Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution function tracking filter for stochastic nonlinear systems with uncertain dynamics

A novel filter design is presented for a class of multivariate nonlinear stochastic systems with uncertain dynamics. The system is subject to non-Gaussian process noises. The entire filter system is proved to be bounded in terms of a specified performance index, provided that the weighting function satisfies a certain condition. An analytical solution of optimal filter gain matrix is also given. Further, the estimation error system is exponentially and ultimately bounded in the mean square sense, even with the presence of system uncertainties. Finally, a simulation example is demonstrated to validate the proposed scheme.
Area Throughput for CSMA based Wireless Sensor Networks

In this paper we present a mathematical approach to evaluate the area throughput of a multi-sink wireless sensor network (WSN), where nodes transmit their packets to a sink, selected among many. Sensors and sinks are both Poisson distributed in a bounded domain. A carrier sensing multiple access (CSMA) based protocol is used by nodes to access the channel. We denote as area throughput the amount of samples per second successfully transmitted to the sinks. This performance metric is strictly related to both connectivity and MAC issues: it depends, in fact, on the probability that a given sensor node is not isolated and that it succeeds in transmitting its packet (i.e., the packet does not collide). The aim of this work is to devise a mathematical model that takes CSMA and connectivity issues into account under a joint approach. Through this model some network optimisation strategies could be derived. As an example, sensors could perform an aggregation procedure, responding sporadically to queries with a single packet composed of all samples taken since the previous transmission. Our model allows the evaluation of the optimum size of the packet that should be transmitted, so that the area throughput is maximised. Finally, the effects of the connectivity on the area throughput are evaluated.
Effect of 3-Hydroxy-3-Methylglutaryl-Coenzyme A Reductase Inhibitor on Disease Activity in Patients With Rheumatoid Arthritis

Abstract HMG-CoA reductase inhibitors (also known as statins) are widely used as lipid-lowering agents in patients with rheumatoid arthritis (RA) to reduce their cardiovascular risk. However, whether they have an effect on RA disease activity is controversial. This study aimed to investigate the effect of statins on disease activity in RA patients. A systematic literature review was performed using the MEDLINE, EMBASE, Cochrane Library, ISI WEB of Knowledge, Scopus, and Clinical Trials Register databases. Only prospective randomized controlled trials or controlled clinical trials comparing the efficacy of statins with placebo on adult RA patients were included. The efficacy was measured according to the ACR criteria, EULAR criteria, DAS28, HAQ score, ESR, or CRP. The Jadad score was used for quality assessment. The inverse variance method was used to analyze continuous outcomes. A fixed-effects model was used when there was no significant heterogeneity; otherwise, a random-effects model was used. For stability of results, we performed leave-one-study-out sensitivity analysis by omitting individual studies one at a time from the meta-analysis. Publication bias was assessed using Egger test. A total 13 studies involving 737 patients were included in the meta-analysis; 11 studies were included in the meta-analysis based on DAS28, while the other 2 studies were only included in the meta-analysis based on ESR or CRP. The standardized mean difference (SMD) in DAS28 between the statin group and the placebo group was −0.55 (95% CI [−0.83, −0.26], P = 0.0002), with an I2 value of 68%. Subgroup analysis showed that patients with more active disease tended to benefit more from statin therapy (SMD −0.73, P = 0.01) than patients with moderate or low disease activity (SMD −0.38, P = 0.03). Statin therapy also significantly reduced tender joint counts, swollen joint counts, ESR, and CRP compared with placebo, but the reduction in HAQ score and VAS was not significant (P > 0.05). This meta-analysis suggested that statin therapy might be effective in the reduction of RA disease activity measured by DAS28, TJC, SJC, as well as ESR and CRP.
Extracting Interpretable Features for Early Classification on Time Series

Early classification on time series data has been found highly useful in a few important applications, such as medical and health informatics, industry production management, safety and security management. While some classifiers have been proposed to achieve good earliness in classification, the interpretability of early classification remains largely an open problem. Without interpretable features, application domain experts such as medical doctors may be reluctant to adopt early classification. In this paper, we tackle the problem of extracting interpretable features on time series for early classification. Specifically, we advocate local shapelets as features, which are segments of time series remaining in the same space of the input data and thus are highly interpretable. We extract local shapelets distinctly manifesting a target class locally and early so that they are effective for early classification. Our experimental results on seven benchmark real data sets clearly show that the local shapelets extracted by our methods are highly interpretable and can achieve effective early classification.
Structure-aware non-negative dictionary learning

Blind spectrogram decompositions are commonly used for tasks such as automatic transcription. In musical spectrograms, signal elements are highly overlapping in both the time and frequency domains, presenting difficulties to the decomposition method. The harmonic structure prevalent in tonal music signals has been exploited in decomposition methods with positive results. The performance of blind decompositions for transcription tasks has been shown to be dependent on the relationship of the learning order to the number of sources in the signal. We consider structure-aware dictionary learning methods, which have prior knowledge of the structure and cardinality of the sources.
Authorship Identification of E-mail as a Multi-Class Task - Notebook for PAN at CLEF 2011

In this paper, we describe a multi-class text categorization approach to authorship attribution and test it on sets of e-mail collections. The PAN 2011 competition data consists of e-mails of variable length, written by various candidate authors, with some represented by signiﬁcantly longer or more e-mails than others. Rather than construct a classiﬁer for each separate author to discriminate it from the others (i.e. binary classiﬁcation), we adopt a multi-class scheme where all authorship classes are learned simultaneously. We explore the effect of the selection of feature types and of the C parameter in the SVM multiclass learning algorithm. Variable-length lexical features showed promising results, neverthe-less our authorship attribution approach only scored a mid position amongst the other competitors, for the S MALL as well as the L ARGE test sets.
Eye gaze tracking with free head movements using a single camera

The problem of eye gaze tracking has been researched and developed for a long time. The most difficult problem in the non-intrusive system of eye gaze tracking is the problem of head movements. Some of existing methods have to use two cameras and an active infrared (IR) illumination to solve this problem. Otherwise, with a single camera, the user has to hold the head uncomfortably still when performing a session of eye gaze tracking. If the head of the user moves away from original position, the accuracy of these eye gaze-tracking systems drops dramatically. In this paper, we propose a solution using Gaussian Processes for eye gaze tracking that allows free head movements with a single camera.
On a small gain theorem for networks of iISS systems

This paper considers networks consisting of integral input-to-state stable (iISS) subsystems and addresses the problem of verifying iISS property of a given network. First, we focus on construction of continuously differentiable Lyapunov functions, and derive a condition ensuring the iISS of the network comprising n subsystems. Although this approach referred to as the sum-type construction has not yet been reduced to an easily computable condition for general n, the n = 2 case recovers the iISS small-gain condition for two subsystems developed recently. Next, in the case of n subsystems, using Lipschitz continuous Lyapunov functions, this paper derives a small-gain condition. It is shown that this second approach referred to as the max-type construction fails to offer a Lyapunov function if there exist subsystems which are not input-to-state stable (ISS). The relation between the two formulations is discussed in the case of two ISS subsystems.
A new method of verifying digital signatures in e-cheque processing

We have considered a scenario in Financial Institutions(FI) like e-banks where there is facility for e-cheques to replace paper cheques. Everyday banks receive a large number of cheques signed by different signers. These cheques need to be submitted to their corresponding clearing banks over internet for clearance. After verification the clearing banks send signed instructions to the cheque submitted bank stating whether the cheque is accepted or rejected. This instruction is very important for any cheque submitting bank and it must verify the signed instruction. To verify this signature, the bank must have access to the signerpsilas public key and have assurance that it corresponds to the signerpsilas private key. But banks cannot store public keys of all possible transacting banks. Therefore there is need for a method to verify a signature without using the public key but still be convinced that it is signed by the actual signer. As e-cheques are transferred over internet, valid signatures of the bank clearing the e-cheque (as the e-cheque leaves are issued by this bank), payer and payee of the e-cheque are already available on the e-cheque submitted by the payee. Therefore we have come up with a method by which one can verify that a new signature received from a signer indeed belongs to the same signer without the help of public key of the signer but instead using the valid signature of the signer available on the e-cheque. This scheme works with the most widely used DSA and ElGamal Schemes. We consider another scenario in which a bank receives n signed cheques out of which some of them may be signed by the same signer and others by different signers. To avoid individual verification of the cheque, we propose a method by which the verifier will be able to verify all the cheques at a time using a single verification equation. This saves ap 160n modular multiplications when compared to individual signature verification of DSA.
Robust Computational Analysis of rRNA Hypervariable Tag Datasets

Next-generation DNA sequencing is increasingly being utilized to probe microbial communities, such as gastrointestinal microbiomes, where it is important to be able to quantify measures of abundance and diversity. The fragmented nature of the 16S rRNA datasets obtained, coupled with their unprecedented size, has led to the recognition that the results of such analyses are potentially contaminated by a variety of artifacts, both experimental and computational. Here we quantify how multiple alignment and clustering errors contribute to overestimates of abundance and diversity, reflected by incorrect OTU assignment, corrupted phylogenies, inaccurate species diversity estimators, and rank abundance distribution functions. We show that straightforward procedural optimizations, combining preexisting tools, are effective in handling large () 16S rRNA datasets, and we describe metrics to measure the effectiveness and quality of the estimators obtained. We introduce two metrics to ascertain the quality of clustering of pyrosequenced rRNA data, and show that complete linkage clustering greatly outperforms other widely used methods.
A comparative study of motion estimation algorithms in cardiac ultrasound sequences

Quantitative analysis and motion estimation of the moving organs, as the heart and lungs, is one of the main objectives pursued in analysis of medical images. In fact, cardiac motion estimation has been widely used with the segmentation to evaluate the cardiac function and a various approaches of motion estimation have been proposed. In this paper, a comparative study of myocardial motion estimation methods, which are applied on ultrasound echographic sequence, is presented.
A Secure Online Reputation Defense System from Unfair Ratings using Anomaly Detections

aggregates these feedbacks as evidence and generates the aggregated results to the normal users. These aggregated results are called reputation scores. We can call this system as online feedback-based reputation system. To protect the reputation system many defense schemes have been developed. In this paper we propose a defense scheme; it is the combination of five modules. Evaluation based filtering, Time domain unfair rating detector, suspicious user correlation analysis, trust analysis based on Dempster-Shafer theory and malicious user identification and reputation recovery. This system identifies the items under attacks, the time when the attacks occur and unfair raters who insert unfair ratings. Compared with existing systems this system achieves detection of high unfair ratings and reduces the detection of false dishonest ratings.
Gender Perceptions of Administrative Team Members Regarding Secondary Principals' Leadership Actions and Behaviors in Managing Change

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Cystatin C in Acute Coronary Syndrome

Cystatin C has been regarded as a novel sensitive marker for the assessment of renal function, and the role of cystatin C as a predictor of cardiovascular events in patients with impaired renal function has been confirmed in clinical studies. In this study we assessed the association between cystatin C and Coronary artery disease [CAD] in a consecutive series of patients with normal kidney function in order to avoid the well-known effect of overt renal insufficiency on coronary atherosclerosis, and evaluate whether cystatin C has an ability to identify individuals at a higher risk for CAD among patients belonging to a low-risk category according to estimated glomerular filtration rate . The current study and review of literature demonstrated that serum levels of cystatin C, were independently associated with the development of CAD.
Relax, but Don't be Too Lazy

Assume that we wish to expand the product h = fg of two formal power series f and g. Classically, there are two types of algorithms to do this: zealous algorithms first expand f and g up to order n, multiply the results and truncate at order n. Lazy algorithms on the contrary compute the coefficients of f, g and h gradually and they perform no more computations than strictly necessary at each stage. In particular, at the moment we compute the coefficient hi of zi in h, only f0,. , fi and g0,. , gi are known.Lazy algorithms have the advantage that the coefficients of f and g may actually depend on "previous" coefficients of h, as long as they are computed before they are needed in the multiplication, i.e. the coefficients fi and gi may depend on h0,. , hi-1. For this reason, lazy algorithms are extremely useful when solving functional equations in rings of formal power series. However, lazy algorithms have the disadvantage that the classical asymptotically fast multiplication algorithms on polynomials--such as the divide and conquer algorithm and fast Fourier multiplication--cannot be used.In a previous paper, we therefore introduced relaxed algorithms, which share the property concerning the resolution of functional equations with lazy algorithms, but perform slightly more computations than lazy algorithms during the computation of a given coefficient of h. These extra computations anticipate the computations of the next coefficients of h and dramatically improve the asymptotic time complexities of such algorithms.In this paper, we survey several classical and new zealous algorithms for manipulating formal power series, including algorithms for multiplication, division, resolution of differential equations, composition and reversion. Next, we give various relaxed algorithms for these operations. All algorithms are specified in great detail and we prove theoretical time and space complexity bounds. Most algorithms have been experimentally implemented in C++ and we provide benchmarks. We conclude by some suggestions for future developments and a discussion of the fitness of the lazy and relaxed approaches for specific applications.This paper is intended both for those who are interested in the most recent algorithms for the manipulation of formal power series and for those who want to actually implement a power series library into a computer algebra system.
Gaudí and CAD

The presence and uptake of the computer, so omni-influential in approaches to design and architectural representation over the last decade, has begun to have an effect on built form and design quality. The computer has a reciprocal involvement in a revolution in thinking about space and time that has created a shift from the stable and metric (Euclidian) concepts inherited from the Classical through Renaissance and Modernist world to a more dynamic, unstable and unpredictable model, more closely aligned with our understanding of natural systems of growth, form and evolution. This paper focuses on a similarly reciprocal relationship between the developing use of computer-aided architectural design (CAD) and the detailed design and construction of the greatest work of a forerunner of this contemporary shift in spatial theory in architecture, the Catalan architect Antoni Gaudi. For fifteen years the introduction of the computer has contributed to the realisation of the highly complex Sagrada Familia church based on the design bequeathed from Gaudi. While it has impacted on the speed, precision, research and design process, and undoubtedly the built outcome, the use of the computer has also contributed to the depth of understanding of the conceptual design system underlying Gaudi’s formal expression. Conceived long before the possibility of electronic computation and still beyond the powers of conventional architectural software, the implementation of this systemic approach to design is a rich source in the quest for meaningful use of computation in design and construction today and tomorrow. It promotes experimental uses of computing in both reverse engineering the design from the original architect’s gypsum plaster models and scant surviving images, and streamlining the communication and construction.
Production and Secretion Stress Caused by Overexpression of Heterologous α-Amylase Leads to Inhibition of Sporulation and a Prolonged Motile Phase in Bacillus subtilis

ABSTRACT Transcriptome analysis was used to investigate the global stress response of the gram-positive bacterium Bacillus subtilis caused by overproduction of the well-secreted AmyQ α-amylase from Bacillus amyloliquefaciens. Analyses of the control and overproducing strains were carried out at the end of exponential growth and in stationary phase, when protein secretion from B. subtilis is optimal. Among the genes that showed increased expression were htrA and htrB, which are part of the CssRS regulon, which responds to high-level protein secretion and heat stress. The analysis of the transcriptome profiles of a cssS mutant compared to the wild type, under identical secretion stress conditions, revealed several genes with altered transcription in a CssRS-dependent manner, for example, citM, ylxF, yloA, ykoJ, and several genes of the flgB operon. However, high-affinity CssR binding was observed only for htrA, htrB, and, possibly, citM. In addition, the DNA macroarray approach revealed that several genes of the sporulation pathway are downregulated by AmyQ overexpression and that a group of motility-specific (σD-dependent) transcripts were clearly upregulated. Subsequent flow-cytometric analyses demonstrate that, upon overproduction of AmyQ as well as of a nonsecretable variant of the α-amylase, the process of sporulation is severely inhibited. Similar experiments were performed to investigate the expression levels of the hag promoter, a well-established reporter for σD-dependent gene expression. This approach confirmed the observations based on our DNA macroarray analyses and led us to conclude that expression levels of several genes involved in motility are maintained at high levels under all conditions of α-amylase overproduction.
A Self-Organizing Neural Network for the Traveling Salesman Problem That Is Competitive with Simulated Annealing

Unsupervised learning applied to an unstructured neural network can give approximate solutions to the traveling salesman problem. For 50 cities in the plane this algorithm performs like the elastic net of Durbin and Willshaw (1987) and it improves when increasing the number of cities to get better than simulated annealing for problems with more than 500 cities. In all the tests this algorithm requires a fraction of the time taken by simulated annealing.
Ant Colony Optimization Based Fuzzy Sliding Mode Controller for the Twin Rotor MIMO system

The ant colony optimization (ACO) algorithm is an evolutionary computational technique based on the behavior of a set of ants that communicate through the deposit of pheromone. It involves a node choice probability which is a function of pheromone strength and inter-node distance to construct a path through a node-arc graph. The algorithm allows fast near optimal solutions to be found compared to other stochastic methods. In this paper, a novel approach for angel positions control of a Twin Rotor Multi input–multi output System (TRMS) by means of a sliding mode controller (SMC), fuzzy logic controller (FLC) and ACO is investigated. For decreasing the chattering problem of the SMC, a FLC is used to replace the discontinuity in the sign function of the reaching law in the SMC. For selecting sliding surface constants and FLC input/output membership function parameters, the basic ACO algorithm is employed to search these parameters. To verify the feasibility and robustness of the control method, simulation results from a TRMS with the designed controller are given as an illustration. Furthermore, the performance comparisons with the Proportional Integral Differential (PID) controller tuned using the same method are provided to show that the control method has better performance in the aspect of tracking error and control signals energy.