Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on performance behavior of compressive sensing measurements for multiple sensor system

In this paper, we will analyze the performance limit for a multiple sensor system (MSS) based on compressive sensing. In our MSS, all of the sensors measure signals from a common source. There exists the redundancy in the measured signal because the measured signal comes from the common source. To reduce communication costs, this redundancy must be removed. For this purpose, we use compressive sensing at each sensor to obtain compressed measurements. After all of the sensors obtain compressed measurements, they transmit them to a central unit. A decoder at the central unit receives all of the transmitted signals and attempts to jointly estimate the correct support set, which is the set of indices corresponding to the locations of the non-zero coefficients of the measured signals. In order to analyze our MSS, we present a jointly typical decoder inspired by recent work [4]. We first obtain the upper bound probability that the jointly typical decoder fails to estimate the correct support set. Next, we prove that as the number of sensors increases, the compressed measurements per sensor (per-sensor measurements) can be reduced to sparsity, which is the number of non-zero coefficients in the measured signal. We present the sufficient number of sensors required with the increase in the noise variance.
Lower Bounds on the Probability of Error for Classical and Classical-Quantum Channels

In this paper, lower bounds on error probability in coding for discrete classical and classical-quantum channels are studied. The contribution of the paper goes in two main directions: 1) extending classical bounds of Shannon to classical-quantum channels, and 2) proposing a new framework for lower bounding the probability of error of channels with a zero-error capacity in the low rate region. The relation between these two problems is revealed by showing that Lovász' bound on zero-error capacity emerges as a natural consequence of the sphere packing bound once we move to the more general context of classical-quantum channels. A variation of Lovász' bound is then derived to lower bound the probability of error in the low rate region by means of auxiliary channels. As a result of this study, connections between the Lovász theta function, the expurgated bound of Gallager, the cutoff rate of a classical channel, and the sphere packing bound for classical-quantum channels are established.
Unsupervised Intralingual and Cross-Lingual Speaker Adaptation for HMM-Based Speech Synthesis Using Two-Pass Decision Tree Construction

Hidden Markov model (HMM)-based speech synthesis systems possess several advantages over concatenative synthesis systems. One such advantage is the relative ease with which HMM-based systems are adapted to speakers not present in the training dataset. Speaker adaptation methods used in the field of HMM-based automatic speech recognition (ASR) are adopted for this task. In the case of unsupervised speaker adaptation, previous work has used a supplementary set of acoustic models to estimate the transcription of the adaptation data. This paper first presents an approach to the unsupervised speaker adaptation task for HMM-based speech synthesis models which avoids the need for such supplementary acoustic models. This is achieved by defining a mapping between HMM-based synthesis models and ASR-style models, via a two-pass decision tree construction process. Second, it is shown that this mapping also enables unsupervised adaptation of HMM-based speech synthesis models without the need to perform linguistic analysis of the estimated transcription of the adaptation data. Third, this paper demonstrates how this technique lends itself to the task of unsupervised cross-lingual adaptation of HMM-based speech synthesis models, and explains the advantages of such an approach. Finally, listener evaluations reveal that the proposed unsupervised adaptation methods deliver performance approaching that of supervised adaptation.
Assessment of iron deficiency in the context of the obesity epidemic: importance of correcting serum ferritin concentrations for inflammation.

BACKGROUND The correction of serum ferritin (SF) concentrations for inflammation because of infectious or parasitic diseases was recently proposed, especially in developing countries, but in many countries, adiposity has become the main cause of inflammation. OBJECTIVE We assessed, overall and by adiposity status, the bias in the estimation of iron deficiency (ID) on the basis of uncorrected SF. DESIGN A cross-sectional survey in 2010 in Rabat-Salé, Morocco, used a random sample of 811 women aged 20-49 y. Adiposity was assessed by body mass index (BMI) (in kg/m²) (normal: BMI <25; overweight: BMI ≥25 to <30; obese: BMI ≥30), waist circumference, and body fat. Inflammation was indicated by a C-reactive protein (CRP) concentration >2 mg/L. ID was indicated by an SF concentration <15 μg/L. The correction factor of SF for inflammation was derived from our sample. Differential effects of SF correction on ID status on the basis of adiposity were assessed by models that included adiposity × correction interactions and accounted for the within-subject correlation. RESULTS The prevalence of overweight was 33.0% and of obesity was 34.0%. Inflammation (42.3%) was strongly linked with adiposity (20.1%, 37.6%, and 68.4% in normal, overweight, and obese subjects, respectively; P < 0.0001). SF increased from a CRP concentration >2 mg/L. The correction factor of SF was 0.65. The prevalence of ID (37.2% compared with 45.2%; difference -8.0%, P < 0.0001) was underestimated by not correcting SF, and the difference increased with adiposity (-2.9%, -8.5%, and -12.4% in normal, overweight, and obese subjects, respectively; P-interaction < 0.0001). Analogous results were observed for other adiposity measures. CONCLUSION In developing countries where ID remains prevalent but rates of obesity are already high, corrected SF should be used when assessing ID status, even if infectious or parasitic diseases are no longer widespread. This trial was registered at clinicaltrials.gov as NCT01844349.
Contemporary urban culture: how community structures endure in an individualised society

This paper examines the ways in which socio-cultural norms have shifted to accommodate higher levels of autonomy in urban communities. Largely critiquing traditional concepts of community as well as current dystopian perspectives on the fluid and vapid state of social organisation, it will show how individualism has been incorporated into societal norms, producing highly autonomous personalised networks that, when combined with large amounts of social interaction and imaginative cultural appropriation, create the common social and cultural practices emblematic of community structure. It also illustrates how many activities, traditionally viewed as indicative of social decay, are socially productive, in that they go towards generating the common bonds and world-views that unite individuals across urban landscapes. Focusing particularly on the spaces of community interaction, the construction of common identities and common sense of belonging, this paper sets out to explore alternative modes of community creation and enactment in a contemporary urban environment.
Feature adaptation using projection of Gaussian posteriors

In this paper we consider the use of non-linear methods for feature adaptation to reduce the mismatch between test and training conditions. The non-linearity is introduced by using the posteriors of a set of Gaussians to adapt the original features. Parameters are estimated to maximize the likelihood of the test data. The modeling framework used is based on the fMPE models [1]. We observe signiﬁcant gains (17% relative) on a test data base recorded in a car. We also see signiﬁcant gains on top of FMLLR (38% relative over the baseline and 8.5% relative over FMLLR).
A CMOS band-gap reference circuit with sub 1 V operation

This paper proposes a CMOS band-gap reference (BGR) circuit, which can successfully operate with sub-1 V. In the conventional BGR circuit, the output voltage, Vref, is the sum of the built-in voltage of the diode, Vf, and the thermal voltage, VT, of kT/q multiplied by a constant. Thereby, Vref is about 1.25 V, which limits a low Vcc operation below 1 V. Conversely, in the proposed BGR circuit, Vref has been converted from the sum of two currents; one is proportional to Vf; and the other is proportional to VT. An experimental BGR circuit, which is simply composed of a CMOS opamp, diodes, and resistors, has been fabricated in a conventional double metal 0.4 /spl mu/m process. Measured Vref is 515 mV/spl plusmn/15 mV (3 /spl sigma/) for 23 samples on the same wafer at 27/spl deg/C through 125/spl deg/C.
A Unified Framework for Fitting Bayesian Semiparametric Models to Arbitrarily Censored Survival Data, Including Spatially Referenced Data

ABSTRACT A comprehensive, unified approach to modeling arbitrarily censored spatial survival data is presented for the three most commonly used semiparametric models: proportional hazards, proportional odds, and accelerated failure time. Unlike many other approaches, all manner of censored survival times are simultaneously accommodated including uncensored, interval censored, current-status, left and right censored, and mixtures of these. Left-truncated data are also accommodated leading to models for time-dependent covariates. Both georeferenced (location exactly observed) and areally observed (location known up to a geographic unit such as a county) spatial locations are handled; formal variable selection makes model selection especially easy. Model fit is assessed with conditional Cox–Snell residual plots, and model choice is carried out via log pseudo marginal likelihood (LPML) and deviance information criterion (DIC). Baseline survival is modeled with a novel transformed Bernstein polynomial prior. All models are fit via a new function which calls efficient compiled C++ in the R package spBayesSurv. The methodology is broadly illustrated with simulations and real data applications. An important finding is that proportional odds and accelerated failure time models often fit significantly better than the commonly used proportional hazards model. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
Spotter: A model based active geolocation service

The localization of Internet hosts opens space for a wide scope of applications, from targeted, location aware content provision to localizing illegal content. In this paper we present a novel probabilistic approach, called Spotter, for estimating the geographic position of Internet devices with remarkable precision. While the existing methods use landmark specific calibration for building their internal models we show that the delay-distance data follow a generic distribution for each landmark. Hence, instead of describing the delay-distance space in a landmark specific manner our proposed method handles all the calibration points together and derives a common delay-distance model. This fundamental discovery indicates that, in contrast to prior techniques, Spotter is less prone to measurement errors and other anomalies such as indirect routing. To demonstrate the robustness and the accuracy of Spotter we test the performance on PlanetLab nodes as well as on a more realistic reference set collected by CAIDA explicitly for geolocation comparison purposes. To the best of our knowledge, we are the first to use this novel ground truth containing over 23000 network routers with their geographic locations.
Non-realistic 3D object stylization

In this paper we introduce the novel paradigm of non-realistic 3D stylization, where the expressiveness of a given 3D model is manifested in the 3D shape itself, rather than only in its rendering. We analyze the input model using abstraction, simplification, and symmetrization operators to determine important features that are later represented by new geometry. Doing so, we create a stylized and expressive representation of the input that can be rendered or might be printed using a 3D printer. We conducted a user study to verify the proposed stylizations and demonstrate the approach by using standard geometry of buildings as well as natural and technical objects.
Women's Appraisals of Sexual-Assault Risk in Dating Situations

This study investigated how 165 female college students appraised their sexual-assault risk in a hypothetical dating situation. A 2 × 2 × 2 between-subjects experiment investigating the effects of male-dating-partner characteristics, story character beverage consumption, and perspective on women's risk appraisals was conducted. Multivariate analyses of variance were performed to test hypotheses regarding the feelings of the dating woman and the occurrence of sexual behaviors. Although the dating woman was rated as feeling more vulnerable on dates when alcohol was consumed, alcohol consumption did not influence ratings regarding the dating man committing nonconsensual sexual acts. Nonconsensual sexual behaviors were rated as more probable when the man had rape-congruent characteristics and when the participants were judging another woman rather than themselves. These findings suggest that women are partially accurate in making sexual-assault risk appraisals and thus may benefit from rape prevention education that specifically targets their inaccuracies.
Coordination nano-space as stage of hydrogen ortho–para conversion

The ability to design and control properties of nano-sized space in porous coordination polymers (PCPs) would provide us with an ideal stage for fascinating physical and chemical phenomena. We found an interconversion of nuclear-spin isomers for hydrogen molecule H2 adsorbed in a Hofmann-type PCP, {Fe(pz)[Pd(CN)4]} (pz=pyrazine), by the temperature dependence of Raman spectra. The ortho (o)–para (p) conversion process of H2 is forbidden for an isolated molecule. The charge density study using synchrotron radiation X-ray diffraction reveals the electric field generated in coordination nano-space. The present results corroborate similar findings observed on different systems and confirm that o–p conversion can occur on non-magnetic solids and that electric field can induce the catalytic hydrogen o–p conversion.
Immunofluorescence Identification of Mycoplasma on Agar by Use of Incident Illumination

The fluorescent-antibody method has been employed for the rapid identification of Mycoplasma colonies growing on agar plates. The method was found to be effective for detection of mixtures of Mycoplasma serotypes growing on primary isolation plates. The technique also helped to define the presence of mycoplasmas which did not produce typical colonies. It was also possible to identify Mycoplasma colonies overgrown by bacterial or fungal contaminants. Conjugates directed against 10 distinct Mycoplasma serotypes have been successfully employed in this system. One of the serotypes is a human oral isolate which has not been previously characterized.
A MULTI-STEP PREDICTION MODEL BASED ON INTERPOLATION AND ADAPTIVE TIME DELAY NEURAL NETWORK FOR TIME SERIES

The drawback of indirect multi-step-ahead prediction is error accumulation. In order to tackle this problem and improve the capacity of adaptive time delay neural network (ATNN) for prediction, a three-stage prediction model SATNN based on spline interpolation and ATNN is presented. With spline interpolation and ATNN, the impact of last prediction errors that would be iterated into the model for the next step prediction is decreased, and then the better prediction can be obtained. The annual sunspot, considered as the benchmark chaotic nonlinear systems, is selected to test the multi-step prediction model. Validation studies indicate that the proposed model is quite effective in multi-step prediction.
Site‐Specific Transfer‐Printing of Individual Graphene Microscale Patterns to Arbitrary Surfaces

massless Dirac fermions, [ 3 ] extremely high mobility, [ 4 ] special quantum Hall effect, [ 3 ] and gate voltage tunable optical transitions. [ 5 ] Those remarkable electrical and optical properties make it an attractive candidate for potential applications in integrated bipolar fi eld-effect transistors (FETs), [ 6 ] transparent electrodes for solar cells, [ 7,8 ] as well as other microscale functional devices. [ 9 ]
Hybrid active damping of LCL-filtered grid connected converter

A method for hybrid active damping in power converters connected to a weak grid using an LCL filter is proposed. It uses feedback of the grid current and capacitor voltage and is derived as an equivalent to the capacitor current feedback active damping method. A co-design procedure for the grid current controller with the proposed hybrid active damping method is presented. The robustness, system bandwidth and harmonic rejection are studied. The proposed method is applied to a single grid connected converter with variable grid inductance to investigate its ability to damp different system resonance frequencies and its effectiveness is verified via frequency domain analysis and time domain simulation.
Preoperative histological classification of primary lung cancer: accuracy of diagnosis and use of the non-small cell category

Aims—To compare the preoperative classification of lung carcinoma made on cytological and histological specimens with the postoperative classification made on the resected specimen. In addition, to find out how often the term “non-small cell lung cancer, not otherwise specified” (NSCLC) was used, and in such cases to note the final diagnosis. Methods—Between 1991 and 1995, 303 patients had a lung resection in Aberdeen for primary carcinoma. For each patient, the departmental records were examined for preoperative specimens (cytological and histological). A note was made of whether each specimen was positive or negative for malignancy and, if positive, what the cell type was. Where patients had more than one sample submitted, the most specific result was taken. Results—Fifty four per cent of patients had a correct specific preoperative diagnosis of malignancy, whereas 34% were labelled as NSCLC. Patients with squamous carcinoma were more likely to have a diagnosis of malignancy (88%) that was specifically correct (75%). Patients who had adenocarcinoma were less likely to have a preoperative diagnosis of malignancy (64%) that was specifically correct (35%). For those in whom a diagnosis of NSCLC was made, 55% turned out to have adenocarcinoma whereas 24% had squamous carcinoma. Conclusions—By adhering strictly to criteria, a high accuracy of diagnosis can be achieved for squamous carcinoma, but the diagnosis of adenocarcinoma seems to be more of a challenge. NSCLC is a useful and appropriate classification, the use of which reduces the rate of inaccurate specific diagnosis. There are occasions when pathologists can provide a more accurate diagnosis by being less precise.
dMath: Linear Algebra for Scaleout GP-GPUs

A new scalable parallel math library, dMath, is presented that demonstrates leading scaling when using intranode, internode, and hybrid-parallelism for deep learning (DL). dMath provides easy-to-use distributed primitives and a variety of domain-specific algorithms. These include matrix multiplication, convolutions, and others allowing for rapid development of scalable applications, including Deep Neural Networks (DNNs), whereas previously one was restricted to libraries that provided effective primitives for only a single GPU, like Nvidia's cuBLAS and cuDNN or DNN primitives from Nervana's neon framework. dMath enables a wide range of developers to utilize parallel and distributed hardware easily. Data is stored persistently on the GPU hardware, avoiding costly transfers between host and device. Advanced memory management techniques are utilized, including caching of transferred data and memory reuse through pooling. dMath delivers performance, portability, and productivity to its specific domain of support. dMath's caching approach addresses one of the key drawbacks of GPUs, which is to keep data sets cached and to avoid overheads of the CPU-GPU memory interface wherever possible.
An unusually effective school/university programme: the Plymouth and Peninsula Model

This article describes a novel UK school/university partnership, the Plymouth Model designed to encourage young people from disadvantaged backgrounds to aim for higher education (HE) study. The model incorporates the activity of university students, researchers and teachers working together to improve aspirations and outcomes for pupils and potentiate their own intellectual, professional and personal development. Background policy and curriculum development models are outlined and a UK study in which inner city primary and secondary school teachers’ views and pupils’ aspirations were gauged before and after the school/university partnership model was implemented. The intervention led to a significant increase in pupils’ motivation to go on to HE study and findings further suggest that the problem of aspiration and motivation for progression to HE may lie not with the pupils themselves, or with their parents or carers but with their teachers. The serious implications of the findings for policy and practice are discussed and suggestions made for future research.
ConsumSense: A Framework for Physical Consuming Behavior Prediction on Smartphones

Automatic track and prediction of consumer behaviors involve huge commercial interests and have been studied extensively in the past. We have seen very successful application of such techniques on online consuming behaviors. However, it is still very challenging to predict consumer behaviors in physical stores, because many operations in the middle are not digitized. As smartphones are becoming indispensible in our daily life, we propose to build a framework, called ConsumSense, into the smartphones that observes in close-up the physical consuming behavior of the user and predicts his/her future purchases. Our framework addresses two difficult issues: (1) how to use the limited number of sensors on a smart phone to observe and predict the consuming behavior of its user? (2) how to verify and correlate the purchases? To demonstrate the feasibility of the proposed framework, we have developed the framework on Android and evaluated it by asking 14 participants to conduct a 3-week experiment by using Easy card during their daily life. The results show that time and location are the most important contexts for predicting consuming activities and our framework can achieve a 76% prediction accuracy.
mRTS: Run-time system for reconfigurable processors with multi-grained instruction-set extensions

We present a run-time system for a multi-grained reconfigurable processor in order to provide a dynamic trade-off between performance and available area budgets for both fine- as well as coarse-grained reconfigurable fabrics as part of one reconfigurable processor. Our run-time system is the first implementation of its kind that dynamically selects and steers a performance-maximizing multi-grained instruction set under run-time varying constraints. It achieves a performance improvement of more than 2× compared to state-of-the-art run-time systems for multi-grained architectures. To elaborate the benefits of our approach further, we also compare it with offline- and online-optimal instruction-set selection schemes.
Recommending Tumblr Blogs to Follow with Inductive Matrix Completion

In microblogging sites, recommending blogs (users) to follow is one of the core tasks for enhancing user experience. In this paper, we propose a novel inductive matrix completion based blog recommendation method to effectively utilize multiple rich sources of evidence such as the social network and the content as well as the activity data from users and blogs. Experiments on a large-scale real-world dataset from Tumblr show the effectiveness of the proposed blog recommendation method.