Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised estimation of the number of endmembers in hyperspectral data

Estimate the number of endmembers in hyperspectral data is a significant step in the process of the spectral unmixing. Since most images contain noise that is not independent and identically distributed (i.i.d.) across bands, methods that assume i.i. d. noise are often avoided. This paper introduces a noise-whitening process into the state-of-the-art signal subspace estimation method. The noise covariance matrix of the image data is used to whiten the noise variances to unity, then the subset of eigenvalues that best represents the signal subspace is selected in the least squared error sense. The results derived from the classical methods and the improved method using simulated hyperspectral data and real hyperspectral data are presented and discussed.
Blocking-resistant communication through domain fronting

Abstract We describe “domain fronting,” a versatile censorship circumvention technique that hides the remote endpoint of a communication. Domain fronting works at the application layer, using HTTPS, to communicate with a forbidden host while appearing to communicate with some other host, permitted by the censor. The key idea is the use of different domain names at different layers of communication. One domain appears on the “outside” of an HTTPS request—in the DNS request and TLS Server Name Indication—while another domain appears on the “inside”—in the HTTP Host header, invisible to the censor under HTTPS encryption. A censor, unable to distinguish fronted and nonfronted traffic to a domain, must choose between allowing circumvention traffic and blocking the domain entirely, which results in expensive collateral damage. Domain fronting is easy to deploy and use and does not require special cooperation by network intermediaries. We identify a number of hard-to-block web services, such as content delivery networks, that support domain-fronted connections and are useful for censorship circumvention. Domain fronting, in various forms, is now a circumvention workhorse. We describe several months of deployment experience in the Tor, Lantern, and Psiphon circumvention systems, whose domain-fronting transports now connect thousands of users daily and transfer many terabytes per month.
SPARC Regulates Microgliosis and Functional Recovery following Cortical Ischemia

Secreted protein acidic rich in cysteine (SPARC) is a matricellular protein that modulates the activity of growth factors, cytokines, and extracellular matrix to play multiple roles in tissue development and repair, such as cellular adhesion, migration, and proliferation. Throughout the CNS, SPARC is highly localized in mature ramified microglia, but its role in microglia—in development or during response to disease or injury—is not understood. In the postnatal brain, immature amoeboid myeloid precursors only induce SPARC expression after they cease proliferation and migration, and transform into mature, ramified resting microglia. SPARC null/CX3CR1-GFP reporter mice reveal that SPARC regulates the distribution and branching of mature microglia, with significant differences between cortical gray and white matter in both controls and SPARC nulls. Following ischemic and excitotoxic lesion, reactive, hypertrophic microglia rapidly downregulate and release SPARC at the lesion, concomitant with reactive, hypertrophic perilesion astrocytes upregulating SPARC. After photothrombotic stroke in the forelimb sensorimotor cortex, SPARC nulls demonstrate enhanced microgliosis in and around the lesion site, which accompanies significantly enhanced functional recovery by 32 d after lesion. Microglia from SPARC nulls also intrinsically proliferate at a greater rate in vitro—an enhanced effect that can be rescued by the addition of exogenous SPARC. SPARC is thus a novel regulator of microglial proliferation and structure, and, in addition to regulating glioma progression, may play an important role in differently regulating the gray and white matter microglial responses to CNS lesion—and modulating behavioral recovery—after injury.
QoS-aware discovery of wide-area distributed services

Global computational grids bring together distributed computation/communication resources. Beyond this, we envision the emergence of global 'service grids', which provide a 'market' of application-level distributed services for clients to discover and to request. We study the issue of wide-area service discovery in service grids. We start with an existing basic wide-area service discovery framework. The framework adopts a scalable architecture consisting of a hierarchy of Discovery Servers. We then identify problems with the basic framework, and propose our enhancement of query responsiveness and QoS awareness. The key techniques we introduce include: (1) the addition of QoS feedback capability to clients; and (2) the caching and propagation of discovery results with QoS feedback in the discovery server hierarchy. With these techniques, the enhanced service discovery framework will be faster in finding qualified service providers. Furthermore, it will select a 'good' (with respect to the QoS to be delivered) service provider for each querying client, based on QoS feedback.
Native Cross-Platform Visualization: A Proof of Concept Based on the Unity3D Game Engine

Today many different devices and operating systems can be used for InfoVis systems. On the one hand, web-based visualizations can be used to be compatible with several systems, but the performance depends on optimized browser engines. On the other hand, it is possible to build a native system which supports all the benefits for just one device. However, transferring the code to another system means parts of the code or the programming language have to be adapted. To close this gap, we present a proof of concept based on the Unity3D game engine. We implemented a prototype following the InfoVis reference model and basic interactions for interactive data exploration. A major advantage is that we have now the ability to deploy native code to over 20 different devices. Additionally, this proof of concept opens new possibilities for a future InfoVis framework which benefits from Unity3D.
Cooperative control of electronic power processors in micro-grids

Micro-grids offer a new challenging domain for power electronics, since they include a variety of power sources and electronic power processors (EPP) interacting each other. In micro-grids, energy efficiency requires smart control of power flow, and power quality calls for voltage support by reactive power regulation, suppression of voltage distortion at load terminals and limitation of current harmonics at utility interface. Pursuing such complex duties requires EPP to perform cooperatively, irrespective of type and power rating. This paper provides a background to cooperative control of distributed EPP in micro-grids, where power capability is limited, voltage supply is often distorted and distribution line impedances play a significant role.
Toward robust estimation of specular flow

Specular ﬂow is an important class of optical ﬂow whose utility in visual tasks has gained much interest in contemporary vision research. Unfortunately, however, reliably estimation of specular ﬂow from image sequences is an open question that was never addressed formally before. In this paper we ﬁrst argue that existing optical ﬂow algorithms are incapable of reliable specular ﬂow estimation due to their typical regularization criteria that conﬂict the unique and singular structure of specular ﬂows. We show these discrepancies both qualitatively and using quantitative evaluation based on a ﬁrst-of-its-kind benchmark dataset with ground truth specular ﬂow data. We then suggest to generalize the popular optical ﬂow variational framework using spatial weighting of different regularizers, and we propose new regularization terms that correspond better to the expected singularities of specular ﬂows. Finally, we show how these contributions signiﬁcantly improves specular ﬂow estimation.
General considerations for lung function testing

SERIES “ATS/ERS TASK FORCE: STANDARDISATION OF LUNG FUNCTION TESTING” Edited by V. Brusasco, R. Crapo and G. Viegi Number 1 in this Series ⇓In preparing the joint statements on lung function testing for the American Thoracic Society (ATS) and the European Respiratory Society (ERS), it was agreed by the working party that the format of the statements should be modified so that they were easier to use by both technical and clinical staff. This statement contains details about procedures that are common for many methods of lung function testing and, hence, are presented on their own. A list of abbreviations used in all the documents is also included as part of this statement. All terms and abbreviations used here are based on a report of the American College of Chest Physicians/ATS Joint Committee on Pulmonary Nomenclature 1. The metrology definitions agreed by the International Standards Organization (ISO) are recommended 2 and some important terms are defined as follows. Accuracy is the closeness of agreement between the result of a measurement and the conventional true value. Repeatability is the closeness of agreement between the results of successive measurements of the same item carried out, subject to all of the following conditions: same method, same observer, same instrument, same location, same condition of use, and repeated over a short space of time. In previous documents, the term reproducibility was used in this context, and this represents a change towards bringing this document in line with the ISO. Reproducibility is the closeness of agreement of the results of successive measurements of the same item where the individual measurements are carried out with changed conditions, such as: method of measurement, observer, instrument, location, conditions of use, and time. Thus, if a technician tests a subject several times, this is looking at the …
A Hybrid Estimation of Distribution Algorithm with Decomposition for Solving the Multiobjective Multiple Traveling Salesman Problem

Evolutionary multiobjective optimization with decomposition, in which the algorithm is not required to differentiate between the dominated and nondominated solutions, is one of the promising approaches in dealing with multiple conflicting objectives. In this paper, the estimation of distribution algorithm (EDA) is integrated into the decomposition framework. The search behavior of the algorithm is further enhanced by hybridizing local search metaheuristic approaches with the decomposition EDA. Three local search techniques, including hill climbing, simulated annealing, and evolutionary gradient search, are considered. A novel multiobjective formulation of the multiple traveling salesman problem is proposed. The hybrid algorithms are used to solve the formulated problem with different number of objective functions, salesmen, and problem sizes. The effectiveness and efficiency of the algorithms are tested and benchmarked against several state-of-the-art multiobjective evolutionary paradigms.
Meta-meta-analysis: A paradigm in the case of surgical publications.

PURPOSE Meta-analyses are considered to provide level I-II evidence. Based on this premise, several statements have been developed to standardize guidelines and optimize results. The purpose of this study was to investigate the quality of the information delivered by meta-analyses. METHODS Meta-analyses published in Annals of Surgery during an 11-year period were reviewed whereas individual publications of each meta-analysis were assessed. An Excel database encompassing 29 parameters was constructed based on the Quality of Reporting of Meta-analyses (QUOROM) statement. RESULTS The present study included 31 consecutive meta- analyses. The number of meta-analyses conforming with each of the parameters considered was as follows: information obtained from more than 2 databases 23/31; language of publication exclusively English 25/31; defined population, intervention, and principal outcomes 31/31; study design encompassing review of randomised controlled trials (RCTs) 10/31; quality assessment of contributing publications 10/31; handling of missing data 10/31; assessment of statistical heterogeneity 30/31; subgroup analysis 23/31; assessment of publication bias 26/31; agreement on selection and validity assessment 22/31; simple summary results 28/31; data available to calculate effect size and confidence interval 27/31; key findings summarized 30/31; clinical inferences based on internal and external validity 24/31; description of potential biases in the review process 23/31; future research agenda suggested 18/31. CONCLUSIONS Evidence derived from meta-analyses must be interpreted with caution. Although QUOROM guidelines were observed, quality assessments showed considerable variability.
A Tighter Real-Time Communication Analysis for Wormhole-Switched Priority-Preemptive NoCs

Simulations and runtime measurements are some of the methods which can be used to evaluate whether a given NoC-based platform can accommodate application workload and fulfil its timing requirements. Yet, these techniques are often time-consuming, and hence can evaluate only a limited set of scenarios. Therefore, these approaches are not suitable for safety-critical and hard real-time systems, where one of the fundamental requirements is to provide strong guarantees that all timing requirements will always be met, even in the worst-case conditions. For such systems the analytic-based real-time analysis is the only viable approach. In this paper the focus is on the real-time communication analysis for wormhole-switched priority-preemptive NoCs. First, we elaborate on the existing analysis and identify one source of pessimism. Then, we propose an extension to the analysis, which efficiently overcomes this limitation, and allows for a less pessimistic analysis. Finally, through a comprehensive experimental evaluation, we compare the newly proposed approach against the existing one, and also observe how the trends change with different traffic parameters.
Combining the sol gel method and spin coating to obtain YIG films with low FMR linewidth on silicon (100) substrate

Combining the sol gel method and spin coating technique, yttrium iron garnet (YIG) films were obtained on silicon (Si) substrate. Four YIG films with different thicknesses were fabricated to achieve low FMR linewidth. The x-ray diffraction has shown a single phase, belonging to the cubic structure of the YIG, while the morphology of the films has presented small pores and some grains on the surface. The FMR linewidth of the YIG films decreased 110 Oe, 108 Oe, 93 Oe and 71 Oe as the film thickness increased 134 nm, 246 nm, 376 nm and 489 nm, respectively. This result indicates that high-quality YIG films can be achieved on Si substrates, controlling the thickness. The sol gel method is shown as a very economical and easy alternative to obtain YIG films with low FMR linewidth, which may be important for making microwave integrated devices.
Scanning X-ray Imaging Techniques for Characterization of Energy Materials

We present an alternative numerical reconstruction algorithm for direct tomographic reconstruction of a sample’s refractive indices from the measured intensities of its far-field coherent diffraction patterns. We formulate the well-known phase-retrieval problem in ptychography in a tomographic framework which allows for simultaneous reconstruction of the illumination function and the sample’s refractive indices in three dimensions. Our iterative reconstruction algorithm is based on the Levenberg-Marquardt algorithm and we demonstrate the performance of our proposed method with simulated and real datasets.
Uncertain Graphs meet Collaborative Filtering

Collaborative ltering (CF) aims at predicting the user interest for a given item. In CF systems a set of users ratings is used to predict the rating of a given user on a given item using the ratings of a set of users who have already rated the item and whose preferences are similar to those of the user. In this paper we propose to use a framework based on uncertain graphs in order to deal with collaborative ltering problems. In this framework relationships among users and items and their corresponding likelihood will be encoded in a uncertain graph that can then be used to infer the probability of existence of a link between an user and an item involved in the graph. In order to solve CF tasks the framework uses an approximate inference method adopting a constrained simple path query language. The aim of the paper is to verify whether uncertain graphs are a valuable tool for CF, by solving classical, complex and structured problems. The performance of the proposed approach is reported when applied to a real-world domain.
Consistent signal parameter estimation with 1-bit dithered sampling

We consider the problem of estimating a parameter θ of a signal s(x; θ) corrupted by noise when only 1-bit precision samples are allowed. We propose and analyze a new estimator based on dithered 1-bit samples. Our estimate is consistent and satisfies an asymptotic CLT for a wide class of dither distributions. In particular, uniformly distributed dither leads to only a logarithmic rate loss compared to the case of full precision samples.
Human tracking with multiple 3D cameras for perceptual sensor network

In this paper, we propose a multiple 3D camera-based human tracking method which is robust to illumination changes and occlusions at indoor environments. To overcome the difficulties due to illumination change, several types of image features are used in a collaborative fashion, for which brightness intensity, hue, local binary pattern (LBP) and depth from 3D camera are considered. In addition, our method also exploits multiple camera views to resolve the occlusion between objects. Our algorithm first implements the background subtraction to extract moving objects from each camera view and then executes the human identification process to determine whether the human is previously confirmed. The proposed algorithm estimates the vertical axes of the humans detected in multiple calibrated camera views, which leads to generating the cross points of the detected human objects. Finally, the cross points (the location of the human objects) are fed into adaptive particle filter based on spatio-temporal information to track the human objects. The performance of the proposed algorithm is examined through experiments performed in varying indoor illumination and occlusion conditions.
Maximally rugged NK landscapes contain the highest peaks

NK models provide a family of tunably rugged fitness landscapes used in a wide range of evolutionary computation studies. It is well known that the average height of local optima regresses to the mean of the landscape with increasing epistasis, k. This fact has been confirmed using both theoretical studies of landscape structure and empirical studies of evolutionary search. We show that the global optimum behaves quite differently: the expected value of the global maximum is highest in the maximally rugged case. Furthermore, we demonstrate that this expected value increases with K, despite the fact that the average fitness of the local optima decreases. That is, the highest peaks are found in the most rugged landscapes, scattered amongst masses of low-lying peaks. We find the asymptotic value of the global optimum as N approaches infinity for both the smooth and maximally rugged cases. In evolutionary search, the optima that are found reflect the local optima that exist in the landscape, the size of these optima -- which corresponds to the size of their basins of attraction, and the effort expended in the search process. Increasing the level of epistasis in an NK landscape stochastically introduces higher peaks, but renders them exponentially more difficult to find.
Ontologies, Dialogue and Knowledge Maturing: Towards a Mashup and Design Study

This paper proposes an initial design study to examine and test some of the key concepts and issues within a large-scale European research project that is exploring and aiming to realise learning as a process of knowledge maturing in the workplace. It will outline some of these concepts, based on a contemporary (or Web 2.0 driven) articulation of how ontologies can be acquired, externalised and exploited by a user-community and introduce a new role for learning dialogue through developing work into „dialogue games‟. An initial scenario, or „thought experiment‟, is proposed that is grounded on currently available ontology development (SOBOLEO) and learning dialogue (InterLoc) web-technologies and how these could be integrated, or „mashed up‟, to improve the management, understanding and application of labour market information in the context of careers advice. Finally, we also consider the potential role of m-learning techniques and the implications about context that these give rise to.
A framework for the study of preference incorporation in multiobjective evolutionary algorithms

We present a formal framework for the study of user preference incorporation into multiobjective evolutionary algorithms. This framework can accommodate virtually any preference model, including those that violate the independence of irrelevant alternatives. We also introduce the Preferanto notation, which permits the specification of a large variety of preference models. A number of properties and indicators are proposed for characterizing preference models. We report the results of a case study experiment assessing the impact of incorporating different preference models into an NSGA-II algorithm.