MAN B&W公司开发的ALPHA智能润滑系统对保持气缸良好润滑状态、节省气缸油、降低废气排放具有重要意义。为研究ALPHA注油器的注油性能,运用AMESim建立了ALPHA注油器的仿真模型,并模拟了其注油过程。分析了一些主要参数,包括柱塞行...MAN B&W公司开发的ALPHA智能润滑系统对保持气缸良好润滑状态、节省气缸油、降低废气排放具有重要意义。为研究ALPHA注油器的注油性能,运用AMESim建立了ALPHA注油器的仿真模型,并模拟了其注油过程。分析了一些主要参数,包括柱塞行程、油管长度和气缸压力对注油性能的影响。仿真结果对ALPHA注油器的优化设计和合理应用具有一定的参考价值。展开更多
Nanosized copper powders were prepared by a gel-casting method using copper nitrate, acrylamide（AM） and N, N′-methylenebisacrylamide（MBAM） as the main raw materials. The as-prepared copper powders were characteri...Nanosized copper powders were prepared by a gel-casting method using copper nitrate, acrylamide（AM） and N, N′-methylenebisacrylamide（MBAM） as the main raw materials. The as-prepared copper powders were characterized by X-ray diffractometry and scanning electron microscopy, and then added into a 48# industrial white oil. Dispersion and wear properties of the compounded lubricating oil were tested. The results show that the copper powders prepared are of high purity, fine dispersibility with mean particle size of about 60 nm and with a narrow particle size distribution. The nanosized copper powders can be well dispersed in the lubricating oil. The addition of the copper powders obviously improves the anti-wear properties of the lubricating oil owing to their good self-repairing performance. Compared with 48# industrial white lubricating oil, the friction coefficient of GCr15 steel with the compounded oil containing 0.6% copper powders reduces by 0.07 and nearly no wear chippings are found in the scratches of the friction counter parts.展开更多
This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is c...This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is constructed to predict a candidate set of annotations with confidence scores, and then model semantic relationship among the candidate annotations by leveraging conditional ran- dom field. In CRF, the confidence scores generated lay the PLSA model and the Fliekr distance be- tween pairwise candidate annotations are considered as local evidences and contextual potentials re- spectively. The novelty of our method mainly lies in two aspects ： exploiting PLSA to predict a candi- date set of annotations with confidence scores as well as CRF to further explore the semantic context among candidate annotations for precise image annotation. To demonstrate the effectiveness of the method proposed in this paper, an experiment is conducted on the standard Corel dataset and its re- sults are ＇compared favorably with several state-of-the-art approaches.展开更多
基金Project(51674095)supported by the National Natural Science Foundation of China
文摘Nanosized copper powders were prepared by a gel-casting method using copper nitrate, acrylamide（AM） and N, N′-methylenebisacrylamide（MBAM） as the main raw materials. The as-prepared copper powders were characterized by X-ray diffractometry and scanning electron microscopy, and then added into a 48# industrial white oil. Dispersion and wear properties of the compounded lubricating oil were tested. The results show that the copper powders prepared are of high purity, fine dispersibility with mean particle size of about 60 nm and with a narrow particle size distribution. The nanosized copper powders can be well dispersed in the lubricating oil. The addition of the copper powders obviously improves the anti-wear properties of the lubricating oil owing to their good self-repairing performance. Compared with 48# industrial white lubricating oil, the friction coefficient of GCr15 steel with the compounded oil containing 0.6% copper powders reduces by 0.07 and nearly no wear chippings are found in the scratches of the friction counter parts.
基金Supported by the National Basic Research Priorities Programme(No.2013CB329502)the National High Technology Research and Development Programme of China(No.2012AA011003)+1 种基金the Natural Science Basic Research Plan in Shanxi Province of China(No.2014JQ2-6036)the Science and Technology R&D Program of Baoji City(No.203020013,2013R2-2)
文摘This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is constructed to predict a candidate set of annotations with confidence scores, and then model semantic relationship among the candidate annotations by leveraging conditional ran- dom field. In CRF, the confidence scores generated lay the PLSA model and the Fliekr distance be- tween pairwise candidate annotations are considered as local evidences and contextual potentials re- spectively. The novelty of our method mainly lies in two aspects ： exploiting PLSA to predict a candi- date set of annotations with confidence scores as well as CRF to further explore the semantic context among candidate annotations for precise image annotation. To demonstrate the effectiveness of the method proposed in this paper, an experiment is conducted on the standard Corel dataset and its re- sults are ＇compared favorably with several state-of-the-art approaches.
