arXiv subjects

Sen Yang

Publications and source records attributed to Sen Yang.

At least 217 records · Page 12Linked to original sources

arXiv2018

A Time Efficient Approach for Decision-Making Style Recognition in Lane-Change Behavior

Fast recognizing driver's decision-making style of changing lanes plays a pivotal role in safety-oriented and personalized vehicle control system design. This paper presents a time-efficient recognition method by integrating k-means clustering (k-MC) with K-nearest neighbor (KNN), called kMC-KNN. The mathematical morphology is implemented to automatically label the decision-making data into three styles (moderate, vague, and aggressive), while the integration of kMC and KNN helps to improve the recognition speed and accuracy. Our developed mathematical morphology-based clustering algorithm is then validated by comparing to agglomerative hierarchical clustering. Experimental results demonstrate that the developed kMC-KNN method, in comparison to the traditional KNN, can shorten the recognition time by over 72.67% with recognition accuracy of 90%-98%. In addition, our developed kMC-KNN method also outperforms the support vector machine (SVM) in recognition accuracy and stability. The developed time-efficient recognition approach would have great application potential to the in-vehicle embedded solutions with restricted design specifications.

eess.SP↗

arXiv2018

CrowdExpress: A Probabilistic Framework for On-Time Crowdsourced Package Deliveries

Speed and cost of logistics are two major concerns to on-line shoppers, but they generally conflict with each other in nature. To alleviate the contradiction, we propose to exploit existing taxis that are transporting passengers on the street to relay packages collaboratively, which can simultaneously lower the cost and accelerate the speed. Specifically, we propose a probabilistic framework containing two phases called CrowdExpress for the on-time package express deliveries. In the first phase, we mine the historical taxi GPS trajectory data offline to build the package transport network. In the second phase, we develop an online adaptive taxi scheduling algorithm to find the path with the maximum arriving-on-time probability "on-the-fly" upon real- time requests, and direct the package routing accordingly. Finally, we evaluate the system using the real-world taxi data generated by over 19,000 taxis in a month in the city of New York, US. Results show that around 9,500 packages can be delivered successfully on time per day with the success rate over 94%, moreover, the average computation time is within 25 milliseconds.

cs.OH↗

arXiv2018

K-theory, local cohomology and tangent spaces to Hilbert schemes

By using K-theory, we construct a map from the tangent space to the Hilbert scheme at a point Y to the local cohomology group. And we use this map to answer affirmatively(after slight modification) a question by Mark Green and Phillip Griffiths in [8] on constructing a map from the tangent space to the Hilbert scheme to the tangent space to the cycle group.

math.AG↗

arXiv2018

Learning with Non-Convex Truncated Losses by SGD

Learning with a {\it convex loss} function has been a dominating paradigm for many years. It remains an interesting question how non-convex loss functions help improve the generalization of learning with broad applicability. In this paper, we study a family of objective functions formed by truncating traditional loss functions, which is applicable to both shallow learning and deep learning. Truncating loss functions has potential to be less vulnerable and more robust to large noise in observations that could be adversarial. More importantly, it is a generic technique without assuming the knowledge of noise distribution. To justify non-convex learning with truncated losses, we establish excess risk bounds of empirical risk minimization based on truncated losses for heavy-tailed output, and statistical error of an approximate stationary point found by stochastic gradient descent (SGD) method. Our experiments for shallow and deep learning for regression with outliers, corrupted data and heavy-tailed noise further justify the proposed method.

cs.LG↗

arXiv2018

Non-classical measurement statistics induced by a coherent spin environment

We demonstrate the role of measurement back-action of a coherent spin environment on the dynamics of a spin (qubit) coupled to it, by inducing non-classical (Quantum Random Walk like) statistics on its measurement trajectory. We show how the long-life time of the spin-bath allows it to correlate measurements of the qubit over many repetitions. We have used Nitrogen Vacancy centers in diamond as a model system, and the projective single-shot readout of the electron spin at low temperatures to simulate these effects. We show that the proposed theoretical model, explains the experimentally observed statistics and their application for quantum state engineering of spin ensembles towards desired states.

quant-ph↗

arXiv2018

Eliminate obstructions: curves on a 3-fold

By using higher K-theory, we reinterpret and generalize an idea on eliminating obstructions to deforming cycles, which is known to Mark Green, Phillip Griffiths and TingFai Ng(for the divisor case). As an application, we show how to eliminate obstructions to deforming curves on a 3-fold. This answers affirmatively an open question by TingFai Ng.

math.AG↗

arXiv2018

Zero map between obstruction spaces: subvarieties versus cycles

For $Y \subset X$ a locally complete intersection of codimension p, Spencer Bloch [2] constructed the semi-regularity map $π: H^{1}(\mathcal{N}_{Y/X}) \to H^{p+1}(Ω_{X/k}^{p-1})$. As an analogue, we construct a map $\tildeπ: H^{1}(\mathcal{N}_{Y/X}) \to H^{p+1}(Ω_{X/\mathbb{Q}}^{p-1})$, without assuming local complete intersections. While the semi-regularity map $π$ is expected to be injective, we show $\tildeπ$ is a zero map. We use this zero map to interpret how to eliminate obstructions to deforming cycles, an idea by Mark Green and Phillip Griffiths in [9].

math.AG↗

arXiv2018

On extending Soulé's variant of Bloch-Quillen identification

Based on Balmer's tensor triangular Chow group [2], we propose (Milnor)K-theoretic Chow groups of derived categories of schemes. These Milnor K-theoretic Chow groups recover the classical ones [6] for smooth projective varieties and can detect nilpotent, while the classical ones can't do. As an application, we extend Soulé's variant of Bloch-Quilled identification from smooth projective varieties to their trivial infinitesimal thickenings. This answers affirmatively a question by Green-Griffiths for trivial deformations, see Question 1.1 below.

math.AG↗

arXiv2018

Deformation of K-theoretic cycles

By using higher K-theory, we study deformation theory of K-theoretic cycles. As an application, we answer two questions posed by Mark Green and Philip Griffiths: (1). How to define tangent spaces to cycle class groups in general? (2). Obstruction issues. The highlight is the appearance of negative K-groups which detects the obstructions to deforming cycles.

math.AG↗

arXiv2018

Generation of long-living entanglement between two distant three-level atoms in non-Markovian environments

In this paper, a scheme for the generation of long-living entanglement between two distant Λ-type three-level atoms separately trapped in two dissipative cavities is proposed. In this scheme, two dissipative cavities are coupled to their own non-Markovian environments and two three-level atoms are driven by the classical fields. The entangled state between the two atoms is produced by performing Bell state measurement (BSM) on photons leaving the dissipative cavities. Using the time-dependent Schördinger equation, we obtain the analytical results for the evolution of the entanglement. It is revealed that, by manipulating the detunings of classical field, the long-living stationary entanglement between two atoms can be generated in the presence of dissipation

quant-ph↗

arXiv2017

Better Algorithms for Hybrid Circuit and Packet Switching in Data Centers

Hybrid circuit and packet switching for data center networking (DCN) has received considerable research attention recently. A hybrid-switched DCN employs a much faster circuit switch that is reconfigurable with a nontrivial cost, and a much slower packet switch that is reconfigurable with no cost, to interconnect its racks of servers. The research problem is, given a traffic demand matrix (between the racks), how to compute a good circuit switch configuration schedule so that the vast majority of the traffic demand is removed by the circuit switch, leaving a remaining demand matrix that contains only small elements for the packet switch to handle. In this paper, we propose two new hybrid switch scheduling algorithms under two different scheduling constraints. Our first algorithm, called 2-hop Eclipse, strikes a much better tradeoff between the resulting performance (of the hybrid switch) and the computational complexity (of the algorithm) than the state of the art solution Eclipse/Eclipse++. Our second algorithm, called BFF (best first fit), is the first hybrid switching solution that exploits the potential partial reconfiguration capability of the circuit switch for performance gains.

cs.NI↗

arXiv2017

Process-oriented Iterative Multiple Alignment for Medical Process Mining

Adapted from biological sequence alignment, trace alignment is a process mining technique used to visualize and analyze workflow data. Any analysis done with this method, however, is affected by the alignment quality. The best existing trace alignment techniques use progressive guide-trees to heuristically approximate the optimal alignment in O(N2L2) time. These algorithms are heavily dependent on the selected guide-tree metric, often return sum-of-pairs-score-reducing errors that interfere with interpretation, and are computationally intensive for large datasets. To alleviate these issues, we propose process-oriented iterative multiple alignment (PIMA), which contains specialized optimizations to better handle workflow data. We demonstrate that PIMA is a flexible framework capable of achieving better sum-of-pairs score than existing trace alignment algorithms in only O(NL2) time. We applied PIMA to analyzing medical workflow data, showing how iterative alignment can better represent the data and facilitate the extraction of insights from data visualization.

cs.DS↗

arXiv2017

Evaluation of Trace Alignment Quality and its Application in Medical Process Mining

Trace alignment algorithms have been used in process mining for discovering the consensus treatment procedures and process deviations. Different alignment algorithms, however, may produce very different results. No widely-adopted method exists for evaluating the results of trace alignment. Existing reference-free evaluation methods cannot adequately and comprehensively assess the alignment quality. We analyzed and compared the existing evaluation methods, identifying their limitations, and introduced improvements in two reference-free evaluation methods. Our approach assesses the alignment result globally instead of locally, and therefore helps the algorithm to optimize overall alignment quality. We also introduced a novel metric to measure the alignment complexity, which can be used as a constraint on alignment algorithm optimization. We tested our evaluation methods on a trauma resuscitation dataset and provided the medical explanation of the activities and patterns identified as deviations using our proposed evaluation methods.

cs.OH↗

arXiv2017

Magnetic criticality-enhanced hybrid nanodiamond-thermometer under ambient conditions

Nitrogen vacancy (NV) centres in diamond are attractive as quantum sensors owing to their superb coherence under ambient conditions. However, the NV centre spin resonances are relatively insensitive to some important parameters such as temperature. Here we design and experimentally demonstrate a hybrid nano-thermometer composed of NV centres and a magnetic nanoparticle (MNP), in which the temperature sensitivity is enhanced by the critical magnetization of the MNP near the ferromagnetic-paramagnetic transition temperature. The temperature susceptibility of the NV center spin resonance reached 14 MHz/K, enhanced from the value without the MNP by two orders of magnitude. The sensitivity of a hybrid nano-thermometer composed of a Cu_{1-x}Ni_{x} MNP and a nanodiamond was measured to be 11 mK/Hz^{1/2} under ambient conditions. With such high-sensitivity, we monitored nanometer-scale temperature variation of 0.3 degree with a time resolution of 60 msec. This hybrid nano-thermometer provides a novel approach to studying a broad range of thermal processes at nanoscales such as nano-plasmonics, sub-cellular heat-stimulated processes, thermodynamics of nanostructures, and thermal remanent magnetization of nanoparticles.

quant-ph↗

arXiv2017

Optical and spin properties of a single praseodymium ion in a crystal

The investigation of single atoms in solids, with both optical and nuclear spin access is of particularly interest with applications ranging from nanoscale sensing to quantum computation. Here, we study the optical and spin properties of single praseodymium ions in an yttrium aluminum garnet (YAG) crystal at cryogenic temperature. The single nuclear spin of single praseodymium ions is detected through a background-free optical upconverting readout technique. Single ions show stable photoluminescence (PLE) with spectrally resolved hyperfine splitting of the praseodymium ground state. Based on this measurement, optical Rabi and optically detected magnetic resonance (ODMR) measurements are performed to study the spin coherence properties. Our results reveal that the spin coherence time of single praseodymium nuclear spins is limited by the strong spin-phonon coupling at experimental temperature.

physics.optics↗

arXiv2017

A phenomenological thermodynamic potential for DyCo$_2$

A phenomenological thermodynamic potential was constructed based on the symmetry analysis and property characterization of bulk DyCo2. An eight-order polynomial of Landau expansion was employed to describe the thermodynamic behavior of DyCo2. Several properties were reproduced including ferromagnetic transition temperature, magnetization curve, temperature dependence of magnetization. The transition behavior was analyzed via the thermodynamic potential. The Landau phenomenological thermodynamic model predicts the correct metamagnetic transition near the Curie temperature.

cond-mat.mtrl-sci↗

arXiv2017

On Kernel of the regulator map

By using the infinitesimal methods due to Bloch, Green and Griffiths, we construct an infinitesimal form of the regulator map and verify that its kernel is $Ω^{1}_{\mathbb{C}/\mathbb{Q}}$, which suggests Question 1.1 seems reasonable at the infinitesimal level.

math.AG↗

arXiv2016

Enhanced valley splitting in monolayer WSe2 due to magnetic exchange field

Exploiting the valley degree of freedom to store and manipulate information provides a novel paradigm for future electronics. A monolayer transition metal dichalcogenide (TMDC) with broken inversion symmetry possesses two degenerate yet inequivalent valleys, offering unique opportunities for valley control through helicity of light. Lifting the valley degeneracy by Zeeman splitting has been demonstrated recently, which may enable valley control by a magnetic field. However, the realized valley splitting is modest, (~ 0.2 meV/T). Here we show greatly enhanced valley spitting in monolayer WSe2, utilizing the interfacial magnetic exchange field (MEF) from a ferromagnetic EuS substrate. A valley splitting of 2.5 meV is demonstrated at 1 T by magneto-reflectance measurements. Moreover, the splitting follows the magnetization of EuS, a hallmark of the MEF. Utilizing MEF of a magnetic insulator can induce magnetic order, and valley and spin polarization in TMDCs, which may enable valleytronic and quantum computing applications.

cond-mat.mes-hall↗