Model of intense pulsed ion beam and simulation study of energy deposited on target

Gaussian type models have been established according to the real detected voltage of magnetically insulated ion diode and intense pulsed ion beam density near the focus of the diode. The energy deposition of Al target irradiated by intense pulsed ion beam has been simulated by Monte Carlo method based on these models. The results of energy depositions of the irradiation of single energy ions and the Gaussian distribution IPIB have been obtained. Especially cases of ion beam irradiating Al target at different angles on one dimension and two dimensions are discussed. The evolution processes of the energy deposition of ions in target have been simulated during a pulse. In addition, incident angles of H⁺ ions and C⁺ ions ranging from 20 to 40° have been researched. We obtained the conclusions that C⁺ ions of the beam affect the physical properties of near surface region, but H⁺ ions affect the deeper layer. The energy of intense pulsed ion beam mainly deposits on target surface, so melting and evaporation begin both from target surface.     

Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling

To enable the immediate and efficient dispatch of relief to victims of disaster, this study proposes a greedy-search-based, multi-objective, genetic algorithm capable of regulating the distribution of available resources and automatically generating a variety of feasible emergency logistics schedules for decision-makers. The proposed algorithm dynamically adjusts distribution schedules from various supply points according to the requirements at demand points in order to minimize unsatisfied demand for resources, time to delivery, and transportation costs. The proposed algorithm was applied to the case of the Chi–Chi earthquake in Taiwan to verify its performance. Simulation results demonstrate that under conditions of a limited/unlimited number of available vehicles, the proposed algorithm outperforms the MOGA and standard greedy algorithm in ‘time to delivery’ by an average of 63.57% and 46.15%, respectively, based on 10,000 iterations.     

Aligning principal and agent’s incentives: A principal–agent perspective of social networking sites

The viability of networked communities depends on the creation and disclosure of user-generated content and the frequency of user visitation (Facebook 10-K Annual Report, 2012). However, little is known about how to align the interests of user and social networking sites. In this study, we draw upon the principal-agent perspective to extend Pavlou et al.’s uncertainty mitigation model of online exchange relationships (2007) and propose an empirically tested model for aligning the incentives of the principal (user) and the agent (service provider). As suggested by Pavlou et al., we incorporated a multi-dimensional measure of trust: trust of provider and trust of members. The proposed model is empirically tested with survey data from 305 adults aged 20-55. The results support our model, delineating how real individuals with bounded rationality actually make decision about information disclosure under uncertainty in the social networking site context. There is show little to no relationship between online privacy concerns and information disclosure on online social network sites. Perceived benefits provide the linkage between the incentives of principal (user) and agent (provider) while usage intensity demonstrated the most significant impact on information disclosure. We argue that the phenomenon may be explained through Communication Privacy Management Theory. The present study enhances our understanding of agency theory and human judgment theory in the context of social media. Practical implications for understanding and facilitating online social exchange relationships are also discussed.     

Determination of temporal information granules to improve forecasting in fuzzy time series

Partitioning the universe of discourse and determining intervals containing useful temporal information and coming with better interpretability are critical for forecasting in fuzzy time series. In the existing literature, researchers seldom consider the effect of time variable when they partition the universe of discourse. As a result, and there is a lack of interpretability of the resulting temporal intervals. In this paper, we take the temporal information into account to partition the universe of discourse into intervals with unequal length. As a result, the performance improves forecasting quality. First, time variable is involved in partitioning the universe through Gath–Geva clustering-based time series segmentation and obtain the prototypes of data, then determine suitable intervals according to the prototypes by means of information granules. An effective method of partitioning and determining intervals is proposed. We show that these intervals carry well-defined semantics. To verify the effectiveness of the approach, we apply the proposed method to forecast enrollment of students of Alabama University and the Taiwan Stock Exchange Capitalization Weighted Stock Index. The experimental results show that the partitioning with temporal information can greatly improve accuracy of forecasting. Furthermore, the proposed method is not sensitive to its parameters.     

Incrementally building frequent closed itemset lattice

A concept lattice is an ordered structure between concepts. It is particularly effective in mining association rules. However, a concept lattice is not efficient for large databases because the lattice size increases with the number of transactions. Finding an efficient strategy for dynamically updating the lattice is an important issue for real-world applications, where new transactions are constantly inserted into databases. To build an efficient storage structure for mining association rules, this study proposes a method for building the initial frequent closed itemset lattice from the original database. The lattice is updated when new transactions are inserted. The number of database rescans over the entire database is reduced in the maintenance process. The proposed algorithm is compared with building a lattice in batch mode to demonstrate the effectiveness of the proposed algorithm.     

An improved global-best harmony search algorithm for faster optimization

In this paper, an improved global-best harmony search algorithm, named IGHS, is proposed. In the IGHS algorithm, initialization based on opposition-based learning for improving the solution quality of the initial harmony memory, a new improvisation scheme based on differential evolution for enhancing the local search ability, a modified random consideration based on artificial bee colony algorithm for reducing randomness of the global-best harmony search (GHS) algorithm, as well as two perturbation schemes for avoiding premature convergence, are integrated. In addition, two parameters of IGHS, harmony memory consideration rate and pitch adjusting rate, are dynamically updated based on a composite function composed of a linear time-varying function, a periodic function and a sign function in view of approximate periodicity of evolution in nature. Experimental results tested on twenty-eight benchmark functions indicate that IGHS is far better than basic harmony search (HS) algorithm and GHS. In further study, IGHS has also been compared with other eight well known metaheuristics. The results show that IGHS is better than or at least similar to those approaches on most of test functions.     

基于无线疲劳监测系统的铝合金材料疲劳损伤研究

铝合金材料具有重量轻、强度高等特点,是国民经济发展的重要基础材料,在诸多领域(如飞行器设计与制造、建筑装饰等)中占有十分重要的地位。然而,其抗疲劳性能较差,在交变荷载作用下容易产生疲劳裂纹和发生疲劳破坏。提出了一种基于无线疲劳监测系统的铝合金材料疲劳损伤研究方法,实时监测了铝合金构件的疲劳应变,并实时分析了构件的疲劳损伤状况,为研究铝合金材料的疲劳性能提供了可借鉴性的方法。     

A high propylene productivity over B2O3/SiO2@honeycomb cordierite catalyst for oxidative dehydrogenation of propane

Boron-based metal-free catalysts for oxidative dehydrogenation of propane (ODHP) have drawn great attention in both academia and industry due to their impressive activity and olefin selectivity. Herein, the SiO₂ and B₂O₃ sequentially coated honeycomb cordierite catalyst is designed by a two-step wash-coat method with different B₂O₃ loadings (0.1%-10%) and calcination temperatures (600, 700, 800 ℃). SiO₂ obtained by TEOS hydrolysis acts as a media layer to bridge the cordierite substrate and boron oxide via abundant Si-OH groups. The welldeveloped straight channels of honeycomb cordierite make it possible to carry out the reactor under high gas hourly space velocity (GHSV) and the thin wash-coated B₂O₃ layer can effectively facilitate the pore diffusion on the catalyst. The prepared B₂O₃/SiO₂@HC monolithic catalyst exhibits good catalytic performance at low boron oxide loading and achieves excellent propylene selectivity (86.0%), olefin selectivity (97.6%, propylene and ethylene) and negligible CO₂ (0.1%) at 16.9% propane conversion under high GHSV of 345,600 ml·(g B₂O₃)^-1·h^-1, leading to a high propylene space time yield of 15.7 g C₃H₆·(g B₂O₃)^-1·h^-1 by suppressing the overoxidation. The obtained results strongly indicate that the boron-based monolithic catalyst can be properly fabricated to warrant the high activity and high throughput with its high gas/surface ratio and straight channels.     

聚氨酯橡胶摩擦轮有限元及疲劳寿命分析

针对汽车滑板输送机聚氨酯橡胶摩擦轮的开裂问题,对摩擦轮与滑板之间的相互作用进行预压紧力和接触摩擦驱动有限元分析,获得摩擦轮的应力和变形分布等结果.在获得摩擦轮周向应力分布的基础上,根据疲劳裂纹扩展公式对聚氨酯橡胶部分进行疲劳寿命分析,验证是否满足设计要求.分析过程和结果能为聚氨酯橡胶摩擦轮的详细设计提供参考.