Kinematics Of Spatial Mechanisms

Large scale endeavor of research on spatial mechanisms started about half a century ago. Although significant research work has been done, the underlying framework of the theory of spatial mechanisms still appears weak. In this thesis, a theoretical foundation for the kinematic analysis and design of spatial mechanisms and robots has been developed.;In the last twenty years, the matrix method and the spherical trigonometry method have emerged as the most efficient ones among approximately ten other different methods for the kinematic analysis of spatial mechanisms. In this thesis a new method, the vector algebraic method, has been introduced. In comparison with the two methods, the proposed method has shown advantages on its efficiency, uniformity and simplicity.;The goal of this thesis is to enhance the education, research and application of spatial mechanisms

What's Missing in your Shopping Cart? A Set Based Recommendation Method for "Cold-Start" Prediction

This thesis studies the problem of predicting the missing items in the current user's session when there is no additional side information available. Many recommender systems fail in general to provide a precise set of recommendations to users with limited interaction history. This issue is regarded as the "Cold Start" problem and is typically resolved by switching to content-based approaches which require additional information. In this thesis, we use a dimensionality reduction algorithm, Word2Vec under the framework of Collaborative Filtering to tackle the "Cold Start" problem using only implicit data . We have named this combined method: Embedded Collaborative Filtering ECF. We are able to show that the ECF approach outperforms other popular state-of-the-art approaches in "Cold Start" scenarios by 2-10% regarding recommendation precision. In the experiment, we also show that the proposed method is 10 times faster in generating recommendations comparing to the Collaborative Filtering baseline method

3-Methyl­quinoxaline-2-carb­oxy­lic acid 4-oxide monohydrate

In the crystal structure of the title compound, C10H8N2O3·H2O, mol­ecules are linked via inter­molecular O—H⋯O and O—H⋯N hydrogen bonds into a two-dimensional network

Research and experimental verification on low-frequency long-range underwater sound propagation dispersion characteristics under dual-channel sound speed profiles in the Chukchi Plateau

The dual-channel sound speed profiles of the Chukchi Plateau and the Canadian Basin have become current research hotspots due to their excellent low-frequency sound signal propagation ability. Previous research has mainly focused on using sound propagation theory to explain the changes in sound signal energy. This article is mainly based on the theory of normal modes to study the fine structure of low-frequency wide-band sound propagation dispersion under dual-channel sound speed profiles. In this paper, the problem of the intersection of normal mode dispersion curves caused by the dual-channel sound speed profile (SSP) has been explained, the blocking effect of seabed terrain changes on dispersion structures has been analyzed, and the normal modes has been separated by using modified warping operator. The above research results have been verified through a long-range seismic exploration experiment at the Chukchi Plateau. At the same time, based on the acoustic signal characteristics in this environment, two methods for estimating the distance of sound sources have been proposed, and the experiment data at sea has also verified these two methods.Comment: 30 pages, 18 figure

Research and experimental verification on low-frequency long-range sound propagation characteristics under ice-covered and range-dependent marine environment in the Arctic

At present, research on sound propagation under the Arctic ice mainly focuses on modeling and experimental verification of sound propagation under sea ice cover and unique sound velocity profiles. Among them, the main research object of concern is sound transmission loss, and this article will delve into the time-domain waveform and fine dispersion structure of low-frequency broadband acoustic signals. Firstly, based on the theory of normal modes, this article derives the horizontal wavenumber expression and warping transformation operator for refractive normal modes in the Arctic deep-sea environment. Subsequently, based on measured ocean environmental parameters and sound field simulation calculations, this article studied the general laws of low-frequency long-range sound propagation signals in the Arctic deep-sea environment, and elucidated the impact mechanism of environmental factors such as seabed terrain changes, horizontal changes in sound velocity profiles (SSPs), and sea ice cover on low-frequency long-range sound propagation in the Arctic. This article validates the above research viewpoint through a sound propagation experiment conducted in the Arctic with a propagation distance exceeding 1000km. The marine environment of this experiment has obvious horizontal variation characteristics. At the same time, this article takes the lead in utilizing the warping transformation of refractive normal waves in the Arctic waters to achieve single hydrophone based separation of normal waves and extraction of dispersion structures, which is conducive to future research on underwater sound source localization and environmental parameter inversion based on dispersion structures.Comment: 46 pages, 35 figure

HDR Video Reconstruction with a Large Dynamic Dataset in Raw and sRGB Domains

High dynamic range (HDR) video reconstruction is attracting more and more attention due to the superior visual quality compared with those of low dynamic range (LDR) videos. The availability of LDR-HDR training pairs is essential for the HDR reconstruction quality. However, there are still no real LDR-HDR pairs for dynamic scenes due to the difficulty in capturing LDR-HDR frames simultaneously. In this work, we propose to utilize a staggered sensor to capture two alternate exposure images simultaneously, which are then fused into an HDR frame in both raw and sRGB domains. In this way, we build a large scale LDR-HDR video dataset with 85 scenes and each scene contains 60 frames. Based on this dataset, we further propose a Raw-HDRNet, which utilizes the raw LDR frames as inputs. We propose a pyramid flow-guided deformation convolution to align neighboring frames. Experimental results demonstrate that 1) the proposed dataset can improve the HDR reconstruction performance on real scenes for three benchmark networks; 2) Compared with sRGB inputs, utilizing raw inputs can further improve the reconstruction quality and our proposed Raw-HDRNet is a strong baseline for raw HDR reconstruction. Our dataset and code will be released after the acceptance of this paper