arXiv subjects

Kun Gao

Publications and source records attributed to Kun Gao.

At least 37 records · Page 2Linked to original sources

arXiv2022

Divergent Effects of Factors on Crashes under Autonomous and Conventional Driving Modes Using A Hierarchical Bayesian Approach

Influencing factors on crashes involved with autonomous vehicles (AVs) have been paid increasing attention. However, there is a lack of comparative analyses between influencing factors on crashes of AVs and human-driven vehicles. To fill this research gap, the study aims to explore the divergent effects of factors on crashes under autonomous and conventional driving modes. This study obtained 154 publicly available autonomous vehicle crash data (70 for the autonomous driving mode and 84 for the conventional driving mode), and 36 explanatory variables were extracted from three categories, including environment, roads, and vehicles. Then, a hierarchical Bayesian approach was applied to analyze the impacting factors on crash type and severity under both driving modes. The results showed that some factors affected both driving modes, but their degrees were different. For example, the presence of turning movement had a greater impact on the crash severity under the conventional driving mode, while the presence of turning movement led to a larger decrease in the likelihood of rear-end crashes under the autonomous driving mode. More influencing factors only had a significant impact on one of the driving modes. For example, in the autonomous driving mode, two sidewalks decreased the severity of crashes, and on-street parking was positively associated with rear-end crashes, but they were not significant in the conventional driving mode. This study could contribute to the understanding and development of autonomous driving systems and the better coordination between autonomous driving and conventional driving.

stat.AP↗

arXiv2022

Merging Control Strategies of Connected and Autonomous Vehicles at Freeway On-Ramps: A Comprehensive Review

On-ramp merging areas are typical bottlenecks in the freeway network, since merging on-ramp vehicles may cause intensive disturbances on the mainline traffic flow and lead to various negative impacts on traffic efficiency and safety. The connected and autonomous vehicles (CAVs), with their capabilities of real-time communication and precise motion control, hold a great potential to facilitate ramp merging operation through enhanced coordination strategies. This paper presents a comprehensive review of the existing ramp merging strategies leveraging CAVs, focusing on the latest trends and developments in the research field. The review comprehensively covers 44 papers recently published in leading transportation journals. Based on the application context, control strategies are categorized into three categories: merging into sing-lane freeways with total CAVs, merging into sing-lane freeways with mixed traffic flows, and merging into multilane freeways. Relevant literature is reviewed regarding the required technologies, control decision level, applied methods, and impacts on traffic performance. More importantly, we identify the existing research gaps and provide insightful discussions on the potential and promising directions for future research based on the review, which facilitates further advancement in this research topic.

eess.SY↗

arXiv2022

Detecting network communities via greedy expanding based on local superiority index

Community detection is a significant and challenging task in network science. Nowadays, plenty of attention has been paid on local methods for community detection. Greedy expanding is a popular and efficient class of local algorithms, which typically starts from some selected central nodes and expands those nodes to obtain provisional communities by optimizing a certain quality function. In this paper, we propose a novel index, called local superiority index (LSI), to identify central nodes. In the process of expansion, we apply the fitness function to estimate the quality of provisional communities and ensure that all provisional communities must be weak communities. Evaluation based on the normalized mutual information suggests: (1) LSI is superior to the global maximal degree index and the local maximal degree index on most considered networks; (2) The greedy algorithm based on LSI is better than the classical fast algorithm on most considered networks.

physics.soc-ph↗

arXiv2021

The strongly quasi-local coarse Novikov conjecture and Banach spaces with Property (H)

In this paper, we introduce a strongly quasi-local version of the coarse Novikov conjecture, which states that certain assembly map from the coarse $K$-homology of a metric space to the $K$-theory of its strongly quasi-local algebra is injective. We prove that the conjecture holds for metric spaces with bounded geometry which can be coarsely embedded into Banach spaces with Property (H), introduced by Kasparov and Yu. Besides, we also generalise the notion of strong quasi-locality to proper metric spaces and provide a (strongly) quasi-local picture for $K$-homology.

math.OA↗

arXiv2020

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, iSeg-2019 challenge (http://iseg2019.web.unc.edu) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. Training/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participating in iSeg-2019. We review the 8 top-ranked teams by detailing their pipelines/implementations, presenting experimental results and evaluating performance in terms of the whole brain, regions of interest, and gyral landmark curves. We also discuss their limitations and possible future directions for the multi-site issue. We hope that the multi-site dataset in iSeg-2019 and this review article will attract more researchers on the multi-site issue.

eess.IV↗

arXiv2020

Community detection on complex networks based on a new centrality indicator and a new modularity function

Community detection is a significant and challenging task in network research. Nowadays, plenty of attention has been focused on local methods of community detection. Among them, community detection with a greedy algorithm typically starts from the identification of local essential nodes called central nodes of the network; communities expand later from these central nodes by optimizing a modularity function. In this paper, we propose a new central node indicator and a new modularity function. Our central node indicator, which we call local centrality indicator (LCI), is as efficient as the well-known global maximal degree indicator and local maximal degree indicator; on certain special network structure, LCI performs even better. On the other hand, our modularity function F2 overcomes certain disadvantages,such as the resolution limit problem,of the modularity functions raised in previous literature. Combined with a greedy algorithm, LCI and F2 enable us to identify the right community structures for both the real world networks and the simulated benchmark network. Evaluation based on the normalized mutual information (NMI) suggests that our community detection method with a greedy algorithm based on LCI and F2 performs superior to many other methods. Therefore, the method we proposed in this paper is potentially noteworthy.

cs.SI↗

arXiv2019

Reasoning about Block-based Cloud Storage Systems

Owing to the massive growth in the storage demands of big data, Cloud Storage Systems (CSSs) have been put forward to improve the storage capacity. Compared with traditional storage systems, CSSs have lots of advantages, such as higher capacity, lower cost, and easier scalability. But they are also with higher complexity. In order to ensure CSSs to be reliable, it is necessary to prove the correctness of CSSs management programs. In fact, we are going to verify Block-based Cloud Storage Systems (BCSSs), since BCSSs are the most popular CSSs. In this paper, the correctness of management programs in BCSSs have been proven, and a verification framework based on separation logic is proposed to finish the proven process. The main contributions are as follows. (1) A novel framework with two-tier heap structure is constructed to reflect the characteristics of BCSSs, and a modeling language is defined based on it. (2) Assertions based on separation logic is constructed to describe the properties of BCSSs. (3) The Hoare-style specifications are proposed to reason about the BCSSs. The results demonstrate that the correctness and reliability of BCSSs can be verified by the above proposed methods. Furthermore, the proposed specifications is sound in the application of reasoning about BCSSs.

cs.LO↗

arXiv2017

An Effective Training Method For Deep Convolutional Neural Network

In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks. The proposed method modifies a family of activation functions as nonlinearity generators (NGs). NGs make the activation functions linear symmetric for their inputs to lower model capacity, and automatically introduce nonlinearity to enhance the capacity of the model during training. The proposed method can be considered an unusual form of regularization: the model parameters are obtained by training a relatively low-capacity model, that is relatively easy to optimize at the beginning, with only a few iterations, and these parameters are reused for the initialization of a higher-capacity model. We derive the upper and lower bounds of variance of the weight variation, and show that the initial symmetric structure of NGs helps stabilize training. We evaluate the proposed method on different frameworks of convolutional neural networks over two object recognition benchmark tasks (CIFAR-10 and CIFAR-100). Experimental results showed that the proposed method allows us to (1) speed up the convergence of training, (2) allow for less careful weight initialization, (3) improve or at least maintain the performance of the model at negligible extra computational cost, and (4) easily train a very deep model.

cs.LG↗

arXiv2017

Low dose and fast grating-based x-ray phase-contrast imaging using the integrating-bucket phase modulation technique

X-ray phase-contrast imaging has experienced rapid development over the last few decades, and in this technology, the phase modulation strategy of phase-stepping is used most widely to measure the sample's phase signal. However, because of its discontinuous nature, phase-stepping has the defects of worse mechanical stability and high exposure dose, which greatly hinder its wide application in dynamic phase measurement and potential clinical applications. In this manuscript, we demonstrate preliminary research on the use of integrating-bucket phase modulation method to retrieve the phase information in grating-based X-ray phase-contrast imaging. Experimental results showed that our proposed method can be well employed to extract the differential phase-contrast image, compared with the current mostly used phase-stepping strategy, advantage of integrating-bucket phase modulation technique is that fast measurement and low dose are promising.

physics.med-ph↗

arXiv2015

Orthologs from maxmer sequence context

Context-dependent identification of orthologs customarily relies on conserved gene order or whole-genome sequence alignment. It is shown here that short-range context--as short as single maximal matches--also provides an effective means to identify orthologs within whole genomes. On pristine (un-repeatmasked) mammalian whole-genome assemblies we perform a genome "intersection" that in general consumes less than one thirtieth of the computation time required by commonly used methods for whole-genome alignment, and we extract "non-embedded maximal matches," maximal matches that are not embedded into other maximal matches, as potential orthologs. An ortholog identified via non-embedded maximal matches is analogous to a "positional ortholog" or a "primary ortholog" as defined in previous literature; such orthologs constitute homologs derived from the same direct ancestor whose ancestral positions in the genome are conserved. At the nucleotide level, non-embedded maximal matches recapitulate most exact matches identified by a Lastz net alignment. At the gene level, reciprocal best hits of genes containing non-embedded maximal matches recover one-to-one orthologs annotated by Ensembl Compara with high selectivity and high sensitivity; these reciprocal best hits additionally include putatively novel orthologs not found in Ensembl (e.g. over two thousand for human/chimpanzee). The method is especially suitable for genome-wide identification of orthologs.

q-bio.QM↗

arXiv2015

Preliminary Research on Dual-Energy X-Ray Phase-Contrast Imaging

Dual-energy X-ray absorptiometry (DEXA) has been widely applied to measure bone mineral density (BMD) and soft-tissue composition of human body. However, the use of DEXA is greatly limited for low-Z materials such as soft tissues due to their weak absorption. While X-ray phase-contrast imaging (XPCI) shows significantly improved contrast in comparison with the conventional standard absorption-based X-ray imaging for soft tissues. In this paper, we propose a novel X-ray phase-contrast method to measure the area density of low-Z materials, including a single-energy method and a dual-energy method. The single-energy method is for the area density calculation of one low-Z material, while the dual-energy method is aiming to calculate the area densities of two low-Z materials simultaneously. Comparing the experimental and simulation results with the theoretic ones, the new method proves to have the potential to replace DEXA in area density measurement. The new method sets the prerequisites for future precise and low-dose area density calculation method of low-Z materials.

physics.med-ph↗

arXiv2015

Performance Analysis of Quantitative Phase Retrieval Method in Zernike Phase Contrast X-ray Microscopy

Since the invention of Zernike phase contrast method in 1930, it has been widely used in optical microscopy and more recently in X-ray microscopy. Considering the image contrast is a mixture of absorption and phase information, we recently have proposed and demonstrated a method for quantitative phase retrieval in Zernike phase contrast X-ray microscopy. In this contribution, we analyzed the performance of this method at different photon energies. Intensity images of PMMA samples are simulated at 2.5 keV and 6.2 keV, respectively, and phase retrieval is performed using the proposed method. The results demonstrated that the proposed phase retrieval method is applicable over a wide energy range. For weakly absorbing features, the optimal photon energy is 2.5 keV, from the point of view of image contrast and accuracy of phase retrieval. On the other hand, in the case of strong absorption objects, a higher photon energy is preferred to reduce the error of phase retrieval. Those results can be used as guidelines to perform quantitative phase retrieval in Zernike phase contrast X-ray microscopy with the proposed method.

physics.optics↗

arXiv2015

Research on the background correction method in x-ray phase contrast imaging with Talbot-Lau interferometer

X-ray Talbot-Lau interferometer has been used widely to conduct phase contrast imaging with a conventional low-brilliance x-ray source. Typically, in this technique, background correction has to be performed in order to obtain the pure signal of the sample under inspection. In this study, we reported on a research on the background correction strategies within this technique, especially we introduced a new phase unwrapping solution for one conventional background correction method, the key point of this new solution is changing the initial phase of each pixel by a cyclic shift operation on the raw images collected in phase stepping scan. Experimental result and numerical analysis showed that the new phase unwrapping algorithm could successfully subtract contribution of the system's background without error. Moreover, a potential advantage of this phase unwrapping strategy is that its effective phase measuring range could be tuned flexibly in some degree for example to be (-pi+3, pi+3], thus it would find usage in certain case because measuring range of the currently widely used background correction method is fixed to be (-pi, pi].

physics.optics↗

arXiv2015

A comprehensive study of the magnetic, structural and transport properties of the III-V ferromagnetic semiconductor InMnP

The manganese induced magnetic, electrical and structural modification in InMnP epilayers, prepared by Mn ion implantation and pulsed laser annealing, are investigated in the following work. All samples exhibit clear hysteresis loops and strong spin polarization at the Fermi level. The degree of magnetization, the Curie temperature and the spin polarization depend on the Mn concentration. The bright-field transmission electron micrographs show that InP samples become almost amorphous after Mn implantation but recrystallize after pulsed laser annealing. We did not observe an insulator-metal transition in InMnP up to a Mn concentration of 5 at./%. Instead all InMnP samples show insulating characteristics up to the lowest measured temperature. Magneotresistance results obtained at low temperatures support the hopping conduction mechanism in InMnP. We find that the Mn impurity band remains detached from the valence band in InMnP up to 5 at./% Mn doping. Our findings indicate that the local environment of Mn ions in InP is similar to GaMnAs, GaMnP and InMnAs, however, the electrical properties of these Mn implanted III-V compounds are different. This is one of the consequences of the different Mn binding energy in these compounds.

cond-mat.mtrl-sci↗

arXiv2014

Disorder and Power-law Tails of DNA Sequence Self-Alignment Concentrations in Molecular Evolution

The self-alignment concentrations, $c(x)$, as functions of the length, $x$, of the identically matching maximal segments in the genomes of a variety of species, typically present power-law tails extending to the largest scales, i.e., $c(x) \propto x^α$, with similar or apparently different negative $α$s ($<-2$). The relevant fundamental processes of molecular evolution are segmental duplication and point mutation, and that recently the stick fragmentation phenomenology has been used to account the neutral evolution. However, disorder is intrinsic to the evolution system and, by freezing it in time (quenching) for the setup of a simple fragmentation model, we obtain decaying, steady-state and the general full time-dependent solutions, all $\propto x^α$ for $x\to \infty$, which is in contrast to the only power-law solution, $x^{-3}$ for $x\to 0$ of the pure model (without disorder). %Other algebraic terms may dominate at intermediate scales, which seems to be confirmed by some species, such as rice. We also present self-alignment results showing more than one scaling regimes, consistent with the theoretical results of the existence of more than one algebraic terms which dominate at different regimes.

q-bio.PE↗

arXiv2014

Experimental research on the feature of an X-ray Talbot-Lau interferometer vs. tube accelerating voltage

X-ray Talbot-Lau interferometer has been used most widely to perform X-ray phase-contrast imaging with a conventional low-brilliance X-ray source, it yields high-sensitivity phase and dark-field images of sample producing low absorption contrast, thus bearing tremendous potential for future clinical diagnosis. In this manuscript, while changing accelerating voltage of the X-ray tube from 35KV to 45KV, X-ray phase-contrast imaging of a test sample were performed at each integer KV position to investigate the characteristic of an X-ray Talbot-Lau interferometer (located in the Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, Japan) vs. tube voltage. Experimental results and data analysis show that this X-ray Talbot-Lau interferometer is insensitive to the tube accelerating voltage within a certain range, fringe visibility around 44% is maintained in the aforementioned tube voltage range. This experimental research implies that potential new dual energy phase-contrast X-ray imaging strategy and rough refraction spectrum measurement is feasible with this X-ray Talbot-Lau interferometer.

physics.optics↗

arXiv2014

Human-chimpanzee alignment: Ortholog Exponentials and Paralog Power Laws

Genomic subsequences conserved between closely related species such as human and chimpanzee exhibit an exponential length distribution, in contrast to the algebraic length distribution observed for sequences shared between distantly related genomes. We find that the former exponential can be further decomposed into an exponential component primarily composed of orthologous sequences, and a truncated algebraic component primarily composed of paralogous sequences.

q-bio.GN↗

arXiv2014

A LabVIEW based user-friendly X-ray phase-contrast imaging system software platform

X-ray phase-contrast imaging can provide greatly improved contrast over conventional absorption-based imaging for weakly absorbing samples, such as biological soft tissues and fibre composites. In this manuscript, we introduce an easy and fast way to develop a user-friendly software platform dedicated to the new grating-based X-ray phase-contrast imaging setup recently built at the National Synchrotron Radiation Laboratory of the University of Science and Technology of China. Unified management and control of 21 motorized positioning stages, of an ultra-precision piezoelectric translation stage and of the X-ray tube are achieved with this platform. The software package also covers the automatic image acquisition of the phase-stepping scanning with a flat panel detector. Moreover, a data post-processing module for signals retrieval and other custom features are in principle available. With a seamless integration of all necessary functions in a unique package, this software platform will greatly support the user activity during experimental runs.

cs.SE↗