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Analyzing Cross-domain Transportation Big Data of New York City with Semi-supervised and Active Learning

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Computers, Materials & Continua 2018年第10期57卷 1-9页

作者： Huiyu Sun suzanne.McIntosh Computer Science Department New York UniversityNew YorkNY 10012USA

The majority of big data analytics applied to transportation datasets suffer from being too domain-specific,that is,they draw conclusions for a dataset based on analytics on the same *** makes models trained from one domain(*** data)applies badly to a different domain(*** data).To achieve accurate analyses on a new domain,substantial amounts of data must be available,which limits practical *** remedy this,we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task:Selectively choosing a small amount of datapoints from a new domain while achieving comparable performances to using all the *** choose the New York City(NYC)transportation data of taxi and Uber as our dataset,simulating different domains with 90%as the source data domain for training and the remaining 10%as the target data domain for *** propose semi-supervised and active learning strategies and apply it to the source domain for selecting *** results show that our adaptation achieves a comparable performance of using all datapoints while using only a fraction of them,substantially reducing the amount of data *** approach has two major advantages:It can make accurate analytics and predictions when big datasets are not available,and even if big datasets are available,our approach chooses the most informative datapoints out of the dataset,making the process much more efficient without having to process huge amounts of data.

关键词： Big data taxi and uber domain adaptation active learning semi-supervised learning

Bayesian partial pooling to reduce uncertainty in overcoring rock stress estimation

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第4期16卷 1192-1201页

作者： Yu Feng Ke Gao suzanne.Lacasse Norwegian Geotechnical Institute OsloNorway Department of Earth and Space Sciences Southern University of Science and TechnologyShenzhenChina

The state of in situ stress is a crucial parameter in subsurface engineering,especially for critical projects like nuclear waste *** one of the two ISRM suggested methods,the overcoring(OC)method is widely used to estimate the full stress tensors in rocks by independent regression analysis of the data from each OC ***,such customary independent analysis of individual OC tests,known as no pooling,is liable to yield unreliable test-specific stress estimates due to various uncertainty sources involved in the OC *** address this problem,a practical and no-cost solution is considered by incorporating into OC data analysis additional information implied within adjacent OC tests,which are usually available in OC measurement ***,this paper presents a Bayesian partial pooling(hierarchical)model for combined analysis of adjacent OC *** performed five case studies using OC test data made at a nuclear waste repository research site of *** results demonstrate that partial pooling of adjacent OC tests indeed allows borrowing of information across adjacent tests,and yields improved stress tensor estimates with reduced uncertainties simultaneously for all individual tests than they are independently analysed as no pooling,particularly for those unreliable no pooling stress estimates.A further model comparison shows that the partial pooling model also gives better predictive performance,and thus confirms that the information borrowed across adjacent OC tests is relevant and effective.

关键词： Overcoring stress measurement Uncertainty reduction Partial pooling Bayesian hierarchical model Nuclear waste repository

Identifying Materials of Photographic Images and Photorealistic Computer Generated Graphics Based on Deep CNNs

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Computers, Materials & Continua 2018年第5期55卷 229-241页

作者： Qi Cui suzanne.McIntosh Huiyu Sun School of Computer and Software Nanjing University of Information Science and TechnologyNing Liu RoadNo.219Nanjing210044China Jiangsu Engineering Centre of Network Monitoring Ning Liu RoadNo.219Nanjing210044China Computer Science Department New York UniversityNew YorkNY 10012USA

Currently,some photorealistic computer graphics are very similar to photographic *** computer generated graphics can be forged as photographic images,causing serious security *** aim of this work is to use a deep neural network to detect photographic images(PI)versus computer generated graphics(CG).In existing approaches,image feature classification is computationally intensive and fails to achieve realtime *** paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks(DCNNs).Compared with some existing methods,the proposed method achieves real-time forensic tasks by deepening the network *** results show that this approach can effectively identify PI and CG with average detection accuracy of 98%.

关键词： Image identification CNN DNN DCNNs computer generated graphics

p53:a tumor suppressor hiding in plain sight

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Journal of Molecular Cell Biology 2019年第7期11卷 536-538页

作者： suzanne.J.Baker Bert Vogelstein St Jude Children's Research Hospital Department of Developmental Neurobiology262 Danny Thomas PlaceMemphisTN 38105USA Ludwig Center Howard Hughes Medical Institute Johns Hopkins Kimmel Cancer Center1650 Orleans Street StBaltimoreMD 21205USA

It is a pleasure to join the other authors in this issue to hon orDr Arnold Levi neand the remarkable impact of his *** paths crossed with Amie's when our genetic analyses of colorectal cancers led us to investigate the p53 gene and identify it as a tumor suppressor gene.p53 was initially identified by Arnie and others as an oncogene and tumor antigen,nearly a decade before its role as a tumor suppressor gene was *** fondly remember Arnie visiting our lab,and we visiting his,to discuss the implications of the genetic alterations our group identified in human cancers and how we could work together to investigate the voluminous new questions these mutations raised.

关键词： pleasure Arnold raised

Transcript profiling of a novel plant meristem,the monocot cambium

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Journal of Integrative Plant Biology 2017年第6期59卷 436-449页

作者： Matthew Zinkgraf suzanne.Gerttula Andrew Groover US Forest Service Pacific Southwest Research StationDavisCaliforniaUSA Department of Computer Science University of CaliforniaDavisUSA Department of Plant Biology University of CaliforniaDavisUSA

While monocots lack the ability to produce a vascular cambium or woody growth, some monocot lineages evolved a novel lateral meristem, the monocot cambium, which supports secondary radial growth of stems. In contrast to the vascular cambium found in woody angiosperm and gymnosperm species, the monocot cambium produces secondary vascular bundles, which have an amphivasal organization of tracheids encircling a central strand of phloem. Currently there is no information concerning the molecular genetic basis of the develop- ment or evolution of the monocot cambium. Here we report high-quality transcriptomes for monocot cambium and early derivative tissues in two monocot genera, Yucca and Cordyline. Monocot cambium transcript profiles were compared to those of vascular cambia and secondary xylem tissues of two forest tree species, Populus trichocarpa and Eucalyptus grandis. Monocot cambium transcript levels showed that there are extensive overlaps between the regulation of monocot cambia and vascular cambia. Candidate regulatory genes that vary between the monocot and vascular cambia were also identified, and included members of the KANADI and CLE families involved in polarity and cell-cell signaling, respectively. We suggest that the monocot cambium may have evolved in part through reactivation of genetic mechanisms involved in vascular cambium regulation.

关键词： Chun-Ming Liu, Institute of Crop Science, CAAS, ChinaReceived Feb. 18, 2017 Accepted Mar. 15, 2017 Online on Mar. 17,2017

Multiple stressors lead to complex responses in reproductive behaviors in an African cichlid

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CURRENT ZOOLOGY 2024年第6期70卷 821-832页

作者： Williams, Bethany Pintor, Lauren Gray, suzanne Univ Missouri Dept Biol 1 Univ Blvd St Louis MO 63121 USA

Exposure to multiple environmental stressors is a common occurrence that can affect organisms in predictable or unpredictable ways. Hypoxia and turbidity in aquatic environments are 2 stressors that can affect reproductive behaviors by altering energy availability and the visual environment, respectively. Here we examine the relative effects of population and the rearing environment (oxygen concentration and turbidity) on reproductive behaviors. We reared cichlid fish (the Egyptian mouthbrooder, Pseudocrenilabrus multicolor) from 2 populations (a swamp and river) until sexual maturity, in a full factorial design (hypoxic/normoxic x clear/turbid) and then quantified male competitive and courtship behaviors and female preference under their respective rearing conditions. Overall, we found that the rearing environment was more important than population for determining behavior, indicating there were few heritable differences in reproductive behavior between the 2 populations. Unexpectedly, males in the hypoxic rearing treatment performed more competitive and courtship behaviors. Under turbid conditions, males performed fewer competitive and courtship behaviors. We predicted that females would prefer males from their own population. However, under the hypoxic and turbid combination females from both populations preferred males from the other population. Our results suggest that reproductive behaviors are affected by interactions among male traits, female preferences, and environmental conditions.

关键词： cichlid competition hypoxia mate choice turbidity

Virtual ballistic impact testing of Kevlar soft armor:Predictive and validated finite element modeling of the V0-V100 probabilistic penetration response

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Defence Technology（防务技术） 2018年第3期14卷 213-225页

作者： Gaurav Nilakantan suzanne.Horner Virginia Halls James Zheng Teledyne Scientific&Imaging Thousand OaksCA 91360USA Program Executive Office Soldier Fort BelvoirVA 22060USA

This works presents the first fully validated and predictive capability to model the V_0-V_(100) probabilistic penetration response of a woven fabric using a yarn-level fabric finite element model. The V_0-V_(100) curve describes the probability of complete fabric penetration as a function of projectile impact velocity. The exemplar case considered in this paper comprises of a single-layer, fully-clamped, plain-weave Kevlar fabric impacted at the center by a 17-gr, 0.22 cal FSP or fragment-simulating projectile. Each warp and fill yarn in the fabric is individually modeled using 3 D finite elements and the virtual fabric microstructure is validated in detail against the experimental fabric microstructure. Material and testing sources of statistical variability including yarn strength and modulus, inter-yarn friction, precise projectile impact location, and projectile rotation are mapped into the finite element model. A series of impact simulations at varying projectile impact velocities is executed using LS-DYNA on the fabric models, with each model comprising unique mappings. The impact velocities together with the outcomes(penetration, nonpenetration) are used to generate the numerical V_0-V_(100) curve which is then validated against the experimental V_0-V_(100) curve. The numerical Vi-Vrdata(impact, residual velocities) is also validated against the experimental Vi-Vrdata. For completeness, this paper also reports the experimental characterization data and its statistical analysis used for model input, viz. the Kevlar yarn tensile strengths, moduli, and inter-yarn friction, and the experimental ballistic test data used for model validation.

关键词： Kevlar 有限元素测试数据验证概率预兆弹道虚拟