Miracle-dz/UniFAR-FTUs huggingface dataset:
Determination of Ethylene Glycol in Serum Utilizing Direct Injection on a Wide‐Bore Capillary Column

A simple, rapid, and reliable procedure for the determination of ethylene glycol (EG) and other diol compounds utilizing direct injection of diluted serum on a unique wide-bore capillary column containing a highly polar stationary phase (Nukol column) is presented. The method uses 1,4-butanediol as the internal standard (IS) and resolves propylene glycol, EG, 1,3-butanediol, and diethylene glycol. The within-run precision of the method yielded at 27.5 mg/L EG, CV = 9.4% (n = 10) and at 222 mg/L EG, CV = 7.3% (n = 10). Absolute recovery of EG at 222 mg/L was 95.9 ± 7.1% (n = 10). At the limit of quantitation, 27.5 mg/L EG, the absolute recovery was 115 ± 13.1% (n = 10). The method was free of interference from common volatile intoxicants, organic acid metabolites, and polar drugs. However, valproic acid was not completely resolved from the IS. The Nukol column has demonstrated an extended column lifetime and versatility for analysis of other polar compounds.
Power optimization algorithm for OFDM underwater acoustic communication using adaptive channel estimation

An adaptive channel estimation algorithm for the channel length is proposed to construct a channel estimation model suitable for orthogonal frequency division multiplexing (OFDM) underwater acoustic communication signals for the dependence of traditional channel estimation algorithms on channel length information. This algorithm can be adopted to evaluate channel estimation quality in real time and to adaptively adjust the channel length of the channel estimation algorithm according to the evaluation result, which satisfies the need of accurate estimation of unknown underwater acoustic channels and communication application; based on the study on the relationship between the OFDM communication bit error rate and the subcarrier signal to noise ratio, a self-adjusting optimization scheme for OFDM subcarrier transmitting power is proposed, which realizes underwater communication with the low bit error rate through higher energy efficiency. The validity of the research content is verified through simulation and field experiments.
Principal varying coefficient estimator for high-dimensional models

ABSTRACT We consider principal varying coefficient models in the high-dimensional setting, combined with variable selection, to reduce the effective number of parameters in semiparametric modelling. The estimation is based on B-splines approach. For the unpenalized estimator, we establish non-asymptotic bounds of the estimator and then establish the (asymptotic) local oracle property of the penalized estimator, as well as non-asymptotic error bounds. Monte Carlo studies reveal the favourable performance of the estimator and an application on a real dataset is presented.
Simulation and estimation of operator scaling stable random fields

Operator-scaling stable random fields are stochastic models which can describe spacial dependencies. Thereby dependencies of different intensities and in different, not necessarily orthogonal, directions are allowed, resulting in anisotropic fields which are used, e.g. in hydrology to represent porous media, or to describe fractal surfaces in physics. In the year 2006, H. Bierme, M. M. Meerschaert and H. -P. Scheffler presented models for operator-scaling stable random fields in harmonizable and in moving average representation, and showed some important properties of these fields. In order to use these fields for practical application, procedures for their numeric simulation are needed, and also methods for the statistical analysis (e.g. parameter estimation) of observed realizations of OSSRFs. The present thesis presents numeric approximations of OSSRFs and examines their deviation from the original OSSRFs. Algorithms for the calculation of these approximations have been also developed and are described in the thesis. For the cases of two- and three-dimensional fields, which are relevant for practical applications, these algorithms for the simulation of OSSRFs have been implemented in the programming languages Matlab and Java. Finally, we present also a method for the estimation of several parameters of a two-dimensional harmonizable OSSRF, and its implementation in Matlab. Operatorskalierende stabile Zufallsfelder (engl. Operator scaling stable random fields, kurz: OSSRFs) sind stochastische Modelle, die raumliche Abhangigkeiten beschreiben konnen. Dabei sind Abhangigkeiten unterschiedlicher Starke und in verschiedenen, nicht notwendigerweise zueinander senkrechten, Richtungen zugelassen. Die resultierenden anisotropen Felder werden z.B. zur Beschreibung poroser Medien in der Hydrologie oder fraktaler Oberflachen in der Physik verwendet. Im Jahr 2006 prasentierten H. Bierme, M. M. Meerschaert und H. -P. Scheffler Modelle fur operator-skalierende stabile Zufallsfelder in harmonizable und in moving-average Darstellungen, und zeigten einige wichtige Eigenschaften dieser Felder. Um diese OSSRFs in praktischen Anwendungen einsetzen zu konnen, werden Methoden fur die numerische Simulation und fur die statistische Analyse (z.B. Parameterschatzung) solcher Felder benotigt. In der vorliegenden Arbeit werden numerische Approximationen von OSSRFs prasentiert und ihre Abweichungen von den ursprunglichen Feldern untersucht. Algorithmen fur die Berechnung dieser Approximationen wurden ebenfalls entwickelt und in dieser Arbeit vorgestellt. Fur die in der Praxis relevanten Falle von zwei- und drei-dimensionalen Feldern wurden diese Algorithmen in den Programmiersprachen Matlab und Java implementiert. Schliesslich stellen wir auch eine Methode fur die Schatzung mehrerer Parameter eines harmonizable OSSRF sowie ihre Implementierung in Matlab vor.
Some remarks on Boas transforms of wavelets

ABSTRACT In this paper, we study Boas transforms of wavelets and obtain a sufficient condition under which the Boas transform of a wavelet is the derivative of another wavelet. Also, a characterization of the Boas transform of a wavelet is given. A sufficient condition is given to obtain higher order vanishing moments of Boas transforms of wavelets. Further, we study the Boas transform of wavelets in . Finally, higher order vanishing moments of Boas transforms of wavelets have been used to approximate finite energy functions.
Edgewise vibration reduction of small size wind turbine blades using shunt damping

Edgewise vibration in wind turbine blades is one of the important factors that results in reducing the performance of wind turbines. Therefore, control or reduction of the mentioned vibrations can be of great help in increasing the efficiency of wind turbines. In this paper, the shunt damping method is proposed to reduce the edgewise blade vibration of horizontal axis wind turbines. For this purpose, partial differential equations governing dynamics of the system are derived using the Lagrange method. These equations are completely nonlinear and linearization is not performed to avoid possible errors in the analysis. In order to evaluate the effectiveness of the proposed shunt damping method in vibration reduction of the wind turbine blade, obtained results by applying shunt damping method are compared with corresponding results obtained by employing a conventional method known as a tuned mass damper (TMD). For better comparison, by considering proper cost functions, the shunt damper and TMD parameters are optimized using a genetic algorithm. Finally, the effectiveness of optimized shunt damper in vibration reduction of the blade is compared with optimized TMD by presenting simulation results.
Semantic Search Revisited

Accuracy of search results over web is improving steadily due to ongoing incorporation of semantic web technologies into traditional information retrieval approaches of the present web. These semantic technologies along with knowledge base they contain are being exploited at large scale by all mainstream web search engines to provide conceptually precise search results to satisfy user's efficient information needs on web. In this paper, first, semantic search and its key concerns have been explored and discussed. Second, it revisits various semantic search approaches which process and consume knowledge from semantic technologies to improve precision of search results. Thirdly, keyword to concept mapping is revisited and illustrated using domain Ontology. Finally, key design issues of search engines incorporating semantics have been revisited.
Understanding the shape of feature code

Feature annotations (por exemplo, diretivas do preprocessador C, na forma de #ifdefs) sao usadas para controlar extensoes de codigo relacionadas a uma feature. Por muito tempo, tais anotacoes tem sido consideradas indesejaveis. Seu uso excessivo pode aumentar o risco de ripple effects, desorganizar o codigo e dificultar sua compreensao e manutencao. Para prevenir esses problemas, desenvolvedores devem monitorar o uso de feature annotations, por exemplo, estabelecendo thresholds (valores de referencia). No entando, pouco se sabe sobre como extrair thresholds na pratica, ou quais valores sao representativos para metricas relacionadas a features. Para contribuir comuma solucao para esse problema, nos analizamos a distribuicao estatistica de metricas relacionadas a feature annotations, extraidas de umcorpus de 20 sistemas baseados no preprocessador C, amplamente conhecidos, com longo historico de evolucao e que abrangem diferentes dominios de funcao. O estudo considera 3 metricas: scattering degree (espalhamento de feature constants), tangling degree (entrelacamento de feature expressions) e nesting depth (profundidade das anotacoes). Os resultados mostram que feature scattering possui uma distribuicao com elevada assimetria. Em 14 sistemas (70 %), a distribuicao de scattering degree segue uma distribuicao power-law, tornando medidas de media e desvio padrao nao confiaveis para estabelecer limites. Em relacao a tangling e nesting, os valores tendem a seguir uma distribuicao uniforme. Embora existam outliers, eles pouco impactam a media, sugerindo que medidas de tendencia central podem gerar thresholds confiaveis. Com base nestes resultados, nos propomos thresholds gerados a partir de nosso benchmark como base para trabalhos futuros. Adicionalmente, nos realizamos uma revisao sistematica da literatura para identificar descobertas e suposicoes reportadas na literatura sobre o uso de ifdefs. Os resultados mostram que os estudos disponiveis nao realizam analise estatistica de metricas relacionadas a features, e nem propoem thresholds.
A high-order finite volume scheme for unsteady convection-dominated convection–diffusion equations

Abstract A finite volume scheme with high-order accuracy is proposed for solving the unsteady convection-dominated transport problems. In this scheme, some weighting parameters are introduced in discretizing both the convection term and time integral. These parameters are determined analytically by making the truncation error of the proposed scheme as small as possible. Since the discretization equations of the proposed scheme share the same band structure as that of the traditional finite volume method based on the central differencing scheme, the proposed scheme does not increase computing cost. Numerical results show that the proposed scheme not only can achieve sixth-order accuracy but also avoids any unphysical oscillations in the steep gradient region of the solutions of the linear and nonlinear convection-dominated convection–diffusion problems.
Sistema de identificação da ordem de produção estampada em tarugos de aço

Esta dissertacao apresenta um estudo sobre as ferramentas de reconhecimento de caracteres para a aplicacao em um problema real na Gerdau Acominas. O problema e a identificacao de numeros de Ordem de Producao (OP) em pecas de aco (tarugos). O reconhecimento visa a automatizacao completa da LIT (linha de inspecao de tarugos). Pelaidentificacao da OP, o sistema modifica as variaveis parametricas da linha de inspecao e separa os tarugos para cada cliente, evitando-se problemas como mistura de pecas e inspecoes com parâmetros errados. O estudo e realizado nas imagens coletadas, visandofornecer requisitos para a escolha dos algoritmos. O problema e dividido em etapas de segmentacao, extracao de caracteristicas e classificacao. Sao estudados e propostos metodos nestas areas, levando em consideracao a variacao de escala e rotacao dos caracteres. Pri-meiramente, sao realizados testes em imagens coletadas em laboratorio, sem condicionamento de escala ou rotacao. A rotacao e resolvida pela analise da caracteristica de textura presente no tarugo, diminuindo o custo computacional e fornecendo rotacao constante para a etapa de extracao de caracteristicas. Esta tecnica forneceu 100% de acerto nas imagens coletadas em laboratorio. Como as etapas de extracao de caracteristicas utilizam como base a imagem limiarizada, um estudo e realizado sobre os diferentes tipos de ferramentas propostas na literatura. Com a analise das imagens e proposto ummetodo para a extracao do caractere a partir da imagem em escala de cinza. Na etapa de reconhecimento foi testado o metodo de casamento de padroes, implementado atraves da correlacao cruzada normalizada. Os resultados demonstram um desempenho de 98% para imagens com bom contraste e pouca deformacao, indicando a necessidade de um maior condicionamento na iluminacao e escala. A segunda fase demonstra resultados prelimi-nares em imagens coletadas na linha de inspecao. A identificacao da rotacao foi correta em 94% das imagens testadas. As imagens apresentam um melhor condicionamento deiluminacao e escala, fornecendo resultados promissores para a implementacao do sistema.
Fourier Spectrum Guidance for Stripe Noise Removal in Thermal Infrared Imagery

Thermal infrared (TIR) imaging has been an indispensable tool in surveillance and remote sensing fields due to the characteristic of this spectrum that enables the sensing system to detect relatively warm targets, especially in low-light conditions. However, the acquired TIR images often suffer from observable stripe noise, which reduces the target detectability to some extent. To remove the noise and keep the image details, this letter proposes a novel method that combines the spectral processing technology with the image-guidance mechanism. Specifically, the frequency band contaminated by stripe noise is corrected with the corresponding Fourier coefficients of a guided image, which can be estimated by existing smoothing methods. Various experiments on the simulated and real TIR images show high performance and efficiency of the proposed method. In addition, in the application of small target detection, it is demonstrated that local contrast between the target and its background is well maintained and the signal-to-clutter ratio is increased when our method is performed.
Robust Optimal Filtering Over Lossy Networks

This paper addresses the robust optimal filtering design over unreliable networks, where the data packet dropouts occur during the signal transmission from the sensor side to the filter. The designed filter is expected, under communication data loss, to provide a guaranteed robustness against disturbance/model uncertainty while achieving the minimized variance of the estimation error under Gaussian white noises and the worst case of the disturbance. The Nash game approach is adopted to deal with such a multiobjective filtering problem. Based on the concept of the mean-square stability, Nash equilibrium strategies are analytically applied in terms of two cross-coupled modified algebraic Riccati equations. The presented design method provides a systematic way to achieve a tradeoff of the estimation performance in the <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_2$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$\mathcal {H}_\infty$</tex-math></inline-formula> senses in the presence of data loss.
Efficient learning variable impedance control for industrial robots

Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively learn to perform repetitive force-sensitive tasks. Current learning impedance control methods usually suffer from inefficiency. This paper establishes an efficient variable impedance control method. To improve the learning efficiency, we employ the probabilistic Gaussian process model as the transition dynamics of the system for internal simulation, permitting long-term inference and planning in a Bayesian manner. Then, the optimal impedance regulation strategy is searched using a model-based reinforcement learning algorithm. The effectiveness and efficiency of the proposed method are verified through force control tasks using a 6-DoFs Reinovo industrial manipulator.
Postbuckling analysis of axially loaded nanoscaled shells embedded in elastic foundations based on Ru's surface elasticity theory

Abstract The nonlinear buckling and postbuckling characteristics of cylindrical nanoshells embedded in elastic foundations are investigated based on a strain-consistent elastic shell model including the both surface tension and the induced residual stress. For this purpose, in contrast to the previous models on the basis of the Gurtin-Murdoch elasticity theory, a new non-classical shell model based on Ru's surface elasticity theory is developed in which the non-strain displacement gradient terms are eliminated from the surface stress-strain relations. Using the virtual work's principle, the governing differential equations incorporating surface effects are derived. After that, the size-dependent governing equations are deduced to a boundary layer type problem which is subsequently solved through employing a two-stepped singular perturbation technique. It is revealed that because the edge supports of nanoshells are movable, before applying the axial compression, surface effects lead to an initial shortening due to induced residual strains, but the terms related to the residual strain and initial surface tension vanish in the size-dependent nonlinear governing equations. As a result, it is observed that before applying the axial compressive load, the surface effects cause an initial end-shortening for very thin nanoshells and these effects quickly diminish by increasing the shell thickness. Communicated by Krzysztof Kamil Żur
A Multilevel Visual Feature-Based Approach for Measuring the Spatial Information in Remote Sensing Images

The information measurement of remote sensing images plays an important role in various geographical applications. As people are the ultimate interpreter of remote sensing images, there is a need to integrate principles of human visual perception into remote sensing image information measurement. Therefore, this article proposes an approach to measure the spatial information of remote sensing images on the basis of visual features. The information measurement model suitable for remote sensing images is first developed according to the Shannon–Hartley theorem. Then, the multidimensional remote sensing image information measurement strategy is proposed based on the multilevel visual features. On this basis, the remote sensing image information can be quantified by incorporating the low-level visual features. Experiments demonstrate that the proposed method can capture the information content of remote sensing images that is highly consistent with human visual cognition. Through comparisons with other methods, it is demonstrated that the proposed method has advantages in accurately revealing the attention rule for the visual information of remote sensing images.
Improved Behavior Monitoring and Classification Using Cues Parameters Extraction from Camera Array Images

Behavior monitoring and classification is a mechanism used to automatically identify or verify individual based on their human detection, tracking and behavior recognition from video sequences captured by a depth camera. In this paper, we designed a system that precisely classifies the nature of 3D body postures obtained by Kinect using an advanced recognizer. We proposed novel features that are suitable for depth data. These features are robust to noise, invariant to translation and scaling, and capable of monitoring fast human bodyparts movements. Lastly, advanced hidden Markov model is used to recognize different activities. In the extensive experiments, we have seen that our system consistently outperforms over three depth-based behavior datasets, i.e., IM-DailyDepthActivity, MSRDailyActivity3D and MSRAction3D in both posture classification and behavior recognition. Moreover, our system handles subject's body parts rotation, self-occlusion and body parts missing which significantly track complex activities and improve recognition rate. Due to easy accessible, low-cost and friendly deployment process of depth camera, the proposed system can be applied over various consumer-applications including patient-monitoring system, automatic video surveillance, smart homes/offices and 3D games.
Computer-assisted proof of ergodicity breaking in expanding coupled maps

From a dynamical viewpoint, basic phase transitions of statistical mechanics can be regarded as a breaking of ergodicity. While many random models exhibiting such transitions at the thermodynamics limit exist, finite-dimensional examples with deterministic dynamics on a chaotic attractor are rare, if at all existent. Here, the dynamics of a family of $N$ coupled expanding circle maps is investigated in a parameter regime where absolutely continuous invariant measures are known to exist. At first, empirical evidence is given of symmetry breaking of the ergodic components upon increase of the coupling strength, suggesting that breaking of ergodicity should occur for every integer $N>2$. Then, a numerical algorithm is proposed which aims to rigorously construct asymmetric ergodic components of positive Lebesgue measure. Due to the explosive growth of the required computational resources, the algorithm successfully terminates for small values of $N$ only. However, this approach shows that phase transitions should be provable for systems of arbitrary number of particles with erratic dynamics, in a purely deterministic setting, without any reference to random processes.
An On-Chip Relaxation Oscillator With Comparator Delay Compensation

In this brief, a relaxation oscillator with comparator delay compensation is presented. Two digital compensation loops are introduced to compensate for the comparator delay. This relaxation oscillator is fabricated in the 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process. The measured average oscillation frequency is 943.1 kHz. The whole oscillator consumes <inline-formula> <tex-math notation="LaTeX">$5.2~\mu \text{W}$ </tex-math></inline-formula> under a 0.9-V supply. The measured average temperature coefficients (TCs) of the oscillation frequency with and without compensation are 93.88 and 618.17 ppm/°C, respectively. It achieves a TC improvement of <inline-formula> <tex-math notation="LaTeX">$6.6\times $ </tex-math></inline-formula>. The measured frequency variation is within ±0.7% from −10 °C to 100 °C by using the DCLs. The measured line sensitivity is 4.37%/V. The measured figure of merit (FOM<sub>2</sub>) is 173.3 dB.