A5100778698- Sparse and Compressive Sensing Techniques
- Advanced Radiotherapy Techniques
- Medical Imaging Techniques and Applications
- Transportation Planning and Optimization
- Traffic control and management
- Radiation Therapy and Dosimetry
- Statistical Methods and Inference
- Optimization and Variational Analysis
- Machine Learning and Algorithms
- Advanced Optimization Algorithms Research
- Stochastic Gradient Optimization Techniques
- Urban Heat Island Mitigation
- Risk and Portfolio Optimization
- Building Energy and Comfort Optimization
- Infrared Target Detection Methodologies
- Outsourcing and Supply Chain Management
- Advanced Chemical Sensor Technologies
- Control Systems and Identification
- Advanced Memory and Neural Computing
- Nuclear Physics and Applications
- Efficiency Analysis Using DEA
- Wind and Air Flow Studies
- Assembly Line Balancing Optimization
- Scheduling and Optimization Algorithms
- Nuclear reactor physics and engineering
Hunan University
2010-2024
University of Florida
2017-2024
First Automotive Works (China)
2022
Beijing Research Institute of Uranium Geology
2013-2021
Northeast Petroleum University
2020
Yunnan Academy of Agricultural Sciences
2011-2019
Ministry of Agriculture and Rural Affairs
2019
Stanford University
2016-2018
Pennsylvania State University
2012-2017
I-Shou University
2013-2017
Immunocyte infiltration and cytotoxicity play critical roles in both inflammation immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of T cells to penetrate tumor stroma, thereby significantly limiting development effective treatments for solid tumors. Here, we present an automated high-throughput microfluidic platform simultaneous tracking dynamics cell within 3D cultures with a tunable stromal makeup. By recourse clinical tumor-infiltrating...
Abstract Brain-inspired hardware emulates the structure and working principles of a biological brain may address bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic function AI computing. Here, we develop Brainoware , living that harnesses computation 3D neural networks in organoid. Brain-like vitro cultures compute by receiving sending information via multielectrode array. Applying...
The precise transportation of small-volume liquids in microfluidic and nanofluidic systems remains a challenge for many applications, such as clinical fluidical analysis. Here, we present reliable digital pump that utilizes acoustic streaming induced by localized fluid–substrate interactions. By locally generating via C-shaped interdigital transducer (IDT) within triangle-edged microchannel, our acoustofluidic can generate stable unidirectional flow (∼nanoliter per second rate) with...
Purpose Current treatment planning remains a costly and labor intensive procedure requires multiple trial‐and‐error adjustments of system parameters such as the weighting factors prescriptions. The purpose this work is to develop an autonomous strategy with effective use prior knowledge in clinically realistic platform facilitate radiation therapy workflow. Method Our technique consists three major components: (i) clinical ( TPS ); (ii) formulation decision‐function constructed using...
One important indicator of traffic network resilience is rapidity, which measures the speed at a system returns to its normal state after disruption. In this paper, we propose day-to-day tolling scheme increase rapidity road systems disturbances caused by natural or man-made events such as accidents, flooding, earthquake, and infrastructure damage. The theory projected dynamical applied model transient behaviour when faced with disruptions. We further provide three computationally tractable...
Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 16 July 2020Accepted: 13 2021Published online: 21 October 2021Keywordsimage reconstruction, nonconvex nonsmooth optimization, learnable optimization algorithm, deep learningAMS Subject Headings90C26, 65K05, 65K10, 68U10Publication DataISSN (online): 1936-4954Publisher: Society for Industrial and Applied MathematicsCODEN: sjisbi
A distributed permutation flow shop scheduling problem (DPFSP) is an NP-hard recently put forward in sphere. Exact algorithms for a DPFSP's solution can be extremely computationally costly. This paper proposes to apply electromagnetism-like mechanism (EM) algorithm as heuristic method DPFSP. To fit into the discrete domain of DPFSP, modifications original EM algorithm, including redefinition distance and movement charge force calculation, have been made, improve performance proposed VNS...
This paper is concerned with solving nonconvex learning problems folded concave penalty. Despite that their global solutions entail desirable statistical properties, they lack optimization techniques guarantee optimality in a general setting. In this paper, we show class of are equivalent to quadratic programs. equivalence facilitates us developing mixed integer linear programming reformulations, which admit finite algorithms find provably optimal solution. We refer reformulation-based...
On the basis of spectral shape thermal infrared (TIR) emissivity for sandy land, a remote sensing sand index called differential (SDEI) is proposed in this article to simply and conveniently detect land over large areas. The SDEI evaluated on ground, airborne, spaceborne data, it shows good characterization performs better identification than two previous indices. was also transition zones China's four mega-sandy lands applied long-term surface obtain spatial distribution variation from 2000...
Thermal infrared remote sensing can acquire large-scale land surface thermal radiance effectively. However, the observed data are affected by and atmospheric conditions. Traditional methods require some prior knowledge, such as emissivity in split-window algorithm correction temperature–emissivity separation algorithm. This information is difficult to obtain directly accurately. Hyperspectral provide possibility for simultaneous retrieval of parameters, temperature (LST), because their...
In recent years, high-dimensional data, such as waveform signals and images have become ubiquitous. This type of data is often represented by multiway arrays or tensors. Several statistical models, including tensor regression, been developed for data. However, these models are sensitive to the presence arbitrary outliers within To address issue, this article proposes a Robust Tensor-On-Tensor (RTOT) regression approach, which has capability modeling when corrupted outliers. Through several...
Occupant behavior has an important impact on building energy consumption, and the accuracy of occupant model directly affects reliability consumption simulation results. Ultra-low buildings are crucial to achieving conservation carbon dioxide reduction in China. In order effectively promote development ultra-low Hot Summer Cold Winter Climate Zones. where most residents adopt a “part-time, part-space” pattern intermittent use behavior, solve problem poor indoor thermal environments high...
This paper proposes a dynamic congestion pricing model that takes into account mobile source emissions. We consider tollable vehicular network where the users selfishly minimize their own travel costs, including time, early/late arrival penalties and tolls. On top of that, we assume part can be tolled by central authority, whose objective is to both total costs road emission on network-wide level. The formulated as mathematical programming with equilibrium constraints (MPEC) problem then...
An important yet challenging problem in LINAC-based rotational arc radiation therapy is the design of beam trajectory, which requires simultaneous consideration delivery efficiency and final dose distribution. In this work, we propose a novel trajectory selection strategy by developing Monte Carlo tree search (MCTS) algorithm during process. To through vast number possible trajectories, MCTS was implemented. approach, candidate explored starting from leaf node sequentially examining next...