Miracle-dz/UniFAR-FTUs huggingface dataset:
Projection-Based Demixing of Spatial Audio

We propose a method to unmix multichannel audio signals into their different constitutive spatial objects. To achieve this, we characterize an audio object through both a spatial and a spectro-temporal modeling. The particularity of the spatial model we pick is that it neither assumes an object has only one underlying source point, nor does it attempt to model the complex room acoustics. Instead, it focuses on a listener perspective, and takes each object as the superposition of many contributions with different incoming directions and interchannel delays. Our spectro-temporal probabilistic model is based on the recently proposed α-harmonisable processes, which are adequate for signals with large dynamics, such as audio. Then, the main originality of this paper is to provide a new way to estimate and exploit interchannel dependences of an object for the purpose of demixing. In the Gaussian α = 2 case, previous research focused on covariance structures. This approach is no longer valid for α <; 2 where covariances are not defined. Instead, we show how simple linear combinations of the mixture channels can be used to learn the model parameters, and the method we propose consists in pooling the estimates based on many projections to correctly account for the original multichannel audio. Intuitively, each such downmix of the mixture provides a new perspective where some objects are canceled or enhanced. Finally, we also explain how to recover the different spatial audio objects when all parameters have been computed. Performance of the method is illustrated on the separation of stereophonic music signals.
Environmental Influences on Daily Emergency Admissions in Sickle-Cell Disease Patients

AbstractPrevious reports have suggested a role for weather conditions and air pollution on the variability of sickle cell disease (SCD) severity, but large-scale comprehensive epidemiological studies are lacking.In order to evaluate the influence of air pollution and climatic factors on emergency hospital admissions (EHA) in SCD patients, we conducted an 8-year observational retrospective study in 22 French university hospitals in Paris conurbation, using distributed lag non-linear models, a methodology able to flexibly describe simultaneously non-linear and delayed associations, with a multivariable approach.During the 2922 days of the study, there were 17,710 EHA, with a mean daily number of 6.1 ± 2.8. Most environmental factors were significantly correlated to each other. The risk of EHA was significantly associated with higher values of nitrogen dioxide, atmospheric particulate matters, and daily mean wind speed; and with lower values of carbon monoxide, ozone, sulfur dioxide, daily temperature (minimal, maximal, mean, and range), day-to-day mean temperature change, daily bright sunshine, and occurrence of storm. There was a lag effect for 12 of 15 environmental factors influencing hospitalization rate. Multivariate analysis identified carbon monoxide, day-to-day temperature change, and mean wind speed, along with calendar factors (weekend, summer season, and year) as independent factors associated with EHA.In conclusion, most weather conditions and air pollutants assessed were correlated to each other and influenced the rate of EHA in SCD patients. In multivariate analysis, lower carbon monoxide concentrations, day-to-day mean temperature drop and higher wind speed were associated with increased risk of EHA.
Comparing National Institutes of Health Stroke Scale Among a Stroke Team and Helicopter Emergency Medical Service Providers

Background and Purpose— The use of tissue-type plasminogen activator is limited to a maximum of 4.5 hours after symptom-onset. Endovascular recanalization may improve outcomes for large-vessel occlusions (LVO), but efficacy decreases with time from symptom-onset. A National Institutes of Health Stroke Scale (NIHSS) score ≥12 is predictive of LVOs and could be used to triage patients if appropriately used by prehospital providers. The NIHSS has been considered too complex and has not been validated in the prehospital setting. Methods— We reviewed all patients with ischemic stroke transported by helicopter emergency medical services (HEMS) to a single comprehensive stroke center in 2010. HEMS NIHSS were compared with in-hospital stroke team physician scores. NIHSS was categorized based on 3 clinically relevant groupings and ability to predict LVO was investigated. Results— Three-hundred five patients met inclusion criteria, 68.9% having LVO. Moderate agreement existed between HEMS and physicians (72.1%; &kgr;=0.571). Interclass correlation was 0.879 (95% confidence interval, 0.849–0.904). Excluding patients with tissue-type plasminogen activator before HEMS transport, there were 216 patients and good agreement (82.7%; &kgr;=0.619). Among patients presenting within 8 hours postonset and NIHSS≥12, HEMS had a sensitivity of 55.9% and positive predictive value of 83.7% in predicting LVO. Conclusions— HEMS providers can administer NIHSS with moderate to good agreement with the receiving stroke team. The use of the NIHSS in HEMS may identify patients with LVO and inform triage decisions for patients ineligible for tissue-type plasminogen activator.
Toward Fuzzy block theory

This study, fundamentals of fuzzy block theory, and its application in assessment of stability in underground openings, has surveyed. Using fuzzy topics and inserting them in to key block theory, in two ways, fundamentals of fuzzy block theory has been presented. In indirect combining, by coupling of adaptive Neuro Fuzzy Inference System (NFIS) and classic block theory, we could extract possible damage parts around a tunnel. In direct solution, some principles of block theory, by means of different fuzzy facets theory, were rewritten.
Proximate Composition and Mineral Contents of Cultured and Wild Tilapia (Oreochromis niloticus) (Pisces: Cichlidae) (Linnaeus, 1758)

Studies were conducted on the proximate composition and mineral contents of wild and cultured tilapia (Oreochromis niloticus) bought from Aqua Vista Fish Farm and artisanal fishermen at Nsidung beach, Calabar, Cross River State, Nigeria. The internationally accepted methods of AOAC were used for the analysis. Results obtained were as follows: Moisture (wild individuals: 80.90%, cultured: 80.80%), crude protein (wild individuals: 17.40%, cultured: 17.10%), crude fat (wild individuals: 0.57%, cultured: 0.30%), ash (wild individuals: 1.20%, cultured: 1.31%), Carbohydrate (wild individuals: 0.22%, cultured: 0.20%); Calcium(wild individuals: 28.3 mg/100 g, cultured: 27.0 mg/100 g), Magnesium (wild individuals: 11.9 mg/100 g, cultured: 2.70 mg/100 g), Potassium (wild individuals: 17.1 mg/100 g, cultured: 11.90 mg/100 g), Iron (wild individuals: 151.0 mg/100 g, cultured: 146.0 mg/100 g), Zinc (wild individuals: 67.10 mg/100 g, cultured: 66.9 mg/100 g and Sodium (wild individuals: 13.0 mg/100 g, cultured: 12.7 mg/100 g).
Effects of Luminosity Functions Induced by Relativistic Beaming on the Statistics of Cosmological Gamma-Ray Bursts

Most gamma-ray burst (GRB) models have predicted that the intrinsic isotropic energy is limited to below ~1053-1054 ergs. Recently claimed high redshifts, correlation with supernovae, and connections to cosmic star formation activity point to a different energy requirement and source evolution history, possibly with strong beaming. We study the effects of the beaming-induced luminosity function on statistics of observed GRBs, assuming the cosmological scenario. We select and divide the BATSE 4B data into 588 long bursts (T90 > 2.5 s) and 149 short bursts (T90 < 2.5 s), and compare the statistics calculated in each subgroup. The ⟨V/Vmax⟩ of the long bursts is 0.2901 ± 0.0113, and that of the short bursts is 0.4178 ± 0.0239. For luminosity function models, we consider a cylindrical beam and a conic beam. We take into account the spatial distribution of GRB sources as well. A broad luminosity function is naturally produced when one introduces beaming of GRBs. We calculate the maximum detectable redshift of GRBs, zmax. The estimated zmax for the cylindrical beam case is as high as ~14 (α = 1.0) and ~6 (α = 2.0) for the long bursts, and ~3 (α = 1.0) and ~1.6 (α = 2.0) for the short bursts, where α is the photon index. The large zmax value for the short bursts is rather surprising, in that the ⟨V/Vmax⟩ for this subgroup is close to the so-called Euclidean value, 0.5. We calculate the fraction of bursts whose redshifts are larger than a certain redshift z′, i.e., f > z'. When we take z′ = 3.42 and apply the luminosity function derived for the cylindrical beam, the expected f > z' is ~75% (α = 1.0) and ~50% (α = 2.0) for long bursts. When we increase the opening angle of the conic beam to Δθ = 3. °0, f > z' decreases to ~20% (α = 1.0) at z′ = 3.42. If we assume α = 2.0, the conic beam with Δθ = 3. °0 cannot explain the redshift distribution of the observed GRBs. We conclude that the beaming-induced luminosity functions are compatible with the redshift distribution of the observed GRBs, although the apparent "Euclidean" value of ⟨V/Vmax⟩ might be explained by the standard model.
Secure Nonlocal Denoising in Outsourced Images

Signal processing in the encrypted domain becomes a desired technique to protect privacy of outsourced data in cloud. In this article, we propose a double-cipher scheme to implement nonlocal means (NLM) denoising in encrypted images. In this scheme, one ciphertext is generated by the Paillier scheme, which enables the mean filter, and the other is obtained by a privacy-preserving transform, which enables the nonlocal search. By the privacy-preserving transform, the cloud server can search the similar pixel blocks in the ciphertexts with the same speed as in the plaintexts; thus, the proposed method can be executed fast. To enhance the security, we randomly permutate both ciphertexts. To reduce the denoising complexity caused by random permutation, a random NLM method is exploited in the encrypted domain. The experimental results show that the quality of denoised images in the encrypted domain is comparable to that obtained in the plain domain.
Receding Horizon FIR Filter and Its Square-Root Algorithm for Discrete Time-Varying Systems

A receding horizon FIR filter is suggested for discrete time-varying systems, combining the Kalman filter with the receding horizon strategy. The suggested filter is shown to be an FIR structure that has many good inherent properties. The suggested filter is represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer that is often robust against system and measurement noises. It is also shown that the suggested filter is an unbiased estimator irrespective of any horizon initial condition. For the amenability to parallel and systolic implementation as well as the numerical stability, a square-root algorithm for the suggested filter is presented. To evaluate performance, the suggested filter is applied to a problem of unknown input estimation and compared with the existing Kalman filter based approach.
Vibration therapy

Whole‐body vibration training is a method for muscle strengthening that is increasingly used in a variety of clinical situations. Key descriptors of vibration devices include the frequency, the amplitude, and the direction of the vibration movement. In a typical vibration session, the user stands on the device in a static position or performs dynamic movements. Most authors hypothesize that vibrations stimulate muscle spindles and alpha‐motoneurons, which initiate a muscle contraction. An immediate effect of a non‐exhausting vibration session is an increase in muscle power. Most studies of the longer term use of vibration treatment in various disorders have pursued three therapeutic aims: increasing muscle strength, improving balance, and increasing bone mass. In a small pilot trial in children we noted improvements in standing function, lumbar spine bone mineral density, tibial bone mass, and calf muscle cross‐sectional area.
Stability analysis of the Instantaneous Power Control (IPC) algorithm for induction machines

Instantaneous power control (IPC) has over recent years been proposed as an alternative method for the control of induction machines. This paper provides a stability analysis of the algorithm using linear techniques. Results are presented which confirm that the algorithm, in its raw form, does have a stability problem in regeneration. However the presence of a PLL based filter on the back-emf estimates, which is essential for practical implementation, stabilises the algorithm.
Fast data-locality profiling of native execution

Performance tools based on hardware counters can efficiently profile the cache behavior of an application and help software developers improve its cache utilization. Simulator-based tools can potentially provide more insights and flexibility and model many different cache configurations, but have the drawback of large run-time overhead.We present StatCache, a performance tool based on a statistical cache model. It has a small run-time overhead while providing much of the flexibility of simulator-based tools. A monitor process running in the background collects sparse memory access statistics about the analyzed application running natively on a host computer. Generic locality information is derived and presented in a code-centric and/or data-centric view.We evaluate the accuracy and performance of the tool using ten SPEC CPU2000 benchmarks. We also exemplify how the flexibility of the tool can be used to better understand the characteristics of cache-related performance problems.
Toward Smart Power Grids: Communication Network Design for Power Grids Synchronization

In smart power grids, keeping the synchronicity of generators and the corresponding controls is of great importance. To do so, a simple model is employed in terms of swing equation to represent the interactions among dynamics of generators and feedback control. In case of having a communication network available, the control can be done based on the transmitted measurements by the communication network. The stability of system is denoted by the largest eigenvalue of the weighted sum of the Laplacian matrices of the communication infrastructure and power network. In this work, we use graph theory to model the communication network as a graph problem. Then, Ant Colony System (ACS) is employed for optimum design of above graph for synchronization of power grids. Performance evaluation of the proposed method for the 39-bus New England power system versus methods such as exhaustive search and Rayleigh quotient approximation indicates feasibility and effectiveness of our method for even large scale smart power grids.
Satellite Lithium-Ion Battery Remaining Cycle Life Prediction with Novel Indirect Health Indicator Extraction

Prognostics and remaining useful life (RUL) estimation for lithium-ion batteries play an important role in intelligent battery management systems (BMS). The capacity is often used as the fade indicator for estimating the remaining cycle life of a lithium-ion battery. For spacecraft requiring high reliability and long lifetime, in-orbit RUL estimation and reliability verification on ground should be carefully addressed. However, it is quite challenging to monitor and estimate the capacity of a lithium-ion battery on-line in satellite applications. In this work, a novel health indicator (HI) is extracted from the operating parameters of a lithium-ion battery to quantify battery degradation. Moreover, the Grey Correlation Analysis (GCA) is utilized to evaluate the similarities between the extracted HI and the battery’s capacity. The result illustrates the effectiveness of using this new HI for fading indication. Furthermore, we propose an optimized ensemble monotonic echo state networks (En_MONESN) algorithm, in which the monotonic constraint is introduced to improve the adaptivity of degradation trend estimation, and ensemble learning is integrated to achieve high stability and precision of RUL prediction. Experiments with actual testing data show the efficiency of our proposed method in RUL estimation and degradation modeling for the satellite lithium-ion battery application.
Model advertising slogan selection system using collective wisdom on the web

Increased demand for web advertising has resulted in a corresponding increase in the need to develop personalized advertisements targeted at individuals online. We propose an automated advertising slogan selection system that can satisfy this requirement. Many customer reviews and comments are available publicly on online shopping sites. The proposed system uses content mining to extract favorable reports from the web and arranges the data into a specific knowledge representation structure to improve the advantage of the target product. For a particular business, the proposed system first extracts tuples, composed of elements that express the knowledge representation from each user-written review. Then, these tuples are selected using a frequency-based approach and emotion corpus. Subsequently, for each tuple, advertising slogans are chosen from the advertising slogan corpora using a neural network. For verification, we used data from an electronic commerce website for hotels to evaluate two aspects of our system (namely, quality of selected tuples and advertising slogans). The results of the experiments confirm that the proposed system can extract suitable tuples when the given data are sufficient. It can also retrieve slogans even when their meanings are convoluted.
REVIEW: Behavioural assessment of drug reinforcement and addictive features in rodents: an overview

Some psychoactive drugs are abused because of their ability to act as reinforcers. As a consequence behavioural patterns (such as drug‐seeking/drug‐taking behaviours) are promoted that ensure further drug consumption. After prolonged drug self‐administration, some individuals lose control over their behaviour so that these drug‐seeking/taking behaviours become compulsive, pervading almost all life activities and precipitating the loss of social compatibility. Thus, the syndrome of addictive behaviour is qualitatively different from controlled drug consumption. Drug‐induced reinforcement can be assessed directly in laboratory animals by either operant or non‐operant self‐administration methods, by classical conditioning‐based paradigms such as conditioned place preference or sign tracking, by facilitation of intracranial electric self‐stimulation, or, alternatively by drug‐induced memory enhancement. In contrast, addiction cannot be modelled in animals, at least as a whole, within the constraints of the laboratory. However, various procedures have been proposed as possible rodent analogues of addiction’s major elements including compulsive drug seeking, relapse, loss of control/impulsivity, and continued drug consumption despite negative consequences. This review provides an extensive overview and a critical evaluation of the methods currently used for studying drug‐induced reinforcement as well as specific features of addictive behaviour. In addition, comic strips that illustrate behavioural methods used in the drug abuse field are provided given for free download under http://www.zi‐mannheim/psychopharmacology.de
Visualizing object oriented software in three dimensions

There is increasing evidence that it is possible to perceive and understand increasingly complex information systems if they are displayed as graphical objects in a three dimensional space. Object-oriented software provides an interesting test case - there is a natural mapping from software objects to visual objects. In this paper we explore two areas. 1) Information perception: we are running controlled experiments to determine empirically if our initial premise is valid; how much more (or less) can be understood in 3D than in 2D? 2) Layout: our strategy is to combine partially automatic layout with manual layout. This paper presents a brief overview of the project, the software architecture and some preliminary empirical results.
Experimenting Hand-Gesture Image Recognition using Simple Deep Neural Network

Traditionally human interacts with a computer by using keyboard and mouse. Considering person with handicapped from the wrist to the fingertip or amputated wrists or fingertips need alternative way; using voice or hand gesture. This work focuses on the use of hand-gesture image recognition. There are two main issues should be considered; less interactivity in static hand gesture recognition, and less accuracy in dynamic hand gesture recognition. This paper attempts to improve the accuracy of hand-gesture image recognition by experimenting simple deep learning neural network (DLNN). As this work uses a simple DLNN, the relation between the hidden layers is not considered. The number of hidden layers in the proposed architecture of the DLNN for the experiments vary from one to five.With the aims to understand the effect of the number of neurons in the hidden layers, the DLNN is experimented using different numbers of hidden neurons. Six different types of hand gestures are considered. 800 videos on hand gestures taken from Vision for Intelligent Vehicles and Applications (VIVA) portal are used in the experiment. The data is divided into two; one as training data and another part is for testing. The best result is achieved when the DLNN uses two hidden layers with 250 neurons in the first hidden layer, and 100 neurons in the second hidden layer. The average of the achieved accuracy level is 77.56%. Experimental results also show that the more number of hidden layer causes over-fitting (does not make the recognition better). It is also observed that the increase of hidden layer number and hidden neurons only affect the accuracy of recognition of the trained dataset and does not improve the recognition of untrained dataset. This result is because the interrelation among the hidden layer are not considered.
Network coding meets information-centric networking: an architectural case for information dispersion through native network coding

User behavior in the Internet has changed over the recent years towards being driven by exchanging and accessing information. Many advances in networking technologies have utilized this change by focusing on the content of an exchange rather than on the endpoints exchanging the content, in particular to better support mobility. Network coding and information-centric networking are two examples of these trends, each being developed largely independently thus far. This paper brings these areas together at the internetworking layer. We outline opportunities for applying network coding in a novel and performance-enhancing way that could push forward the case for information-centric networking itself.