Motion state recognition of debris ejected in vehicular collision after contact with the ground

The motion state of debris ejected from the vehicle involved in vehicular collision is important for finding out the vehicle collision speed. This research developed an analytical model to recognise the debris motion state. With the model, analyses were conducted, which reveal that if α, which is the contact angle between the debris and the ground at the moment when the debris collides the ground, is within the range from 0° to its boundary value, then the debris slides; if α is within the range from its boundary value to 90°, then the debris bounces. With debris' initial angular velocity ω = 0, the boundary value is 11.8° for sphere debris and 7.8° for rectangular debris; with ω ≠ 0, the boundary value for rectangular debris is arcsin(g/Rω2) where g represents the acceleration due to gravity and R is the distance from the debris centre to the point of its contact with the ground. Experiment tests were conducted for debris motion states with ω = 0, which confirmed the analytical results

Research on evaporation of Taiyuan basin area by using remote sensing

International audienceTaiyuan basin is enclosed by hills and mountains, located in the middle of Shanxi province, standing between longitudes 111°40'?113°00'E and latitude 37°00'?38&deg00'N. With various types and wide distribution, the mineral resources are very abundant in this basin area. However, there is a great shortage of water resources. Due to continual fall of groundwater level caused by excessive extraction of ground water, some severe environmental problems are induced in this area, such as ground subsidence, etc. The goal of this paper is to estimate the spatial distribution of actual evaporation over the basin by using remote sensing data. The Surface Energy Balance System (SEBS) has been developed (Su, 2001, 2002). Using visible and infrared satellite remote sensing data, SEBS is based on land surface energy balance theory combined with the in-situ meteorological data or the product of atmospheric numerical model to estimate land surface turbulent flux and the relative evaporation at different scales. SEBS was served as the core methodology of this paper and was used for evaporation estimation. On the basis of hydro-geological data and NOAA satellite data, the SEBS was used in this paper for the estimation of actual evaporation of Taiyuan basin. The spatial distribution of the evaporative fraction and daily evaporation over the basin area was shown. On the other hand, the difference of land surface parameters and evaporation for various target types in the basin area was discussed

Remote sensing of global monthly evapotranspiration with an energy balance (eb) model

A global monthly evapotranspiration (ET) product without spatial-temporal gaps for 2000&amp;ndash;2017 is delivered by using an energy balance (EB) algorithm and MODIS satellite data. It provides us with a moderate resolution estimate of ET without spatial-temporal gaps on a global scale. The model is driven by monthly remote sensing land surface temperature and ERA-Interim meteorological data. A global turbulent exchange parameterization scheme was developed for global momentum and heat roughness length calculation with remote sensing information. The global roughness length was used in the energy balance model, which uses monthly land-air temperature gradient to estimate the turbulent sensible heat, and take the latent heat flux as a residual of the available energy. This study produced an ET product for global landmass, at a monthly time step and 0.05-degree spatial resolution. The performance of ET data has been evaluated in comparison to hundreds flux sites measurements representing a broad range of land covers and climates. The ET product has a mean bias of 3.3 mm/month, RMSE value of 36.9 mm/month. The monthly ET product can be used to study the global energy and hydrological cycles at either seasonal or inter-annual temporal resolution.</p

Characterizing Ranked Chinese Syllable-to-Character Mapping Spectrum: A Bridge Between the Spoken and Written Chinese Language

One important aspect of the relationship between spoken and written Chinese is the ranked syllable-to-character mapping spectrum, which is the ranked list of syllables by the number of characters that map to the syllable. Previously, this spectrum is analyzed for more than 400 syllables without distinguishing the four intonations. In the current study, the spectrum with 1280 toned syllables is analyzed by logarithmic function, Beta rank function, and piecewise logarithmic function. Out of the three fitting functions, the two-piece logarithmic function fits the data the best, both by the smallest sum of squared errors (SSE) and by the lowest Akaike information criterion (AIC) value. The Beta rank function is the close second. By sampling from a Poisson distribution whose parameter value is chosen from the observed data, we empirically estimate the $p$-value for testing the two-piece-logarithmic-function being better than the Beta rank function hypothesis, to be 0.16. For practical purposes, the piecewise logarithmic function and the Beta rank function can be considered a tie.Comment: 15 pages, 4 figure

Development of ultra-high performance concrete with high fire resistance

© 2018 Elsevier Ltd Fire or high temperature is a big challenge to ultra-high performance concrete (UHPC). Strength loss of UHPCs can reach up to 80% after exposure to 800 °C. In this study, a total of six UHPC mixtures were designed and tested after subjected to elevated temperatures up to 1000 °C. The effects of aggregate type, fibre type and heating rate were investigated. Residual compressive strengths and stress-strain relationships were studied. Besides, attention was paid to explosive spalling since UHPCs are usually of compact structure and thus more vulnerable to explosive spalling than other concretes. Scanning electron microscope (SEM) analysis was conducted to help understand the mechanism of variation of internal structure under different temperatures. It was found the mixture containing steel slag and hybrid fibre had excellent fire resistance. After being subjected to 1000 °C, this mixture retained a residual compressive strength of 112.8 MPa or a relative value of 69%

Residual magnifier: A dense information flow network for super resolution

© 2019 IEEE. Recently, deep learning methods have been successfully applied to single image super-resolution tasks. However, some networks with extreme depth failed to achieve better performance because of the insufficient utilization of the local residual information extracted at each stage. To solve the above question, we propose a Dense Information Flow Network (DIF-Net), which can fully extract and utilize the local residual information at each stage to accomplish a better reconstruction. Specifically, we present a Two-stage Residual Extraction Block (TREB) to extract the shallow and deep local residual information at each stage. The dense connection mechanism is introduced throughout the model and within TREBs to dramatically increase the information flow. Meanwhile this mechanism prevents the shallow features extracted earlier from being diluted. Finally, we propose a lightweight subnet (residual enhancer) to efficiently recycle the overflow residual information from the backbone net for detail enhancement of the residual image. Experimental results demonstrate that the proposed method performs favorably against the state-of-the-art methods with relatively-less parameters

Effects of microbus front structure on pedestrian head injury

In order to study the effects of the microbus front structure on pedestrian head injury happened in pedestrian-microbus collisions, the mathematic models of the impact angle and microbus front configuration are developed, which illustrate the relationship between the impact angle, pedestrian size, and oblique angles of the engine hood and windscreen. The mathematic models are then verified by simulating experiments using LY-Dyna. The impact angle α, which is measured between the contact surface and the pedestrian head's impact direction at the contact point, is an important parameter indicating the relationship of pedestrian head injury with the microbus front structure. The analysis and simulation results reveal that (1) in the case of collision with the windscreen, the pedestrian head injury increases while α increases; (2) in the case of collision with the engine hood, the pedestrian head incurs the most serious injury when α = 90o, the pedestrian head injury increases while α increases when α 90o. Six microbus models are taken as examples to verify the results obtained

Exploiting Cognitive Structure for Adaptive Learning

Adaptive learning, also known as adaptive teaching, relies on learning path recommendation, which sequentially recommends personalized learning items (e.g., lectures, exercises) to satisfy the unique needs of each learner. Although it is well known that modeling the cognitive structure including knowledge level of learners and knowledge structure (e.g., the prerequisite relations) of learning items is important for learning path recommendation, existing methods for adaptive learning often separately focus on either knowledge levels of learners or knowledge structure of learning items. To fully exploit the multifaceted cognitive structure for learning path recommendation, we propose a Cognitive Structure Enhanced framework for Adaptive Learning, named CSEAL. By viewing path recommendation as a Markov Decision Process and applying an actor-critic algorithm, CSEAL can sequentially identify the right learning items to different learners. Specifically, we first utilize a recurrent neural network to trace the evolving knowledge levels of learners at each learning step. Then, we design a navigation algorithm on the knowledge structure to ensure the logicality of learning paths, which reduces the search space in the decision process. Finally, the actor-critic algorithm is used to determine what to learn next and whose parameters are dynamically updated along the learning path. Extensive experiments on real-world data demonstrate the effectiveness and robustness of CSEAL.Comment: Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD'19

Quantum simulation of artificial Abelian gauge field using nitrogen-vacancy center ensembles coupled to superconducting resonators

We propose a potentially practical scheme to simulate artificial Abelian gauge field for polaritons using a hybrid quantum system consisting of nitrogen-vacancy center ensembles (NVEs) and superconducting transmission line resonators (TLR). In our case, the collective excitations of NVEs play the role of bosonic particles, and our multiport device tends to circulate polaritons in a behavior like a charged particle in an external magnetic field. We discuss the possibility of identifying signatures of the Hofstadter "butterfly" in the optical spectra of the resonators, and analyze the ground state crossover for different gauge fields. Our work opens new perspectives in quantum simulation of condensed matter and many-body physics using hybrid spin-ensemble circuit quantum electrodynamics system. The experimental feasibility and challenge are justified using currently available technology.Comment: 6 papes+supplementary materia