Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensity detecting refractive index sensors with long-period fiber gratings written in STS structure

A refractive index intensity detecting sensor with long-period grating written in the single-mode–thin-core–single-mode fiber (STS) structure is proposed and optimized theoretically. The sensor is composed of two single-mode fibers connected by a section of long-period fiber grating fabricated on thin-core fiber. After optimization and benefitting from the phase matching point, the loss peak of the structure can reach 62.8 dB theoretically. The wavelength of the characteristic peak is fixed at the phase matching point, so intensity detection can be achieved. The sensitivity can reach 272.5 dB/RIU. The structural optimization in this Letter provides a reference for the fabrication of an easy-made all-fiber sensor without extra cladding.
Polarization-Graded AlGaN Solar-Blind p-i-n Detector With 92% Zero-Bias External Quantum Efficiency

We report on record high zero-bias external quantum efficiency (EQE) of 92% for back-illuminated Al<sub>0.40</sub>Ga<sub>0.60</sub>N p-i-n ultra-violet (UV) photodetectors on sapphire. The zero-bias responsivity measured 211 mA/W at 289 nm, which is the highest value reported for solar-blind, p-i-n detectors realized over any epitaxial wide band-gap semiconductor. This is also the first report for a p-i-n detector, where a polarization-graded Mg-doped AlGaN layer is utilized as the p-contact layer. The devices exhibited a ten-orders of magnitude rectification, a low reverse leakage current density of 1 nA/cm<sup>2</sup> at 10 V, a high <inline-formula> <tex-math notation="LaTeX">$\text{R}_{{0}}\text{A}$ </tex-math></inline-formula> product of <inline-formula> <tex-math notation="LaTeX">$1.3\times 10^{{11}} \Omega $ </tex-math></inline-formula>. cm<sup>2</sup> and supported fields exceeding 5 MV/cm. The light-to-dark current ratio and the UV-to-visible rejection ratio for the detectors exceeded six-orders of magnitude and the thermal noise limited detectivity (D*) measured <inline-formula> <tex-math notation="LaTeX">$6.1\times 10^{{14}}$ </tex-math></inline-formula> cmHz<sup>1/2</sup>W<sup>−1</sup>. The state-of-the-art performance parameters can be attributed to a high crystalline quality absorbing AlGaN epi-layer resulting from the use of an AlN/AlGaN superlattice buffer and an improved p-contact via polarization grading.
Model-free spatial Interpolation and error prediction for survey data acquired by mobile platforms

The paper proposes a new randomized Cross Validation (CV) criterion specially designed for use with data acquired over non-uniformly scattered designs, like the linear transect surveys typical in environmental observation. Numerical results illustrate the impact of randomized cross-validation in real environmental datasets showing that it leads to interpolated fields with smaller error at a much lower computational load. Randomized CV enables a robust parameterization of interpolation algorithms, in a manner completely driven by the data and free of any modelling assumptions. The new method proposed here resorts to tools and concepts from Computational Geometry, in particular the Yao graph determined by the set of sampled sites. The method randomly chooses the hold-out sets such that they reflect, statistically, the geometry of the design with respect to the unobserved points of the area where the observations are to be extrapolated, minimizing biases due to the particular geometry of the designs.
A Process-Based Climatological Evaluation of AIRS Level 3 Tropospheric Thermodynamics over the High-Latitude Arctic

Measurements from spaceborne sensors have the unique capacity to fill spatial and temporal gaps in ground-based atmospheric observing systems, especially over the Arctic, where long-term observing stations are limited to pan-Arctic landmasses and infrequent field campaigns. The AIRS level 3 (L3) daily averaged thermodynamic profile product is widely used for process understanding across the sparsely observed Arctic atmosphere. However, detailed investigations into the accuracy of the AIRS L3 thermodynamic profiles product using in situ observations over the high-latitude Arctic are lacking. To address this void, we compiled a wealth of radiosounding profiles from long-term Arctic land stations and included soundings from intensive icebreaker-based field campaigns. These are used to evaluate daily mean thermodynamic profiles from the AIRS L3 product so that the community can understand to what extent such data records can be applied in scientific studies. Results indicate that, while the mid- to upper-troposphere temperature and specific humidity are captured relatively well by AIRS, the lower troposphere is susceptible to specific seasonal, and even monthly, biases. These differences have a critical influence on the lower-tropospheric stability structure. The relatively coarse vertical resolution of the AIRS L3 product, together with infrared radiation through persistent low Arctic cloud layers, leads to artificial thermodynamic structures that fail to accurately represent the lower Arctic atmosphere. These thermodynamic errors are likely to introduce artificial errors in the boundary layer structure and analysis of associated physical processes.
A critical comparison of two methods of statistical discrimination

Important clinical differences arising in the application of commonly advocated discriminant or diagnostic methods demand a thorough assessment of the realism of their different assessments. Recent theoretical work on the estimation of density functions provides reasons for these differences and suggests which methods should provide greater realism. These suggestions are strongly supported by a simulation study. Specific recommendations are made concerning statistical diagnostic practice.
Multiple Instance Learning with Deep Instance Selection for Video-based Face Recognition

a lnfw01@163.com Keywords: Multiple instance learning, deep learning, video-based face recognition. Abstract. In many real-world video-based face recognition scenarios, videos are usually captured under unconstrained conditions. It is very challenging because of low face resolutions, varying head pose and complex lighting. To address this issue, we present a new method by formulating the video-based face recognition issue as a multi-instance learning (MIL) problem. Specifically, given a pair of videos, we generate a bag composed of all the frame pairs from the two videos. The bag is positive if the given pair of videos is from the same person, otherwise it is negative. In this way, the recognition task is formulated as a binary classification problem in MIL. Then we propose a novel MIL algorithm with deep instance selection (MILDIS), which maps each bag into a feature space defined by the selected instances via an instance similarity measure. Our work achieves the state-of-the-art performances on the real-world datasets YouTube Faces (YTF) according to the restricted protocol.
Universal quantum computation with quantum-dot cellular automata in dephasing-free subspace

We investigate the possibility to have electron-pairs in dephasing-free subspace (DFS), by means of the quantum-dot cellular automata (QCA) and single-spin rotations, to carry out a high-fidelity and deterministic universal quantum computation. We show that our QCA device with electrons tunneling two dimensionally is very suitable for DFS encoding, and argue that our design favors a scalable quantum computation robust to collective dephasing errors.
Backward error analysis for linearizations in heavily damped quadratic eigenvalue problem

Heavily damped quadratic eigenvalue problem (QEP) is a special type of QEPs. It has a large gap between small and large eigenvalues in absolute value. One common way for solving QEP is to linearize the original problem via linearizations. Previous work on the accuracy of eigenpairs of not heavily damped QEP focuses on analyzing the backward error of eigenpairs relative to linearizations. The objective of this paper is to explain why different linearizations lead to different errors when computing small and large eigenpairs. To obtain this goal, we bound the backward error of eigenpairs relative to the linearization methods. Using these bounds, we build upper bounds of growth factors for the backward error. We present results of numerical experiments that support the predictions of the proposed methods.
An automated performance budget estimator: a process for use in instrumentation

Current day astronomy projects continue to increase in size and are increasingly becoming more complex, regardless of the wavelength domain, while risks in terms of safety, cost and operability have to be reduced to ensure an affordable total cost of ownership. All of these drivers have to be considered carefully during the development process of an astronomy project at the same time as there is a big drive to shorten the development life-cycle. From the systems engineering point of view, this evolution is a significant challenge. Big instruments imply management of interfaces within large consortia and dealing with tight design phase schedules which necessitate efficient and rapid interactions between all the stakeholders to firstly ensure that the system is defined correctly and secondly that the designs will meet all the requirements. It is essential that team members respond quickly such that the time available for the design team is maximised. In this context, performance prediction tools can be very helpful during the concept phase of a project to help selecting the best design solution. In the first section of this paper we present the development of such a prediction tool that can be used by the system engineer to determine the overall performance of the system and to evaluate the impact on the science based on the proposed design. This tool can also be used in "what-if" design analysis to assess the impact on the overall performance of the system based on the simulated numbers calculated by the automated system performance prediction tool. Having such a tool available from the beginning of a project can allow firstly for a faster turn-around between the design engineers and the systems engineer and secondly, between the systems engineer and the instrument scientist. Following the first section we described the process for constructing a performance estimator tool, followed by describing three projects in which such a tool has been utilised to illustrate how such a tool have been used in astronomy projects. The three use-cases are; EAGLE, one of the European Extremely Large Telescope (E-ELT) Multi-Object Spectrograph (MOS) instruments that was studied from 2007 to 2009, the Multi-Object Optical and Near-Infrared Spectrograph (MOONS) for the European Southern Observatory’s Very Large Telescope (VLT), currently under development and SST-GATE.
Research on Complex Products based on Digital Layout Design and Simulation Modeling

From the point of view of digital product development, this paper makes a deep discussion and research on the key technologies of pipeline layout design, pipeline layout optimization, and assembly simulation in the process of complex product development. We introduce an automatic pipe layout techniques based on improved rapidly exploring random tree, it could able to quickly establish the framework model of pipeline system, on this basis are discussed a pipeline of the simulated annealing algorithm based on automatic optimization algorithm, and interactive pipeline layout method, using computer artificial intelligence and design personnel manual intervention method to improve the quality of pipe layout. Also, we make the system realization of automatic layout of pipe line, and put forward related Suggestions.
ANN-Based Control of a Wheeled Inverted Pendulum System Using an Extended DBD Learning Algorithm

This paper presents a dynamic model for a self-balancing vehicle using the Euler-Lagrange approach. The design and deployment of an artificial neuronal network (ANN) in a closed-loop control is described. The ANN is characterized by integration of the extended delta-bar-delta algorithm (DBD), which accelerates the adjustment of synaptic weights. The results of the control strategy in the dynamic model of the robot are also presented.
Describing seasonal differences in tree crown delineation using multispectral UAS data and structure from motion

ABSTRACT Unmanned Aerial Systems (UAS) have emerged as a platform capable of providing valuable data on vegetation structure, health, and productivity. The platform provides maximum temporal flexibility in data collection and customizability of spatial footprints which is important for mapping and monitoring vegetation conditions especially for high spectrally and structurally heterogeneous landscapes. In this letter, we investigate the potential improvement in structural information when using sensor payloads that include infrared bands (730–810 nm) in addition to the typical visible bands of many UAS sensor payloads. Specifically, we use derived point clouds and imagery collected from UAS-mounted sensors at a test site in Louisville, Kentucky, USA to assess whether multispectral sensors improve estimates of vegetation structure for plant greenness (leaf-on) and senescence (leaf-off) periods. Results indicate that including detailed multispectral reflectance information beyond the visible portion of the electromagnetic spectrum aids in estimating structural characteristics of woody vegetation, regardless of season. While both leaf-on and leaf-off periods result in reasonable crown height estimates, leaf-on conditions also improve radial estimates, likely due to continuous canopy surfaces. These findings advance research for remote sensing analyses assessing structural composition in heterogeneous landscapes where varying levels of vegetation structure have implications on land use and land function.
An Enhanced Web Document Search Engine using a Semantic Network

With the rapid advancement of ICT technology, the World Wide Web (referred to as the Web) has become the biggest information repository whose volume keeps growing on a daily basis. The challenge is how to find the most wanted information from the Web with a minimum effort. This paper presents a novel ontology-based framework for searching the related web pages to a given term within a few given specific websites. With this framework, a web crawler first learns the content of web pages within the given websites, then the topic modeller finds the relations between web pages and topics via key words found on the web pages using the Latent Dirichlet Allocation (LDA) technique. After that, the ontology builder establishes an ontology which is a semantic network of web pages based on the topic model. Finally, a reasoner can find the related web pages to a given term by making use of the ontology. The framework and related modelling techniques have been verified using a few test websites and the results convince its superiority over the existing web search tools.
The Standard Errors of Persistence

A large literature on persistence finds that many modern outcomes strongly reflect characteristics of the same places in the distant past. However, alongside unusually high t statistics, these regressions display severe spatial autocorrelation in residuals, and the purpose of this paper is to examine whether these two properties might be connected. We start by running artificial regressions where both variables are spatial noise and find that, even for modest ranges of spatial correlation between points, t statistics become severely inflated leading to significance levels that are in error by several orders of magnitude. We analyse 27 persistence studies in leading journals and find that in most cases if we replace the main explanatory variable with spatial noise the fit of the regression commonly improves; and if we replace the dependent variable with spatial noise, the persistence variable can still explain it at high significance levels. We can predict in advance which persistence results might be the outcome of fitting spatial noise from the degree of spatial autocorrelation in their residuals measured by a standard Moran statistic. Our findings suggest that the results of persistence studies, and of spatial regressions more generally, might be treated with some caution in the absence of reported Moran statistics and noise simulations.
A new approach to the use of decision tables in software engineering

JAN V ANTHIENEN ELKEDRIES Katholieke U niversiteit Leuven Department of Applied Economic Sciences Dekenstraat 2, B-3000 Leuven (Belgium) The ability of the decision table to represent complex decision situations in a clear, well-structured manner, easy to check for completeness, consistency and correctness, makes it a valuable tool in software engineering. In the past, however, almost all the attention went to an efficient processing of the table and few or none to its development. Moreover, it was always assumed that the decision table, once designed, also had to be specified as a table in the software specification, leading to a variety of syntactical problems. In this paper, a new approach to the use of decision tables in software engineering is proposed. It is argued that an automated construction process of the decision table offers a solution to the above mentioned problems and allows an effective application of the decision table technique in software engineering. The proposed approach has been applied successfully in numerous real world applications.
Unsteady aerodynamics, reduced-order modelling, and predictive control in linear and nonlinear aeroelasticity with arbitrary kinematics

This thesis concerns the development of computational methods for efficient flexible-aircraft flight dynamics analyses. An argument is made for a hierarchy of methods that provide predictive capability for loads and stability analyses, and the ability to create low-order dynamic models for control system synthesis. The proposed aeroelastic models are formulated using three-dimensional unsteady aerodynamics in the form of an unsteady vortex-lattice method developed to model the relatively complex kinematics inherent in flexible-aircraft dynamics, and in particular the unsteady induced drag. No assumptions are made relating to the kinematics of the fluid-structure interface (inputs) and use of the three-dimensional Joukowski relation naturally resolves all components of the unsteady aerodynamic forcing (outputs). A consistent linearization of this method about an arbitrary reference state yields nondimensional (independent of free-stream dynamic pressure) discrete-time state-space models that resolve frequencies up to a spatio-temporal Nyquist limit defined by the wake discretization, and have a convenient form for coupling with structural dynamics models. Aircraft structural components are modelled using a geometrically-exact composite beam formulation, and, additionally, in the case of linear dynamics, a generic modal description. The latter allows the linear aerodynamics to be expressed in a reduced set of inputs and outputs, thus obtaining a time-domain alternative to the classical frequency-domain-based doublet-lattice method. The models modified for these modal degrees-of-freedom are shown to be amenable to balanced realization and truncation, and are verified in flutter analyses where only 10-100 balanced states are required (compared to 1000-10,000 physical states) for converged results. Finally, predictive controllers and linear-quadratic regulators are synthesized using reduced-order aeroelastic models, and are applied in nonlinear simulations for gust-load alleviation.
A Framework on Synchronization Verification in System-Level Design

This paper presents a formal verification framework targeting the synchronization problem in SpecC language, a C-based system-level design language that supports HW/SW design seamlessly. Based on the Counter-Example Guided Abstraction Refinement (CEGAR) paradigm, we can briefly describe our framework as follows. The SpecC descriptions are abstracted and translated into descriptions that contain only boolean variables, or so called “boolean SpecC”. The boolean SpecC descriptions are translated into an equality/inequality formula. This formula is then checked using an Integer Linear Programming (ILP) solver. Once the results are satisfied, the verification process stops with the synchronization property holds. Otherwise, a counterexample is given. The process of counterexample analysis and abstraction refinement is also proposed in this paper.
Experimental characterisation and comparison of a model helicopter rotor tip vortex and fixed wing tip vortex

Interference effects of trailing vortices from aircraft have implications for the safe operation of following aircraft. This paper presents the first phase of an investigation into the interference effects of rotorcraft vortices. In this phase, the trailing vortex characteristics of a model rotor and those of a fixed wing were measured experimentally in the Seven Metre Wind Tunnel at the CSIR in South Africa. The tests on the rotorcraft vortices were carried out using a radio controlled model of an Agusta 109 helicopter, with a fully articulated four bladed main rotor of 1337 mm diameter. A 1200 mm span, NACA 0012 profile wing, with a chord of 200 mm was tested at similar lift values to those obtained during the rotor tests. A three-wire orthogonal hotwire probe was used for the measurement of the wake characteristics. Wing and rotor data was compared in terms of vortex strength, tangential velocity, and radius for a representative flight condition. The vortex structure of the wing was compared to results obtained by Corsiglia et al. The trailing vortex data captured for the wing was successfully compared with published data and with data from the rotor. Significant differences between the wing and the rotor trailing vortex structures were identified.
ANÁLISIS DE DOS MODELOS DE ECUACIONES ESTRUCTURALES ALTERNATIVOS PARA MEDIR LA INTENCION DE COMPRA

ABSTRACT Structural equation modeling (SEM) is a useful statistical technique that establishes measurement models and structural models. This research empirically compares two alternative structural equation models testing the purchase intention for manufacturer brands, shedding light on interesting implications. Results reveal that the proposed model which incorporates latent variables as mediators shows more statistically significant relationships than the model without mediator variables. The findings support some empirical limitations since the two models were compared into a specific sector. KEY WORDS: Structural equation modeling, purchase intention, brand equity MSC: 91B42 JEL CODES : M30 RESUMEN Los modelos de ecuaciones estructurales (Structural Equation Modeling) son una herramienta estadistica que establece modelos de medida y modelos estructurales. Este estudio supone una aplicacion empirica que compara dos modelos de ecuaciones estructurales alternativos, aplicados a la intencion de compra de marcas del fabricante, aportando interesantes implicaciones. Los resultados revelan que el modelo propuesto que incorpora variables latentes como mediadoras, posee mayor numero de relaciones significativas que el modelo que no los incorpora. Los resultados obtenidos muestran, sin embargo, algunas limitaciones empiricas debido a que los dos modelos se comparan para un contexto determinado.