Miracle-dz/UniFAR-FTUs huggingface dataset:
Anand model calibration for SAC305 solder joints based on the evolution of the shear stress and strain hysteresis loops for different thermal cycling conditions

Since 2006 and the introduction of the RoHS legislation preventing the use of lead in electronic assemblies, lead-free solder alloys have gained interest amongst the industry and academics with the introduction of new solder alloy compositions. Solder joint durability has been widely studied, especially the SAC305 solder composition, one of the most common lead-free alloy used in electronic equipment. Assessing solderjoint durability can consists in performing Accelerated Temperature Cycling (ATC) tests to measure durability data. Finite Element Analysis (FEA) can also be performed in order to correlate a thermomechanical fatigue criterion, such as the inelastic strain energy density, with the durability data for different test configurations to develop a fatigue model. However, accurately calculating the inelastic strain energy density dissipated in solder interconnections during thermal cycling requires knowledge of the solder material’s behavior law. Under thermal cycling conditions, SAC305 solder behaves as a highly viscoplastic material and is often described using the Anand model.This study presents the methodology considered to determine the Anand viscoplastic model representative of actual SAC305 solder joints. The experimental procedure which consists of a custom-made 76 I/O Ceramic Ball Grid Array (CBGA76) assembly instrumented with four strain gauges and subjected to three different thermal cycling conditions is described $(\triangle \mathrm{T}=[-25^{\circ}\mathrm{C}, 125^{\circ}\mathrm{C}], [0^{\circ}\mathrm{C}, 100^{\circ}\mathrm{C}]$ and [−40°C, 85°C]). The strain gauges allow to determine the shear stresses and shear strains applied on the critical solder balls during temperature cycles. The obtained experimental shear stress and strain hysteresis loops are compared with the numerical hysteresis loops determined with the FEA. By assessing the effect of each Anand parameter on the shape of the hysteresis loop plotted for the thermal cycle between −25°C to 125°C, the best-fit parameters for the Anand viscoplastic model was derived. The model was then validated considering the temperature cycles between −40°C to 85°C and 0°C to 100°C.
The Contiguity Ratio and Statistical Mapping

The problem discussed in this paper is to determine whether statistics given for each "county" in a "country" are distributed at random or whether they form a pattern. The statistical instrument is the contiguity ratio c defined by formula (1.1) below, which is an obvious generalization of the Von Neumann (1941) ratio used in one-dimensional analysis, particularly time series. While the applications in the paper are confined to oneand two-dimensional problems, it is evident that the theory applies to any number of dimensions. If the figures for adjoining counties are generally closer than those for counties not adjoining, the ratio will clearly tend to be less than unity. The constants are such that when the statistics are distributed at random in the counties, the average value of the ratio is unity. The statistics will be regarded as contiguous if the actual ratio found is significantly less than unity, by reference to the standard error. The theory is discussed from the viewpoints of both randomization and classical normal theory. With the randomization approach, the observations themselves are the "universe" and no assumption need be made as to the character of the frequency distribution. In the "normal case," the assumption is that the observations may be regarded as a random sample from a normal universe. In this case it seems certain that the ratio tends very rapidly to normality as the number of counties increases. The exact values of the first four semi-invariants are given for the normal case. These functions depend only on the configuration, and the calculated values for Ireland, with number of counties only 26, show that the distribution of the ratio is very close to normal. Accordingly, one can have confidence in deciding on significance from the standard error.
Automatic tracking algorithm based on Kalman filter and scale and orientation adaptive mean shift for a moving object

Mean shift is a traditional moving target tracking algorithm, which has some deficiencies such as: A tracking window of a target needs to be initialed manually in the first frame; the window size cannot be adaptively changed according to a moving object in the process of tracking; if a target is obscured, it might be lost in the tracking window. In order to solve these problems, a method combining Kalman filter and Scale and Orientation Adaptive Mean Shift Tracking (SOAMST) is proposed. Firstly we use Kalman filter to locate a moving target at the beginning. Then the ratio of the first order moment to the zero order moment is used to estimate its center, and the second order center moment is used to estimate its size and orientation. Meanwhile, whether the target is obscured is determined by the Bhattacharyya coefficient based on the target model and a candidate one. A candidate model is more similar to the target and the estimation result of the target is more reliable when the Bhattacharyya coefficient is closer to 1. On the contrary, if the Bhattacharyya coefficient decreases to 0, the target will be lost for being totally obscured. If the target is partially obscured or not obscured, SOAMST is used directly to track the target; if totally obscured, Kalman filter is imposed to estimate the location of the target in the next frame before SOAMST. The experiments show that the proposed algorithm can track a moving target automatically at the initial frame without prior knowledge. It can also track a completely obscured target accurately by Kalman filtering based location estimation.
The Choice of the Cost Parameter in the PELT Method for Determining the Change Points for Time Series Parameters in the Hidden Channel Model

In this paper, the problem of choosing the cost parameter in the Pruned Exact Linear Time (PELT) method for determining the change points for the parameters of time series is considered. It is shown that it is reasonable to use a variant of the method with L2 metric to solve a special problem. It is demonstrated that the algorithm quality significantly depends on the parameter’s choice for the segment cost function and the cost parameter. The problems and possibilities of a hidden channel realization using the PELT method for determining change points for parameters of a time series are discussed.
High Performance Single Walled CNT-ZnO NW Hybrid Heterostructure for UV Photodetection

The optoelectronic properties of Single Walled Carbon nanotubes (SWCNTs) especially in UV photodetection was explored by fabricating a heterostructure (HS) incorporating SWCNTs with Zinc Oxide (ZnO). The structural analysis confirms the formation of the proposed SWCNT/ZnO NW HS. The inclusion of SWCNTs has drastically improved the performance of the HS by giving high responsivity value upto 50 A/W with rise and fall times in the order of milliseconds. The HS fares much better on comparison with existing UV based SWCNT/metal-oxide based HS.
Multi-dimensional feature fusion based on narrowband RCS for UAV target recognition

A UAV target feature mining and recognition method based on the combination of narrow-band radar RCS and sparse auto-encoder is proposed in this paper. The narrowband RCS data and its characteristics can be used for real time recognition of UAV targets. As a “black box”, deep learning network can only extract the characteristics or change laws of limited data samples, and cannot extract the characteristics of some hidden physical mechanisms. Polarization invariants have clear physical meaning, but only reflect the inherent physical characteristics of the target implied by RCS data. Therefore, the integration of RCS data and polarization invariant features can complement each other, effectively improve the feature mining ability of deep learning network, and improve the accuracy of target classification and recognition. The recognition results show that the fusion of RCS and polarization invariant data can effectively realize the recognition of UAV.
Robust Filter Method for SINS/DVL/USBL Tight Integrated Navigation System

In order to solve the problem of strap-down inertial navigation system (SINS)/Doppler velocity log (DVL)/ultrashort baseline (USBL) system interference in complex underwater environment, an asynchronous sequential robust filter method is proposed in this article. The USBL original information of azimuth, slant range and altitude are introduced as the measurement information. The problem of large amount of computation caused by the high measurement dimension of multisensor information fusion is solved by introducing asynchronous sequential filter technology. Meanwhile, a robust Kalman filter (KF) algorithm is proposed, which is based on the Mahalanobis distance. The outlier detection is designed based on statistical characteristics. Finally, the effectiveness of the method proposed in this article is verified by simulation and River experiments. The experimental results show that the method proposed in this article can effectively eliminate outliers and improve the navigation accuracy while reducing the amount of computation.
Atomistic Insights on Surface Quality Control via Annealing Process in AlGaN Thin Film Growth

Aluminum gallium nitride (AlGaN) is a nanohybrid semiconductor material with a wide bandgap, high electron mobility, and high thermal stability for various applications including high-power electronics and deep ultraviolet light-emitting diodes. The quality of thin films greatly affects their performance in applications in electronics and optoelectronics, whereas optimizing the growth conditions for high quality is a great challenge. Herein, we have investigated the process parameters for the growth of AlGaN thin films via molecular dynamics simulations. The effects of annealing temperature, the heating and cooling rate, the number of annealing rounds, and high temperature relaxation on the quality of AlGaN thin films have been examined for two annealing modes: constant temperature annealing and laser thermal annealing. Our results reveal that for the mode of constant temperature annealing, the optimum annealing temperature is much higher than the growth temperature in annealing at the picosecond time scale. The lower heating and cooling rates and multiple-round annealing contribute to the increase in the crystallization of the films. For the mode of laser thermal annealing, similar effects have been observed, except that the bonding process is earlier than the potential energy reduction. The optimum AlGaN thin film is achieved at a thermal annealing temperature of 4600 K and six rounds of annealing. Our atomistic investigation provides atomistic insights and fundamental understanding of the annealing process, which could be beneficial for the growth of AlGaN thin films and their broad applications.
The Potential of Nabis americoferus and Orius insidiosus as Biological Control Agents of Lygus lineolaris in Strawberry Fields

Simple Summary The tarnished plant bug, Lygus lineolaris, is a major pest in eastern Canada strawberry fields. The objective of the present study was to evaluate the potential of two omnivorous predators of the pest: the damsel bug, Nabis americoferus, and the minute pirate bug, Orius insidiosus. The results in the laboratory showed that N. americoferus attacked all stages of the tarnished plant bug and, in the field, reduced its population for several weeks. Additionally, the impact was significant for every tested release period. Conversely, O. insidiosus only attacked smaller nymphs, and its effect was marginal. These results lead the way for an effective biological control strategy based on the use of N. americoferus against the tarnished plant bug. Abstract The tarnished plant bug, Lygus lineolaris, is a major strawberry pest. Only marginally effective control methods exist to manage this pest. Various predators attack L. lineolaris, but their potential is overlooked. In this study, we explore the potential of two omnivorous predators of the tarnished plant bug: the damsel bug, Nabis americoferus, and the minute pirate bug, Orius insidiosus. Firstly, the predation rate of these predators was measured in laboratory tests. Secondly, their potential release rates and release periods were determined in the field using strawberry plants. The results show that N. americoferus feeds on all nymphal stages and adults of the tarnished plant bug, while O. insidiosus attacks only smaller nymphs (up to the N2 stage). In the field, all tested densities of N. americoferus (0.25, 0.5, and 0.75 individual/plant) reduced the population of the tarnished plant bug for several weeks compared with the control treatment, but the effect of O. insidiosus alone was marginal. Additionally, for all the release periods tested, Nabis americoferus was efficient in reducing the pest population. These results demonstrate the potential of N. americoferus to control the tarnished plant bug in strawberry fields. We discuss the possible application of these results for establishing an effective and economically viable biological control strategy.
An Improved Thompson Sampling Method for Dynamic Spectrum Access in Non-Stationary Environments

We consider the dynamic spectrum access problem in wireless sensor networks, where the unlicensed sensor nodes opportunistically access the licensed channels when they are not used by the licensed users. The sensor nodes try to access the channel with the highest probability of being idle to maximize their achievable data transmission. Due to the user mobility and the fluctuating traffic in the licensed network, the idle probabilities of the licensed channels vary with time. We propose a Thompson sampling based method assisted by a change detection technique to track the time-varying channel statistics. Numerical results show that our proposed method yields more channel access opportunities than the state-of-the-art ones.
New data on chert catchment analysis in inland Iberia during the Late Pleistocene

In this paper, we present the first results obtained after new fieldwork and laboratory studies of chert catchment sources during the Middle and Upper Palaeolithic in inland Iberia, a region that has been traditionally depicted as marginal and sparsely populated during the last glacial due to its harsh ecological conditions compared to the coastal areas of the Iberian Peninsula. Our main aim is to determine the mobility strategies and social networks of the last Neandertals and first modern humans settled in inland Iberia and neighbouring regions, and eventually test the hypothesis that the last glacial human settlement in the Iberian hinterland was more dense and complex than previously thought. In this study, we focus on the cherts exploited at two archaeological sites: the Peña Cabra and Peña Capón rock shelters. These sites are located in the southeastern foothills of the Central System range, in the province of Guadalajara (Spain), and they have yielded a sequence of human occupations from the Middle and Upper Palaeolithic, respectively. To obtain a detailed picture of the mobility patterns and catchment strategies of the hunter‐gatherers settled at these sites, our fieldwork focussed on identifying chert outcrops that could have been frequented and exploited by them. After two field seasons, 22 chert outcrops from eight geological formations were identified and more than 300 samples were collected and analysed. We conducted textural, micropalaeontological, petrographical and geochemical analyses, with the aim of comprehensively characterising the various rock resources available in the study area. Results have shown that different siliceous varieties were available in the area surrounding the sites and both Neandertals and modern humans could have provisioned there. Also, they suggest the potential existence of a network connecting the Tagus and Ebro valleys, but this is a working hypothesis to be tested with future research.
The reproducing kernel algorithm for handling differential algebraic systems of ordinary differential equations

The aim of the present analysis is to implement a relatively recent computational method, reproducing kernel Hilbert space, for obtaining the solutions of differential algebraic systems for ordinary differential equations. The reproducing kernel Hilbert space ⊕j=1mW22a,b⊕⊕j=m+1nW_21a,b is constructed in which the initial conditions of the systems are satisfied. While, two smooth kernel functions are used throughout the evolution of the algorithm in order to obtain the required grid points. An efficient construction is given to obtain the numerical solutions for the systems together with an existence proof of the exact solutions based upon the reproducing kernel theory. In this approach, computational results of some numerical examples are presented to illustrate the viability, simplicity, and applicability of the algorithm developed. Finally, the utilized results show that the present algorithm and simulated annealing provide a good scheduling methodology to such systems. Copyright © 2016 John Wiley & Sons, Ltd.
AN ACE-BASED NONLINEAR EXTENSION TO TRADITIONAL EMPIRICAL ORTHOGONAL FUNCTION ANALYSIS

This paper shows the application of the empirical orthogonal functions/principal component transformation on global sea surface height and temperature data from 1996 and 1997. A nonlinear correlation analysis of the transformed data is proposed and performed by applying the alternating conditional expectations algorithm. New canonical variates are found that indicate that the highest correlation between ocean temperature and height is associated with the build-up of the El Niño during the last half of 1997.
Permanent Magnet Wind Generator with Double Excitation for Smart Grids

The contribution begins with the attention that there is attention of directly grid connected wind turbine systems with generator designs adapting to the grid constraints. This paper considers permanent magnet synchronous generator topologies with rotor field coils to achieve reduced mass with good efficiency for smart grids. Conventional double-excited synchronous generators have surface mounted permanent magnets. However, the low relative permeability of PMs results in an increased air-gap size. This increased air-gap size limits the minimal copper-mass of the rotor-field-winding. To improve on this limitation, Interior permanent magnets (IPM) are used. Three rotor topologies with IPM are presented in this paper. The analysis of their 2D FEM results and optimization are shown considering their magnetizing current, torque, Back EMF for smart grids application. The three rotor topologies are compared on the overall active mass and their performance by considering PM and rotor copper mass, torque capabilities and efficiency. The spoke-type topology with rectangular magnets achieves the lowest total rotor mass reduction of 39% total mass reduction when compared to the topology with PMs that are buried horizontally. The reduced copper mass and flux variation capabilities are good characteristics in wind energy conversion generators with direct grid connections for smart grid.
The Fine Power Spectra of the Southern Oscillation Index and Its Components and their Implication

As is evident from its definition, Southern Oscillation Index variability conformed to a combination of the variations of Darwin and Tahiti pressure. Over the El-Nino Southern Oscillation spectra, the Darwin pressure shared variations associated with the SSN tendency while the Tahiti had a connection with the stratospheric quasi-biennial oscillation modulating annual cycle. The power peak near the 3.5-year period comprised the third harmonic of the sun and the second of the modulated annual cycle. The derived harmonics came from both sources, so the initiation of El-Nino could be predicted more successfully when including the effects of the sun and QBO.
Spectroscopic Studies and Numerical Modelling on Nanoparticle based Toxic Heavy Metal Sensor for the Development of a Low-Cost Prototype in Field Use

With the advent of technology, a sustainable solution of environmental pollution is the selective monitoring of pollutants in the environment. Herein, we report a spectroscopic detection of lead (Pb), one of the toxic heavy metal pollutants. Spectroscopic studies have been utilized to study the self-aggregation of citrate functionalized gold nanoparticles in presence of lead. The Longitudinal Surface Plasmon Resonance (LSPR) of gold nanoparticles increases as the lead concentration increases, and a new peak emerges in the red region of the EM spectrum indicative of the generation of larger aggregates. We have used quasi-static approximation based numerical modelling to determine the percentage of aggregation of the gold nanoparticles in presence of P$\mathrm{b}^{2+}$ ions. We are of the opinion that these key findings will pave the path towards the development of low-cost lead sensor for monitoring of lead pollution in the ecosystem. We have developed a prototype for the measurement of heavy metal toxicity in real world applications in a cost effective way.
Kinematics and workspace-based dimensional optimization of a novel haptic device for assisted navigation

ABSTRACT This article presents the development of a multi-point force feedback device, composed of five mechanisms that each provide a two degree-of-freedom (DOF) haptic feedback for every finger for a total of 10 DOF. This work investigates the theoretical workspace of a human index finger and uses a two DOF 7-bar linkage mechanism that is synthesized based on such a workspace. This research determines the closed-form solutions to the forward and inverse position, and presents a prototype that is built and tested as a proof of concept of the novel device. The workspace of the constructed mechanism is compared with theoretical models in order to assess their similarity and the feasibility of accelerometers as position-sensing instruments is also tested. Two sets of experiments test the performance of the mechanism and its reliability as a human–machine interface. Firstly, an operator successfully navigates an unmanned aerial vehicle avoiding an obstacle as force replaces audiovisual feedback. In the second experiment, the operator searches a chemical source using an unmanned ground vehicle, where chemical gradient is transmitted to the user as force signals.
Perchlorate on Mars: a chemical hazard and a resource for humans

Abstract Perchlorate (ClO4−) is widespread in Martian soils at concentrations between 0.5 and 1%. At such concentrations, perchlorate could be an important source of oxygen, but it could also become a critical chemical hazard to astronauts. In this paper, we review the dual implications of ClO4− on Mars, and propose a biochemical approach for removal of perchlorate from Martian soil that would be energetically cheap, environmentally friendly and could be used to obtain oxygen both for human consumption and to fuel surface operations.