面向决策的信任融合模型研究

信任关系模型无论是在现实生活中还是在开放网络中都是最复杂的社会关系模型之一,是一个很难度量的抽象的心理认知,因为它涉及假设、期望、行为和环境等多种因素。借鉴以往的研究经验,综合考虑多种信任关系要素,提出了一种新的面向决策的信任融合模型。该模型基于直接信任度、间接信任度和信誉值的演化,依据信任融合获得决策信任度,为主体评判下一次的交互提供依据。为了证明信任融合模型的有效性,假设客体在ω类活动中以期望为PωX的概率从事该项活动。实验证明,信任融合模型得到的决策信任度和客体可信度的差异明显小于直接信任度、间接信任度或信誉值。     

Strength Analysis of Steam Turbine Diaphragm with a Crack

The diaphragm of steam turbine is one of the main parts of the passage unit for air flowing and the diaphragm of steam turbine is generally made by welding, but during the course of welding, some cracks often have happened, these cracks threaten safety production on the spot, so it is necessary to analyze the strength of steam turbine diaphragm with a crack. For studying its working condition and performance with a crack, the three-dimensional finite element model(FEM) with the software ANSYS 10.0 is established according to the actual working parameters. With the model, the deformation results and stress field results are analyzed and the maximum displacement and stress value are calculated, meanwhile, the maximum stress change with crack depth of steam turbine diaphragm is analyzed. It provides a good foundation for solving the problem in production.     

基于3D扫描技术的数控雕刻系统

本文介绍了一种基于3D扫描技术来实现先进高速雕刻的数控雕刻系统.即利用物体表面三维形状测量技术来获取实物模型表面的3D扫描数据,经计算机处理之后,存储为3D格式文件,再将该格式的文件转换成刀路NC格式文件,最后输入到数控雕刻系统的输入单元内雕刻出物体的3D模型.整个系统的软硬件自行设计搭建,并在文中给出了实例制作过程.     

核电站堆芯温度场软测量方法研究

核电站堆芯内部温度是反应堆安全运行的重要参数,由于受到测点安装条件的限制,无法直接测量。为解决该问题,在现有压水堆堆芯功率模型的基础上,结合稳态传热热量守恒方程,构建堆芯温度场的计算模型,推算出堆芯内部温度。并通过数值模拟计算结果与堆芯出口实测值的比较,运用数据不确定度作为判断依据,验证了方法的可行性,得到了堆芯内部不同截面的二维温度分布图,为堆芯内部温度的实时监测提供了理论依据。     

基于计算思维的“加涅式”新型计算机课程教学法

为适应军队在实战与军事训练等方面的迫切需要,我军队院校亟需培养大批知识型、创新型、复合型的军事人才,提出一种关于计算机课程的教学改革方法——基于计算思维的"加涅式"新型计算机课程教学法。该教学方法的核心目标是"两个中心",即以培养"计算思维"能力为中心和以"学员为中心"的"加涅式"教学方法。将这两种教学理念有机结合,将会大大提高新型军事人才的"自主学习及创新探索"能力,从而进一步提升了我军信息化、网络化的实战高度与要求。     

柬教官计算机专业外训教学探索

近年来,我室承担了柬埔寨教官计算机专业培训的外训教学任务,由于没有外训经验,教学过程中面临许多新问题,任务艰巨。如何有效实施计算机专业外训教学,提升外训教学水平是当前迫切需要探索的课题。从柬教官的特点和计算机专业的特点出发,对外训教学的规范化问题提出了几点看法,以期为提高教学效果提供借鉴。     

多参数融合的飞行品质评估模型的建立

目前航空管理机构与航空公司进行飞行品质评估主要是依据经验与简单飞行参数统计数字,这样做难以得出科学、客观的评估结果。基于提升全行业安全保障能力和运行品质的需求,研究了利用计算机技术对飞行品质进行综合评估的方法。选取了理想值逼近法作为飞行品质综合评估的手段,结合波动通道模型作为飞行品质评估的理论基础,基于提出的飞行品质评估模型对飞行品质评估系统进行了设计。对真实的飞行参数数据建立综合评估模型,同时考察多次航班的多个飞行参数,给出综合的飞行品质评估结论,为飞行评估、训练提供理论基础和科学的评判方法。     

A study of 3D cover glass design that improves handheld device drop reliability

Cover glass in commercial handheld devices is now evolving from flat (2D) to curved (3D) shapes. For example, some commercial devices have utilized sled‐shape cover glass, 1 which partially covers long edges of the device. According to the patents published by key handheld manufacturers, 2 , 3 we can expect more variety of 3D shaped cover glass for handheld devices in the market. In this study, we have focused on the reliability of 3D cover glass when it is dropped to a rigid surface. The key parameters under study are the corner/edge bend radius and angle of the cover glass, which determines the 3D shape of the cover glass. To achieve this goal, we developed a finite element model to simulate the drop 4 - 13 of a handheld device with 3D‐shaped glass. The model uses explicit algorithm to simulate the high speed impact on the device during the drop test. The glass performance was evaluated based on contact force between the glass and the ground and maximum principal stress in the glass. We showed that to avoid severe damage because of first impact between the glass and the ground, the bend angle of 3D glass has to be in the range between 0 and 45°. For drop angles of 45° and higher, with the proposed glass bend angle, the impact can be taken over by the edge of the back cover of the device. In addition, we showed that optimum glass bend radius is in the range of 3.8 mm and larger. This is required to reduce stress in glass because of impact. The approach and conclusions from the current study can serve as a general guideline to improve the 3D cover glass reliability of a handheld device.     

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., \({{\mathrm{sum}}}\), \(\max \)) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of \(\phi M\) objects in Q for some support \(0< \phi \le 1\). We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.     

Rotation,scaling and translation invariant texture recognition by Bessel-Fourier moments

The ideal of Bessel-Fourier moments (BFMs) for image analysis and only rotation invariant image cognition has been proposed recently. In this paper, we extend the previous work and propose a new method for rotation, scaling and translation (RST) invariant texture recognition using Bessel-Fourier moments. Compared with the others moments based methods, the radial polynomials of Bessel-Fourier moments have more zeros and these zeros are more evenly distributed. It makes Bessel-Fourier moments more suitable for invariant texture recognition as a generalization of orthogonal complex moments. In the experiment part, we got three testing sets of 16, 24 and 54 texture images by way of translating, rotating and scaling them separately. The correct classification percentages (CCPs) are compared with that of orthogonal Fourier-Mellin moments and Zernike moments based methods in both noise-free and noisy condition. Experimental results validate the conclusion of theoretical derivation: BFM performs better in recognition capability and noise robustness in terms of RST texture recognition under both noise-free and noisy condition when compared with orthogonal Fourier-Mellin moments and Zernike moments based methods.