Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing active vibration control with minimum order for flexible structure

This paper concerned with the designing active control for flexible structure. The structure has 4 stories and each story is modeled such that it has a single degree of freedom in the transverse direction and one more degree of freedom in the angle of torsion around the centroid of the story. The model of structure, absorber and stroke are combined such that the number of state is 30. The order of state is reduced up to 7th order by using the balanced truncation. The active control is designed by using the H∞ -control theory.
Two-norm optimal controllers deliver optimal robust disturbance attenuation

This paper shows that, in the SISO case, optimal mixed-sensitivity 2-norm controllers are also solutions to the optimal robust disturbance attenuation problem (ORDAP). That is, they deliver robust sensitivity reduction despite unstructured uncertainty at the optimal level. We explicitely identify one set of ORDAP weights for which such a controller is ORDAP optimal. Functional analysis duality theory is used to establish our conclusions.
Assessment of differences in linear growth among populations in the WHO Multicentre Growth Reference Study

Aim: To assess differences in length/height among populations in the WHO Multicentre Growth Reference Study (MGRS) and to evaluate the appropriateness of pooling data for the purpose of constructing a single international growth standard. Methods: The MGRS collected growth data and related information from 8440 affluent children from widely differing ethnic backgrounds and cultural settings (Brazil, Ghana, India, Norway, Oman and the USA). Eligibility criteria included breastfeeding, no maternal smoking and environments supportive of unconstrained growth. The study combined longitudinal (birth to 24 mo) and cross‐sectional (18–71 mo) components. For the longitudinal component, mother–infant pairs were enrolled at delivery and visited 21 times over the next 2 y. Rigorous methods of data collection and standardized procedures were applied across study sites. We evaluate the total variability of length attributable to sites and individuals, differences in length/height among sites, and the impact of excluding single sites on the percentiles of the remaining pooled sample. Results: Proportions of total variability attributable to sites and individuals within sites were 3% and 70%, respectively. Differences in length and height ranged from −0.33 to +0.49 and −0.41 to +0.46 standard deviation units (SDs), respectively, most values being below 0.2 SDs. Differences in length on exclusion of single sites ranged from −0.10 to +0.07, −0.07 to +0.13, and −0.25 to +0.09 SDs, for the 50th, 3rd and 97th percentiles, respectively. Corresponding values for height ranged from −0.09 to +0.08, −0.12 to +0.13, and −0.15 to +0.07 SDs.
OPTIMUM UPDATE STEP FOR MOTION-COMPENSATED LIFTED WAVELET CODING ( Invited Paper )

In motion-compensated lifted wavelet video coding, the update step typically reverses the motion vectors from the prediction step. Where motion compensation is not invertible, heuristic rules are used for the update step. This paper derives a closed-form expression for the optimal update step for a given general linear prediction step and applies the result to motion-compensated wavelet coding. Our analysis justifies using reversed motion vectors, where possible, and yields new results on proper inversion of subpixel motion compensation and optimal treatment of motion discontinuities. The analysis is extended to longer filters such as biorthogonal 5/3 wavelet transform to show the applicability of the proposed method. Experimental results confirm that optimizing the update step improves the ratedistortion performance for a motion-compensated wavelet video coder and provide justification for heuristics used in conventional techniques.
Topology Simulation for Aeronautical Communication Protocols with ns-3 and DCE

The currently used aeronautical communication systems have huge limitations and need to be replaced in order to meet the requirements for air-ground communications due to a constant growth in air traffic. In order to develop, test and optimize protocols it is desired to have proper tools to simulate large scale (up to global) networks of ground and mobile stations. We propose an ns-3 topology module that is tailor fit for aeronautical communication protocols, compatible with typical location information and provides propagation parameters for communications between nodes.
Host-specific HCV evolution and response to the combined interferon and ribavirin therapy

Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.
Unsupervised Variable Selection: when random rankings sound as irrelevancy

Whereas the variable selection has been extensively studied in the context of supervised learning, the unsupervised variable selection has attracted attention of researchers more recently as the available amount of unlabeled data has exploded. Many unsupervised variable ranking criteria were proposed and their relevance is usually demonstrated using either external cluster validity indexes or the accuracy of a classifier which are both supervised criteria. Actually, the major issue of the variable subset selection according to a ranking measure has been adressed only by few authors in the unsupervised learning context. In this paper, we propose to combine multiple ranking to go ahead toward a stable consensus variable subset in a totally unsupervised fashion.
Clinical field-strength MRI of amyloid plaques induced by low-level cholesterol feeding in rabbits

Two significant barriers have limited the development of effective treatment of Alzheimer's disease. First, for many cases the aetiology is unknown and likely multi-factorial. Among these factors, hypercholesterolemia is a known risk predictor and has been linked to the formation of β-amyloid plaques, a pathological hallmark this disease. Second, standardized diagnostic tools are unable to definitively diagnose this disease prior to death; hence new diagnostic tools are urgently needed. Magnetic resonance imaging (MRI) using high field-strength scanners has shown promise for direct visualization of β-amyloid plaques, allowing in vivo longitudinal tracking of disease progression in mouse models. Here, we present a new rabbit model for studying the relationship between cholesterol and Alzheimer's disease development and new tools for direct visualization of β-amyloid plaques using clinical field-strength MRI. New Zealand white rabbits were fed either a low-level (0.125–0.25% w/w) cholesterol diet (n = 5) or normal chow (n = 4) for 27 months. High-resolution (66 × 66 × 100 µm3; scan time = 96 min) ex vivo MRI of brains was performed using a 3-Tesla (T) MR scanner interfaced with customized gradient and radiofrequency coils. β-Amyloid-42 immunostaining and Prussian blue iron staining were performed on brain sections and MR and histological images were manually registered. MRI revealed distinct signal voids throughout the brains of cholesterol-fed rabbits, whereas minimal voids were seen in control rabbit brains. These voids corresponded directly to small clusters of extracellular β-amyloid-positive plaques, which were consistently identified as iron-loaded (the presumed source of MR contrast). Plaques were typically located in the hippocampus, parahippocampal gyrus, striatum, hypothalamus and thalamus. Quantitative analysis of the number of histologically positive β-amyloid plaques (P < 0.0001) and MR-positive signal voids (P < 0.05) found in cholesterol-fed and control rabbit brains corroborated our qualitative observations. In conclusion, long-term, low-level cholesterol feeding was sufficient to promote the formation of extracellular β-amyloid plaque formation in rabbits, supporting the integral role of cholesterol in the aetiology of Alzheimer's disease. We also present the first evidence that MRI is capable of detecting iron-associated β-amyloid plaques in a rabbit model of Alzheimer's disease and have advanced the sensitivity of MRI for plaque detection to a new level, allowing clinical field-strength scanners to be employed. We believe extension of these technologies to an in vivo setting in rabbits is feasible and that our results support future work exploring the role of MRI as a leading imaging tool for this debilitating and life-threatening disease.
Extracting Semantic Orientations of Phrases from Dictionary

We propose a method for extracting semantic orientations of phrases (pairs of an adjective and a noun): positive, negative, or neutral. Given an adjective, the semantic orientation classification of phrases can be reduced to the classification of words. We construct a lexical network by connecting similar/related words. In the network, each node has one of the three orientation values and the neighboring nodes tend to have the same value. We adopt the Potts model for the probability model of the lexical network. For each adjective, we estimate the states of the nodes, which indicate the semantic orientations of the adjective-noun pairs. Unlike existing methods for phrase classification, the proposed method can classify phrases consisting of unseen words. We also propose to use unlabeled data for a seed set of probability computation. Empirical evaluation shows the effectiveness of the proposed method.
Risk based parameter selection for polarimetric SAR speckle reduction

In this paper, we introduce an automatic parameter selection technique for the polarimetric bilateral filter. The method is inspired by the theory of unbiased risk estimation that allows to compare different estimators with respect to a loss function. Moreover, a local risk estimation allows spatially varying parameters. We demonstrate our approach on experimental data and show how the method improves the smoothing capabilities of the filter in homogeneous areas while retaining its edge preserving properties.
Image Compression: Seeing what's not there

The HTML file that contains all the text for this article is about 25,000 bytes. That's less than one of the image files that was also downloaded when you selected this page. Since image files typically are larger than text files and since web pages often contain many images that are transmitted across connections that can be slow, it's helpful to have a way to represent images in a compact format. In this article, we'll see how a JPEG file represents an image using a fraction of the computer storage that might be expected. We'll also look at some of the mathematics behind the newer JPEG 2000 standard.
ShuttleKickers: Exploring Social Persuasions to Encourage Physical Activities

In the HCI domain, many researches have been carried out on how to apply Persuasive Technology (PT) to stimulate a more active lifestyle. Regarding collectivist cultures, social influence has been considered as one of the most impactful factors among others in PT. Within one societal context, however, different individuals may need different motivational mechanisms based on social persuasion. In this paper, we designed the prototype ShuttleKickers embedding different social persuasive mechanisms to stimulate more physical activities in China. Subsequently, we conducted the field-test of our prototype with sportive groups and sedentary groups, identified by Transtheoretical Model, which results in a set of implications on how to apply social persuasions for active behaviours for these two different groups respectively.
Perceived Risk and Segmentation Variables in Traditional vs. Non- Traditional College Courses: An Exploratory Analysis

A novel pyrrolotriazole derivative is disclosed, represented by any one of formulae (I), (II), (III), (IV), or (V): (I) (II) (III) (IV) (V) A heat transfer dye providing material is also disclosed, comprising a support having thereon a dye providing layer containing a heat migrating dye, said dye providing layer containing at least one pyrrolotriazole azomethine dye represented by any one of formulae (I), (II), (III), or (IV).
Efficient Energy Saving in Wireless Sensor Networks Through Hierarchical-based Clustering

Prolonged network lifetime, scalability, and load balancing are important requirements for many wireless sensor network applications. Clustering sensor nodes is an effective approach for achieving these goals. In this paper, we propose a Distributed Energy-efficient Clustering-based Hierarchy Protocol (DECHP), which distributes the energy dissipation evenly among all sensor nodes to improve network lifetime and average energy savings. The performance of DECHP is then compared to different clustering-based schemes. Simulation results show that DECHP reduces overall energy consumption and improves network lifetime over its comparatives.
An Empirical Study on Influencing Factors of Knowledge Sharing inVirtual Learning Community

Increasing organizations and educational institutions have implemented virtual learning communities to en- courage knowledge sharing. Virtual Learning Community was able to serve the learning goals of community members by relying on the knowledge sharing. In this paper, some individual factors and environmental factors were used to study the knowledge sharing among community members. In virtual learning community, the sense of community and trust are im- portant indicators for the development of community, and the members of mature community tend to have strong a sense of community and trust. Ten hypothesizes and the way of questionnaire survey were presented to explore the impact of social interaction, perceptual learning, trust, a sense of community and self-efficacy for knowledge sharing among mem- bers in community. The empirical results show that social interaction behavior between members has a significant role in promoting trust and a sense of belonging, and trust, a sense of community and a sense of self-efficacy among members has a significant effect to the knowledge sharing in virtual learning community, while a sense of self-efficacy among members in the virtual learning community is largely affected by the learning community perception.
Comparison of hemostatic forceps with soft coagulation versus argon plasma coagulation for bleeding peptic ulcer – a randomized trial

Background and study aims: Endoscopic high-frequency soft coagulation is used to manage visible bleeding or nonbleeding vessels during endoscopic submucosal dissection. The aim of the present study was to compare the efficacy of hemostasis by soft coagulation (using hemostatic forceps) with argon plasma coagulation (APC), in a prospective randomized trial. Patients and methods: From January 2013 to June 2014, 276 patients were randomly assigned into two groups: epinephrine injection plus APC (the APC group); or epinephrine injection plus soft coagulation using hemostatic forceps (the HFSC group). As the primary outcome we compared recurrent bleeding rates within 30 days after initial hemostasis in a noninferiority design. Results: After exclusion, 75 patients in the APC group and 76 in the HFSC group were finally evaluated. In the APC group 72 patients (96 %) were successfully treated with the assigned treatment alone vs. 73 (96 %) in the HFSC group. Initial endoscopic hemostasis using a single or combined modality was achieved in all patients. Recurrent bleeding within 30 days was experienced by five patients (6.7 %) and seven patients (9.2 %) in the AFC and HFSC groups, respectively (P = 0.563), and within 7 days by three patients (4.0 %) and five patients (6.6 %), respectively (P = 0.719). We found no significant difference in the rates of adverse events (1.3 % vs. 2.6 %) or mortality (2.7 % vs. 2.6 %) between the groups. Conclusions: The efficacy and safety of soft coagulation using endoscopic hemostatic forceps is not inferior to APC when used to treat patients with bleeding peptic ulcers. Clinicaltrials.gov NCT02020603.
Recognition of sintering state in rotary kiln using a robust extreme learning machine

Sintering is a key process for the industrial clinker production. The sintering state estimation in clinker is an essential factor for its process control. In this paper, a feature extraction method from flame image and a robust extreme learning machine (RB-ELM) classifier are provided to recognize sintering process in rotary kiln. After a preprocessing of image denoising and illumination compensation, material region of flame image is segmented by region growing algorithm and a 5-D statistic feature vector is extracted from it for the following classifier. In order to reduce the influence of outliers in training data caused by blurring image and to achieve a real-time application on site, a robust extreme learning machine, which adopted iterative weight least square (IWLS) method based on M-estimator, is used for fast classification of sintering state. Experimental results show that the proposed method can recognize sintering state accurately, quickly and robustly.
Swift and infra-red observations of the blazar 3C 454.3 during the giant X-ray flare of May 2005

We present the results of a series of Swift and quasi simultaneous ground-based infra-red observations of the blazar 3C 454.3 carried out in April-May 2005 when the source was 10 to 30 times brighter than previously observed. We found 3C 454.3 to be very bright and variable at all frequencies covered by our instrumentation. The broad-band Spectral Energy Distribution (SED) shows the usual two-bump shape (in Log v - Log [vf(v)] space) with the Infra-red, optical and UV data sampling the declining part of the synchrotron emission that, even during this extremely large outburst, had its maximum in the far-infrared. The X-ray spectral data from the XRT and BAT instruments are flat and due to inverse Compton emission. The remarkable SED observed implies that at the time of the Swift pointings 3C 454.3 was one of the brightest objects in the extragalactic sky with a γ-ray emission similar or brighter than that of 3C 279 when observed in a high state by EGRET. Time variability in the optical-UV flux is very different from that in the X-ray data: while the first component varied by about a factor two within a single exposure, but remained approximately constant between different observations, the inverse Compton component did not vary on short time-scales but changed by more than a factor of 3 between observations separated by a few days. This different dynamical behaviour illustrates the need to collect simultaneous multi-frequency data over a wide range of time-scales to fully constrain physical parameters in blazars.
Parameter estimation from tomographic data using self-organising maps

The paper reports on the potential of using a type of artificial neural network, the self-organising map, for processing tomographic data from pipe separators to estimate interface levels. This is motivated by a desire to estimate process parameters without recourse to image reconstruction. Results show direct quantitative estimation of volume fraction of two-component flow mixtures containing oil and water from electrical capacitance tomography measurements. Parameter extraction from the trained feature map is realised using Gaussian mixture modelling. Parametric information of a mixture is determined by using the probability estimation of sample map and comparing the result with the model's topology. The SOM Toolbox in MATLAB was used for training and developing the models. After preparing the training data the SOM mixture model can be trained in less than 20 seconds. 75% of the two-component mixture test samples are classified within 5% of the sample's true composition.
WMAP normalization of inflationary cosmologies

We use the three-year WMAP observations to determine the normalization of the matter power spectrum in inflationary cosmologies. In this context, the quantity of interest is not the normalization marginalized over all parameters, but rather the normalization as a function of the inflationary parameters n and r with marginalization over the remaining cosmological parameters. We compute this normalization and provide an accurate fitting function. The statistical uncertainty in the normalization is 3 percent, roughly half that achieved by COBE. We use the k–l relation for the standard cosmological model to identify the pivot scale for the WMAP normalization. We also quote the inflationary energy scale corresponding to the WMAP normalization.
A useful prediction variable for student models: cognitive development level

Making a realistic update of a user model based on evidence in the environment is not an easy task, unless a great deal of time with a large variety of users is available. Creating general categories of users that behave in a certain way is important for any kind of user model. To obtain such a broad classification we need to understand general factors that influence user behavior. We describe the use of pretests to measure cognitive development of student users and how this factor is input to a student model. We describe how measures of cognitive ability enhance the predictive power of a student model in an intelligent tutoring system for a population of young (elementary school) students.
Alternatives to conventional thermal treatments in fruit-juice processing. Part 1: Techniques and applications

ABSTRACT This paper provides an overview of alternatives to conventional thermal treatments and a review of the literature on fruit-juice processing for three key operations in fruit-juice production such as microbial inactivation, enzyme inactivation, and juice yield enhancement, these being radiation treatments (UV light, high-intensity light pulses, γ-irradiation), electrical treatments (pulsed electric fields, radiofrequency electric fields, ohmic heating), microwave heating, ultrasound, high hydrostatic pressure, inert gas treatments (supercritical carbon dioxide, ozonation), and flash-vacuum expansion. The nonthermal technologies discussed in this review have the potential to meet industry and consumer expectations. However, the lack of standardization in operating conditions hampers comparisons among different studies, and consequently ambiguity arises within the literature. For the juice industry to advance, more detailed studies are needed on the scaling-up, process design, and optimization, as well as on the effect of such technologies on juice quality of juices in order to maximize their potential as alternative nonthermal technologies in fruit-juice processing.