Miracle-dz/UniFAR-FTUs huggingface dataset:
Improvement of DEM Interpolation Algorithms Based on Moving Surface Fitting and Distance-weighted

A method was provided in this article which combined moving surface fitting with distance-weighted based on analyzing their characteristic.It could learn from other’s strong points to offset one’s weakness.For reference points,a judging and pre-processing has been done before complex surface fitting.Testing different interpolation methods by some data that randomly extracted from a set of raw data,we could get the order of different interpolation methods’ accuracy,the results show that the proposed interpolation method has sme advantages.
Design of High Sensitivity Cellulose Filter Paper-based SERS Flexible Substrate for Testing Harmful Rust of Bronze Ware

Surface-enhanced Raman scattering (SERS), a simple, highly sensitive, and fast analytical method can be used to detect corrosion components on the surface of bronze ware, a difficult problem. The silver mirror reaction is suggested for depositing precious metal nanoparticles on cellulose filter paper in order to create a quick, easy, and low-cost approach for creating SERS substrates. After an 8-minute deposition time, optical microscopy and scanning electron microscopy (SEM) revealed a uniform dispersion of precious metals on cellulose filter paper. To examine the SERS characteristics of the substrate, copper chloride oxide, the main ingredient in the damaging rust of trace bronze ware, was used as the probe molecule. The findings show that cellulose filter paper with a uniform distribution of precious metals achieves the best SERS performance. The flexible substrate enables effective trace analysis of damaging rust on bronze surfaces.
A hybrid adaptive sampling algorithm for obtaining reduced order models for systems with frequency dependent state‐space matrices

This paper proposes a hybrid adaptive sampling algorithm to automate the generation of reduced order models for systems described by large‐scale frequency dependent state‐space models. The evaluation of the frequency dependent state‐space model for each frequency sample can be computationally expensive. The distribution of frequency samples must be optimized to avoid oversampling and undersampling. In order to have an optimum number of frequency samples, the proposed algorithm uses the reflective exploration technique for the adaptive selection of samples, and the sampling is further refined using a binary search to validate the frequency dependent reduced order models. Projection‐based model order reduction techniques are used for obtaining the reduced order model. The projection matrix for each frequency sample is merged to obtain a common projection matrix for all samples. However, in certain cases when the number of sample points increases, the merged projection matrix also increases in dimension and might fail to provide a satisfactory reduction in model size. Thus, the merged projection matrix is truncated based on its singular values to obtain a compact common projection matrix. Then, the reduced order state‐space matrices per frequency are interpolated over the frequency range of interest to obtain the system response. Pertinent examples validate the proposed hybrid adaptive sampling algorithm. Copyright © 2015 John Wiley & Sons, Ltd.
A comparison between steepest descent and non-linear conjugate gradient algorithms for binding energy minimization of organic molecules

The main intention of optimization is to bring about the “best” of any model by prioritizing the needs along with a given set of constraints. There is a wide range of optimization problems, among which, unfortunately, the problems that are formulated from nature are not convex in nature. Solving non-convex optimization problems are quite trickier than the conventional method of derivatives. One such problem is Computing the minimum value of binding free energy of various molecules. Minimization of free energy of a molecule is highly significant in the field of Molecular mechanics which is the foundation of computational biology. For any molecule, free energy refers to the amount of energy needed to separate an individual particle from a system of particles or to disseminate all particles in a system. The significance of free energy is that it can be used to compute the lowest energy conformation, which corresponds to the least Steric energy. Hence, this paper aims at computing the minimum value of binding free energy of various organic molecules in isolated conditions using the steepest descent algorithm and conjugate gradient algorithm and comparing them.
Antireflective Indium-Tin-Oxide Nanobranches for Efficient Organic Solar cells

Indium tin oxide (ITO) nanobranched structures with low reflectance have been designed for application to organic solar cells. The ITO nanobranches are deposited on the front surface of glass without damages to organic active layer by using an electron beam deposition. Through a finite-difference time-domain, we find that the field intensity in the glass region is enhanced with ITO nanobranches. Consequently, the number of incident photons induces strong absorption within the PTB7-PC70BM active layer, leading to the enhanced short circuit current density (Jsc). Compared with a flat device (power conversion efficiency (PCE) = 6.53%, Jsc = 13.3 mA/cm2), improved PCE of 7.09% is achieved in an antireflection coating, which is mainly due to the increased Jsc of 14.2 mA/cm2.
Analysis of bandwidth limitation in time-stretch compressive sampling imaging system

Compressive sampling (CS) is an emerging field that provides a new framework for image reconstruction and has potentially powerful implications for the design of optical imaging devices. Single-pixel camera, as a representative example of CS, enables the use of exotic detectors and can operate efficiently across a much broader spectral range than conventional silicon-based cameras. Recently, time-stretch CS imaging system is proposed to overcome the speed limitation of the conventional single-pixel camera. In the proposed system, as ultra-short optical pulses are used for active illumination, the performance of the imaging system is affected by the detection bandwidth. In this paper, we experimentally analyze the bandwidth limitation in the CS-based time-stretch imaging system. Various detector bandwidths are introduced in the system and the mean square error (MSE) is calculated to evaluate the quality of reconstructed images. The results show that the decreasing detection bandwidth leads to serious energy spread of the pulses, where the MSE increases rapidly and system performance is degraded severely.
Hypocenter Relocation of Local Earthquake using Double Difference Method in Central Sulawesi from BMKG Network Data: Time Periods of July 26 - August 18, 2021

Last July 2021, a destructive earthquake occurred in the northern Ampana area, Central Sulawesi, with the epicenter at sea. We investigated the earthquake and found 101 hypocenter points with a magnitude of 2-6 Mw from 26 July to 18 August 2021 using the BMKG network. Of the 101 earthquakes, we relocated the hypocenter using the multiple difference method and obtained 75 earthquake events resulting from the relocation. The results obtained from the relocation are that several earthquake events with a fixed depth of 10 km have been updated. To validate the results, we used a histogram of travel time results, which depict the relocation results as good, and some close to zero. The results of the hypocenter relocation have a depth of 5 to 30 km and are collected in one location. The shift’s direction and angle from the relocation results show that most of them are in a dominant direction to the north. It is interpreted that the earthquake was caused by force activity caused by the Balantak thrust, which is in the east and has a north direction towards the study site.
Surface Mounted Production Line Capacity Prediction Based on Data Driven

Capacity prediction of surface mount production lines is important for improving productivity, dynamic production scheduling, and optimizing production structure. An integrated mutual information-cuckoo search-extreme learning machine (MI-CS-ELM) prediction model is proposed for the impact of nonlinear and high-dimensional features of surface-mounted production lines on capacity. Firstly, the features affecting the production capacity are ranked based on the mutual information method, and the predictive input data set is reconstructed. Secondly, the input parameters of the prediction model are adjusted by the cuckoo search algorithm and the capacity prediction model is built based on an extreme limit learning machine. Finally, the rationality of the proposed method is verified by an example to guide capacity planning and production scheduling optimization.
Calculation of Asymmetry factor using the Solution of Equilibrium Problem

In this work we presented a theoretical calculation of the asymmetry factor (Shafranov parameter) by solving the simplest Grad–Shafranov Equation (GSE) with the Solove’v assumption for a low-beta and large-aspect-ratio tokamak with a circular cross section. In this paper we calculated the current-independent relation for the asymmetry factor (Shafranov parameter).
The Validity and Precision of the Comparative Interrupted Time-Series Design

We explore the conditions under which short, comparative interrupted time-series (CITS) designs represent valid alternatives to randomized experiments in educational evaluations. To do so, we conduct three within-study comparisons, each of which uses a unique data set to test the validity of the CITS design by comparing its causal estimates to those from a randomized controlled trial (RCT) that shares the same treatment group. The degree of correspondence between RCT and CITS estimates depends on the observed pretest time trend differences and how they are modeled. Where the trend differences are clear and can be easily modeled, no bias results; where the trend differences are more volatile and cannot be easily modeled, the degree of correspondence is more mixed, and the best results come from matching comparison units on both pretest and demographic covariates.
A Distributed Nearest Neighbor Heuristic with Bounding Function

The TSP(Traveling Salesman Problem) has been known as NP-complete, there have been various studies to find the near optimal solution. The nearest neighbor heuristic is more simple than the other algorithms which are to find the optimal solution. This paper designs and implements a new distributed nearest neighbor heuristic with bounding function for the TSP using the master/slave model of PVM(Parallel Virtual Machine). Distributed genetic algorithm obtains a near optimal solution and distributed nearest neighbor heuristic finds an optimal solution for the TSP using the near optimal value obtained by distributed genetic algorithm as the initial bounding value. Especially, we get more speedup using a new genetic operator in the genetic algorithm.
Research on Human Behavior Feature Recognition and Intelligent Early Warning Methods in Safety Supervision Scene Video based on Yolov7

With the continuous improvement of infrastructure construction in China, the construction of various supporting power facilities is constantly followed up. A large number of ultra-high voltage or high-voltage power facilities, such as high-voltage transmission towers, transformers, or substations, are gradually emerging in populated areas, farmland, or fishponds where people still pass by sometimes. In such circumstances, people who do not have the qualification to contact power facilities at times approach, contact, or even climb these dangerous high-voltage transmission and distribution facilities illegally for various reasons, which not only poses a huge hidden peril or even threat to the safety of people’s lives and property but also cause a huge negative impact on the smooth operation of power infrastructure. To solve this intractable problem, this topic proposes a pedestrian detection and recognition algorithm, which can accurately distinguish between ordinary pedestrians and power grid maintenance inspectors based on YOLOv7, providing a reliable method for timely detection and early warning of pedestrians who may contact power facilities.
Interdigital transducers in structural health monitoring based on Lamb waves: a state of the art

IDTs have the potential of increasing the versatility of SHM systems by their multiple capabilities. Migration of the IDT technology in SHM systems and devices is reviewed in this paper. A summary review of different types of IDTs is presented and their salient features are presented in terms of applicability in the Lamb wave based SHM systems. Comprehensive review is provided concerning the implementation of IDT capabilities towards the development of SHM systems. Experimental results obtained with prototype IDTs are provided for illustration. Finally, future development directions of the IDTs dedicated to SHM systems are outlined.
Designing the METIS SCAO and LTAO systems

METIS, the Mid-nfrared E-ELT Imager and Spectrometer, will be providing high-sensitivity imaging and high-resolution spectroscopy in the mid-infrared (3-19 micrometer) to the E-ELT. In order to achieve the exceptional performance required by its driving science cases, exoplanets and proto-planetary disks, METIS will be featuring two Adaptive Optics (AO) systems — a first-light Single Conjugate Adaptive Optics (SCAO) system, complemented by a Laser Tomographic Adaptive Optics (LTAO) system, most likely, a few years after first light. METIS, being one of the three first light science instruments on the European Extremely Large Telescope (E-ELT), will be one of the first instruments using the integrated deformable mirror of the E-ELT for its Adaptive Optics (AO) correction. The internal SCAO system designed to maximize the performance for bright targets and has its wavefront sensors (WFSs) build inside the METIS cryostat to minimize the number of warm surfaces towards the science detectors. Although the internal dichroic will reflect all light short wards of 3 micrometers towards the WFS, only the IR light will most likely be used, mainly due to the expected improved performance at longer wavelengths for the WFS. A trade-off has been made between both visible versus infrared wave front sensing as well as Pyramid versus Shack-Hartmann, under various observing conditions and target geometries, taking into account performance, target availability, reliability and technology readiness level. The base line for the SCAO system is to minimize system complexity, thereby ensuring system availability and reliability even under first-light conditions. Since the SCAO system will require a bright guide star near the science target, it can only be used for a limited number of targets. The LTAO system, consisting of up to 6 LGS and up to 3 low-order NGS WFS and located outside the cryostat, is designed to increase the sky coverage on arbitrary targets to >80%. Investigations are ongoing if the internal SCAO system can be used as either a Low-Order WFS or metrology system.
Approximate likelihood inference for the Bingham distribution

Likelihood inference for the Bingham distribution is difficult because the density function contains a normalization constant that cannot be computed in closed form. We propose to estimate the parameters by means of Approximate Maximum Likelihood Estimation (AMLE), thus bypassing the problem of evaluating the likelihood function. We study the impact of the input parameters of the AMLE algorithm and suggest some methods for choosing their numerical values. Moreover, we compare AMLE to the standard approach consisting in maximizing numerically the (approximate) likelihood obtained with the normalization constant estimated via the Holonomic Gradient Method (HGM). For the Bingham distribution on the sphere, simulation experiments and real-data applications produce similar outcomes for both methods. On the other hand, AMLE outperforms HGM when the dimension increases.
REGULARIZED LANCZOS METHOD FOR MODEL UPDATING

In model updating,linear equations derived from the sensitivity approach are often ill-conditioned and with rank deficiency.When the modal measurements are contaminated by noise,the minimum norm solution rarely leads to physically meaningful updated parameters.The regularization is an efficient method for solving these problems.Here,the regularized Lanczos method is used to update a FEM model.The L-curve criterion is used to determine the regularization parameter.Numerical examples show that the regularized Lanczos method can better be used for model updating.
DIRECTIONAL WAVELET TRANSFORM AND ITS APPLICATION IN MOVING DIM TARGET DETECTION

One new kind of wavelet transform in 2-dimension is defined,called directional wavelet trans- form.It not only has the ability of fine analysis in time-frequency domain,but also has good directionality. Based on it,one multi-scale algorithm for moving dim targets detection is developed,which can be used to speed the detection for unstable speckle targets.
On the validity of interferences from non-random samples

SUMMARY Random sampling schemes satisfy the conditions for ignoring the selection mechanism in a model-based approach to inference in an observational study, such as a sample survey. In many studies non-random sampling is employed. Conditions for ignoring non-random selection mechanisms are examined. Particular attention is paid to post- statification and to quota sampling. Randomization, whether in the application of treatments to experimental material or in the selection of units to be observed in a sample survey, is one of the most important contributions of statistics to science. The arguments for randomization are twofold. The first, and most important for science, is that randomization eliminates personal choice and hence eliminates the possibility of subjective selection bias. The second is that the randomization distribution provides a basis for statistical inference. The question for scientists is whether such statistical inferences are relevant for scientific inference. In most of applied science any uncertainty in "nature" is represented by a stochastic model of the phenomenon under study. The problems of statistical inference are then the problems of testing the fit of alternative models and of making inferences about the parameters of a given model. Even when randomization is employed the randomization distribution plays no direct role in this type of statistical inference. However, the selection of the units to be studied can affect
Evaluation Based on Fuzzy Clustering on the in-Class Teaching Quality

Author applies the approach of fuzzy clustering to analyze in-class teaching.This approach means to select appropriate similar coefficient,and to set up fussy similar matrix,and to use direct clustering to make classification.Though this method couldn′t realize the sequence of position in the traditional sense,it could achieve to combine the evaluation of quantification and that of qualification,realizing the function of diagnosis;to provide basis for informational feedback,realizing the function of guide and encouragement of evaluation.
Behavior of ionic conducting IPN actuators in simulated space conditions

The presentation focuses on the performances of flexible all-polymer electroactive actuators under space-hazardous environmental factors in laboratory conditions. These bending actuators are based on high molecular weight nitrile butadiene rubber (NBR), poly(ethylene oxide) (PEO) derivative and poly(3,4-ethylenedioxithiophene) (PEDOT). The electroactive PEDOT is embedded within the PEO/NBR membrane which is subsequently swollen with an ionic liquid as electrolyte. Actuators have been submitted to thermal cycling test between -25 to 60°C under vacuum (2.4 10-8 mbar) and to ionizing Gamma radiations at a level of 210 rad/h during 100 h. Actuators have been characterized before and after space environmental condition ageing. In particular, the viscoelasticity properties and mechanical resistance of the materials have been determined by dynamic mechanical analysis and tensile tests. The evolution of the actuation properties as the strain and the output force have been characterized as well. The long-term vacuuming, the freezing temperature and the Gamma radiations do not affect significantly the thermomechanical properties of conducting IPNs actuators. Only a slight decrease on actuation performances has been observed.
Plasma-assisted InP-to-Si low temperature wafer bonding

The applicability of wafer bonding as a tool to integrate the dissimilar material system InP-to-Si is presented and discussed with recent examples of InP-based optoelectronic devices on Si. From there, the lowering of annealing temperature in wafer bonding by plasma-assisted bonding is the essence of this review paper. Lower annealing temperatures would further launch wafer bonding as a competitive technology and enable a wider use of it. Oxygen plasma treatment has been proven to be very feasible in achieving a strong bonding already at low temperatures. It was also seen that in our experimental setups the results depended on what plasma parameters that were used, since different plasma parameters create different surface conditions.
A DDoS Attacks Detection Based on Conditional Heteroscedastic Time Series Models

Abstract Dynamic development of various systems providing safety and protection to network infrastructure from novel, unknown attacks is currently an intensively explored and developed domain. In the present article there is presented an attempt to redress the problem by variability estimation with the use of conditional variation. The predictions of this variability were based on the estimated conditional heteroscedastic statistical models ARCH, GARCH and FIGARCH. The method used for estimating the parameters of the exploited models was determined by calculating maximum likelihood function. With the use of compromise between conciseness of representation and the size of estimation error there has been selected as a sparingly parameterized form of models. In order to detect an attack-/anomaly in the network traffic there were used differences between the actual network traffic and the estimated model of the traffic. The presented research confirmed efficacy of the described method and cogency of the choice of statistical models.
Search for Weakly-interacting, Long-lived particles that Decay to Displaced Hadronic Jets in Proton-Proton Collisions at $\sqrt{s}=8$ TeV with the ATLAS Detector.

Search for Weakly-interacting, Long-lived particles that Decay to Displaced Hadronic Jets in Proton-Proton Collisions at √ s = 8 TeV with the ATLAS Detector. Daniel Blackburn Chair of the Supervisory Committee: Professor Henry Lubatti Department of Physics A search is presented for the decay of the Standard Model Higgs boson or another scalar boson to a pair of weakly-interacting, long-lived particles in 20.3 fb−1 of proton-proton collisions at √ s = 8 TeV recorded in 2012 by the ATLAS detector. The strategy requires that one of the long-lived particles decay inside the muon spectrometer. The second long-lived particle is required to decay in the inner detector or the muon spectrometer. No excess of events is observed above the expected background. Limits are derived on the scalar boson’s production cross section times branching ratio as a function of the long-lived particle’s proper decay length.