Clustering Analysis of User Loyalty Based on K-means

In recent years, the rise of machine learning has made it possible to further explore large data in various fields. In order to explore the attributes of loyalty of public transport travelers and divide these people into different clustering clusters, this paper uses K-means clustering algorithm (K-means) to cluster the holding time, recharge amount and swiping frequency of bus travelers. Then we use Kernel Density Estimation Algorithms (KDE) to analyze the density distribution of the data of holding time, recharge amount and swipe frequency, and display the results of the two algorithms in the way of data visualization. Finally, according to the results of data visualization, the loyalty of users is classified, which provides theoretical and data support for public transport companies to determine the development potential of users

Self-supervised arbitrary scale super-resolution framework for anisotropic MRI

In this paper, we propose an efficient self-supervised arbitrary-scale super-resolution (SR) framework to reconstruct isotropic magnetic resonance (MR) images from anisotropic MRI inputs without involving external training data. The proposed framework builds a training dataset using in-the-wild anisotropic MR volumes with arbitrary image resolution. We then formulate the 3D volume SR task as a SR problem for 2D image slices. The anisotropic volume's high-resolution (HR) plane is used to build the HR-LR image pairs for model training. We further adapt the implicit neural representation (INR) network to implement the 2D arbitrary-scale image SR model. Finally, we leverage the well-trained proposed model to up-sample the 2D LR plane extracted from the anisotropic MR volumes to their HR views. The isotropic MR volumes thus can be reconstructed by stacking and averaging the generated HR slices. Our proposed framework has two major advantages: (1) It only involves the arbitrary-resolution anisotropic MR volumes, which greatly improves the model practicality in real MR imaging scenarios (e.g., clinical brain image acquisition); (2) The INR-based SR model enables arbitrary-scale image SR from the arbitrary-resolution input image, which significantly improves model training efficiency. We perform experiments on a simulated public adult brain dataset and a real collected 7T brain dataset. The results indicate that our current framework greatly outperforms two well-known self-supervised models for anisotropic MR image SR tasks.Comment: 10 pages, 5 figure

Research on Planning and Model Design of Micro-cycle Bus Line Based on Metro Station Connection

Public transport coverage fails to keep pace with urbanization and urban expansion, which makes the “last kilometer" problem of residents’ travel increasingly prominent”. However, the practice has proved that microcirculation public transportation plays an important role in expanding the coverage of public transportation and promoting the integration of public transportation. Therefore, this paper takes a city bus community as an example. Firstly, it analyses the bus travel demand of commuters connecting to the subway station during the early workday rush hours on basis of IC Big Data, obtains candidate stations of microcirculation bus lines through K-means clustering. Secondly, it establishes the model, the target of which is to minimize  the cost residents' travel and bus operation, under the limited condition of walking distance, passenger number, station spacing and departure frequency. Finally, the genetic algorithm is used to find the optimal solution of the model, so it’s no doubt that the most feasible circular bus route is obtained. The results have positive significance for promoting the construction and operation of public transport integration and promoting the convenience and efficiency of public transport travel.

High-performance quantum entanglement generation via cascaded second-order nonlinear processes

In this paper, we demonstrate the generation of high-performance entangled photon-pairs in different degrees of freedom from a single piece of fiber pigtailed periodically poled LiNbO$_3$ (PPLN) waveguide. We utilize cascaded second-order nonlinear optical processes, i.e. second-harmonic generation (SHG) and spontaneous parametric down conversion (SPDC), to generate photon-pairs. Previously, the performance of the photon pairs is contaminated by Raman noise photons from the fiber pigtails. Here by integrating the PPLN waveguide with noise rejecting filters, we obtain a coincidence-to-accidental ratio (CAR) higher than 52,600 with photon-pair generation and detection rate of 52.3 kHz and 3.5 kHz, respectively. Energy-time, frequency-bin and time-bin entanglement is prepared by coherently superposing correlated two-photon states in these degrees of freedom, respectively. The energy-time entangled two-photon states achieve the maximum value of CHSH-Bell inequality of S=2.708$\pm$0.024 with a two-photon interference visibility of 95.74$\pm$0.86%. The frequency-bin entangled two-photon states achieve fidelity of 97.56$\pm$1.79% with a spatial quantum beating visibility of 96.85$\pm$2.46%. The time-bin entangled two-photon states achieve the maximum value of CHSH-Bell inequality of S=2.595$\pm$0.037 and quantum tomographic fidelity of 89.07$\pm$4.35%. Our results provide a potential candidate for quantum light source in quantum photonics.Comment: 29 pages,7 figure

Weakly coupled lithospheric extension in southern Tibet

AbstractWest–east extension is a prominent tectonic feature of southern and central Tibet despite ongoing north–south (N–S) convergence between India and Eurasia. Knowledge of deep structure beneath the N–S trending rifts is key to evaluating models proposed for their origin, including gravitational collapse, oblique convergence along the arcuate plate boundary, and mantle upwelling. We model direct S and Moho-reflected SsPmp phases at teleseismic distances to constrain variations in crustal thickness across the major rifts crossed by a ∼900-km long, W–E broadband array in the Lhasa Terrane. Crustal thicknesses are ∼70–80 km. However, Moho depth decreases by ∼10 km within a horizontal distance of 100 km west of the Yadong–Gulu rift (YGR) and Nyainquentanghla mountains (NQTL). This Moho uplift, taken with deep, extensional focal mechanisms and reduced seismic velocity in the upper mantle, suggests that asthenospheric upwelling has significantly contributed to the pattern of extension across the YGR and NQTL. The ∼100-km separation between surface rift and Moho uplift is likely enabled by partial decoupling across a ductile middle crust

New Aggregation-Induced Delayed Fluorescence Luminogens With Through-Space Charge Transfer for Efficient Non-doped OLEDs

In this work, two tailor-made luminogens comprising of electron donors (acridine and phenoxazine) and acceptor (triazine) bridged by the through-space conjugated hexaphenylbenzene (HPB) are synthesized and characterized. Their thermal stability, electrochemical behaviors, crystal, and electronic structures, and photophysical properties are systematically investigated. The crystal and electronic structures reveal that the peripheral phenyls in HPB are closely aligned in a propeller-like fashion, rendering efficient through-space charge transfer between donor and electron moieties. These molecules display weak fluorescence with negligible delayed component in solutions but strong fluorescence with greatly increased delayed component upon aggregate formation, namely aggregation-induced delayed fluorescence (AIDF). Their neat films exhibit high photoluminescence quantum yields (PLQY), and prominent delayed fluorescence. The non-doped organic light-emitting diodes (OLEDs) based on these new luminogens exhibit excellent performance with maximum external quantum efficiency of 12.7% and very small efficiency roll-off of 2.7% at 1,000 cd m−2. Designing AIDF molecules with through-space charge transfer could be a promising strategy to explore robust luminescent materials for efficient non-doped OLEDs

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

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