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Search Results: 1 - 10 of 29258 matches for " Bo Yao "
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Essential Oil Composition of Artemisia scoparia Waldst. & Kitag from Qinghai-Tibetan Plateau of China  [PDF]
Lihong Yao, Haibo Bo
Journal of Analytical Sciences, Methods and Instrumentation (JASMI) , 2016, DOI: 10.4236/jasmi.2016.61001
Abstract: The oils extracted by hydro distillation from the aerial parts of Artemisia scoparia waldst. & kitag growing wild in two regions on Qinghai-Tibetan Plateau were analyzed by GC-MS. Eighty-three components were identified representing 97.5% of the total components detected. The major constituents of the oil from the samples obtained in the eastern of Riyue Mountain (2700 - 3200 m) were 2-ethenyl-naphthalene (45.1%), beta-pinene (11.2%), 3-carene (8.7%), 3,7-dimethyl-1,3,6- octatriene (7.9%), limonene (5.4%), alpha-pinene (3.5%) and beta-myrcene (2.0%). Whereas the oil from the plant collected in Qilian Mountain (3300 - 3500 m) was composed mainly of thujone (21.4%), 1,8-cineole (18.9%), camphor (9.1%), 4-methyl-1-(1-methyl ethyl)-3-cyclo hexen-1-ol (7.8%), 4-methyl-1-(1-methylethyl)-bicyclo[3.1.0]hexan-3-one (5.3%) and 2-isopropyl-5-methyl- 3-cyclohexen-1-one(5.0%).
Large-scale Surveillance System based on Hybrid Cooperative Multi-Camera Tracking  [PDF]
Xiao Yan, Dan Xu, Bo Yao
Open Journal of Applied Sciences (OJAppS) , 2013, DOI: 10.4236/ojapps.2013.31B016
Abstract: In this paper, we proposed an optimized real-time hybrid cooperative multi-camera tracking system for large-scale au-tomate surveillance based on embedded smart cameras including stationary cameras and moving pan/tilt/zoom (PTZ) cameras embedded with TI DSP TMS320DM6446 for intelligent visual analysis. Firstly, the overlapping areas and projection relations between adjacent cameras' field of view (FOV) is calculated. Based on the relations of FOV ob-tained and tracking information of each single camera, a homography based target handover procedure is done for long-term multi-camera tracking. After that, we fully implemented the tracking system on the embedded platform de-veloped by our group. Finally, to reduce the huge computational complexity, a novel hierarchical optimization method is proposed. Experimental results demonstrate the robustness and real-time efficiency in dynamic real-world environ-ments and the computational burden is significantly reduced by 98.84%. Our results demonstrate that our proposed sys-tem is capable of tracking targets effectively and achieve large-scale surveillance with clear detailed close-up visual features capturing and recording in dynamic real-life environments.
Recycling of Cobalt by Liquid Leaching from Waste 18650-Type Lithium-Ion Batteries  [PDF]
Liangmou Yu, Bo Shu, Shiwen Yao
Advances in Chemical Engineering and Science (ACES) , 2015, DOI: 10.4236/aces.2015.54043
Abstract: In this work, we recover cobalt from waste 18650-type lithiumion batteries by acid leaching. The cathode material is completely dissolved, after leaching waste batteries by using 10 mol/L industrial sulfuric acid at 70℃ for 1 h. The rate of cobalt leaching is nearly 100%. Removal of sodium carbonate, iron, aluminum and other impurities from the leaching solution was well performed by adjusting the pH to 2-3 with stirring vigorously. Finally, under the conditions of 55℃-60℃ of 240 A/m2 current density, electrodeposition current efficiency was 90.01%, the quality of the electrical output achieved cobalt 1A standard electrolytic cobalt, cobalt until greater than 90% yield. The process is easy and suitable for large-scale lithiumion batteries used in the recovery of valuable metals.
Analysis of Yellow Water in Liquor Fermentation with Sensor Array  [PDF]
Bo Chen, Yi Yao, Haijiao Luo
Journal of Sensor Technology (JST) , 2019, DOI: 10.4236/jst.2019.91001
Abstract: Yellow water is a by-product of liquor in the solid state fermentation process, and contains a large amount of nutrients, such as acids, esters, alcohols and aldehydes produced by fermentation. The components in the yellow water reflect the fermentation information to a certain extent, so the fermentation process can be monitored by detecting the yellow water component online. A sensor array detection device is designed for detecting yellow water. In addition, chemical titration is used to obtain data such as acidity, reducing sugar and starch of yellow water. Principal component analysis and discriminant function analysis were performed on the data; and a multivariate linear regression was used to establish a prediction model for the data. The results showed that the prediction bias for acidity and alcohol was small, 0.39 and 0.43, respectively.
Situated Learning of a Behavior-Based Mobile Robot Path Planner
Yao Shu,Zhang Bo
计算机科学技术学报 , 1995,
Abstract: In this paper,we propose a behavior-based path planner that can self-learn in an unknown environment.A situated learning algorithm is designed which allows the robot to learn to coordinate several concurrent behaviors and improve its performance by interacting with the environment.Behaviors are implemented using CMAC neural networks.A simulation environment is set up and some simulation experiments are carried out to rest our learning algorithm.
Design of Evaluation Index System of Brand Space Expansion Capacity Based on the Brand DNA
Bo ZHANG,Huili YAO
International Business and Management , 2011, DOI: 10.3968/j.ibm.1923842820110301.075
Abstract: The combination of ecology and brand management promotes the development of brand ecological management effectively. This study, from the perspective of biology DNA, analogy describes Brand DNA and builds the model of Brand DNA elements. Then, establish evaluation index of the brand space expansion capacity systematically from brand foundation developing capacity, brand operation management capacity, brand market control capacity, brand sustainable developing capacity and brand relationship management capacity, etc. It is aimed at providing decision-making basis for enterprise to execute brand space expansion strategy scientificly. Key words: Brand DNA; Brand space expansion; Evaluation index system
The Learning Convergence of CMAC in Cyclic Learning
Yao Shu,Zhang Bo,
Yao Shu
,Zhang Bo

计算机科学技术学报 , 1994,
Abstract: In this paper we discuss the learning convergence of the cerebellar model articulation controller (CMAC) in cyclic learning.We prove the following results.First,if the training samples are noiseless,the training algorithm converges if and only if the learning rate is chosen from (0,2).Second,when the training samples have noises,the learning algorithm will converge with a probability of one if the learning rate is dynamically decreased.Third,in the case with noises,with a small but fixed learning rate ε the mean square error of the weight sequences generated by the CMAC learning algorithm will be bounded by O(ε).Some simulation experiments are carried out to test these results.
What geometrical factors determine the in situ solar wind speed?
Bo Li,Yao Chen,LiDong Xia
Chinese Science Bulletin , 2012, DOI: 10.1007/s11434-011-4965-2
Abstract: At present it remains to address why the fast solar wind is fast and the slow wind is slow. Recently we have shown that the field line curvature may substantially influence the wind speed ν, thereby offering an explanation for the Arge et al. finding that ν depends on more than just the flow tube expansion factor. Here we show by extensive numerical examples that the correlation between ν and field line curvature is valid for rather general base boundary conditions and for rather general heating functions. Furthermore, the effect of field line curvature is even more pronounced when the proton-alpha particle speed difference is examined. We suggest that any solar wind model has to take into account the field line shape for any quantitative analysis to be made.
Twenty-Year Reform of Teaching Biochemistry and Molecular Biology at Fourth Military Medical University in China  [PDF]
Jing Zhao, Yan Li, Bo Yan, Lintao Jia, Xia Li, Lifeng Wang, Xinping Liu, Libo Yao
Open Journal of Social Sciences (JSS) , 2014, DOI: 10.4236/jss.2014.24029
Abstract: Higher medical education in China is dually challenged by inadequate understanding of career motivation among high school graduates and by insufficient self-directed learning capability as a result of long-term exam-based education. Biochemistry and Molecular Biology is one of the most essential basic courses at Fourth Military Medical University (FMMU), but students usually feel torn to deal with it. We have been making efforts to improve teaching efficiency for over twenty years. Our teaching reform involves design of students-centered experimental course, reorganization of theoretical course and attempt to evoke critical thinking in class. A few tips are shared with regards to how to make the course of Biochemistry and Molecular Biology more rewarding.
EigenGP: Sparse Gaussian process models with data-dependent eigenfunctions
Yuan Qi,Bo Dai,Yao Zhu
Computer Science , 2012,
Abstract: Gaussian processes (GPs) provide a nonparametric representation of functions. However, classical GP inference suffers from high computational cost and it is difficult to design nonstationary GP priors in practice. In this paper, we propose a sparse Gaussian process model, EigenGP, based on the Karhunen-Loeve (KL) expansion of a GP prior. We use the Nystrom approximation to obtain data dependent eigenfunctions and select these eigenfunctions by evidence maximization. This selection reduces the number of eigenfunctions in our model and provides a nonstationary covariance function. To handle nonlinear likelihoods, we develop an efficient expectation propagation (EP) inference algorithm, and couple it with expectation maximization for eigenfunction selection. Because the eigenfunctions of a Gaussian kernel are associated with clusters of samples - including both the labeled and unlabeled - selecting relevant eigenfunctions enables EigenGP to conduct semi-supervised learning. Our experimental results demonstrate improved predictive performance of EigenGP over alternative state-of-the-art sparse GP and semisupervised learning methods for regression, classification, and semisupervised classification.
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