Miracle-dz/UniFAR-FTUs huggingface dataset:
Tensor Prediction, Rademacher Complexity and Random 3-XOR

Here we study the tensor prediction problem, where the goal is to accurately predict the entries of a low rank, third-order tensor (with noise) given as few observations as possible. We give algorithms based on the sixth level of the sum-of-squares hierarchy that work with roughly $m = n^{3/2}$observations, and we complement our result by showing that any attempt to solve tensor prediction with $m = n^{3/2 - \epsilon}$ observations through the sum-of-squares hierarchy needs $n^{2 \epsilon}$ rounds and consequently would run in moderately exponential time. In contrast, information theoretically roughly $m = n$ observations suffice. This work is part of a broader agenda of studying computational vs. statistical tradeoffs through the sum-of-squares hierarchy. In particular, for linear inverse problems (such as tensor prediction) the natural sum-of-squares relaxation gives rise to a sequence of norms. Our approach is to characterize their Rademacher complexity. Moreover, both our upper and lower bounds are based on connections between this, and the task of strongly refuting random $3$-XOR formulas, and the resolution proof system.
Capturing Time-of-Flight data with confidence

Time-of-Flight cameras provide high-frame-rate depth measurements within a limited range of distances. These readings can be extremely noisy and display unique errors, for instance, where scenes contain depth discontinuities or materials with low infrared reflectivity. Previous works have treated the amplitude of each Time-of-Flight sample as a measure of confidence. In this paper, we demonstrate the shortcomings of this common lone heuristic, and propose an improved per-pixel confidence measure using a Random Forest regressor trained with real-world data. Using an industrial laser scanner for ground truth acquisition, we evaluate our technique on data from two different Time-of-Flight cameras1. We argue that an improved confidence measure leads to superior reconstructions in subsequent steps of traditional scan processing pipelines. At the same time, data with confidence reduces the need for point cloud smoothing and median filtering.
Reproducing the Hemoglobin Saturation Profile, a Marker of the Blood Oxygenation Level Dependent (BOLD) fMRI Effect, at the Microscopic Level

The advent of functional MRI in the mid-1990s has catalyzed progress pertaining to scientific discoveries in neuroscience. With the prospect of elucidating the physiological aspect of the Blood Oxygenation Level Dependent (BOLD) effect we present a computational capillary-tissue system capable of mapping venous hemoglobin saturation— a marker of the BOLD hemodynamic response. Free and facilitated diffusion and convection for hemoglobin and oxygen are considered in the radial and axial directions. Hemoglobin reaction kinetics are governed by the oxyhemoglobin dissociation curve. Brain activation, mimicked by dynamic transitions in cerebral blood velocity (CBv) and oxidative metabolism (CMRO2), is simulated by normalized changes in m = (ΔCBv/CBv)/(ΔCMRO2/CMRO2) of values 2, 3 and 4. Venous hemoglobin saturation profiles and peak oxygenation results, for m = 2, based upon a 50% and a 25% increase in CBv and CMRO2, respectively, lie within physiological limits exhibiting excellent correlation with the BOLD signal, for short-duration stimuli. Our analysis suggests basal CBv and CMRO2 values of 0.6 mm/s and 200 μmol/100g/min. Coupled CBv and CMRO2 responses, for m = 3 and m = 4, overestimate peak hemoglobin saturation, confirming the system’s responsiveness to changes in hematocrit, CBv and CMRO2. Finally, factoring in neurovascular effects, we show that no initial dip will be observed unless there is a time delay in the onset of increased CBv relative to CMRO2.
A Difference Engine for Images with Applications to Wavelet Decompression

The low level components of a new raster graphics architecture have proven to have novel uses in image reconstruction. The display hardware can be regarded as a very fast (11ns per operation) difference engine that works in two-dimensions. The speed is partly achieved by the use of custom VLSI components for the most primitive operations and this permits the video rate reconstruction of images and other signals compressed by encoding them on various polynomial bases. The paper describes the architecture and its operating parameters. The results are presented of a feasibility study into the use of the system as an image decompression system. The study also shows that the system can be applied to the decompression of spline wavelet encoded images.
Performance analysis of two-way relaying satellite mobile communication

In this paper, a two-way relaying GEO satellite communication scheme is proposed, which significantly reduces the transmission delay as compared to conventional satellite communication strategy. The outage probability of this scheme under Ricean channel model is further analyzed, and a theoretical expression is found. Simulation results show that the derived expression of outage probability is consistent with the numerical results. The BER performances of the proposed scheme under different Ricean factors are also investigated.
Statistical Approaches to Excitation Modeling in HMM-Based Speech Synthesis

In our previous study, we proposed the waveform interpolation (WI) approach to model the excitation signals for hidden Markov model (HMM)-based speech synthesis. This letter presents several techniques to improve excitation modeling within the WI framework. We propose both the time domain and frequency domain zero padding techniques to reduce the spectral distortion inherent in the synthesized excitation signal. Furthermore, we apply non-negative matrix factorization (NMF) to obtain a low-dimensional representation of the excitation signals. From a number of experiments, including a subjective listening test, the proposed method has been found to enhance the performance of the conventional excitation modeling techniques. key words: HMM-based speech synthesis, waveform interpolation, principal component analysis, non-negative matrix factorization
Oculomotor inhibition of salient distractors: Voluntary inhibition cannot override selection history

ABSTRACT Several studies have demonstrated that salient distractors can be proactively inhibited to prevent attentional capture. Traditional theories frame attentional guidance effects such as this in terms of explicit goals. However, several researchers have recently argued that that unconscious factors – such as the features of attended and ignored items on previous trials (called selection history) – play a stronger role in guiding attention and can overpower explicit goals. The current study assessed whether voluntary inhibition can overpower selection history. We directly compared both forms of top-down control by measuring overt eye movements, which offer an unambiguous measure of which location has won the competition for attention. We repeatedly found that selection history overpowered any effects of voluntary goals, such that observers were unable to avoid fixating a salient distractor of a known color if the target had been presented in that color on the previous trial. Moreover, a salient distractor of a particular color captured gaze even when the observer had voluntarily chosen this color to be the distractor color just moments before. Taken together, these experiments suggest that the ability to inhibit a salient color singleton is primarily a result of recent experience and not a result of explicit goals.
A Novel Method of Wavelet Threshold Shrinkage Based on Genetic Algorithm and Sample Entropy

In order to denoise different type of noisy signals, the genetic algorithm and sample entropy are applied to the wavelet transform threshold shrinkage (WTS) method. As the genetic algorithm is used, the parameters needed in WTS, such as the wavelet function, decomposition levels, threshold functions and threshold can be optimized automatically. For the sample entropy can measure the complexity of different signals, it is adopted in the fitness function with the root mean square error of wavelet coefficients after and before denoising process, and so the individual of genetic algorithm can be evaluated more effectively. The proposed method can achieve the optimal denoising results for different type signals, and finally the effectiveness of this method is validated by the results of simulation for four benchmark signals.
Scalable relevance feedback using click-through data for web image retrieval

Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalability, efficiency and effectiveness issues. In this paper we proposed a scalable relevance feedback mechanism using click-through data for web image retrieval. The proposed mechanism regards users' click-through data as implicit feedback which could be collected at lower cost, in larger quantities and without extra burden on the user. During RF process, both textual feature and visual feature are used in a sequential way. To seamlessly combine textual feature-based RF and visual feature-based RF, a query concept-dependent fusion strategy is automatically learned. Experimental results on a database consisting of nearly three million Web images show that the proposed mechanism is wieldy, scalable and effective.
Robustness comparison of clustering — Based vs. non-clustering multi-label classifications for image and video annotations

This paper reports robustness comparison of clustering-based multi-label classification methods versus non-clustering counterparts for multi-concept associated image and video annotations. In the experimental setting of this paper, we adopted six popular multi-label classification algorithms, two different base classifiers for problem transformation based multi-label classifications, and three different clustering algorithms for pre-clustering of the training data. We conducted experimental evaluation on two multi-label benchmark datasets: scene image data and mediamill video data. We also employed two multi-label classification evaluation metrics, namely, micro F1-measure and Hamming-loss to present the predictive performance of the classifications. The results reveal that different base classifiers and clustering methods contribute differently to the performance of the multi-label classifications. Overall, the pre-clustering methods improve the effectiveness of multi-label classifications in certain experimental settings. This provides vital information to users when deciding which multi-label classification method to choose for multiple-concept associated image and video annotations.
Rhythm: harnessing data parallel hardware for server workloads

Trends in increasing web traffic demand an increase in server throughput while preserving energy efficiency and total cost of ownership. Present work in optimizing data center efficiency primarily focuses on the data center as a whole, using off-the-shelf hardware for individual servers. Server capacity is typically increased by adding more machines, which is cheap, though inefficient in the long run in terms of energy and area. Our work builds on the observation that server workload execution patterns are not completely unique across multiple requests. We present a framework---called Rhythm---for high throughput servers that can exploit similarity across requests to improve server performance and power/energy efficiency by launching data parallel executions for request cohorts. An implementation of the SPECWeb Banking workload using Rhythm on NVIDIA GPUs provides a basis for evaluating both software and hardware for future cohort-based servers. Our evaluation of Rhythm on future server platforms shows that it achieves 4x the throughput (reqs/sec) of a core i7 at efficiencies (reqs/Joule) comparable to a dual core ARM Cortex A9. A Rhythm implementation that generates transposed responses achieves 8x the i7 throughput while processing 2.5x more requests/Joule compared to the A9.
Space-time correlation of MIMO flat Rayleigh fading channels

In order to analyze and design mobile communication systems having multiple transmit and receive antennas, a statistical multiple-input-multiple-output channel model that characterizes the received signal in both spatial and temporal domains is needed. In this work, we derive a correlation function that takes into account both the time lag, the base station antenna separation, and the mobile terminal antenna separation. The mobile terminal is assumed to be surrounded by a ring of scatterers. The properties of the space-time correlation function in some practical cases are also analyzed.
Topology matching for 3D video compression

This paper presents a new technique to reduce the storage cost of high quality 3D video. In 3D video, a sequence of 3D objects represents scenes in motion. Every frame is composed by one or several accurate 3D meshes with attached high fidelity properties such as color and texture. Each frame is acquired at video rate. The entire video sequence requires a huge amount of free disk space. To overcome this issue, we propose an original approach using Reeb graphs, which are well-known topology based shape descriptors. In particular, we take advantage of the augmented multiresolution Reeb graph properties to store the relevant information of the 3D model of each frame. This graph structure has shown its efficiency as a motion descriptor, being able to track similar nodes all along the 3D video sequence. Therefore we can describe and reconstruct the 3D models of all frames with a very low-cost data size. The algorithm has been implemented as a fully automatic 3D video compression system. Our experiments show the robustness and accuracy of the proposed technique by comparing reconstructed sequences against challenging real ones.
Stem cell therapy for chronic heart failure.

H eart failure is an increasing clinical problem. Its prevalence is estimated to be 1-2% in the Western world and its incidence approaches 1% per year. As mortality from acute coronary syndromes, such as myocardial infarction, decreases due to revascularization therapy, more patients proceed towards the development of incurable chronic heart failure: incurable because of permanent loss of cardiac contractile tissue and a subsequent decrease of left ventricular performance. Unlike other organs such as the liver, the heart lacks an adequate auto-regeneration ability, although increased proliferative activity has recently been demonstrated after injury. Current treatment options, however, do not lead to more than moderate improvement in either the patient’s quality of life or the prognosis.
INTERNET-BASED MANUFACTURING : A Perspective from the AARIA Project

Intelligent Automation, Inc. Major market trends and demographic realities are placing critical pressures on the existing manufacturing infrastructure. The Internet and related technologies offer significant new capabilities that will allow manufacturers to respond to these pressures. These capabilities are poised to create a new era of Internetbased manufacturing, where manufacturing enterprises will not just communicate over the Internet, but exist over the Internet. Manufacturing as we know it will change forever. In turn, because manufacturing and the efficient delivery of goods are such significant economic forces, these manufacturing changes can also be expected to change the Internet. The AARIA project (Autonomous Agents at Rock Island Arsenal) is a demonstration of how the Internet and related technologies can alter the future of manufacturing to respond to these pressures, and how the future of manufacturing can alter the Internet. The existing manufacturing infrastructure is experiencing significant pressures in the following forms. Distribution: Manufacturing is inherently distributed, yet existing manufacturing information systems are artificially centralized on larger and larger server computers. Current trends are for manufacturing to become even more decentralized. The pressure is on manufacturers to manage this distributed manufacturing complex better and to provide better customer service and more cost effective utilization of the involved resources. As demonstrated in the AARIA project, the Internet provides a natural platform for managing the distributed manufacturing complex. Agility: Business opportunities are rising and falling at a faster and faster rate. The manufacturing complex has to respond better to these changes and will continue to have significant pressure to reconfigure itself quickly when presented with unexpected changes[6]. As shown in the AARIA project, software agents implemented over local and wide area networks offer such essential agility features. Customization: Consumers are demanding higher and higher levels of customized products. The longterm trend is towards mass customization, where every consumer is given the exact product they want [4]. This puts significant pressure on the existing mass production facilities to become substantially more flexible. As demonstrated in the AARIA project, software agents can address this problem through the agile configuration of productive resources over the Internet for each product produced.
Theory of mind and its relationship with behavioural inhibition in Chilean preschools / Teoría de la mente y su relación con inhibición conductual en pre-escolares chilenos

Abstract This study’s main objective was to determine whether the five-step theory of mind scale is associated with responses to behavioural inhibition tasks. The data collected for this were the responses to the scale given by 65 Chilean children aged three to five from medium-low socioeconomic levels, and were derived from the changing locations, happy-sad Stroop, day-night and Dimensional Change Card Sort (DCCS) tasks they carried out. Results showed that there was a significant association between the five-step theory of mind scale and behavioural inhibition (r = .28) and behavioural inhibition with the false belief task (r = .31), controlling for age, sex and language. These data support the emergence model as the best model to describe the relationship between theory of mind and behavioural inhibition. Finally, the results are discussed and future lines of study in this subject are put forward.
Costs of Housing Crises: International Evidence

This paper analyzes the costs of housing crises in terms of GDP growth and the economic conditions under which crises are particularly costly. Housing crises are often followed by recessions that are longer than other recessions. According to empirical estimates, a housing crisis reduces the GDP growth rate in the following year on average by two percentage points and has still a considerable negative impact in the second year. One important channel through which the effect of housing crises is passed on seems to be the banking sector. In addition, our results suggest that negative wealth effects possibly cause further reductions in GDP.
Testing the velocity field in non-scale-invariant cold dark matter models

We analyze the cosmic peculiar velocity field as traced by a sample of 1184 spiral, elliptical and S0 galaxies, grouped in 704 objects. We perform a statistical analysis, by calculating the bulk flow, Cosmic Mach Number and velocity correlation function for this sample and for mock catalogs extracted from a set of N--body simulations. We run four cold dark matter (CDM) simulations: two tilted models (with spectral index $n=0.6$ and $n=0.8$), the standard model ($n=1$) and a ``blue" one ($n=1.2$), with different values of the linear bias parameter $b$. By means of a Maximum Likelihood analysis we estimate the ability of our models to fit the observations, as measured by the above statistics, and to reproduce the Local Group properties. On the basis of this analysis we conclude that the best model is the unbiased standard model $(n,~b)=(1,~1)$, even though the overall flatness of the joint likelihood function implies that one cannot strongly discriminate models in the range $0.8 \le n \le 1$, and $1 \le b \le 1.5$. Models with $b \geq 2.5$ are rejected at the $95\%$ confidence level. For $n=0.8$ the values of $b$ preferred by the present analysis, together with the {\em COBE} data, require a negligible contribution to $\Delta T/T$ by gravitational waves. Finally, the blue model, normalized to {\em COBE}, does not provide a good fit to the velocity data.
Low Resistance Electrical Layer Formation: A Simulation Study of Diffusive Rapid Thermal Process on Implanted Dopant Species for Electronics Active Devices

A simple and economical spin-on-dopants simulation technique for ultra thin layer formation is presented; the Ultra thin for the purpose of shallow junction formation in large scaled integrated technology is one of the most challenging in device fabrication. Low energy ion implantation is the most widely used technique at present to form ultra shallow junction but this method has some limitations such as silicon surface damage, however, many attempt have been made to overcome this but it seems difficult to do away with this limitation. An ultra high shallow junction formation of <; 20 nm was proposed through thermal diffusion from spin-on dopants into silicon, the study presented a determination of the junction depth and the sheet resistance of the shallow junction in order to fulfill the standard semiconductor device design requirements. Ultra shallow junction which is defined to be less than 20 nm in depth was obtained through this simulation using very simple and easy spin-on dopants technique.
Chapter XX Using Cases to Teach Usability Engineering : Designing the Tapped In Case Study

Our group has been developing an online library of hypermedia case studies in usability engineering for use in teaching courses in human-computer interaction (UCS, http://ucs.ist.psu.edu). The cases describe actual system development projects and how usability was managed in these projects. We have about a dozen partnering institutions (mainly in North America) and are continuing to develop new cases, case-based activities, and assessment tools for case-based learning. In this paper, we describe the development of the Tapped In case, a redesign of a teacher professional development online community portal (http://tappedin.org/). We will describe the process of content identification, mapping, and verification used in creating the case. These are all critical methodological issues for anyone who wants to use realistic case materials in technical education, and particularly important for anyone who wants to place such materials in online repositories for general use.
A WEB Platform Using UNL: CELTA's Showcase

Economic globalization is changing the way companies communicate. The ease and speed of accessing information and taking decisions is better for everyone on the decision chain. To speed up access to information it is important to present information in one's native language and create a language-independent communications channel. To assist business-to-business operations, the development team at the Instituto UNDL Brasil designed the pilot project "CELTA's Showcase" to demonstrate that it is possible to create a multilingual business-to-business platform using UNL.