Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Instrument Recognition in Polyphonic Music Using Convolutional Neural Networks

Traditional methods to tackle many music information retrieval tasks typically follow a two-step architecture: feature engineering followed by a simple learning algorithm. In these "shallow" architectures, feature engineering and learning are typically disjoint and unrelated. Additionally, feature engineering is difficult, and typically depends on extensive domain expertise. In this paper, we present an application of convolutional neural networks for the task of automatic musical instrument identification. In this model, feature extraction and learning algorithms are trained together in an end-to-end fashion. We show that a convolutional neural network trained on raw audio can achieve performance surpassing traditional methods that rely on hand-crafted features.
D-Fi: A diversity-aware Wi-Fi using an OFDM-based Bloom filter

To exploit frequency diversity in Wi-Fi channels, instantaneous channel quality must be estimated. However, there is a trade-off between acquiring channel quality information and improving protocol efficiency because channel estimation consumes time and frequency resource that ideally should be used for data transfer. In this paper, we present D-Fi (Diversity-aware Wi-Fi), a novel Wi-Fi PHY/MAC protocol, that capitalizes on frequency diversity gains while sustaining protocol efficiency. The D-Fi design allows to estimate channel quality while D-Fi is performing channel contention using an OFDM-based Bloom filter. To resolve the ambiguity caused by the Bloom filter, we adopt two methods: (i) An analysis-based multi channel backoff method enables to explore/exploit frequency diversity while reducing the occurrence of the ambiguity. (ii) Applying machine learning (ML) methods to the D-Fi PHY/MAC protocol corrects the ambiguity taken place already and makes our protocol reliable. We have shown the feasibility of D-Fi by implementing it on the USRP/GNURadio platform. Experiments and trace-driven simulations show that D-Fi successfully achieves frequency diversity gains without losing improved protocol efficiency.
Childhood Apraxia of Speech : Technical Report

This technical report was developed by the American Speech-Language-Hearing Association (ASHA) Ad Hoc Committee on Apraxia of Speech in Children. The report reviews the research background that supports the ASHA position statement on Apraxia of Speech in Children [DATE]. Members of the Committee were Lawrence Shriberg (chair), Christina Gildersleeve-Neumann, David Hammer, Rebecca McCauley, Shelley Velleman, and Roseanne Clausen (ex officio). Celia Hooper, ASHA vice president for professional practices in speech-language pathology (2003–2005), and Brian Shulman, ASHA vice president for professional practices in speech-language pathology (2006–2008), served as the monitoring officers. The Committee thanks Sharon Gretz, Heather Lohmeier, Rob Mullen, and Alison Scheer-Cohen, as well as the many select and widespread peer reviewers who provided insightful comments on drafts of this report.
A novel hybrid module of skin detector using grouping histogram technique for Bayesian method and segment adjacent-nested technique for neural network

Skin detection is a common ancient image processing applications for detecting human images. The applications include video surveillance, naked image filters within unit-spam systems and face detection. Skin color is considered as a useful and discriminating spatial feature for many skin detection related applications, but it is not robust enough to deal with complex image environments. Skin tone ranges from dark (some Africans) to light white (Caucasians and some Europeans). Other factors like light-changing conditions and the presence of objects with skin-like colors could create major difficulties in face pixel-based skin detector when color feature is used. Thus, this paper proposed a novel hybrid module using grouping histogram technique for Bayesian method and back propagation neural network with segment adjacent-nested (SAN) technique based on YCbCr and RGB color space in improving the skin detection performance. The researcher was able to increase the classification reliability in discriminating human skin color and regularizing the skin detection that is exposed to different light conditions. This novel skin detector method depends on three factors. The first part of the method involves the Bayesian part that is applied to a novel grouping histogram technique which uses 600 non-skin images in the processing and then calculates the probability density for each pixel. The second part involves applying the adjacent-nested technique in the preprocessing and calculating the probability density for each pixel in the neural part. Then a combination of the neural part and normalization technique is used to normalize the inputs and targets, so that the target falls in the interval [-1, 1] for each segment, which is created and trained with the training set of the skin and non skin segments. The third part involves a combination of the Bayesian method with the neural network segmentation methods and novel hybrid method. The study, tested on human images, has an upright frontal skin with any background. As such, the results show that the proposed system is able to achieve high detection rates of 98% segmentation and low false positives when compared with the existing methods. Key words: Skin detector, Bayesian method, neural network.
Computer-aided reconstruction of traumatic fronto-orbital osseous defects: aesthetic considerations.

BACKGROUND In addition to functional goals, a satisfactory aesthetic outcome is important for reconstruction of fronto-orbital osseous defects. The purpose of this study is to report on a method for presurgical fabrication of custom implants using 3-dimensional (3-D) imaging data and computer-assisted manufacturing techniques. METHODS Preoperative 3-D computed tomography data were processed and displayed for evaluation of defects. Implants were created by a computer-aided design/computer-aided manufacturing (CAD/CAM) program. A rapid prototyping system was applied for production of the physical models. Rehearsal of surgery was performed using the implants and skull models. Negative castings were created and were used during the operations to prepare the surgical implant utilizing methyl methacrylate. Traumatic fronto-orbital defects in 4 patients were reconstructed using this method. The follow-up period ranged from 29 to 55 months. RESULTS Results showed that the custom implants perfectly fit the defects during the operation. Symmetry and normal fronto-orbital contours were achieved. There were no peri- or postoperative complications. All patients were satisfied with the results. CONCLUSIONS Computer-aided presurgical simulation and fabrication of implants is a reliable and effective method for the reconstruction of traumatic fronto-orbital defects, with reduced anesthesia time and improved aesthetic outcomes.
An empirical study of the effect of time constraints on the cost-benefits of regression testing

Regression testing is an expensive process used to validate modified software. Test case prioritization techniques improve the cost-effectiveness of regression testing by ordering test cases such that those that are more important are run earlier in the testing process. Many prioritization techniques have been proposed and evidence shows that they can be beneficial. It has been suggested, however, that the time constraints that can be imposed on regression testing by various software development processes can strongly affect the behavior of prioritization techniques. Therefore, we conducted an experiment to assess the effects of time constraints on the costs and benefits of prioritization techniques. Our results show that time constraints can indeed play a significant role in determining both the cost-effectiveness of prioritization, and the relative cost-benefit tradeoffs among techniques, with important implications for the use of prioritization in practice.
A Functional Model of Cognitive Rehabilitation in Occupational Therapy

Persons who sustain cerebral injuries often have cognitive impairments. Occupational therapists are active in providing cognitive rehabilitation that aims to minimize the effects of cognitive deficits in their clients' lives. This paper presents a brief review of the literature in the area of cognitive rehabilitation including major characteristics of existing occupational therapy models related to the treatment of people who need cognitive rehabilitation. A model of cognitive rehabilitation is proposed that emphasizes functional components of occupational therapy in different rehabilitation settings. This model, called the Functional Model of Cognitive Rehabilitation, supports the use of activities in naturalistic settings in treatment, in order to enable those with cognitive impairments to fulfill their occupational roles.
The everyday Bogans: Identity and community amongst Heavy Metal fans

Since the mid-twentieth century some social psychologists have demarcated communities as static entities; conceptual and physical boundaries were placed around communities to facilitate scholarly analysis. This theoretical and methodological bias is contrasted against the consideration of the dynamic flow of communities and, by association, identity formation. The application of social interactionism provides one method through which to remedy the partiality of preferred approaches to community as practised in contemporary social psychology. Opening up analysis to the consideration of processes of communing exposes the interconnection of identity and community, symbiosis that develops through social interactions across places via the creative use of music and material objects. Evidence collected through auto-ethnographic engagement with New Zealand Heavy Metal fans clarifies the complex associations that shape and maintain individual identity and community associations. Social ties are negotiated and maintained across online and offline spaces, through personal interactions and shared experiences, via object recognition, and threshold maintenance. Social psychological research needs to return to early works of psychology and symbolic interactionism to account more fully for the complex and emplaced nature of identity and community.
Consistency maintenance based on the mark & retrace technique in groupware systems

Replicated architecture is widely used for concealing network delay. However, consistency maintenance in fully replicated architecture is a major technical challenge. In this paper, we report a Mark & Retrace based method in replicated groupware systems. Compared with the Operation Transformation technique, it does not adjust the operation's position but retraces the document's address space to the state at the time of the operation's generation. Then the operation can be executed directly in this address space. Mark & Retrace method can not only achieve the same goal of consistency maintenance but also provide a better support for Undo. This paper provides the proof of the algorithm's correctness of consistency maintenance, in which both the orders of character nodes and marks of each node at all sites are kept consistent. Furthermore, the amortized efficiency can reach O(log n).
Heated Cooling Flows

In conventional models of galactic and cluster cooling flows widespread cooling (mass dropout) is assumed to avoid accumulation of unacceptably large central masses. This assumption is often criticized because the observed mass of cooled gas and newly formed stars is much less than the cooling rates imply. Moreover, recent XMM observations have failed to find spectral evidence for locally cooling gas. This remarkable discovery has revived the notion that cooling flows do not cool in the manner previously assumed but are instead heated by some process such as an intermittent or low-level active galactic nucleus in the central galaxy. To explore this hypothesis, we consider the gasdynamical consequences of heated galactic cooling flows under many different heating scenarios without specifying the detailed physics of the heating process. We have been unable to find a single acceptable heated flow in reasonable agreement with well-observed hot gas temperature and density profiles. Even for poor fits to the observations, these models require finely tuned heating scenarios. Idealized flows in which radiative cooling is perfectly balanced by global heating are grossly incompatible with observations. Flows heated by central feedback often result in episodic cooling that is associated with quasi-cyclic changes in the hot gas density profile; at present there is no observational evidence for this. Paradoxically, when cooling flows are centrally heated (or pressurized), they experience spontaneous nonlinear compressions that result in spatially widespread cooling instabilities. Therefore, spectral evidence for cooling gas is expected in either traditional cooling flows with ad hoc mass dropout or heated cooling flows without the dropout assumption.
Diagnosis of pulmonary embolism with magnetic resonance angiography.

BACKGROUND Diagnosing pulmonary embolism may be difficult, because there is no reliable noninvasive imaging method. We compared a new noninvasive method, gadolinium-enhanced pulmonary magnetic resonance angiography, with standard pulmonary angiography for diagnosing pulmonary embolism. METHODS A total of 30 consecutive patients with suspected pulmonary embolism underwent both standard pulmonary angiography and magnetic resonance angiography during the pulmonary arterial phase at the time of an intravenous bolus of gadolinium. All magnetic resonance images were reviewed for the presence or absence of pulmonary emboli by three independent reviewers who were unaware of the findings on standard angiograms. RESULTS Pulmonary embolism was detected by standard pulmonary angiography in 8 of the 30 patients in whom pulmonary embolism was suspected. All 5 lobar emboli and 16 of 17 segmental emboli identified on standard angiograms were also identified on magnetic resonance images. Two of the three reviewers reported one false positive magnetic resonance angiogram each. As compared with standard pulmonary angiography, the three sets of readings had sensitivities of 100, 87, and 75 percent and specificities of 95, 100, and 95 percent, respectively. The interobserver correlation was good (k=0.57 to 0.83 for all vessels, 0.49 to 1.0 for main and lobar vessels, and 0.40 to 0.81 for segmental vessels). CONCLUSIONS In this preliminary study, gadolinium-enhanced magnetic resonance angiography of the pulmonary arteries, as compared with conventional pulmonary angiography, had high sensitivity and specificity for the diagnosis of pulmonary embolism. This new technique shows promise as a noninvasive method of diagnosing pulmonary embolism without the need for ionizing radiation or iodinated contrast material.
THE EFFECTS OF COUNSEL ON THE SEVERITY OF CRIMINAL SENTENCES: A STATISTICAL ASSESSMENT

Information on a sample of felony cases in Columbus, Ohio is used to estimate the effect of counsel (appointed or retained) on the relative severity of criminal sentences. Applying two multivariate statistical techniques, both the direct and indirect effects of counsel are isolated. Generally, the results reveal few systematic differences in sentence severity between types of counsel and provide further confirmatory evidence for the proposition that case and defendant-related variables-not the identity of counsel-are primarily repsonsible for the severity of criminal sentences.
Neurogenic Vasodilation of Cat Cerebral Arteries

Transmural nerve stimulation (TNS) with 0.3-msec pulses between 1 and 25 Hz dilated cat cerebral artery segments in the presence of active muscle tone. Maximum vasodilatation occurred at 8 Hz. The dilator response to exogenous acetylcholine, but not to TNS, was abolished by atropine. Neither physostigmine nor hemicholinium affected the dilator response to TNS, which persisted after administration of guanethidine, phenoxybenzamine, propranolol, reserpine, and chronic sympathectomy. However, it was abolished by tetrodotoxin and cold storage. When examined histochemically, cat and rabbit cerebral arteries exhibited a rich plexiform distribution of acetylcholinesterase which was not affected appreciably by sympathetic denervation. These results suggest that vasodilation is not mediated through modification of sympathetic activity. They also indicate the existence of a nonadrenergic, possibly noncholinergic, vasodilator innervation in cat cerebral arteries. Preliminary studies suggest that the transmitter is not histamine, ATP, prostaglandins, γ-aminobutyric acid, dopamine, or serotonin. The cat cerebral artery segments contrast with the isolated rabbit cerebral arteries which predominantly constrict in response to TNS and show a small dilator response.
GROWTH ANALYSIS OF COMPONENT CROPS IN A MAIZE-SOYBEAN INTERCROPPING SYSTEM AS AFFECTED BY TIME OF PLANTING AND SPATIAL ARRANGEMENT

Two field trials were conducted in 2007 and 2008 to determine the appropriate sequence of planting and spatial arrangement for the maize-soybean intercropping system for optimum growth. The experimental design was a randomized complete block design with three replicates. Treatments consisted of combinations of five relative times of planting either maize or soybean and two spatial arrangements of soybean (alternate or double rows). One sole crop each of maize and soybean was added for comparison. Results of the growth analysis indicated that maize planted simultaneously with soybean or before soybean recorded significantly higher values of leaf area index (LAI), crop growth rate (CGR) and net assimilation rate (NAR). Spatial arrangement did not influence these parameters in maize. Interaction between time of planting and spatial arrangement was however significant. LAI and CGR for maize increased with time while NAR declined. For the soybean crop, soybean planted on the same day with maize or planted before maize recorded significant LAI, CGR and NAR values. Soybean planted in double row arrangement with maize recorded significant higher growth than soybean planted in alternate row arrangement with maize.
Iterative multiuser joint decoding: unified framework and asymptotic analysis

The synchronous chip-rate discrete-time CDMA channel with channel coding is analysed and the corresponding factor graph is presented. Iterative joint decoding can be derived in a simple and direct way by applying the sum-product algorithm to the factor graph. Since variables have degree 2, no computation takes place at the variable nodes. Computation at the code nodes is just soft-in soft-out (SISO) decoding, whose output is the extrinsic PMF of the coded symbols. Computation at the channel transition nodes is equivalent to MAP symbol-by-symbol multiuser detection, whose complexity is generally exponential in K. We show that several previously proposed low-complexity algorithms based on interference cancellation (IC) can be derived in a simple direct way by approximating the extrinsic PMF output by the SISO decoders either as a single mass-point PMF (hard decision) or as a Gaussian PDF with the same mean and variance (moment matching). Differently from all previously presented methods (derived from heuristic reasoning), we see clearly that extrinsic rather than a posteriori PMF should be fed back. This yields important advantages in terms of limiting achievable throughput.
Nutritional factors in relation to endometrial cancer: A report from a population‐based case‐control study in Shanghai, China

We evaluated the role of dietary nutrients in the etiology of endometrial cancer in a population‐based case‐control study of 1,204 newly diagnosed endometrial cancer cases and 1,212 age frequency‐matched controls. Information on usual dietary habits was collected during an in‐person interview using a validated, quantitative food frequency questionnaire. Logistic regression analysis was conducted to evaluate the association of nutrients with endometrial cancer risk using an energy density method (e.g., nutrient intake/1,000 kilocalories of intake). Higher energy intake was associated with increased risk, which was attributable to animal source energy and a high proportion of energy from protein and fat. Odds ratios comparing highest versus lowest quintiles of intake were elevated for intake of animal protein (Odds ratio (OR) = 2.0, 95% confidential interval: 1.5–2.7) and fat (OR = 1.5, 1.2–2.0), but reduced for plant sources of these nutrients (OR = 0.7, 0.5–0.9 for protein and OR = 0.6, 0.5–0.8 for fat). Further analysis showed that saturated and monounsaturated fat intake was associated with elevated risk, while polyunsaturated fat intake was unrelated to risk. Dietary retinol, β‐carotene, vitamin C, vitamin E, fiber, and vitamin supplements were inversely associated with risk. No significant association was observed for dietary vitamin B1 or vitamin B2. Our findings suggest that associations of dietary macronutrients with endometrial cancer risk may depend on their sources, with intake of animal origin nutrients being related to higher risk and intake of plant origin nutrients related to lower risk. Dietary fiber, retinol, β‐carotene, vitamin C, vitamin E, and vitamin supplementation may decrease the risk of endometrial cancer. © 2007 Wiley‐Liss, Inc.
Proposal for the 252 Cf source upgrade to the ATLAS facility

Beams of accelerated exotic neutron-rich nuclei allow access to little known regions of the nuclear landscape that are important both structurally and for r-process nucleosynthesis. We propose to increase the radioactive beam capabilities of the ATLAS accelerator facility by the installation of a new source of ions to provide beams of shortlived neutron-rich isotopes. These isotopes will be obtained from a 1 Ci Cf fission source located in a large gas catcher from which the radioactive ions will be extracted and transferred to an ECR ion source for charge breeding before acceleration in the ATLAS superconducting linac. The technique is fast, universal and highly efficient. It will provide accelerated neutron-rich beam intensities of up to 7 · 10 ions per second on target at energies that are difficult to access at other facilities. This upgrade will enhance the reach of ATLAS and offer world-unique capabilities to study neutron-rich nuclei. It will also help advance technologies critical for the RIA facility.
Numerical analysis and computational testing of a high accuracy Leray‐deconvolution model of turbulence

We study a computationally attractive algorithm (based on an extrapolated Crank‐Nicolson method) for a recently proposed family of high accuracy turbulence models, the Leray‐deconvolution family. First we prove convergence of the algorithm to the solution of the Navier‐Stokes equations and delineate its (optimal) accuracy. Numerical experiments are presented which confirm the convergence theory. Our 3d experiments also give a careful comparison of various related approaches. They show the combination of the Leray‐deconvolution regularization with the extrapolated Crank‐Nicolson method can be more accurate at higher Reynolds number that the classical extrapolated trapezoidal method of Baker (Report, Harvard University, 1976). We also show the higher order Leray‐deconvolution models (e.g. N = 1,2,3) have greater accuracy than the N = 0 case of the Leray‐α model. Numerical experiments for the 2d step problem are also successfully investigated. Around the critical Reynolds number, the low order models inhibit vortex shedding behind the step. The higher order models, correctly, do not. To estimate the complexity of using Leray‐deconvolution models for turbulent flow simulations we estimate the models' microscale. © 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2008