|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Characteristics of carbonaceous aerosols in Beijing, China显示文摘 | Fengkui Duan Kebin He Yongliang Ma Yingtao Jia Fumo Yang Yu Lei S. Tanaka T. Okuta | 2005 | Chemosphere2005，，3： | 3 |
| 2 | A modified image matching algorithm based on robust Hausdorff distance显示文摘Hausdorff distance measure is one of the widely adopted feature-based image matching algorithms due to its simplicity and accuracy.However,it is considered that its robustness still needs to be improved.In this paper,various forms of original and improved Hausdorff distance(HD) and their limitations are studied.Focusing on robust Hausdorff distance(RHD),an improved RHD with an adaptive outlier point threshold selection method is proposed.Furthermore,another new form of the Hausdorff distance which possesses the merits of RHD and M-HD is prsented.Finally,a recursive algorithm is introduced to accelerate the image matching speed of Hausdorff algorithms.Extensive simulation and experiment results are presented to validate the feasibility of the proposed Hausdorff distance algorithm. | 吴强 Wu Xuefeng Li Xuwen Jia Kebin | 2014 | High Technology Letters2014，20，1： | 3 |
| 3 | A generative model of identifying informative proteins from dynamic PPI networks显示文摘Informative proteins are the proteins that play critical functional roles inside cells.They are the fundamental knowledge of translating bioinformatics into clinical practices.Many methods of identifying informative biomarkers have been developed which are heuristic and arbitrary,without considering the dynamics characteristics of biological processes.In this paper,we present a generative model of identifying the informative proteins by systematically analyzing the topological variety of dynamic protein-protein interaction networks(PPINs).In this model,the common representation of multiple PPINs is learned using a deep feature generation model,based on which the original PPINs are rebuilt and the reconstruction errors are analyzed to locate the informative proteins.Experiments were implemented on data of yeast cell cycles and different prostate cancer stages.We analyze the effectiveness of reconstruction by comparing different methods,and the ranking results of informative proteins were also compared with the results from the baseline methods.Our method is able to reveal the critical members in the dynamic progresses which can be further studied to testify the possibilities for biomarker research. | ZHANG Yuan CHENG Yue JIA KeBin ZHANG AiDong | 2014 | Science China(Life Sciences)2014，57，11： | 2 |
| 4 | Co-regulated Protein Functional Modules with Varying Activities in Dynamic PPI Networks显示文摘Current methods for the detection of differential gene expression focus on finding individual genes that may be responsible for certain diseases or external irritants. However, for common genetic diseases, multiple genes and their interactions should be understood and treated together during the exploration of disease causes and possible drug design. The present study focuses on analyzing the dynamic patterns of co-regulated modules during biological progression and determining those having remarkably varying activities, using the yeast cell cycle as a case study. We first constructed dynamic active protein-protein interaction networks by modeling the activity of proteins and assembling the dynamic co-regulation protein network at each time point. The dynamic active modules were detected using a method based on the Bayesian graphical model and then the modules with the most varied dispersion of clustering coefficients, which could be responsible for the dynamic mechanism of the cell cycle, were identified. Comparison of results from our functional module detection with the state-of-art functional module detection methods and validation of the ranking of activities of functional modules using GO annotations demonstrate the efficacy of our method for narrowing the scope of possible essential responding modules that could provide multiple targets for biologists to further experimentally validate. | Yuan Zhang Nan Du Kang L Kebin Jia Aidong Zhang | 2013 | Tsinghua Science and Technology2013，18，5： | 2 |
| 5 | A fast stereoscopic video coding algorithm based on JMVM显示文摘In order to exploit the intra-view and inter-view dependencies in stereo video coding, a fast joint motion and disparity estimation algorithm is proposed in this paper. An efficient search strategy based on the motion-disparity constraint is developed, in which both the motion and disparity vectors can be obtained simultaneously with low complexity. Moreover, a credible initial predictive vector set is designed with the aid of the temporal and spatial neighboring blocks so that the coding efficiency can be further enhanced. The experimental results demonstrate that the proposed algorithm can reduce more than 96% coding time compared with the JMVM full search with a negligible quality drop. | DENG ZhiPin JIA KeBin CHAN YuiLam FU ChangHong & SIU WanChi | 2011 | Science China(Information Sciences)2011，54，6： | 2 |
| 6 | Identification of Weather Phenomena Based on Lightweight Convolutional Neural Networks显示文摘Weather phenomenon recognition plays an important role in the field of meteorology.Nowadays,weather radars and weathers sensor have been widely used for weather recognition.However,given the high cost in deploying and maintaining the devices,it is difficult to apply them to intensive weather phenomenon recognition.Moreover,advanced machine learning models such as Convolutional Neural Networks(CNNs)have shown a lot of promise in meteorology,but these models also require intensive computation and large memory,which make it difficult to use them in reality.In practice,lightweight models are often used to solve such problems.However,lightweight models often result in significant performance losses.To this end,after taking a deep dive into a large number of lightweight models and summarizing their shortcomings,we propose a novel lightweight CNNs model which is constructed based on new building blocks.The experimental results show that the model proposed in this paper has comparable performance with the mainstream non-lightweight model while also saving 25 times of memory consumption.Such memory reduction is even better than that of existing lightweight models. | Congcong Wang Pengyu Liu Kebin Jia Xiaowei Jia Yaoyao Li | 2020 | Computers, Materials & Continua2020，，9： | 2 |
| 7 | A New Image Mosaics Algo- rithm Based on Feature Points Matching显示文摘 | Gao Guandong Jia Kebin | 2007 | The Second In- ternational Conference on Innovative Computing Informa- tion and Control (ICICIC2007)2007，，： | 1 |
| 8 | Holographic storage scheme based on digital signal processing 显示文摘 | Kebin Jia Dapeng Yang Shubo Dun | 2003 | Chin Opt Lett2003，1，10： | 1 |
| 9 | Fast motion and disparity estimation with adaptive search range adjustment in stereoscopic video coding显示文摘 | DENG Zhipin CHAN Yuilam JIA Kebin | 2012 | IEEE Transactions on Broadcasting2012，58，1： | 1 |
| 10 | Trends in hazardous trace metal concentrations in aerosols collected in Beijing, China from 2001 to 2006显示文摘 | Tomoaki Okuda Masayuki Katsuno Daisuke Naoi Shunsuke Nakao Shigeru Tanaka Kebin He Yongliang Ma Yu Lei Yingtao Jia | 2008 | Chemosphere2008，，6： | 1 |
| 11 | Characteristics of carbonaceous aerosols in Beijing, China显示文摘 | Fengkui Duan Kebin He Yongliang Ma Yingtao Jia Fumo Yang Yu Lei S. Tanaka T. Okuta | 2005 | Chemosphere2005，，3： | 1 |
| 12 | An adaptive motion esti- mation scheme for video coding 显示文摘 | Liu Pengyu Gao Yuan Jia Kebin | 2014 | The Scientific World Jour- nal2014，，38： | 1 |
| 13 | Opportunities for Computational Techniques for Multi-Omics Integrated Personalized Medicine显示文摘Personalized medicine is defined as 'a model of healthcare that is predictive, personalized, preventive,and participator' and has very broad content. With the rapid development of high-throughput technologies, an explosive accumulation of biological information is collected from multiple layers of biological processes, including genomics, transcriptomics, proteomics, metabonomics, and interactomics(omics). Implementing integrative analysis of these multiple omics data is the best way of deriving systematical and comprehensive views of living organisms, achieving better understanding of disease mechanisms, and finding operable personalized health treatments. With the help of computational methods, research in the field of biology and biomedicine has gained tremendous benefits over the past few decades. In the new era of personalized medicine, we will rely more on the assistance of computational analysis. In this paper, we briefly review the generation of multiple omics and their basic characteristics. And then the challenges and opportunities for computational analysis are discussed and some state-of-art analysis methods that were recently proposed by peers for integrative analysis of multiple omics data are reviewed. We foresee that further integrated omics data platform and computational tools would help to translate the biological knowledge to clinical usage and accelerate development of personalized medicine. | Yuan Zhang Yue Cheng Kebin Jia Aidong Zhang | 2014 | Tsinghua Science and Technology2014，19，6： | 0 |
| 14 | Detour-phased perovskite ultrathin planar lens using direct femtosecond laser writing显示文摘Perovskite-enabled optical devices have drawn intensive interest and have been considered promising candidates for integrated optoelectronic systems.As one of the important photonic functions,optical phase modulation previously was demonstrated with perovskite substrate and complex refractive index engineering with laser scribing.Here we report on the new scheme of achieving efficient phase modulation by combining detour phase design with 40 nm ultrathin perovskite films composed of nanosized crystalline particles.Phase modulation was realized by binary amplitude patterning,which significantly simplifies the fabrication process.Perovskite nanocrystal films exhibit significantly weak ion migration effects under femtosecond laser writing,resulting in smooth edges along the laser ablated area and high diffractive optical quality.Fabrication of a detour-phased perovskite ultrathin planar lens with a diameter of 150μm using femtosecond laser scribing was experimentally demonstrated.A high-performance 3D focus was observed,and the fabrication showed a high tolerance with different laser writing powers.Furthermore,the high-quality imaging capability of perovskite ultrathin planar lenses with a suppressed background was also demonstrated. | WENKAI YANG LIGE LIU DASHAN DONG XIN ZHANG HAN LIN YUNKUN WANG HONG YANG YUNAN GAO HAIZHENG ZHONG BAOHUA JIA KEBIN SHI | 2022 | Photonics Research2022，10，12： | 0 |
| 15 | A new projection model based robust 2D-3D registration method on Fourier-Mellin space for image guided intervention显示文摘An automatic method is proposed to solve the registration problem,which aligns a single 2D fluoroscopic image to a 3D image volume without demanding any additional media like calibration plate or user interactions.First,a mathematic projection model is designed which can reduce the influence of projection distortion on parameter optimization and improve the registration accuracy.Then,a two stage optimization method is proposed,which enables a robust registration in a wide parameter space.Furthermore,an automatic registration framework is proposed based on the FourierMellin robust image comparison descriptor.Experimental results show that the registration method has a high accuracy with average rotation error of 0.6 degree and average translation error of 1.4mm. | 魏嵬 Jia Kebin | 2013 | High Technology Letters2013，19，4： | 0 |
| 16 | Adverse Effects and Intervention of Frailty on Elderly Cancer Patients显示文摘Purpose:To study the adverse effects of frailty on elderly cancer patients and explore effective interventions.Methods:The convenience sampling method was used to select 362 elderly cancer patients who were consecutively admitted to the Oncology Department of the Affiliated Hospital of Hebei University from April 2020 to March 2021.The patients had five physical dimensions of activity tested and were divided into a frail group(n=128)and a non-frail group(n=234)based on the test results.The Chinese version of the Vulnerable Elders Questionnaire was formed on the basis of the Vulnerable Elders Survey-13(VES-13).The two groups of patients were surveyed within three days of admission.The questionnaire includes general information(age,gender,education level,marital status,monthly income,living area,smoking,and alcohol history,hearing,vision,and sleep status),Geriatric Depression Scale(GDS),Mini Nutritional Assessment(MNA),Mini-Mental State Examination(MMSE),and Charlson Comorbidity Index(CCI).Results:(1)By comparing the general information of the two groups of patients,it was found that the gender,education level,marital status,living area,and history of tobacco and alcohol had no statistical significance(P>0.05).In contrast,the frail group’s age,hearing status,vision status,and sleep status are significantly worse than those of the non-frail group(P<0.05);(2)Analysis of Vulnerable Elderly Questionnaire results found that the GDS scores in the frail group were higher than those in the non-frail group,and the MNA and MMSE scores were lower than those in the non-frail group(P<0.05).This indicated that the patients in the frail group had more severe depression,poor nutritional status,and specific impairments in cognitive function.Conclusion:Frailty adversely affects elderly cancer patients,and effective measures should be taken to intervene. | Tingting Li Jia Feng Qian Sun Yanhong Shang Youchao Jia Kebin Zheng Ce Wang Jing Li Yanling Li | 2023 | Proceedings of Anticancer Research2023，7，5： | 0 |
| 17 | An Effective CU Depth Decision Method for HEVC Using Machine Learning显示文摘This paper presents an effective machine learning-based depth selection algorithm for CTU(Coding Tree Unit)in HEVC(High Efficiency Video Coding).Existing machine learning methods are limited in their ability in handling the initial depth decision of CU(Coding Unit)and selecting the proper set of input features for the depth selection model.In this paper,we first propose a new classification approach for the initial division depth prediction.In particular,we study the correlation of the texture complexity,QPs(quantization parameters)and the depth decision of the CUs to forecast the original partition depth of the current CUs.Secondly,we further aim to determine the input features of the classifier by analysing the correlation between depth decision of the CUs,picture distortion and the bit-rate.Using the found relationships,we also study a decision method for the end partition depth of the current CUs using bit-rate and picture distortion as input.Finally,we formulate the depth division of the CUs as a binary classification problem and use the nearest neighbor classifier to conduct classification.Our proposed method can significantly improve the efficiency of interframe coding by circumventing the traversing cost of the division depth.It shows that the mentioned method can reduce the time spent by 34.56%compared to HM-16.9 while keeping the partition depth of the CUs correct. | Xuan Sun Pengyu Liu Xiaowei Jia Kebin Jia Shanji Chen Yueying Wu | 2021 | Computer Systems Science & Engineering2021，39，11： | 0 |
| 18 | Impolite Pedestrian Detection by Using Enhanced YOLOv3-Tiny显示文摘In recent years,the problem of“Impolite Pedestrian”in front of the zebra crossing has aroused widespread concern from all walks of life.The traffic sector’s governance measures have become more serious.The traditional way of governance is on-site law enforcement,which requires a lot of manpower and material resources and is low efficiency.An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring.By modifying the backbone network structure of YOLOv3-tiny model,introducing deep detachable convolution operation,and designing the basic residual block unit of the network,the feature extraction ability of the backbone network is enhanced.The improved model is trained on the VOC2007+VOC2012 training set,and the trained model is tested for performance on the test data set.The experimental results show that:the mean Average Precision(mAP)increased from 0.672 to 0.732,increasing the measurement accuracy by 9%.The Intersection over Union(IoU)increased from 0.783 to 0.855,increasing the coverage accuracy by 7.2%.The enhanced YOLOv3-tiny model has higher measurement accuracy than the original model.Applying this model to the 1080P traffic video on the NVIDIA RTX 2080,the detection speed is 150 FPS,which can fully achieve real-time detection.Through the analysis of pedestrians and vehicle coordinates,it is judged whether or not illegal acts occur.For illegal vehicles,save three pictures as the basis for law enforcement,which forms an important supplement to off-site law enforcement. | Yanming Wang Kebin Jia Pengyu Liu | 2020 | Journal on Artificial Intelligence2020，2，3： | 0 |
| 19 | Nonlinear Correction of Pressure Sensor Based on Depth Neural Network显示文摘With the global climate change,the high-altitude detection is more and more important in the climate prediction,and the input-output characteristic curve of the air pressure sensor is offset due to the interference of the tested object and the environment under test,and the nonlinear error is generated.Aiming at the difficulty of nonlinear correction of pressure sensor and the low accuracy of correction results,depth neural network model was established based on wavelet function,and Levenberg-Marquardt algorithm is used to update network parameters to realize the nonlinear correction of pressure sensor.The experimental results show that compared with the traditional neural network model,the improved depth neural network not only accelerates the convergence rate,but also improves the correction accuracy,meets the error requirements of upper-air detection,and has a good generalization ability,which can be extended to the nonlinear correction of similar sensors. | Yanming Wang Kebin Jia Pengyu Liu | 2020 | Journal on Internet of Things2020，2，3： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员