Miracle-dz/UniFAR-FTUs huggingface dataset:
Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators

Tests based on generalized-method-of-moments estimators often have true levels that differ greatly from their nominal levels when asymptotic critical values are used. This paper gives conditions under which the bootstrap provides asymptotic refinements to the critical values of t tests and the test of overidentifying restrictions. Particular attention is given to the case of dependent data. It is shown that, with such data, the bootstrap must sample blocks of data and that the formulae for the bootstrap versions of the test statistics differ from the formulae that apply with the original data. Copyright 1996 by The Econometric Society.
Polarization fluctuations in vertical-cavity semiconductor lasers

We report, theoretically and experimentally, how polarization fluctuations in vertical-cavity semiconductor lasers are affected by optical anisotropies. We develop a spin-eliminated ~class A! description of laser polarization and show how the various model parameters can be extracted from the experimental data. In practice, the linear anisotropies are often much stronger than the nonlinear anisotropies, so that the polarization modes defined by the linear anisotropies form a useful basis. For this case we derive a one-dimensional model for polarization noise, with simple expressions for the relative strength of the polarization fluctuations and the rate of polarization switches. For the other, more extreme, case where the nonlinear anisotropies are as strong ~or even stronger ! than the linear anisotropies, the spin-eliminated description remains valid. However, in this case the concept of polarization modes is shown to lose its meaning, as a strong four-wave-mixing peak appears in the optical spectrum and polarization fluctuations become highly nonuniform. @S1050-2947 ~98! 06311-2#
Tidal friction in triple stars

Tidal friction in close binaries, with periods of a few days, is expected to circularize the orbit on a time-scale long compared with human observation but shorter than, or comparable to, the lifetimes of main-sequence stars. In a hierarchical triple star, however, the perturbing effect of the distant third star may decircularize the inner orbit significantly on a time-scale of the order of days (as in λ Tau) or centuries (as in β Per). If the inner pair is observed to be semidetached, however, it is plausible to assume that the eccentricity is small. This may be because tidal friction is operating on a comparably short time-scale, and so it is in principle amenable to observation. We attempt to determine a lower limit to the strength of tidal friction in λ Tau and β Per, on the basis of this consideration. Tidal friction will also lead to a secular transfer of angular momentum from the inner orbit to the outer orbit. Too rapid a transfer may lead to orbital shrinkage that is fast compared with the nuclear time-scales of the inner systems, and this can also be ruled out on observational grounds. Thus we may be able to set an upper as well as a lower limit to the strength of tidal friction, on the basis of observations. In a young hierarchical triple, provided that the orbits are fairly nearly orthogonal, tidal friction can serve to reduce the inner orbital period from months to days within a fairly short period of time, of order P2out/Pin. This may be a significant mechanism for producing young short-period binaries.
OSO-7 observations of the X-ray nova 3U 1543-47

The intensity and spectrum of the transient X-ray source 3U 1543--47 were measured by the MIT X-ray detectors on the OSO-7 satellite on 13 occasions between 1971 November and 1972 December. The results, together with observations of the same object by the Vela and Uhuru satellites, can be described in terms of four qualitatively distinct phases in the X-ray light curve: outburst (1971 July 26); relatively steady intensity and spectrum (1971 August 1 to 1971 November 20); rapid decrease in intensity and decrease in apparent temperature (1971 November 20 to 1972 January 6); irregular intensity fluctuations with complex spectra (1972 January 6 onward). The term ''X-ray nova'' is proposed to characterize this and similar transient sources, and a new model for such X-ray novae is proposed. (AIP)
The role of transjugular intrahepatic portosystemic shunt in patients with cirrhosis and ascites: Recent evolution and open questions

In selected patients with cirrhosis and ascites, transjugular intrahepatic portosystemic shunt (TIPS) placement improves control of ascites and may reduce mortality. In this review, we summarize the current knowledge concerning the use of TIPS for the treatment of ascites in patients with cirrhosis, from pathophysiology of ascites formation to hemodynamic consequences, patient selection, and technical issues of TIPS insertion. The combination of these factors is important to guide clinical decision‐making and identify the best strategy for each individual patient. There is still a need to identify the best timing for TIPS placement in the natural history of ascites (recurrent vs. refractory) as well as which type and level of renal dysfunction is acceptable when TIPS is proposed for the treatment of ascites in cirrhosis. Future studies are needed to define the optimal stent diameter according to patient characteristics and individual risk of shunt‐related side effects, particularly hepatic encephalopathy and insufficient cardiac response to hemodynamic consequences of TIPS insertion.
Mission Resilience Experimentation and Evaluation Testbed

As the complexity of DoD systems increases exponentially, the DoD continues to struggle with understanding and improving the resilience of its mission software. The Applied Resilience for Mission Systems (ARMS) Testbed is an environment that enables resilience improvement by experimentation and assessment of different mission system architectures and approaches. This Testbed consists of components for deploying mission system software for testing, capturing system performance, generating traffic, introducing disruptions into the mission system, orchestrating controlled experiments, and assessing and comparing the performance of mission systems. This paper covers the implementation of this Testbed, analysis for mission resilience comparisons, and their application to an operational terrestrial network architecture. Additionally, we introduce the Distance to Failure metric for comparing the resilience of arbitrary mission systems variations.
Automatic Selection of White Paint Types for Automotive Industry

In this work, we design an optical experimental setup and a data augmentation methodology to generate 384 images of automotive parts, painted with two different types of white paint. We also perform the automatic classification of the database considering two different classes. To obtain the highest precision, we have used two different classification scenarios, 3 algorithms, and 4 metrics. Also, we assume that the results can be improved by extracting the image characteristics using the convolutional neural network ResNet50 and using them as input. Our results show that an error-free classification can be obtained independently of the scenario or classifier. We obtained 100 % in each of the 4 metrics in the six studied variations. Therefore, the machine time is the parameter we can use to select the optimal classifier, where the classifier Multinomial Naïve-Bayes under the Training and Test Set scenario was the fastest algorithm with 65 s, and the classifier Machine Vector Support under the Cross-Validation scenario, the slowest with 79.12 s.
An Alternative Stabilization Approach for Delayed Takagi-Sugeno Discrete Fuzzy Systems

The focus of this study is on the stability and stabilization of constant delay Takagi-Sngeno Fuzzy, TSF systems. We adopt a recently proposed approach based on the products of local matrix norms. This approach is initially used for evaluating stability of state delayed systems with constant retardance. Thereafter, stability conditions for closed-loop controlled plant are established. In light of these results, a TSF controller design approach, PDC, is introduced to stabilize the closed-loop system. An example of stabilization of a state delayed TSF system illustrates the application of the obtained results.
The Application of RNN-based API Data Security Detection in Government Cloud Service

As the government has accelerated the transition to the public service-oriented government and deepened smart government affairs, the electronic government model based on cloud computing has gradually become an important foundation for improving the efficiency of government service and strengthening the government’s own construction. Electronic government uses Application Programming Interface (API) to provide user interfaces and manage business communication, resulting in more and more government services exposed its business services through APIs to government clouds. Therefore, the security of the government cloud has also become the main concern and key success factor. This paper proposes an API anomaly detection method based on Recurrent Neural Network(RNN). By extracting API call features and analyzing its security, this method can provide security protection for API-based business system, intelligently identify security risks from users and applications during operation and prevent hackers from invading.
A Hybrid Approach for Detection of Fake News in Sinhala Text

The impact of technology on people’s lives has grown continuously. The consumption of online news is one of the important trends as the share of population with internet access grows rapidly over time. Global statistics have shown that the internet and social media usage has an increasing trend. Recent developments like the Covid 19 pandemic have amplified this trend even more. However, the credibility of online news is a very critical issue to consider since it directly impacts the society and the people’s mindsets. Majority of users tend to instinctively believe what they encounter and come into conclusions based upon them. It is essential that the consumers have an understanding or prior knowledge regarding the news and its source before coming into conclusions. This research proposes a hybrid model to predict the accuracy of a particular news article in Sinhala text. The model combines the general news content based analysis techniques using machine learning/ deep learning classifiers with social network related features of the news source to make predictions. A scoring mechanism is utilized to provide an overall score to a given news item where two independent scores- Accuracy Score (by analyzing the news content) and Credibility Score (by a scoring mechanism on social network features of the news source) are combined. The hybrid model containing the Passive Aggressive Classifier has shown the highest accuracy of 88%. Also, the models containing deep neural netWorks has shown accuracy around 75-80%. These results highlight that the proposed method could efficiently serve as a Fake News Detection mechanism for news content in Sinhala Language. Also, since there’s no publicly available dataset for Fake News detection in Sinhala, the datasets produced in this work could also be considered as a contribution from this research.
Energy efficiency approaches in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) send their data collaboratively across the network to the main base station responsible for analyzing and processing data. In WSNs, a battery with limited energy is used to drive the systems. Thus, energy consumption in WSNs is a serious problem that hinders their applications. The sensor will fail or be scrapped after consumption of the energy. This work gives an overview about the energy consumption problem in Wireless Sensor Networks (WSNs) and provides a survey on approaches used to optimize the sensors consumption on power. Different strategies used to rise the lifetime of the battery-based sensing nodes by energy minimization are analyzed and commented in this work.
Gradient Boosting Regression Trees for Nonlinear Delay Identification in a Polymer Extrusion Process

Modern polymer extrusion processes, such as pipe productions, usually consist of several interconnected processing steps exhibiting nonlinear behavior. To support the operators at the production line, elaborate control designs are required based on data-driven models. For this purpose, finite impulse response (FIR) models are used to determine the system's behavior, particular the response delay. Unfortunately, conventional linear FIR models do not account for nonlinear dependencies and are prone to high variance for long process delays. On the other hand, Gradient Boosting Regression Tree (GBRT) is an established method in the field of machine learning producing competitive results for numerous nonlinear problems. Consequently, this work proposes a nonlinear FIR model using GBRT at its core. The method is compared to the conventional linear approach and cross-validated based on actual data from a polymer extrusion process. Additionally, the bias and consistency of the GBRT estimator for process delays are examined with the means of a Monte Carlo simulation. It is shown, that the GBRT FIR model shows superior results for the investigated nonlinear, noisy and slow process with long delays.
Clustered Distributed Spatial Multiplexing

This paper introduces distributed spatial multiplexing (DSM) with cooperative communications based on clustering of single-antenna radios. Clusters co-transmit their shared messages toward a destination radio equipped with multiple antennas. In the baseline configuration, there is no coordination beyond message sharing, and the resulting incoherent DSM scheme offers user cooperation diversity for each data stream. A second, novel variant of clustered DSM leverages distributed beamforming (DBF) techniques, wherein each cluster independently coordinates for RF phase alignment at a different destination radio antenna. In sample topologies, the resulting clustered coherent DSM outperforms the baseline incoherent variant by a large margin, and operates with close proximity to the idealized capacity-achieving (yet impractical) DSM based on singular value decomposition (SVD) of the distributed channel matrix.
Threat modeling for robotic-based production plants

The benefits of applying and integrating robotics and automation machinery in production plans are being followed by the peak of cybersecurity issues associated with them. This study presents the threat model for a production plant integrated with different components such as PLCs, machine tools, sensors, actuators, and robots. Attending to the heterogeneity of components, protocols, and devices, this paper tries to represent the possible threats that would be affecting the factory and proposes a set of changes and mitigations that would increase their cybersecurity and resilience.
Influence of dielectric properties of a substrate upon plasmon resonance spectrum of supported Ag nanoparticles

Plasmon resonance spectra of supported Ag nanoparticles are studied by depositing the particles on different substrates. It was found that the dielectric properties of the substrates have significant effects on the spectral line shape, except the resonance frequency. Beyond the plasmon resonance band, the spectral shape is mainly governed by the dielectric function, particularly its imaginary part, of the substrate. The plasmon resonance band, on the other hand, may be severely distorted if the substrate is absorbing strongly.
Guide for Stabilization and Heuristic Optimization of Second-order Systems Controlled by P/I-delayed Controllers

The present paper shows the procedure for the stabilization and subsequent optimization of second-order systems using a proportional plus integral delayed controller. Stabilizing closed-loop control systems using a controller comprehends several techniques to increase the control circuit's stability. Even in some simple second-order plants, the classical proportional integral controller cannot be applied to pursue closed-loop stability. However, the design requires constant reference tracking capability, for example. Moreover, if there is a time delay in the feedback loops inside a controlled system, the system has an infinite spectrum – infinitely many roots (poles); this degrades the control's quality, especially in terms of stability, robustness, and oscillation response. For these reasons, it is also necessary to optimize the transient response of the system. The main objective of this paper is to provide a guide for optimal control of second-order systems controlled by a proportional integral-delayed controller. Some examples are chosen as benchmarks to verify the effectiveness of the stabilization and subsequent heuristic optimization. In future research, we would like to focus on implementing selected modern optimization algorithms for solving non-smooth, non-convex, and non-Lipschitz optimization problems.
Multiple Hierarchical Analysis

A multivariate method for exploratory scalogram analysis of binary data is developed—Multiple Hierarchical Analysis (MHA). This method, based on certain factor analytic methodology, is demon strated using an illustrative data set. It is concluded that the MHA methodology will be functional in identifying underlying independent and noninde pendent scales in binary data.
Reflected Brownian Motion on an Orthant

We consider a K-dimensional diffusion process Z whose state space is the nonnegative orthant. On the interior of the orthant, Z behaves like a Kdimensional Brownian motion with arbitrary covariance matrix and drift vector. At each of the (K-1) dimensional hyperplanes that form the boundary of the orthant, Z reflects instantaneously in a direction that is constant over that hyperplane. There is no extant theory of multidimensional diffusion that applies to this process, because the boundary of its state space is not smooth. We adopt an approach that requires a restriction on the directions of reflection, but Reiman has shown that this restriction is met by all diffusions Z arising as heavy traffic limits in open K-station queuing networks. Our process Z is defined as a path-to-path mapping of K-dimensional Brownian motion. From this construction it follows that Z is a continuous Markov process and a semimartingale. Using the latter property, we obtain a change of variable formula from which one can develop a complete analytical theory for the process Z.
Relative timing of electron acceleration and injection at solar flares: A case study

Multiple-wavelength observations of a C-class solar flare and in situ measurements of high-energy electrons at 1 AU are combined for a detailed analysis of the relative timing of solar electromagnetic emission and high-energy electron injection. The primary energy release for the C8.0 flare on 2002 June 02 (10:05-10:30 UT) is studied using hard X-ray data of the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). The propagation of disturbances through the solar corona and interplanetary space is investigated by means of dynamic radio spectra obtained by ground-based observatories (Ondřejov, Czech Republic, and Potsdam, Germany). The time sequence of these indirect manifestations of highly energetic electrons is correlated with the extrapolated injection time obtained by a transit time analysis from Sun to Earth using the enhancement in the 27-182 keV electron intensity observed at the Wind spacecraft. This back-mapping of high-energy electrons shows that the particles are injected roughly 18 min after the lirst hard X-ray maximum. Almost at the same time there are observations of metric type II and IV radio bursts indicating the presence of a coronal shock wave and a moving plasmoid whose kinematics are analysed by means of dynamic radio spectra and radio images from the Nancay Radioheliograph (France). Implications for possible acceleration and injection scenarios are discussed.
Development of a spherical induction motor with two degrees of freedom

This paper reports on the development of a spherical actuator with two actuated degrees of freedom (DOFs). The electromechanical conversion principle is that of an induction motor. The paper first discusses possibilities of adapting the actuator to a spherical rotor actuated with an unlimited angular range along two DOFs. These concepts are then characterized and compared by analytical and numerical modeling, and the final shape of the actuator, composed of a two-layer rotor with teeth surrounded by five inductors, is described. A prototype has been built, and its performance, in terms of characteristic torque-speed and efficiency, has been measured.
Experimental study on the evolution of traveling waves over an undulated incline

We present experimental results on the evolution of traveling waves over a strongly undulated incline. In order to investigate the difference between waves in the linearly stable and unstable region, we set the Reynolds number near the neutral curve. That way, we were able to cross the neutral curve by increasing the frequency of excitation, without changing the velocity field of the basic flow. The amplitude of excitation was also varied, to analyze the evolution of both linear and nonlinear waves. We report on a rich variety of phenomena, including: (a) energy transfer from the excitation frequency to its higher harmonics, (b) the growth rate of the traveling waves, (c) the stability of traveling waves depending on its amplitude, and (d) the amplitude of saturation depending on the excitation frequency. We compare our results to those so far available in the literature. To our knowledge, this is the first experimental work on the development of traveling waves over strongly undulated substrate geometries.
Edge-Connectivity Augmentation Preserving Simplicity

Given a simple graph G=(V,E), our goal is to find a smallest set F of new edges such that G=(V,E\cup F) is k-edge-connected and simple. Recently this problem was shown to be NP-complete. In this paper we prove that if OPT_P^k$ is high enough---depending on k only---then OPT _S^k= OPT_P^k$ holds, where OPT_S^k$ (OPT_P^k$) is the size of an optimal solution of the augmentation problem with (without) the simplicity-preserving requirement, respectively. Furthermore, OPT_S^k- OPT _P^k\leq g(k) holds for a certain (quadratic) function of k. Based on these facts an algorithm is given which computes an optimal solution in time O(n4) for any fixed k. Some of these results are extended to the case of nonuniform demands as well.
A recursive algorithm for nonparametric analysis with missing data

SUMMARY The mixture of Dirichlet processes posterior that arises in nonparametric Bayesian analysis has been analysed most effectively using Markov chain Monte Carlo. As a computationally simple alternative, we introduce a recursive approximation based on one-step posterior predictive distributions. Asymptotic calculations provide theoretical support for this approximation, and we investigate its actual behaviour in several numerical examples. From a non-Bayesian perspective, this new recursion may be used to obtain solutions of the self-consistency equations.