Miracle-dz/UniFAR-FTUs huggingface dataset:
An approximation algorithm for minimum-delay peer-to-peer streaming

Peer-to-peer (P2P) technology provides a scalable solution in multimedia streaming. Many streaming applications, such as IPTV and video conferencing, have rigorous constraints on end-to-end delays. Obtaining assurances on meeting those delay constraints in dynamic and heterogenous network environments is a challenge. In this paper, we devise a streaming scheme which minimizes the maximum end-to-end streaming delay for a mesh-based overlay network paradigm. We first formulate the minimum-delay P2P streaming problem, called the MDPS problem, and prove its NP-completeness. We then present a polynomial-time approximation algorithm to this problem, and show that the performance of our algorithm is bounded by a ratio of O. Our simulation study reveals the effectiveness of our algorithm, and shows a reasonable message overhead.
GeoPW: Laying Blocks for the Geospatial Processing Web

Recent advances in Web‐related technologies have significantly promoted the wide sharing and integrated analysis of distributed geospatial data. Geospatial applications often involve diverse sources of data and complex geoprocessing functions. Existing Web‐based GIS focuses more on access to distributed geospatial data. In scientific problem solving, the ability to carry out geospatial analysis is essential to geoscientific discovery. This article presents the design and implementation of GeoPW, a set of services providing geoprocessing functions over the Web. The concept of the Geospatial Processing Web is discussed to address the geoprocessing demands in the emerging information infrastructure, and the role of GeoPW in establishing the Geospatial Processing Web is identified. The services in GeoPW are implemented by developing middleware that wraps legacy GIS analysis components to provide a large number of geoprocessing utilities over the Web. These services are open and accessible to the public, and they support integrated geoprocessing on the Web.
Durational Evidence for Syllable Boundary of /n/ and /l/ in Text-to-Speech Synthesis

The Text-to-Speech (TTS) system does rely on syllable boundary information for segmental duration. However, ambisyllabic consonants always pose a problem to TTS because the system requires clear syllable boundaries to segment and concatenate. In order to provide a possible solution to this problem, /n/ and /l/ in V L C A V R are chosen in this paper as the target to be examined whether their durations behave more like the syllabic onset or coda when comparing with the durational properties of /n/ and /l/ both as onsets in CV and codas in VC . As the syllable boundaries, onset C shows much more sensitivity to stress than coda C while coda C shows more sensitivity to syllabic position than onset C . Moreover, C A in V L C A V R is also influenced by two variables of stress and position as C in CV and VC . The results show that the intervocalic C A holds the properties of both the syllabic onset and coda, which states the possibility that intervocalic consonants should be considered as a rather independent concatenative unit in TTS synthesis.
Framework for Stochastic Modelling of Multi-dimensional Real-Time Sensor Data

Sensors are a common way of collecting health data on any sophisticated machinery. Utilizing the real time machine sensor data in order to predict problems ahead in time to mitigate the risk associated with unplanned failures has been of great interest to statisticians and reliability engineers as there are direct cost saving benefits. In effort to reduce downtime and improve overall reliability of the system, a robust, scalable modelling technique is desired to understand and forecast the future dynamics of the system as whole. We propose and analyze a framework for stochastic modeling of multidimensional machine sensor data. The system developed is self-adaptive and can be used with live data feed to provide real time predictions. We utilize the concept of low rank matrix approximation for efficient storage, retrieval and faster computation of real time data. Markov chain is used to model the process dynamics and to calculate short and long range probabilities of the system which can be used to identify potential failure introduction points in the system.
Spinster Homolog 2 (Spns2) Deficiency Causes Early Onset Progressive Hearing Loss

Spinster homolog 2 (Spns2) acts as a Sphingosine-1-phosphate (S1P) transporter in zebrafish and mice, regulating heart development and lymphocyte trafficking respectively. S1P is a biologically active lysophospholipid with multiple roles in signalling. The mechanism of action of Spns2 is still elusive in mammals. Here, we report that Spns2-deficient mice rapidly lost auditory sensitivity and endocochlear potential (EP) from 2 to 3 weeks old. We found progressive degeneration of sensory hair cells in the organ of Corti, but the earliest defect was a decline in the EP, suggesting that dysfunction of the lateral wall was the primary lesion. In the lateral wall of adult mutants, we observed structural changes of marginal cell boundaries and of strial capillaries, and reduced expression of several key proteins involved in the generation of the EP (Kcnj10, Kcnq1, Gjb2 and Gjb6), but these changes were likely to be secondary. Permeability of the boundaries of the stria vascularis and of the strial capillaries appeared normal. We also found focal retinal degeneration and anomalies of retinal capillaries together with anterior eye defects in Spns2 mutant mice. Targeted inactivation of Spns2 in red blood cells, platelets, or lymphatic or vascular endothelial cells did not affect hearing, but targeted ablation of Spns2 in the cochlea using a Sox10-Cre allele produced a similar auditory phenotype to the original mutation, suggesting that local Spns2 expression is critical for hearing in mammals. These findings indicate that Spns2 is required for normal maintenance of the EP and hence for normal auditory function, and support a role for S1P signalling in hearing.
Rapid prototyping of digital controls for power electronics

The process for designing digital controls for power electronics is typically quite convoluted and affords many opportunities for errors to occur. We present here a new and complete method for rapid prototyping of digital controls that allows rapid realization of new designs. The approach uses a collection of tools that include both software (the virtual test bed (VTB) and Matlab/Simulink) and hardware (dSpace DSP). An example application of the methodology completes the discussion.
Responsive task modelling

In this paper we present a new tool for specifying task models (Responsive CTT), which can be accessed through touch-based mobile devices such as smartphones and tablets as well. The tool is Web-based and responsive in order to provide adapted user interfaces to better support the most common activities in task modelling through various types of devices. We describe the relevant aspects to take into account for this purpose and how we have addressed them in designing the tool. We also report on first user tests.
Visually guided bottom-up table detection and segmentation in web documents

In the AllRight project, we are developing an algorithm for unsupervised table detection and segmentation that uses the visual rendition of a Web page rather than the HTML code. Our algorithm works bottom-up by grouping word bounding boxes into larger groups and uses a set of heuristics. It has already been implemented and a preliminary evaluation on about 6000 Web documents has been carried out.
Gabor filter based multi-class classifier for scanned document images

When scanning documents with a large number of pagessuch as books, it is often feasible to provide a minimalnumber of training samples to personalize the system tocompensate for global shifts in how the document wascreated or in scanning parameters. In this paper, wepresent a supervised multi-class classifier based onGabor filters that is used to classify the scripts, font-faces,and font-styles (bold, italic, normal etc.) in anapplication where the classes are known. Classificationis performed at the word level (glyphs separated by whitespace) given training samples of each class. This methodwas applied to a variety of bilingual dictionaries toidentify different scripts, and simultaneously, to classifyRoman scripts into bold, italic and normal font-styles.Experimental results show the effectiveness of thisapproach in increasing performance over classifierstrained for general documents.
Cytotoxicity evaluation of gelatin sponges prepared with different cross-linking agents

Gelatin is a natural polymer used in pharmaceutical and medical applications, especially in the production of biocompatible and biodegradable wound dressings and drug delivery systems. Gelatin granules hydrate, swell and solubilize in water, and rapidly degrade in vivo. The durability of these materials could, however, be prolonged by cross-linking by aldehydes, carbodiimides, and aldose sugars, but the biocompatibility of collagenous biomaterials is profoundly influenced by the nature and extent of cross-linking. In this study, gelatin sponges were prepared by using various cross-linkers such as glutaraldehyde (GA), 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide hydrochloride (EDAC), and D-fructose. The effects of the type and the amount of cross-linker on thermal and mechanical properties, stability, and cytotoxicity were investigated. The mechanical analysis data showed that an increase in the amount of GA in the sponge structures caused a slight increase in the modulus of elasticity but had almost no effect on the tensile strength. Increase in the EDAC concentration produced a maximum in the modulus of elasticity and tensile strength values. The stability of the sponges and the time required for complete degradation in aqueous media increased in parallel with the cross-linker content. In vitro studies carried out with fibroblast cells demonstrated a higher cell viability for the samples cross-linked with low concentrations of GA than for those cross-linked with EDAC.
Robust Tracking Scheme for Wheeled Mobile Robot with Actuator Saturations Via Uncertain T-S Fuzzy Model

In this paper, a constrained robust guaranteed cost tracking scheme for Wheeled Moving Robot (WMR) with actuator saturations is proposed. First, tracking error dynamics of WMR is represented by uncertain Tagaki-Sugeno (T-S) fuzzy model, where varying velocity in desired trajectory is look as uncertain parameter, so we can represent the T-S subsystem via Then constrained robust guaranteed controller in the form of state feedback is derived for each subsystem by solving LMI based semi-definite programming problems. Finally, The overall controller then is constructed in the framework of PDC and the Lyapunov stability of the closed-loop system is tested finally. Simulation results are given and discussed to validate the proposed scheme.
Image processing and neural computing used in the diagnosis of tuberculosis

A method far automating the detection of tubercle bacilli in sputum specimens is described. A fluorescence microscope with an attached digital camera is used to manually locate and capture images of tubercle bacilli. The method comprises two phases: (a) image processing and analysis techniques are applied to the images for enhancement and feature extraction; (b) object recognition techniques are used for the automatic identification of tubercle bacilli in the images. The eventual implementation of the system will be semi-automatic, where the best candidate images containing bacilli are presented to the medical technologist together with a bacillus count, confidence measures and recommended diagnosis. The final diagnosis could be performed by the technologist in less than a minute for typical cases. Furthermore, the results should be more accurate due to the higher number of view-fields processed. The study presented in this paper indicates that machine-assisted diagnosis of tuberculosis is certainly feasible.
Performing Regression Test Prioritization for Time-Constrained Execution Using a Genetic Algorithm

Test case prioritization techniques organize the test cases in a test suite, allowing for an increase in the effectiveness of testing. One performance goal, the fault-detection rate, is a measure of how quickly faults are detected during the testing process. An improved rate of fault detection can provide faster feedback regarding the quality of the system under test, but frequently, complete testing is too expensive. This is often the case with regression testing, the process of validating modified software to detect whether new errors have been introduced into previously tested code and to provide confidence that modifications are correct. By increasing the rate of fault detection earlier in the test suite, more errors can be found in the code at the beginning of testing. This paper proposes a new test case prioritization technique using a genetic algorithm (GA) to order test cases in a way that will optimize the rate of fault detection within a specified execution time. Fitness functions for the GA will be generated using test adequacy criteria and static metrics. Test adequacy criteria determine the possible effectiveness of a test based on the test’s likelihood of causing faults to infect the data state of the program and propagate to the program’s output. Static metrics consider the code of the program under test in a static state, for example, the number of lines of
Fast and Robust Object Detection and Tracking for Lightweight Visual Surveillance Systems

In this paper, we present a novel method for moving object detection using background subtraction and tracking for lightweight visual surveillance systems. The proposed moving object detection method using background subtraction is based on a “Gaussianity test” and a shading model. The method has been shown to be robust to dynamic scenes such as sudden illumination changes and presence of relatively small scene clutter motion (e.g. waving tree branches and leaves). A fast implementation of the method using an extension of integral images is presented. A fast implementation of object tracking using a particle filtering framework is also presented using a probability density function of the visual features of the target object. A weighting scheme based on non-uniform kernel filtering of the probability density function is described for better tracking performance. We also show in our proposed background subtraction method that the construction of the object tracking appearance model has speed improvements of orders of magnitudes compared to traditional methods such as convolution.
Research protocol for a case study of crowdsourcing software development

Crowdsourcing is an emerging topic within software engineering research. This report presents the protocol for our case study of crowdsourcing at a multi-national company. The findings of the case study are presented in a paper in the proceedings of the 36 International Conference on Software Engineering (2014) (see ref. [37]). This protocol presents additional details that provide more insight regarding the background, design and execution of our study. The research design can also be used for replicating the case study so as to be able to more easily compare different case studies.
Mining users' significant driving routes with low-power sensors

While there is significant work on sensing and recognition of significant places for users, little attention has been given to users' significant routes. Recognizing these routine journeys, can open doors for the development of novel applications, like personalized travel alerts, and enhancement of user's travel experience. However, the high energy consumption of traditional location sensing technologies, such as GPS or WiFi based localization, is a barrier to passive and ubiquitous route sensing through smartphones. In this paper, we present a passive route sensing framework that continuously monitors a vehicle user solely through a phone's gyroscope and accelerometer. This approach can differentiate and recognize various routes taken by the user by time warping angular speeds experienced by the phone while in transit and is independent of phone orientation and location within the vehicle, small detours and traffic conditions. We compare the route learning and recognition capabilities of this approach with GPS trajectory analysis and show that it achieves similar performance. Moreover, with an embedded co-processor, common to most new generation phones, it achieves energy savings of an order of magnitude over the GPS sensor.
Internet Traffic Engineering : History monitoring information featuring routing algorithms

As Internet evolves into a standard communications network, new techniques for the management of the available assets must be introduced. This paper discusses the mechanisms of exercising traffic engineering in IP networks. It provides a thorough analysis of the existent traffic engineering approaches and focuses on presenting the most recent proposals made in the specified area. The interesting point of the research efforts reviewed is that they all follow the growing trend of incorporating history monitoring information in route determination procedure. We finally conclude with the formulation of a history aware traffic engineering
Texture Analysis for Automatic Segmentation of Intervertebral Disks of Scoliotic Spines From MR Images

This paper presents a unified framework for automatic segmentation of intervertebral disks of scoliotic spines from different types of magnetic resonance (MR) image sequences. The method exploits a combination of statistical and spectral texture features to discriminate closed regions representing intervertebral disks from background in MR images of the spine. Specific texture features are evaluated for three types of MR sequences acquired in the sagittal plane: 2-D spin echo, 3-D multiecho data image combination, and 3-D fast imaging with steady state precession. A total of 22 texture features (18 statistical and 4 spectral) are extracted from every closed region obtained from an automatic segmentation procedure based on the watershed approach. The feature selection step based on principal component analysis and clustering process permit to decide among all the extracted features which ones resulted in the highest rate of good classification. The proposed method is validated using a supervised k-nearest-neighbor classifier on 505 MR images coming from three different scoliotic patients and three different MR acquisition protocols. Results suggest that the selected texture features and classification can contribute to solve the problem of oversegmentation inherent to existing automatic segmentation methods by successfully discriminating intervertebral disks from the background on MRI of scoliotic spines.
Nonlinear Signal Processing for Voice Disorder Detection by Using Modified GP Algorithm and Surrogate Data Analysis

Acoustic voice analysis is an effective, cheap and non-invasive tool that can be used to confirm the initial diagnosis and provides an objective determination of the impairment. The nonlinearities of the voice source mechanisms may cause the existence of chaos in human voice production. Voice pathology can cause to addition colored noise to voice wave. Added noise to a chaotic signal causes reduction of the deterministic property and therefore increases correlation dimension of signal. Surrogate data analysis can measure this deviation and give a criterion for amount of noise added to the chaotic signal. By using this criterion a threshold level is set to separate disordered voice from normal voice and 95% accuracy is achieved.
An absolute requirement for Fyn in T cell receptor‐induced caspase activation and apoptosis

The mechanisms by which caspases are stimulated following T cell receptor engagement are presently unknown. We show here that TCR cross‐linking induces caspase activation, annexin V binding, loss of cell viability, Fyn cleavage, and apoptosis in a T cell hybridoma. All these events are increased in T cells overexpressing wild‐type Fyn and are inhibited in cells expressing a kinase dead mutant or a soluble form of Fyn. Moreover, DNA fragmentation mediated by various proapoptotic stimuli and anti‐CD3‐induced caspase activation and DNA fragmentation are reduced significantly in mouse embryo fibroblasts and thymocytes from Fyn knockout mice respectively. These results indicate that an active and membrane‐anchored Fyn is required for T cell receptor‐induced caspase activation and apoptosis in T lymphocytes and point out a specific role of Fyn in caspase activation and apoptosis in T cells.
Galectin-1-mediated cell adhesion, invasion and cell death in human anaplastic large cell lymphoma: Regulatory roles of cell surface glycans

Galectin-1 is known to be one of the extracellular matrix proteins. To elucidate the biological roles of galectin-1 in cell adhesion and invasion of human anaplastic large cell lymphoma, we performed cell adhesion and invasion assays using the anaplastic large cell lymphoma cell line H-ALCL, which was previously established in our laboratory. From the cell surface lectin array, treatment with neuraminidase from Arthrobacter ureafaciens which cleaves all linkage types of cell surface sialic acid enhanced Arachis hypogaea (PNA), Helix pomatia (HPA) and Phaseolus vulgaris-L (L-PHA) lectin binding reactivity to cell surface of lymphoma cells suggesting that neuraminidase removes cell surface sialic acid. In cell adhesion and invasion assays treatment with neuraminidase markedly enhanced cell adhesion to galectin-1 and decreased cell invasive capacity through galectin-1. α2,6-linked sialic acid may be involved in masking the effect of the interaction between galectin-1 and cell surface glycans. H-ALCL cells expressed the β-galactoside-α2,6-sialyltransferase ST6Gal1. On resialylation assay by recombinant ST6Gal1 with CMP-Neu5Ac, α2,6-resialylation of L-PHA reactive oligosaccharide by ST6Gal1 resulted in inhibition of H-ALCL cell adhesion to galectin-1 compared to the desialylated H-ALCL cells. On knockdown experiments, knockdown of ST6Gal1 dramatically enhanced cell adhesion to galectin-1. N-glycosylation inhibitor swainsonine treatment resulted in enhancement of cell adhesion to galectin-1. In glycomic analysis using the lectin blocking assay treatment with PNA, Artocarpus integrifolia (Jacalin), Glycine max (SBA), Helix pomatia (HPA), Vicia villosa (VVA), Ulex europaeus (UEA-1), Triticum vulgaris (WGA), Canavalia ensiformis (ConA), Phaseolus vulgaris-L (L-PHA), Phaseolus vulgaris-E4 (E-PHA), Datura stramonium (DSA) lectins resulted in modulation of lymphoma cell to galectin-1 suggesting that several types of glycans may regulate cell adhesion to galectin-1 by steric hindrance. The adhesive capacity of H-ALCL cells is regulated by phosphatidylinositol 3 phosphate kinase (PI3K) and actin cytoskeleton, and the invasive capacity of H-ALCL cells is regulated by PI3K, mitogen-activated protein kinase (MAPK), Rho and actin cytoskeleton. Furthermore, galectin-1-induced cell death in H-ALCL cells was accompanied by inhibition of CD45 protein tyrosine phosphatase (PTP) activity. In conclusion, cell adhesion and invasion to galectin-1 appeared to be regulated by cell surface sialylation and N-glycosylation, and galectin-1 regulates cell death through inhibition of CD45 PTP activity of H-ALCL.
Dynamic evaluation of online display advertising with randomized experiments: an aggregated approach

We perform a randomized experiment to estimate the effects of a display advertising campaign on online user conversions. We present a time series approach using Dynamic Linear Models to decompose the daily aggregated conversions into seasonal and trend components. We attribute the difference between control and study trends to the campaign. We test the method using two real campaigns run for 28 and 21 days respectively from the Advertising.com ad network.