Miracle-dz/UniFAR-FTUs huggingface dataset:
A positional error compensation method for industrial robots combining error similarity and radial basis function neural network

To solve the problem of low absolute position accuracy for industrial robots in application, a positional error compensation method combing error similarity and RBF neural networks is proposed. The positional errors experience error similarity when describing the degree of error similarity developed with the error model based on a robot kinematic model. The experimental semivariogram is fitted by using a set of robot joint angles and corresponding positional errors. The bandwidth of the RBF neural network is modified by using the parameter of semivariogram. Then, an RBF neural network is constructed to estimate the positional errors of the target positions. The estimated positional errors are used to modify the target position. The modified position is given to the robot controller. To verify the proposed method, a simulation study and experiments are respectively carried out with a simulated robot and a KUKA KR210 industrial robot. The experimental results show that, after compensation, the average residual positional error is reduced by 91.99% from 1.361 mm to 0.109 mm and the maximum residual positional error is reduced by 85.41% from 1.741 mm to 0.254 mm. In addition, the proposed method can enhance the absolute position accuracy of industrial robots.
Contribution of Floquet-Bloch states to high-order harmonic generation in solids

Jian-Zhao Jin,1,* Hao Liang,1,* Xiang-Ru Xiao,1 Mu-Xue Wang,1 Si-Ge Chen,1 Xiao-Yuan Wu,1 Qihuang Gong,1,2,3 and Liang-You Peng1,2,3,† 1State Key Laboratory for Mesoscopic Physics and Collaborative Innovation Center of Quantum Matter, School of Physics, Peking University, Beijing 100871, China 2Beijing Academy of Quantum Information Sciences, Beijing 100193, China 3Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China
A Novel Method for Intelligent Single Fault Detection of Bearings Using SAE and Improved D–S Evidence Theory

In order to realize single fault detection (SFD) from the multi-fault coupling bearing data and further research on the multi-fault situation of bearings, this paper proposes a method based on features self-extraction of a Sparse Auto-Encoder (SAE) and results fusion of improved Dempster–Shafer evidence theory (D–S). Multi-fault signal compression features of bearings were extracted by SAE on multiple vibration sensors’ data. Data sets were constructed by the extracted compression features to train the Support Vector Machine (SVM) according to the rule of single fault detection (R-SFD) this paper proposed. Fault detection results were obtained by the improved D–S evidence theory, which was implemented via correcting the 0 factor in the Basic Probability Assignment (BPA) and modifying the evidence weight by Pearson Correlation Coefficient (PCC). Extensive evaluations of the proposed method on the experiment platform datasets showed that the proposed method could realize single fault detection from multi-fault bearings. Fault detection accuracy increases as the output feature dimension of SAE increases; when the feature dimension reached 200, the average detection accuracy of the three sensors for bearing inner, outer, and ball faults achieved 87.36%, 87.86% and 84.46%, respectively. The three types’ fault detection accuracy—reached to 99.12%, 99.33% and 98.46% by the improved Dempster–Shafer evidence theory (IDS) to fuse the sensors’ results—is respectively 0.38%, 2.06% and 0.76% higher than the traditional D–S evidence theory. That indicated the effectiveness of improving the D–S evidence theory by evidence weight calculation of PCC.
The case of flow and learning revisited

ABSTRACT Many business schools are criticized for being ineffective in helping students learn proper management skills and knowledge. Flow theory has been cited as being helpful in many learning environments in that flow experience can enhance student learning. The authors conducted a study of 315 students in an undergraduate operations management (OM) class to assess learning outcomes and flow experience. Results show that student learning performance and flow are related. Implications and suggestions for further research are provided.
GoCity: a context-aware adaptive Android application

Supervisory Committee Dr. Hausi A. Müller, (Department of Computer Science) Supervisor Dr. Alex Thomo, (Department of Computer Science) Departmental Member GoCity is designed to provide city visitors with up-to-date and context-aware information while they are exploring a city using Android mobile phones. This thesis not only introduces the design and analysis of GoCity, but also discusses four problems in leveraging three concepts—context-awareness, self-adaptation, and usability—in current mobile application design. First, few contexts other than location and time have been used in actual mobile applications. Second, there is no clear classification of context information for mobile application design. Third, mobile application designers lack systematic mechanisms to address sensing and monitoring requirements under changing context situations. This is crucial for effective self-adaptation. Fourth, most mobile applications have low usability due to poor user interface (UI) design. The model proposed in this thesis addresses these issues by (i) supporting diverse context dimensions, (ii) monitoring context changes continuously and tailoring the application behavior according to these changes, and (iii) improving UI design using selected usability methods. In addition, this thesis proposes two classifications of context information for mobile applications: source-based classification—personal context, mobile device context, and environmental context; and property-based classification— static context and dynamic context. The combination of these two classifications helps iv determine the observed context and its polling rate—the rate at which the context is collected—effectively. A distinctive feature of GoCity is that it supports two interaction modes—static mode and dynamic mode. In static mode, the application generates results only after the user sends the request to it. In other words, it does not actively generate results for users. In contrast, in the dynamic mode, the application continuously updates results even if the user does not send any request to it. The notion of an autonomic element (AE) is used for the dynamic mode to make GoCity self-adaptive. The polling rates on different contexts are also handled differently in the dynamic mode because of the differences among context properties. In addition, GoCity is composed of, but not limited to, four subapplications. Each sub-application employs a variety of context information and can be implemented as an independent mobile application. Regarding usability, GoCity focuses on providing a simple and clear user interface as well as supporting user expectations for personalization. An experiment which involves a person visiting the city of Victoria was conducted to evaluate GoCity. In this evaluation, three determining factors of usability were employed to qualitatively and quantitatively assess GoCity. In addition, the static mode and dynamic mode were evaluated separately.
Optimal Boundary Control of Non-Isothermal Viscous Fluid Flow

We study an optimal control problem for the mathematical model that describes steady non-isothermal creeping flows of an incompressible fluid through a locally Lipschitz bounded domain. The control parameters are the pressure and the temperature on the in-flow and out-flow parts of the boundary of the flow domain. We propose the weak formulation of the problem and prove the existence of weak solutions that minimize a given cost functional. It is also shown that the marginal function of this control system is lower semi-continuous.
Business Studies Teachers and Student Needs

This paper is a report on the findings of a study conducted on the direct users of the Business Studies curriculum in Malaysia to uncover the perceived gap between what was experienced with what was wanted. Interviews were used to examine the needs of the Form Six (equivalent to “A” level) Business Studies teachers and students. Findings indicate that teachers wanted some form of practical work but were worried about the time constraint in carrying it out. Certain topics such as business law, cooperatives and non-profit organisations should be discarded from the curriculum or revamped. Students clamour for practical work and emphasise the need to improve their communication, problem solving and leadership skills. Teachers and students felt values such as honesty, integrity and responsibility should be inculcated in students. Positive attitude, hardworking and strongly motivated are attitudes necessary for success in the business world, and these should be emphasised as well. The Malaysian Examination Council, which is the developer of the curriculum, needs to take a serious look at the lack in the curriculum to ensure a comprehensive curriculum is developed.
Wind–wave coupling study using LES of wind and phase-resolved simulation of nonlinear waves

We present a study on the interaction between wind and water waves with a broad-band spectrum using wave-phase-resolved simulation with long-term wave field evolution. The wind turbulence is computed using large-eddy simulation and the wave field is simulated using a high-order spectral method. Numerical experiments are carried out for turbulent wind blowing over a wave field initialised using the Joint North Sea Wave Project spectrum, with various wind speeds considered. The results show that the waves, together with the mean wind flow and large turbulent eddies, have a significant impact on the wavenumber–frequency spectrum of the wind turbulence. It is found that the shear stress contributed by sweep events in turbulent wind is greatly enhanced as a result of the waves. The dependence of the wave growth rate on the wave age is consistent with the results in the literature. The probability density function and high-order statistics of the wave surface elevation deviate from the Gaussian distribution, manifesting the nonlinearity of the wave field. The shape of the change in the spectrum of wind-waves resembles that of the nonlinear wave–wave interactions, indicating the dominant role played by the nonlinear interactions in the evolution of the wave spectrum. The frequency downshift phenomenon is captured in our simulations wherein the wind-forced wave field evolves for $O(3000)$ peak wave periods. Using the numerical result, we compute the universal constant in a wave-growth law proposed in the literature, and substantiate the scaling of wind–wave growth based on intrinsic wave properties.
Inferring Alignments I: Exploring the Accuracy and Precision of Two Statistical Approaches

Using computer simulations, this paper explores and quantifies the accuracy and precision of two approaches to the statistical inference of the most likely targets of a set of structural orientations. It discusses the curvigram method (also known as kernel density estimation or summed probability distribution) in wide currency in archaeoastronomy, and introduces the largely unutilised maximum likelihood (ML) method, which has popularity in other academic fields. An analysis of both methods’ accuracy and precision is done, using a scenario with a single target, and the resulting equations can be used to estimate the minimum number of surveyed structures required to ensure a high-precision statistical inference. Two fundamental observations emerge: firstly, that although both approaches are quite accurate, the ML approach is considerably more precise than the curvigram approach; and secondly, that underestimating measurement uncertainty severely undermines the precision of the curvigram method. Finally, the implications of these observations for past, present and future archaeoastronomical research are discussed.
An Analytic Calculus for the Intuitionistic Logic of Proofs

The goal of this paper is to take a step towards the resolution of the problem of finding an analytic sequent calculus for the logic of proofs. For this, we focus on the system Ilp, the intuitionistic version of the logic of proofs. First we present the sequent calculus Gilp that is sound and complete with respect to the system Ilp; we prove that Gilp is cut-free and contraction-free, but it still does not enjoy the subformula property. Then, we enrich the language of the logic of proofs and we formulate in this language a second Gentzen calculus Gilp∗. We show that Gilp∗ is a conservative extension of Gilp, and that Gilp∗ satisfies the subformula property. Keyword cut-elimination, logic of proofs, normalisation, proof sequents 2010 MSC: 03F05, 03B60
Modeling of Ablatant Deposition from Electromagnetically Driven Radiative Pellets for Disruption Mitigation Studies

Abstract The electromagnetic particle injector (EPI) concept is advanced through the simulation of ablatant deposition into ITER H-mode discharges with calculations showing penetration past the H-mode pedestal for a range of injection velocities and granule sizes concurrent with the requirements of disruption mitigation. As discharge stored energy increases in future fusion devices such as ITER, control and handling of disruption events become critical issues. An unmitigated disruption could lead to failure of the plasma-facing components resulting in financially and politically costly repairs. Methods to facilitate the quench of an unstable high-current discharge are required. With the onset warning time for some ITER disruption events estimated to be less than 10 ms, a disruption mitigation system needs to be considered that operates at injection speeds greater than gaseous sound speeds. Such an actuator could then serve as a means to augment presently planned pneumatic injection systems. The EPI uses a railgun concept whereby a radiative payload is delivered into the discharge by means of the J×B forces generated by an external current pulse, allowing for injection velocities in excess of 1 km/s. The present status of the EPI project is outlined, including the addition of boost magnetic coils. These coils augment the self-generated railgun magnetic field and thus provide a more efficient acceleration of the payload. The coils and the holder designed to constrain them have been modeled with the ANSYS code to ensure structural integrity through the range of operational coil currents.
Size-reduced tunable hairpin bandpass filter using aperture coupling with enhanced selectivity and constant bandwidth

In this paper, a size-reduced aperture-coupled tunable hairpin bandpass filter which has improved selectivity and has constant bandwidth is proposed. We used an aperture coupling between first and second stage of the filter to reduce the size of the filter. Varactors are loaded to open end of the quarter-wave resonators to tune the center frequency. The open stub of the filter makes transmission zero which enhances the selectivity of the filter. Furthermore, we also loaded varactors to end of the open stubs to control the notch frequency. Thus, we could obtain the constant bandwidth over the tuning range. The varactor loaded open stub of the hairpin resonator which works as a K-inverter makes possible to meet the wideband coupling relationship in overall frequency tuning range. The measurement results show the proposed aperture-coupled tunable hairpin bandpass filter not only has small size but also enhanced selectivity and constant bandwidth. The proposed filter has 19.4 % tuning range from 1.4 GHz to 1.7 GHz and constant bandwidth within the tuning range. The proposed filter is designed and tested and 50 % size reduction was achieved.
Adaptive Generalized Likelihood Ratio Test for Change Detection in SAR Images

Generalized likelihood ratio test (GLRT) was widely used in the change detection of synthetic aperture radar (SAR) images and employed as a competitive method in many studies. GLRT is applied to the neighborhood areas corresponding to the same geographical area in multitemporal SAR images. Generally, the difference image is acquired by applying the GLRT on a moving window empirically determined by the user, which is clearly unreasonable because the different pixels in an image may have different optimal windows. To overcome this drawback, we propose an adaptive GLRT (AGLRT) method for change detection in SAR images. AGLRT adaptively selects the homogeneity window for each pixel and can decrease the uncertainty of change detection due to manual selection of the moving window. Experiments are conducted on two data sets to confirm the performance of the proposed method. Experimental results show that AGLRT can both suppress the influence of noise and preserve edge details and improve the accuracy of change detection.
Evolution cosmologique du taux de fusion des galaxies à partir des champs profonds MUSE

Au cours des dernieres decennies, de nombreuses preuves que les galaxies ont subit une profonde evolution depuis leur formation s'accumulent. Les fusions de galaxies, un des principaux mecanismes a l'origine de la croissance des galaxies, ont-elles joue un role dans leur evolution lorsque l’univers etait encore jeune ? En raison de la difficulte a detecter des interactions entre galaxies a grand redshifts, le taux de fusions majeures de galaxies, qui impliquent la fusion de deux galaxies de masses et de tailles similaires, etait seulement contraint jusqu’a un redshift de 3, grâce aux etudes precedentes portant sur des sondages spectroscopiques. Grace a sa technologie innovante, le spectrographe integral de champ MUSE, un nouvel instrument installe sur le VLT au Chili, convient parfaitement a l'identification de paires proches de galaxies. Ses mesures de redshift spectroscopique ont permis d'etendre l'etude de l'evolution du taux de fusion jusqu’a z = 6. Ainsi durant ma these, j'ai tente d'apporter de nouvelles contraintes sur la croissance des galaxies depuis les 12 derniers milliard d'annees, en etudiant l'evolution du taux de fusion des galaxies. Je presente ici les resultats obtenus sur l'analyse des champs les plus profonds obtenus jusqu'alors avec MUSE, tout d'abord dans le Hubble Ultra Deep Field et dans le Hubble Deep Field South. En tout 23 paires proches de galaxies ont ete identifiees a grand redshift (z > 3) a travers leur emissions Lyα. Pour ces galaxies, certains biais ont ete pris en compte. J'ai ainsi pu donner une premiere estimation du taux de fusions majeures entre z > 4 et z ∼ 6. Dans une seconde etude, j'ai etendu cette analyse a deux autres regions observees par MUSE : Abell 2744 et COSMOS-GR30. Les criteres de selection des paires proches de galaxies ont ete ameliores avec une etude sur la distance de separation et difference de vitesse de paires de galaxies et sa probabilite de fusionner plus tard, dans les simulations Illustris. Pres de 372 paires proches ont pu etre identifiees a partir d'un echantillon parent de 2483 galaxies distribuees sur un grand domaine de redshift (0.2 < z < 6) et de masses stellaires. Ceci nous fournit les premieres contraintes sur la fusion de galaxies majeures et mineures sur pres de 12 milliard d'annees d'evolution. Nos resultats montrent que les fusions majeures atteignent un maximum autour z = 2 − 3 pour ensuite lentement decroitre de z > 3 a z = 6. Les fusions mineures quant a elles semblent suivre une evolution moins marquee en fonction du temps, avec une fraction autour de 20% a z = 1.5 et une legere decroissance jusqu’a 8-13% pour z > 3. Dans un dernier temps, le taux de fusions majeures et mineures de galaxies au cours du temps cosmique est estime a partir de ces fractions. Cette etude illustre bien le potentiel de MUSE pour etudier les fusions de galaxies a grand redshift.
Local (thick-disc) white dwarfs and the Galactic mass budget

The stars of the solar neighbourhood essentially originate from two stellar populations: Population I (the thin disc) and Population II (the thick disc). Recently, we completed an unbiased sample of long-lived solar-type stars and demonstrated that the local normalization of the thick disc versus thin disc is about 20 per cent. In this second paper, we present the observational evidence that at least this percentage is also met in the realm of their degenerate counterparts and may even be as high as one-third. Along with the results from the solar-type stars, this is a direct confirmation of the thick disc being the massive and dark baryonic population of the Milky Way.
Ion Clock Busts into New Precision Regime

W hich periodic oscillator would make the best clock? Nobody really knows. But in 1982 Hans Dehmelt—who would later win the Nobel prize for his development of the ion trap—realized that the “ultimate” time keeper might be a single ion, trapped by electric fields and cooled with lasers [1]. The frequency of light emitted by the ion as it transitions between two internal states could, Dehmelt estimated, be measured with a fractional uncertainty of 10−18, allowing a similarly precise definition of the second as a fixed num-
A portable low-cost 3D point cloud acquiring method based on structure light

A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.
QUT ielab at CLEF eHealth 2017 Technology Assisted Reviews Track: Initial experiments with learning to rank

In this paper we describe our participation to the CLEF eHealth 2017 Technology Assisted Reviews track (TAR). This track aims to evaluate and advance search technologies aimed at supporting the creation of biomedical systematic reviews. In this context, the track explores the task of screening prioritisation: the ranking of studies to be screened for inclusion in a systematic review. Our solution addresses this challenge by developing ranking strategies based on learning to rank techniques and exploiting features derived by the use of the PICO framework. PICO (Population, Intervention, Control or comparison and Outcome) is a technique used in evidence based practice to frame and answer clinical questions and is used extensively in the compilation of systematic reviews. Our experiments show that the use of the PICO-based feature within learning to rank provides improvements over the use of baseline features alone.