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| 1 | Separation-and-Recovery Technology for Organic Waste Liquid with a High Concentration of Inorganic Particles显示文摘 | Hualin Wang Pengbo Fu Jianping Li Yuan Huang Ying Zhao Lai Jiang Xiangchen Fang Tao Yang Zhaohui Huang Cheng Huang | 2018 | Engineering2018，4，3： | 3 |
| 2 | 3-41 Bio-audiovisual Feedback Breathing Guidance Technique for Synchrotron-based Ion Beam Delivery显示文摘Based on the periodic synchrotron-based beam delivery,a bio-audiovisual feedback breathing guidance technique has been developed to mitigate the interplay between target motion and dynamic beam delivery for ion beam therapy,in which variable beam extraction and generation of individualized breathing guidance curve are two key factors.Shown in Fig.1 is the schematic diagram of the breathing guidance technique.Through the simulations with 15 healthy volunteers for the breathing guidance technique,we found not only the treatment efficiency of synchrotron-based pulsed ion beam could be increased effectively,but also the residual movement of respiration during gating window could be reduced. | Li Qiang He Pengbo Liu Xinguo Dai Zhongying Ma Yuanyuan Shen Guosheng Yan Yuanlin Huang Qiyan Fu Tingyan | 2014 | IMP & HIRFL Annual Report2014，，1： | 0 |
| 3 | 3-44 Monte Carlo Simulation Study on Optimizing the Active Beam Delivery System at HIRFL显示文摘To obtain carbon ion beam suitable for the active spot scanning beam delivery system at the Heavy Ion ResearchFacility in Lanzhou (HIRFL), the Monte Carlo (MC) program SHIELD-HIT12A was used to study the influencesof beam delivery distance and structure period of mini ridge filter on full width at the half maximum (FWHM) ofbeam spot and dose flatness at the iso-center of the treatment room. | Yan Yuanlin Liu Xingguo Dai Zhongying Ma Yuanyuan Huang Qiyan He Pengbo Shen Guosheng Fu Tingyan Li Qiang | 2014 | IMP & HIRFL Annual Report2014，，1： | 0 |
| 4 | Decorative Wood Fiber/High-Density Polyethylene Composite with Canvas or Polyester Fabric显示文摘Wood-plastic composite is an environmentally friendly material,due to its use of recycled thermoplastics and plant fibers.However,its surface lacks attractive aesthetic qualities.In this paper,a method of decorating wood fiber/high-density polyethylene(WF/HDPE)without adding adhesive was explored.Canvas or polyester fabrics were selected as the surface decoration materials.The influence of hot-pressing temperature and WF/HDPE ratio on the adhesion was studied.The surface bonding strength,water resistance,and surface color were evaluated,and observation within the infrared spectrum and under scanning electron microscopy was used to analyze the bonding process.The results showed that the fabric and WF/HDPE substrate could be closely laminated together depending on the HDPE layer accumulated on the WF/HDPE surface.The molten HDPE matrix penetrates canvas more easily than polyester fabric,and the canvasveneered composite shows a greater bonding strength than does the polyester fabric-veneered composite.A higher proportion of the thermoplastic component in the substrate improved the bonding.When the hot-pressing temperature exceeded 160°C,the fabric-veneered WF/HDPE panels had greater water resistance,although the canvas fabric changed more obviously in terms of fiber shape and color,compared with the polyester fabric.For the canvas fabric,140°C–160°C was a suitable hot-pressing temperature,whereas 160°C–180°C was more suitable for polyester fabric.The proportion of the thermoplastic component in the composite should be not less than 30%to achieve adequate bonding strength. | Jialin Lv Rao Fu Yinan Liu Xuelian Zhou Weihong Wang Pengbo Xie Tingwei Hu | 2020 | Journal of Renewable Materials2020，8，8： | 0 |
| 5 | Multi-feedback Pairwise Ranking via Adversarial Training for Recommender显示文摘Personalized recommendation systems predict potential demand by analyzing user preferences.Generally,user feedback information is inferred from implicit feedback or explicit feedback.Nevertheless,feedback can be contaminated by user’s mis-operations or malicious operations,and may thus lead to incorrect results.We propose a novel Multi-feedback pairwise ranking method via Adversarial training(AT-MPR)for recommender to enhance the robustness and overall performance in the event of rating pollution.The MPR method extends Bayesian personalized ranking(BPR)to cover three types of feedback:positive,negative,and unobserved.It obtains user preferences in a probabilistic way through multiple feedbacks at different levels.To reduce the impact of feedback noise,we train an MPR objective function using minimax adversarial training.Experiments on two datasets show that the AT-MPR model achieves satisfactory performance and outperforms the state-of-the-art implicit feedback collaborative ranking models in two evaluation metrics. | WANG Jianfang FU Zhiyuan NIU Mingxin ZHANG Pengbo ZHANG Qiuling | 2020 | Chinese Journal of Electronics2020，29，4： | 0 |
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