Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Metric Learning for Saliency Detection

In this paper, we propose a novel adaptive metric learning algorithm (AML) for visual saliency detection. A key observation is that the saliency of a superpixel can be estimated by the distance from the most certain foreground and background seeds. Instead of measuring distance on the Euclidean space, we present a learning method based on two complementary Mahalanobis distance metrics: 1) generic metric learning (GML) and 2) specific metric learning (SML). GML aims at the global distribution of the whole training set, while SML considers the specific structure of a single image. Considering that multiple similarity measures from different views may enhance the relevant information and alleviate the irrelevant one, we try to fuse the GML and SML together and experimentally find the combining result does work well. Different from the most existing methods which are directly based on low-level features, we devise a superpixelwise Fisher vector coding approach to better distinguish salient objects from the background. We also propose an accurate seeds selection mechanism and exploit contextual and multiscale information when constructing the final saliency map. Experimental results on various image sets show that the proposed AML performs favorably against the state-of-the-arts.
A Case-Based Approach to Reactive Control for Autonomous Robots *

We propose a cause-based method of selecting behavior sets as an addition to traditional reactive robotic control systems. The new system (ACBARR -A Case BAsed Reactive Robotic system) provides more flexible performance in novel environments, as well as overcoming a standard "hard" problem for reactive systems, the box canyon. Additionally, ACBARR is designed in a manner which is intended to remain as close to pure reactive control as possible. Higher level reasoning and memory functions are intentionally kept to a minimum. As a result, the new reasoning does not significantly slow the system down from pure reactive speeds. not foresee. They are also incapable of taking advantage of navigational successes; even if a behavior has proven extremely successful, it is not used more than any other behavior in the system, nor is it allowed to alter to become even more successful. A third problem is that most reactive control systems do not utilize sets of behaviors; instead, they rely on a single type of behavior to guide the system. In order to achieve better robotic control, we feel that behavior sets need to be used along with adaptations of existing behaviors to new environments. One option is to have the system modify its current behavior based on immediate past experience. While useful, this is only a local response to the problem. A more global solution is to have the system select completely new sets of behaviors based on the current environment in which it finds itself.
On one-bit quantized ZF precoding for the multiuser massive MIMO downlink

We study low complexity precoding for a downlink massive MIMO multiuser system assuming a base station that employs one-bit digital-to-analog converters (DACs) in order to mitigate power usage. The use of one-bit DACs is equivalent to constraining the transmit signal to be drawn from a QPSK alphabet. While the precoding problem can be formulated using a standard maximum likelihood (ML) encoder, the implementation cost is prohibitive for massive numbers of antennas, even if a sphere encoding approach is used. Instead, we study the performance of a one-bit quantized zero-forcing precoder, and we show that it asymptotically provides the desired downlink vector with low complexity. Simulations show that the quantized ZF precoder can actually outperform the ML encoder for low to moderate signal-to-noise ratios.
Comparison of wavelet thresholding methods for industrial data compression

Nowadays in industry, data acquisition system signals are often compressed by piecewise linear trending. Many authors have indicated that compression with use of a wavelet transform provides better results. In this paper, the threshold selection algorithms, such as VisuShrink, SureShrink, BayesShrink, and NeighCoeffs are compared experimentally using real industrial data from the Damadics benchmark. The impact of the compression on the decoded signal is analysed. The results of the calculations are compared with a standard piecewise linear trending approach.
CDO Valuation: Term Structure, Tranche Structure, and Loss Distributions 1

This article describes a new approach to the risk-neutral valuation of CDO tranches, based on a general specification of the loss distribution, and the expected loss at zero default, for the reference portfolio. The new approach can describe tranche term-structures, and the generality with which the basic distributions are specified allows it to be perfectly calibrated to any set of market prices (for any number of tranches and maturities) that is arbitrage-free. Also, given a set of arbitrage-free market prices, arbitrage-free interpolated term structures (plots of tranche price versus maturity for a given tranche) and tranche structures (plots of tranche price versus tranche for a given maturity), as well as implied loss distributions, can be obtained, allowing bespoke tranches to be priced. The marking to market of tranche prices, and the establishment of forward-start premiums for the index are discussed. An efficient linear programming approach to valuation, essential to the implementation, is also described. The article also makes use of a new, simple yet general, approach to the problem of unequal notionals, and of random, time-dependent, risk-neutral, recovery rates. keywords: collateralized debt obligations, risk-neutral valuation, term structure
Overlapping, Additive and Counterregulatory Effects of Type II and I Interferons on Myeloid Dendritic Cell Functions

Dendritic cells (DCs) are central player in immunity by bridging the innate and adaptive arms of the immune system (IS). Interferons (IFNs) are one of the most important factors that regulate both innate and adaptive immunity too. Thus, the understanding of how type II and I IFNs modulate the immune-regulatory properties of DCs is a central issue in immunology. In this paper, we will address this point in the light of the most recent literature, also highlighting the controversial data reported in the field. According to the wide literature available, type II as well as type I IFNs appear, at the same time, to collaborate, to induce additive effects or overlapping functions, as well as to counterregulate each one's effects on DC biology and, in general, the immune response. The knowledge of these effects has important therapeutic implications in the treatment of infectious/autoimmune diseases and cancer and indicates strategies for using IFNs as vaccine adjuvants and in DC-based immune therapeutic approaches.
Reverse link performance of packet data with LDPC and soft handoff in cellular CDMA

Performance analysis of data services is studied in CDMA network by incorporating Low Density Parity Check (LDPC) codes in presence of soft handoff. This scheme is found to enhance throughput and reduce delay and packet error rate significantly. A stop and wait ARQ has been assumed. Both the cases of coded and un-coded data transmission are investigated.
Modern concept of vascular cognitive impairment.

BACKGROUND Vascular cognitive impairment (VCI) has superseded vascular dementia and multi-infarct dementia as the concept to be used in cognitive decline due to cerebrovascular disease. METHOD The literature was reviewed with regard to the concept of VCI and its incidence, pathophysiological substrate, clinical features and management. RESULTS A change in the diagnostic paradigm from the current Alzheimer-based definition of vascular dementia to VCI will allow the earlier identification of cases and will identify a different population from that recognized using the current criteria for vascular dementia. CONCLUSIONS Case identification at the earliest possible stage affords the greatest opportunity for treatment that may slow the rate of progression.
JAAVR: Introducing the Next Generation of Security-Enabled RFID Tags

JAAVR stands for Just Another AVR, is a clone of the popular ATmega128 microprocessor, and is used as the core component of a security-enabled RFID tag. First, we evaluate different hardware designs using JAAVR to communicate via ISO 14443A. Second, we implement AES, Gr{\o}stl and Elliptic Curve Cryptography (ECC) and present several new runtime and low-memory records. Third, we add those assembly-optimized implementations to our RFID platform and investigate their impact in chip area and power consumption. Our designs are fully synthesizable as ASIC and FPGA and were tested using a discrete analog front-end and a standard RFID reader.
Fast Automatic Video Retrieval using Web Images

We describe a real-time video retrieval framework based on short text input queries in which weakly labelled training samples from the web are obtained, after the query is known. Concept discovery methods in such a setting train hundreds of detectors at test time and apply them to every frame in the video database. Hence, they are not practical for use in a text based video retrieval setting. We show that an efficient visual representation for a new query can be constructed on-line that enables matching against the test set in real-time. We evaluate a few combinations of encoding, pooling, and matching schemes that are efficient and find that such a system can be built with surprisingly simple and well-known components. We are not only able to construct and apply query models in real-time, but with the help of a re-ranking scheme, we also outperform state-of-the-art methods by a significant margin.
Course of illness, hippocampal function, and hippocampal volume in major depression

Studies have examined hippocampal function and volume in depressed subjects, but none have systematically compared never-treated first-episode patients with those who have had multiple episodes. We sought to compare hippocampal function, as assessed by performance on hippocampal-dependent recollection memory tests, and hippocampal volumes, as measured in a 1.5-T magnetic resonance imager, in depressed subjects experiencing a postpubertal onset of depression. Twenty never-treated depressed subjects in a first episode of depression were compared with matched healthy control subjects. Seventeen depressed subjects with multiple past episodes of depression were also compared with matched healthy controls and to the first-episode patients. Both first- and multiple-episode depressed groups had hippocampal dysfunction apparent on several tests of recollection memory; only depressed subjects with multiple depressive episodes had hippocampal volume reductions. Curve-fitting analysis revealed a significant logarithmic association between illness duration and hippocampal volume. Reductions in hippocampal volume may not antedate illness onset, but volume may decrease at the greatest rate in the early years after illness onset.
Local computation of lightness on articulated surrounds

Lightness of a grey target on a uniform light (or dark) surround changes by articulating the surround (articulation effect). To elucidate the processing of lightness underlying the articulation effect, the present study introduced transparency over a dark surround and investigated its effects on lightness of the target. The transparency was produced by adding a contiguous external field to the dark surround while keeping local stimulus configuration constant. Results showed that the target lightness did not change on the articulated surround when a dark transparent filter was perceived over the target, although it did on the uniform surround. These results suggest that image decomposition into a transparent filter and an underlying surface does not necessarily change lightness of the surface if the surface is articulated. Moreover, the present study revealed that articulating the surround does not always enhance lightness contrast; it can reduce the contrast effect when the target luminance is not the highest within the surround. These findings are consistent with the theoretical view that lightness perception on articulated surfaces is determined locally within a spatially limited region, and they also place a constraint on how the luminance distribution within the limited region is scaled.
Evaluation of intelligibility of noisy whisper enhanced by compressive sensing

Noisy whisper contaminated by different types of noise are enhanced by compressive sensing method. The intelligibility performance of the enhanced whisper is measured using the short time objective index (STOI). To assess the effect of spectra density on compressive sensing, the real-valued discrete Gabor transform is used to transform the noisy whisper into the time-frequency domain. Experimental results show that, similar to conventional speech enhancement algorithm, the compressive sensing based speech enhancement method can not efficiently improve intelligibility of the whisper.
Instrumented and active exoskeletons for human anatomical joints: Design methodology and applications

This paper addresses the design of instrumented single joint and multi-joints active orthoses for musculoskeletal and neuromuscular disorder exploration and functional rehabilitation. The use of these multi-contact exoskeletons, operating a selective limb joint mobilization, allows the measurement and the control of physiological parameters (instantaneous helical axis (IHA) motion, joint motion and torque) of each individual anatomical joint. Passive joints have to be added into the kinematic chain of the exoskeleton in order to eliminate residual stresses in limb/orthose interaction due to misalignment between the device principal axis of rotation and the IHA of the anatomical joint. The kinematic design and the control of spatial orthotic mechanisms to obtain an adaptation and a best-fit to the joints kinematics are discussed afterward. Examples of active orthosis design for knee, elbow joint and lower limbs are also given.
The methodic of calculations of the contamination of the ground waters on the irigated lands and the ajoined territories

The general methodic of calculations of the contamination spreading of the different origin in the ground waters on the irrigated lands and ajoined territories on the base of the modern mathematical models of the masstransfer is proposed. Some features of the calculation models and the criterias of its using are analysed. The methodic example of the analytic solution of the masstransfer problem for the case of the homogeneous watersaturated media is presented.
A Recommendation Cascade for E-learning

This paper is concerned with the presentation of a collaborative recommendation system that implements a cascade of strategies in order to support the learning process. Similarities between learners are determined by taking advantage of the underlying implicit or explicit personalization and of the non-personalised modes of interaction. In the personalised approach implicit profiles are based on the patterns of behaviour of learners, while explicit profiles are generated from the results of a questionnaire on learning style. The non-personalisation approach relies on the cumulative intervention of a community of learners implied by the recorded frequency of the usage of objects by learners, and by the expert rating of objects by teachers. Content-based and collaborative approaches are combined into a hybrid model that widens the range of objects to which a learner may be exposed. The quality of service of the recommendation system is evaluated by considering the accuracy of its predictive capability on a publicly available data set.
Oral prednisolone for preschool children with acute virus-induced wheezing.

BACKGROUND Attacks of wheezing induced by upper respiratory viral infections are common in preschool children between the ages of 10 months and 6 years. A short course of oral prednisolone is widely used to treat preschool children with wheezing who present to a hospital, but there is conflicting evidence regarding its efficacy in this age group. METHODS We conducted a randomized, double-blind, placebo-controlled trial comparing a 5-day course of oral prednisolone (10 mg once a day for children 10 to 24 months of age and 20 mg once a day for older children) with placebo in 700 children between the ages of 10 months and 60 months. The children presented to three hospitals in England with an attack of wheezing associated with a viral infection; 687 children were included in the intention-to-treat analysis (343 in the prednisolone group and 344 in the placebo group). The primary outcome was the duration of hospitalization. Secondary outcomes were the score on the Preschool Respiratory Assessment Measure, albuterol use, and a 7-day symptom score. RESULTS There was no significant difference in the duration of hospitalization between the placebo group and the prednisolone group (13.9 hours vs. 11.0 hours; ratio of geometric means, 0.90; 95% confidence interval, 0.77 to 1.05) or in the interval between hospital admission and signoff for discharge by a physician. In addition, there was no significant difference between the two study groups for any of the secondary outcomes or for the number of adverse events. CONCLUSIONS In preschool children presenting to a hospital with mild-to-moderate wheezing associated with a viral infection, oral prednisolone was not superior to placebo. (Current Controlled Trials number, ISRCTN58363576.)
Identifying Opportunities for Byte-Addressable Non-Volatile Memory in Extreme-Scale Scientific Applications

Future exascale systems face extreme power challenges. To improve power efficiency of future HPC systems, non-volatile memory (NVRAM) technologies are being investigated as potential alternatives to existing memories technologies. NVRAMs use extremely low power when in standby mode, and have other performance and scaling benefits. Although previous work has explored the integration of NVRAM into various architecture and system levels, an open question remains: do specific memory workload characteristics of scientific applications map well onto NVRAMs' features when used in a hybrid NVRAM-DRAM memory system? Furthermore, are there common classes of data structures used by scientific applications that should be frequently placed into NVRAM? In this paper, we analyze several mission-critical scientific applications in order to answer these questions. Specifically, we develop a binary instrumentation tool to statistically report memory access patterns in stack, heap, and global data. We carry out hardware simulation to study the impact of NVRAM for both memory power and system performance. Our study identifies many opportunities for using NVRAM for scientific applications. In two of our applications, 31% and 27% of the memory working sets are suitable for NVRAM. Our simulations suggest at least 27% possible power savings and reveal that the performance of some applications is insensitive to relatively long NVRAM write-access latencies.
Virtual machines and data security

Our concern is the ability of the computing system to ensure that data under its control is accessed only in accordance with the explicit intention of the owner of the data, as expressed in the directory or access control table of the system. We intend to use VM/370 as the base system for a study of how the security of data may be compromised. Our goal for this study is to be better able to evaluate different types of hardware and software system architectures with regard to their ability to provide security.
Unequal Error Protection Rateless Codes for Scalable Information Delivery in Mobile Networks

In this paper, we are interested in the design and performance of unequal error protection (UEP) rateless codes. These codes have interesting properties in the deployment of mobile peer to peer (MP2P) and mobile broadcast systems. As our main contribution, we propose a new UEP rateless code structure that is composed of a bank of precoders and a common rateless code. Through the bank of precoders, information layers are first expanded into encoded layers with a diminishing coding rate as the priority of the layer increases. The output of precoders are then concatenated and fed into a rateless encoder. The output of the rateless encoder naturally constitutes UEP encoding blocks carrying disproportionately more information on the higher priority layers. The decoder at the receiver end performs the inverse operations to recover each layer separately. We evaluate our proposed scheme comparing against the alternative solutions. Results show that over a broad class of rateless code structures the proposed scheme can substantially reduce the time required to recover higher priority layers while minimally impacting the time required to recover the lower priority layers.
Multidimensional scaling and visualization of large molecular similarity tables

Multidimensional scaling (MDS) is a collection of statistical techniques that attempt to embed a set of patterns described by means of a dissimilarity matrix into a low‐dimensional display plane in a way that preserves their original pairwise interrelationships as closely as possible. Unfortunately, current MDS algorithms are notoriously slow, and their use is limited to small data sets. In this article, we present a family of algorithms that combine nonlinear mapping techniques with neural networks, and make possible the scaling of very large data sets that are intractable with conventional methodologies. The method employs a nonlinear mapping algorithm to project a small random sample, and then “learns” the underlying transform using one or more multilayer perceptrons. The distinct advantage of this approach is that it captures the nonlinear mapping relationship in an explicit function, and allows the scaling of additional patterns as they become available, without the need to reconstruct the entire map. A novel encoding scheme is described, allowing this methodology to be used with a wide variety of input data representations and similarity functions. The potential of the algorithm is illustrated in the analysis of two combinatorial libraries and an ensemble of molecular conformations. The method is particularly useful for extracting low‐dimensional Cartesian coordinate vectors from large binary spaces, such as those encountered in the analysis of large chemical data sets. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 488–500, 2001