words in a bunsetsu and their applications. The target corpus for the word-level dependency annotation is a large spontaneous Japanese-speech corpus, the Corpus of Spontaneous Japanese (CSJ). One application of word-level dependency relationships is to find basic units for constructing accent phrases.
Fault localization based on information flow coverage

Failures triggered by hard to debug defects usually involve complex interactions between many program elements. This paper hypothesizes that information flows present a good model for such interactions and presents a new fault localization technique based on information flow coverage. Using a test suite, the technique ranks the statements in a program in terms of their likelihood of being faulty by comparing the information flows induced by the failing runs with the ones induced by the passing runs. The ranking of the statements associated with a given flow is primarily determined by contrasting the percentage of failing runs to the percentage of passing runs that induced it. Generally, a higher percentage of failing runs implies a higher rank. To show its potential, the technique was applied to several open‐source Java programs and was compared, with respect to its fault localization effectiveness, with three other coverage techniques that use similar style metrics that are defined for statements, branches, and def–use pairs, respectively. The results revealed that information flow, branch, and def–use coverage performed consistently better than statement coverage. In addition, in a considerable number of cases information flow coverage performed better than branch and def–use coverage. Specifically, it was always safer but not always more precise. Copyright © 2009 John Wiley & Sons, Ltd.
Improving Performance of Movie Recommendation in Collaborative Filtering Systems

Collaborative filtering has been most widely used in commercial sites to recommend items based on the history of user preferences for items. The idea behind this method is to find similar users whose ratings for items are incorporated to make recommendation. Hence, similarity calculation is most critical in recommendation performance. For movie recommendation, this paper enhances performance of previous similarity measures by incorporating information on genre difference as well as the number of movies co-rated by two users. Extensive experiment results are provided to demonstrate far enhanced performance improvement for several popular classic CF methods.
On distributed codes with noisy relays

In this paper, we address the design of distributed coding schemes for the 3-node relay channel with half-duplex constraint. We first discuss the general problem of optimally re-encoding noisy data at the relay and summarize recently proposed approximations. Based on an analysis of the extrinsic information transfer characteristics of the component codes we investigate the potential of ldquoweakrdquo turbo or LDPC codes which are employed by the source node in order to increase the reliability of the relay when decoding is not possible. The results show that we can indeed gain from the proposed code design.
The Interpretation of the Emission Spectra of the Seyfert 2 Galaxy NGC 7130: Determination of the Active Galactic Nucleus and Starburst Contributions

Detailed modeling of the different regions of NGC 7130 is presented, accounting for its composite nature of an active galactic nucleus (AGN) and a starburst galaxy. Shock waves, created by stellar winds from hot massive stars and by supernova ejecta, are evident in the continuum and line spectra emitted from the clouds. Therefore, the SUMA code, which accounts consistently for photoionization and shocks, is adopted in model calculation. The results show that the nuclear region is dominated by gas ionized by a power-law radiation flux from the active center (AC). High-velocity (Vs = 1000 km s-1) clouds, which account for the broad FWHM component of the line profile, are found close to the AC and are characterized by a high dust-to-gas ratio (>10-12, while the dust-to-gas ratio is about 10-14 throughout the galaxy). Massive stars with temperatures of (5-7) × 104 K photoionize and heat the gas in the outer regions, and old star population (T* = 3000 K) background radiation contributes to the fit of the continuum in the optical-near-IR range. The AGN-starburst connection is discussed on the basis of model results, considering, particularly, the distribution of densities and velocities throughout the galaxy.
A greedy power-aware routing algorithm for software-defined networks

We consider the problem of minimizing the routing power consumption in software-defined networks. The network is composed of software-defined networking (SDN) nodes and a central controller where routing decisions are centralized. More specifically, the central controller minimizes the routing power consumption by routing flows on the minimum number of active links with the lowest discrete link rates. Thus, it maximizes the number of inactive links and the level of link rates, which reflects significant saving in power consumption. This problem is a mixed-integer programming problem and known to be NP-hard. Therefore, we propose a low-complexity greedy heuristic to minimize the number of active links and link rates by rerouting flows and aggregating them on common links. Numerical results show that the proposed algorithm achieves 17.18% to 32.97% power saving in real network topologies relative to a base shortest path algorithm. The savings are achieved with minimal increase in average path length that is less than 0.2 hops.
Autocorrelation analysis of spatial features for mobile video services

The growing deployment of mobile video applications is calling for new methods to measure quality as perceived by humans. The suitable quality metrics may explore spatial and temporal video features that quantify the presence of related artifacts in an examined mobile video service. Considering a video as a sequence of images, computation of spatial features for each involved image would pose significant strain on system resources such as battery power and potentially induce large computational load in the mobile terminal. In this paper, we therefore examine the progression of spatial features in mobile videos over time using an autocorrelation approach. This enables us to reveal the duration over which spatial feature values of a mobile video may be considered as constant. In analogy to the characterization of mobile radio channels, we refer to this duration as the coherence time of an examined spatial feature for a given video. The provided numerical results illustrate that large reductions in the frequency of computing spatial features in mobile videos may be obtained. This in turn reduces the consumption of resources in the mobile terminal.
Interver: Drilling into Categorical-Numerical Relationships

Data analytics is increasingly performed by non-expert analysts (e.g., casual business users). In this context, future analytics tools need easy-to-use techniques to reveal relations between columns of data in a spreadsheet or table. For example, a market analyst, may want to find if industry categories and funding amounts are related: i.e., if some industries receive amounts within distinctive intervals. Traditional filtering and script-based querying poorly support non-expert users in such explorations because they require iterative parameter adjusting and query writing until a meaningful result is found. In this paper, we focus on supporting the analysis of relationships between categorical and numerical columns. We present a novel visualization, Interver, which dynamically reveals insights as the user selects an interval within the relationship. With a concrete scenario, specific analysis tasks, and an informal evaluation, we show how Interver can help non-expert analysts self-serve and answer realistic questions.