超声CO激光的现状和展望(续)

介绍了200kWCW超声电子束连续CO激光器（SSCO－EIL）开环实物模型的能量和光谱特征的实验研究结果，以及增加SSCO－EIL的输出功率，谱线选择性，Q－开关激光作用的数字计算结果，同时讨论了SSCO－EIL的特性对几种激光技术效率的影响，由于激光能量利用率的增加和能量成本的降低，SSCO－EIL拥有的无与伦比的能量和特有的特征，将大大拓宽激光技术的应用领域。     

工业PTA氧化过程4-CBA浓度的模糊神经网络模型

A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

A trustworthy QoS-based collaborative filtering approach for web service discovery

Many network services which process a large quantity of data and knowledge are available in the distributed network environment, and provide applications to users based on Service-Oriented Architecture (SOA) and Web services technology. Therefore, a useful web service discovery approach for data and knowledge discovery process in the complex network environment is a very significant issue. Using the traditional keyword-based search method, users find it difficult to choose the best web services from those with similar functionalities. In addition, in an untrustworthy real world environment, the QoS-based service discovery approach cannot verify the correctness of the web services’ Quality of Service (QoS) values, since such values guaranteed by a service provider are different from the real ones. This work proposes a trustworthy two-phase web service discovery mechanism based on QoS and collaborative filtering, which discovers and recommends the needed web services effectively for users in the distributed environment, and also solves the problem of services with incorrect QoS information. In the experiment, the theoretical analysis and simulation experiment results show that the proposed method can accurately recommend the needed services to users, and improve the recommendation quality.     

Inhibitory Effect of Monoterpenes on Response of Pityogenes bidentatus to Aggregation Pheromone Released by Piezoelectric Sprayer for Precision Release of Semiochemicals

A piezoelectric sprayer for dispensing semiochemicals was developed and used for a field test of bark beetle semiochemicals. The sprayer consists of a geared pump that pushes a syringe slowly to dispense semiochemicals in solvents through a microtube to a glass micropipet fixed to a piezoelectric high-frequency vibrator. The frequency is adjusted via a function generator to about 120 kHz until the harmonic properties of the glass micropipet, drawn by an electrophysiological pipet puller, cause vibrations that atomize the solvent from the micropipet tip. The sprayer, syringe, pump, function generator, and power supply were hung on one arm of a rotating trap pair (traps 6 m apart) that was slowly rotated at 2 revolutions per hour (rph) to even out the position effects on trap catches. The aggregation pheromone components of Pityogenes bidentatus, grandisol and cis-verbenol, were released by standard tube dispensers in one trap and compared to the release of similar amounts by the sprayer in the other trap. No significant differences in catch were observed. No effect of the solvent hexane on aggregation could be observed. The trap pair also caught approximately equal numbers of bark beetles when the baits were identical. The release of (+)and (–)--pinene, (+)-3-carene, and terpinolene, monoterpenes of host Scotch pine, Pinus sylvestris, at increasing rates from 0.01 to 10 log-equivalents in decadic steps (each at 0.1–100 g/min) resulted in decreasing responses to aggregation pheromone (only 9% at highest rate). Inhibition by the individual monoterpenes tested at the 100 g/min rate was significant for (+)and (–)--pinene and terpinolene (12, 13, and 15% of control, respectively). The inhibition by the host Scotch pine monoterpenes may allow P. bidentatus to avoid resistant trees that release large amounts of toxic monoterpenes in their resin and instead colonize dying and diseased limbs or slash, the usual host substrate. The piezoelectric sprayer should prove generally useful to dispense precise amounts of semiochemicals in field and laboratory experiments.     

浅谈皮带定量给料机的机械配置选型

皮带定量给料机是目前水泥生产企业中最为常见的过程计量和配料的设备。作者结合多年来开发、调试和使用皮带定量给料机的实践经验与资料积累，介绍了如何根据实际需要和使用量程，通过对皮带定量给料机的主要机械参数的计算来合理地选用定量给料机的型号和规格。     

动筛跳汰系统设计中若干环节的探讨

论述了动筛跳汰机的选型原则及技术要求,提出了4m2动筛跳汰机分选系统设计中各环节技术参数及所用设备的选择条件,同时对动筛跳汰系统各环节的布置进行了探讨。     

基于奇偶树型交互学习机与遗传算法的密文优化系统

为使图像加密系统具备优化功能,并解决当前遗传算法无法实现全局最优、收敛速率慢等问题,提出奇偶树型交互学习机耦合全局离散遗传算法的密文优化系统。定义权值更新机制,耦合混沌映射,构造奇偶树型交互学习机及其互扰模型。将切断型轮盘赌择取机制引入均匀交叉算子中,以图像分块的相邻像素相关系数和密文信息熵为目标,根据权重理论设计加权适应度函数,提出一种全局离散遗传算法,最终形成"初始加密-密文优化"的加密结构。实验结果表明,与超混沌算法、离散遗传算法、元胞自动机相比,该系统的加密质量较好,并且具备全局优化功能,可优化所有迭代结果,使最终输出密文的信息熵最大,相关系数最小。     

多交叉混沌选择反向小生境遗传算法

为提高小生境遗传算法的全局以及局部搜索能力,提出一种多交叉混沌选择反向小生境遗传算法。利用分段线性混沌映射函数生成一组混沌数序列,在每次进行交叉操作前,依据序列中对应元素的数值大小选择不同的交叉算子进行操作,通过小生境遗传算法产生较优的子代种群。针对子代种群,应用反向搜索策略获得反向种群,在子代种群和反向种群中进行精英选择得到最终新种群,以进一步加强算法的局部寻优能力。仿真实验结果表明,该算法在最优解及均值方面好于小生境遗传算法,从而证明其可行性和优越性。     

改进贝叶斯分类的智能短信分类方法

随着移动通信技术的不断发展,手机的普及率在不断上升,而短信作为传统的移动通信服务,长久以来一直在人们的日常生活中占据着极为重要的位置。可以说,短信在一定程度上记录了人们生活的轨迹。但是,现有的短信管理系统仅对短信进行以联系人为特征分类、以时间为顺序显示的简单非智能化的管理,导致了用户手机中各类短信混杂不清,短信的管理效率极低。通过研究短信的特征,分析传统的基于文档频率的特征值提取方法和基于互信息的特征值提取方法的优势与不足,提出了一种适用于短信的基于词频和互信息的特征值提取方法,并结合短信长度实现了一种改进的贝叶斯分类算法。实验证明,算法在进行短信分类时可以得到相当可观的召回率和准确率。