Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuro-Fuzzy Control of Antilock Braking System Using Variable-Structure-Systems-Based Learning Algorithm

A neuro-fuzzy adaptive control approach for nonlinear systems with model uncertainties is proposed. The implemented control scheme consists of a proportional plus derivative controller that is provided both to guarantee global asymptotic stability in compact space and as an inverse reference model of the response of the controlled system. Its output is used as an error signal by an on-line learning algorithm to update the parameters of a neuro-fuzzy feedback controller. The latter is able to gradually replace the conventional controller from the control of the system. The proposed learning algorithm makes direct use of the variable structure systems theory and establishes a sliding motion in terms of the neuro-fuzzy controller parameters. An integrating term has been additionally applied to the overall control signal of the two controllers and the performance of the control scheme has been tested on the wheel slip control problem within an antilock breaking system model. The analytical claims have been justified under the existence of model uncertainties and large initial errors.
Fast Learning with Nonconvex L1-2 Regularization

Convex regularizers are often used for sparse learning. They are easy to optimize, but can lead to inferior prediction performance. The difference of $\ell_1$ and $\ell_2$ ($\ell_{1-2}$) regularizer has been recently proposed as a nonconvex regularizer. It yields better recovery than both $\ell_0$ and $\ell_1$ regularizers on compressed sensing. However, how to efficiently optimize its learning problem is still challenging. The main difficulty is that both the $\ell_1$ and $\ell_2$ norms in $\ell_{1-2}$ are not differentiable, and existing optimization algorithms cannot be applied. In this paper, we show that a closed-form solution can be derived for the proximal step associated with this regularizer. We further extend the result for low-rank matrix learning and the total variation model. Experiments on both synthetic and real data sets show that the resultant accelerated proximal gradient algorithm is more efficient than other noncovex optimization algorithms.
Zigzag super cut-off CMOS (ZSCCMOS) block activation with self-adaptive voltage level controller: an alternative to clock-gating scheme in leakage dominant era

A block activation/deactivation technique uses zigzag super cut-off CMOS to improve wake up time by 8/spl times/ in 0.6 /spl mu/m CMOS versus super cutoff CMOS. Our clock-gating substitute achieves a 200 ps wake-up time and 3 orders of magnitude leakage reduction for leakage dominant LSI's.
Misleading tacrolimus concentration value in blood taken from a catheter used for tacrolimus administration.

PURPOSE A misleading blood tacrolimus concentration (BTC) value caused by the contamination of a central venous catheter previously used for tacrolimus administration is described. SUMMARY A 59-year-old woman with severe chronic obstructive pulmonary disease successfully underwent double lung transplantation. In the intensive care unit, she received a continuous i.v. infusion of tacrolimus from days 1 to 5 after transplantation through the distal lumen of a polyurethane triple-lumen central venous catheter. The catheter lumen was flushed twice a day with 0.9% sodium chloride injection. The proximal lumen was used for blood sampling after being flushed; the first 10 mL of blood was discarded. BTCs determined in whole blood one, four, and five days after transplantation were within the therapeutic range of 5-15 ng/mL. On day five the patient was transferred to the thoracic surgery ward and was switched to oral tacrolimus 1.5 mg twice daily. The BTC on day 6 was unexpectedly high at 134.5 ng/mL. The patient's clinical status was normal, and no signs of tacrolimus toxicity were observed. On day 7, blood samples were drawn from a peripheral vein and simultaneously through the central venous catheter. Although the central venous catheter had not been exposed to tacrolimus during the preceding two days, it yielded blood with a BTC eight times higher than the BTC in blood from the peripheral vein (41.4 ng/mL versus 5.1 ng/mL). CONCLUSION The collection of blood from a central venous catheter lumen that had been used for tacrolimus administration resulted in a BTC about eight times higher than what was measured in peripheral blood.
Neurodynamical modeling of arbitrary visuomotor tasks

El aprendizaje visuomotor condicional es un paradigma en el que las asociaciones estimulo-respuesta se aprenden a traves de una recompensa. Un experimento tipico se desarrolla de la siguiente forma: cuando se presenta un estimulo a un sujeto, este debe decidir que accion realizar de entre un conjunto. Una vez seleccionada la accion, el sujeto recibira una recompensa en el caso de que la accion escogida sea correcta. En este tipo de tareas interactuan distintas regiones cerebrales, entre las que destacan el cortex prefrontal, el cortex premotor, el hipocampo y los ganglios basales. El objetivo de este proyecto consiste en estudiar la dinamica neuronal subyacente a esta clase de tareas a traves de modelos computacionales. Proponemos el termino processing pathway para describir como ejecuta esta tarea el cerebro y explicar los roles e interacciones entre las distintas areas cerebrales. Ademas, tratamos el procesamiento anomalo en una hipotesis neurodinamica de la esquizofrenia.
GPU-accelerated joint 1D and 2D barcode localization on smartphones

The built-in cameras and powerful processors have turned smartphones into ubiquitous barcode scanners. In smartphone-based barcode scanning, barcode localization is an important preprocessing step that quickly scans the entire camera image and passes barcode candidates to the actual decoder. This paper presents the implementation steps of a robust joint 1D and 2D barcode localization algorithm on the mobile GPU. The barcode probability maps are derived from the structure matrix and the color of the individual pixels. The different steps of the localization algorithm are formulated as OpenGL ES 2.0 fragment shaders and both 1D and 2D barcode saliency maps are computed directly on the graphics hardware. The presented method can detect barcodes at various scales and orientations at 6 frames per second in HD resolution images on current generation smartphones.
An Optimal Reduced Representation of a MoG with Applicatios to Medical Image Database Classification

This work focuses on a general framework for image categorization, classification and retrieval that may be appropriate for medical image archives. The proposed methodology is comprised of a continuous and probabilistic image representation scheme using Gaussian mixture modeling (MoG) along with information-theoretic image matching measures (KL). A category model is obtained by learning a reduced model from all the images in the category. We propose a novel algorithm for learning a reduced representation of a MoG, that is based on the unscented-transform. The superiority of the proposed method is validated on both simulation experiments and categorization of a real medical image database.
Feasible cooperative communication with IEEE 802.11a based devices for multi-hop networks

Wireless multi-hop networks are candidate communication infrastructures in developing regions because their installation cost is quite low comparing to that for conventional wired networks. Reliable and scalable dissemination mechanism is required in practical multi-hop networks. Cooperative communication is a new scheme to improve communication performance to realize a reliable dissemination mechanism. However, high mobility networks have a big issue for autonomous control for cooperative communication. Additionally, conventional cooperative schemes cannot reduce packet collisions even if packet collisions are a big degradation factor of performance in dense multi-hop networks. We have discussed a new cooperative communication scheme that employs Orthogonal Frequency-Division Multiplexing (OFDM). Our scheme can improve communication performance and reduce packet collisions based on distributed control matter. Our advance evaluation has shown a good potential of the proposed scheme to improve communication performance in multi-hop network simulations. On the contrary, the feasibility of the proposed scheme with a real hardware device was not shown. This paper evaluates the feasibility of our original cooperative communication scheme on IEEE 802.11a standard devices. Almost all conventional cooperative communication schemes require a special physical layer and a media access control mechanism. We have focused on a characteristic of OFDM, where a receiver can demodulate multiple signals within a guard interval period. The experimental evaluation has been performed with software defined radio devices (USRP B200). We have implemented multiple transmitters, a receiver and a fading simulator for each transmitter with two USRP B200 devices. The results can show that the proposed scheme works well on IEEE 802.11a standard devices and improves communication performance in practical situations. Hence, the proposed scheme will be a new candidate of cooperative communication mechanisms that can employ general consumer devices and can realize effective dissemination mechanism for multi-hop networks.
The role of intervention mapping in designing disease prevention interventions: A systematic review of the literature

Objective To assess the role of Intervention Mapping (IM) in designing disease prevention interventions worldwide. Methods Systematic search and review of the relevant literature—peer-reviewed and grey—was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Findings Only five of the twenty two included studies reviewed were RCTs that compared intervention using IM protocol with placebo intervention, and provided the outcomes in terms of percentage increase in the uptake of disease-prevention programmes, and only one of the five studies provided an effect measure in the form of relative risk (RR = 1.59, 95% CI = 1.08–2.34, p = 0.02). Of the five RCTs, three were rated as strong evidences, one as a medium evidence and one as a weak evidence, and they all reported statistically significant difference between the two study groups, with disease prevention interventions that have used the intervention mapping approach generally reported significant increases in the uptake of disease-prevention interventions, ranging from 9% to 28.5% (0.0001 ≤ p ≤ 0.02), On the other hand, all the 22 studies have successfully identified the determinants of the uptake of disease prevention interventions that is essential to the success of disease prevention programmes. Conclusion Intervention Mapping has been successfully used to plan, implement and evaluate interventions that showed significant increase in uptake of disease prevention programmes. This study has provided a good understanding of the role of intervention mapping in designing disease prevention interventions, and a good foundation upon which subsequent reviews can be guided.
Accuracy of predictive ability measures for survival models

One aspect of an analysis of survival data based on the proportional hazards model that has been receiving increasing attention is that of the predictive ability or explained variation of the model. A number of contending measures have been suggested, including one measure, R2(β), which has been proposed given its several desirable properties, including its capacity to accommodate time‐dependent covariates, a major feature of the model and one that gives rise to great generality. A thorough study of the properties of available measures, including the aforementioned measure, has been carried out recently. In that work, the authors used bootstrap techniques, particularly complex in the setting of censored data, in order to obtain estimates of precision. The motivation of this work is to provide analytical expressions of precision, in particular confidence interval estimates for R2(β). We use Taylor series approximations with and without local linearizing transforms. We also consider a very simple expression based on the Fisher's transformation. This latter approach has two great advantages. It is very easy and quick to calculate, and secondly, it can be obtained for any of the methods given in the recent review. A large simulation study is carried out to investigate the properties of the different methods. Finally, three well‐known datasets in breast cancer, lymphoma and lung cancer research are given as illustrations. Copyright © 2017 John Wiley & Sons, Ltd.
Linear-size approximate voronoi diagrams

Given a set <i>S</i> of <i>n</i> points in IR<sup><i>d</i></sup>, a (<i>t,</i> ε)-<i>approximate Voronoi diagram (AVD)</i> is a partition of space into constant complexity cells, where each cell <i>c</i> is associated with <i>t</i> representative points of <i>S,</i> such that for any point in <i>c,</i> one of the associated representatives approximates the nearest neighbor to within a factor of (1 + ε). The goal is to minimize the number and complexity of the cells in the AVD. We show that it is possible to construct an AVD consisting of <i>O</i>(<i>n</i>/ε<sup><i>d</i></sup>) cells for <i>t</i> = 1, and <i>O</i>(<i>n</i>) cells for <i>t</i> = <i>O</i>(1/ε<sup>(<i>d</i>-1)/2</sup>). In general, for a real parameter 2 ≤ γ ≤ 1/ε, we show that it is possible to construct a (<i>t,</i> ε)-AVD consisting of <i>O</i>(<i>n</i>γ<sup><i>d</i></sup>) cells for <i>t</i> = <i>O</i>(1/(εγ)<sup>(<i>d</i>-1)/2</sup>). The cells in these AVDs are cubes or differences of two cubes. All these structures can be used to efficiently answer approximate nearest neighbor queries. Our algorithms are based on the well-separated pair decomposition and are very simple.
Data description in subspaces

We investigate how the boundary of a data set can be obtained in case of (very) low sample sizes. This boundary can be used to detect if new objects resemble the data set and therefore make the subsequent classification more confident. When a large number of training objects is available it is possible to directly estimate the density. After thresholding the probability density a boundary around the data is obtained. However, in the case of very low sample sizes, extrapolations have to be performed. In this paper we propose a simple method based on nearest neighbor distances which is capable of finding data boundaries in these low sample sizes. It appears to be especially useful when the data is distributed in subspaces.
Performance evaluation of multirate DS-CDMA communication systems with adaptive antennas

Adaptive antennas, with spatial processing, used in code division multiple access (CDMA) systems can enhance range, reliability, and capacity. Moreover, the adaptive beamforming technologies can remove unwanted noise and interference from the received signal. In this paper, we propose the adaptive direct sequence (DS) CDMA antenna receivers and compare their performances in three existing multirate methodologies—variable processing gain (VPG), variable chip rate, and multicode systems for multiuser communications in multipath fading channels. Simulation results show that the processing powers of both narrowband and wideband adaptive antennas are not enough. We propose a powerful processing technique named Wiener Code Filter (WCF) to retrieve the shortcomings. Mean square error (MSE) analyses are also given in this paper. Some simulation examples are given to compare the performances of the proposed multirate structures. Copyright © 2010 John Wiley & Sons, Ltd.
From Sequences to Papers: An Information Retrieval Exercise

Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences that might be useful in the explanation of the function or activity of the newly discovered ones. In current web sites and data bases of sequences there are, usually, a set of paper references linked to each sequence. Those links are very useful because the papers describe useful information concerning the sequences. They are, therefore, a good starting point to look for relevant information related to a set of sequences. One way is to implement such approach is to do a blast with the new decoded sequences, and collect similar sequences. Then one looks at the papers linked with the similar sequences. Most often the number of retrieved papers is small and one has to search large data bases for relevant papers. In this paper we propose a process of generating a classifier based on the initially set of relevant papers that are directly linked to the similar sequences retrieved and use that classifier to automatically enlarge the set of relevant papers by searching the MEDLINE using the automatically constructed classifier. We have empirically evaluated our proposal and report very promising results.
The Method of Location Error Detection and Correcting in Smart Home Environments

The location awareness system is an essential factor for the development of low cost sensor networks for use in the smart home environments and ubiquitous networking. This paper addresses the problem of tracking a moving intelligent robot using the pharos indoor location system. Our motivating applications include intelligent robot navigation, where location sensors provide position information to a moving robot. All of these applications require the position of a device moving at human speeds to be tracked. Ubiquitous indoor environments often contain substantial amounts of metal and other such reflective materials that affect the propagation of radio frequency signals in non-trivial ways, causing severe multi-path effects, dead-spots, noise, and interference. In this paper, we address the location error detection and correcting problems of the sensor network platform with RF and ultrasonic for location tracking system. Especially we present a novel detecting error of location and correcting using LQI that is particularly well suited to support context-aware smart home computing. It is achieved by considering the speed variance of the moving object and the corrected the interference errors. This proposed scheme applied the method of an error correct to the mobile object. We brought a 5% efficiencies comparing with a three existing schemes (listener inference algorithm). And The system called Pharos, aims to combine the advantages of real-time tracking systems that implement distributed environment with regardless of infrastructure or infrastructure-less wireless sensor networks.
Towards Interactive Agents that Infer Emotions from Voice and Context Information

Conversational agents are increasingly being used for training of social skills. One of their most important benefits is their ability to understand the user`s emotions, to be able to provide natural interaction with humans. However, to infer a conversation partner’s emotional state, humans typically make use of contextual information as well. This work proposes an architecture to extract emotions from human voice in combination with the context imprint of a particular situation. With that information, a computer system can achieve a more human-like type of interaction. The architecture presents satisfactory results. The strategy of combining 2 algorithms, one to cover ‘common cases’ and another to cover ‘borderline cases’ significantly reduces the percentage of mistakes in classification. The addition of context information also increases the accuracy in emotion inferences.
Dynamic compression of rabbit adipose‐derived stem cells transfected with insulin‐like growth factor 1 in chitosan/gelatin scaffolds induces chondrogenesis and matrix biosynthesis

Articular cartilage is routinely subjected to mechanical forces and growth factors. Adipose‐derived stem cells (ASCs) are multi‐potent adult stem cells and capable of chondrogenesis. In the present study, we investigated the comparative and interactive effects of dynamic compression and insulin‐like growth factor‐I (IGF‐I) on the chondrogenesis of rabbit ASCs in chitosan/gelatin scaffolds. Rabbit ASCs with or without a plasmid overexpressing of human IGF‐1 were cultured in chitosan/gelatin scaffolds for 2 days, then subjected to cyclic compression with 5% strain and 1 Hz for 4 h per day for seven consecutive days. Dynamic compression induced chondrogenesis of rabbit ASCs by activating calcium signaling pathways and up‐regulating the expression of Sox‐9. Dynamic compression plus IGF‐1 overexpression up‐regulated expression of chondrocyte‐specific extracellular matrix genes including type II collagen, Sox‐9, and aggrecan with no effect on type X collagen expression. Furthermore, dynamic compression and IGF‐1 expression promoted cellular proliferation and the deposition of proteoglycan and collagen. Intracellular calcium ion concentration and peak currents of Ca2+ ion channels were consistent with chondrocytes. The tissue‐engineered cartilage from this process had excellent mechanical properties. When applied together, the effects achieved by the two stimuli (dynamic compression and IGF‐1) were greater than those achieved by either stimulus alone. Our results suggest that dynamic compression combined with IGF‐1 overexpression might benefit articular cartilage tissue engineering in cartilage regeneration. J. Cell. Physiol. 227: 2003–2012, 2012. © 2011 Wiley Periodicals, Inc.
Motion Tracking of Discontinuous Sea Ice

The purpose of this paper is twofold: 1) to develop a high-resolution sea ice motion tracking system at the geospatial mesoscale (1-100 km2) and 2) to propose an algorithm that measures motion at close proximity to discontinuous regions. Here, we present a motion tracking system that computes differential motion at 400 m resolution and validate the accuracy/precision of this system via four studies. The first study measures the accuracy against displacements measured from in situ Global Positioning System (GPS) buoys deployed at the Sea-ice Experiment: Dynamic Nature of the Arctic (SEDNA) and the Surface HEat Budget of the Arctic Ocean (SHEBA) experiments. The estimates are found to be statistically comparable with GPS, with an average error of 361.9 and 600.6 m for the experiments, respectively. The second study compares the estimated displacements to those measured by the RADARSAT Geophysical Processing System. A precision error of 75.7 m is found between the two motion tracking systems. The third study uses intensity warping of randomly sampled measurements to evaluate discontinuous motion tracking. A one-tailed Wilcoxon signed rank test is used to validate these measurements at α = 0.01. Results from this paper prove that anisotropic smoothing produces significantly smaller errors at discontinuous locations (W = 4240 and p <; 0.001) over conventional isotropic smoothing. The fourth study compares displacements measured by anisotropic smoothing against manual measurements. This paper demonstrates an average reduction of the estimation error by 50 m with the use of anisotropic smoothing over the conventional isotropic smoothing.