基于PROLOG与DBASEⅢ的演绎数据库系统

演绎数据库是人工智能与数据库技术相结合的产物,具有逻辑推理及数据处理功能。本文首先分析了演绎数据库的实现技术,介绍了我们设计实现的基于PROLOG及DBASE Ⅲ系统,并基于该系统开发了一个决策支持系统。

AN INVISCID MODEL FOR THE BASE PRESSURE OF TRANSONIC TURBINE CASCADE

An inviscid base pressure model for transonic turbine blade has been presented. It has been shown that for a given back pressure the base pressure at the trailing edge, and the profile loss of a turbine blade are fixed according to the model and the base pressure can be calculated with the help of an inviscid numerical scheme. A parameteric study on the model shows that a blade profile with positive curvature downstream of the throat is advantageous for generating less loss, whilst the worst situation is when the exit flow reaches the sonic condition.

The Boundary Processing of Wavelet Based Image Compression

When an image, which is decomposed by bi-orthogonal wavelet bases, is reconstructed, some information will be lost at the four edges of the image. At the same time, artificial discontinuities will be introduced. We use a method called symmetric extension to solve the problem. We only consider the case of the two-band filter banks, and the results can be applied to M-band filter banks. There are only two types of symmetric extension in analysis phrase, namely the whole-sample symmetry (WS), the half-sample symmetry (HS), while there are four types of symmetric extension in synthesis phrase, namely the WS, HS, the whole-sample anti-symmetry (WA), and the half-sample anti-symmetry (HA) respectively. We can select the exact type according to the image length and the filter length, and we will show how to do these. The image can be perfectly reconstructed without any edge effects in this way. Finally, simulation results are reported. Key words edge effect - image compression - wavelet - biorthogonal bases - symmetric extension CLC number TP 37 Foundation item: Supported by the National 863 Project (20021111901010)Biography: Yu Sheng-sheng (1944-), male, Professor, research direction: multimedia information processing, SAN.

Detection of Edge with the Aid of Mollification Based on Wavelets

In preceding papers, the present authors proposed the application of the mollification based on wavelets to the calculation of the fractional derivative (fD) or the derivative of a function involving noise. We study here the application of that method to the detection of edge of a function. Mathieu et al. proposed the CRONE detector for a detection of an edge of an image. For a function without noise, we note that the CRONE detector is expressed as the Riesz fractional derivative (fD) of the derivative. We study here the application of the mollification to the calculation of the Riesz fD of the derivative for a data involving noise, and compare the results with the results obtained by our method of applying simple derivative to mollified data.

Adjoint-based optimization of flapping plates hinged with a trailing-edge flap

It is important to understand the impact of wing-morphing on aerodynamic performance in the study of flapping-wing flight of birds and insects. We use a flapping plate hinged with a trailing-edge flap as a simplified model for flexible/morphing wings in hovering. The trailing-edge flapping motion is opti- mized by an adjoint-based approach. The optimized configuration suggests that the trailing-edge flap can substantially enhance the overall lift. Further analysis indicates that the lift enhancement by the trailing- edge flapping is from the change of circulation in two ways： the local circulation change by the rotational motion of the flap, and the modification of vortex shedding process by the relative location between the trailing-edge flao and leading-edge main plate.

Comparison of Ontology-Based Semantic-Similarity Measures in the Biomedical Text

In recent years, there are many types of semantic similarity measures, which are used to measure the similarity between two concepts. It is necessary to define the differences between the measures, performance, and evaluations. The major contribution of this paper is to choose the best measure among different similarity measures that give us good result with less error rate. The experiment was done on a taxonomy built to measure the semantic distance between two concepts in the health domain, which are represented as nodes in the taxonomy. Similarity measures methods were evaluated relative to human experts’ ratings. Our experiment was applied on the ICD10 taxonomy to determine the similarity value between two concepts. The similarity between 30 pairs of the health domains has been evaluated using different types of semantic similarity measures equations. The experimental results discussed in this paper have shown that the Hoa A. Nguyen and Hisham Al-Mubaid measure has achieved high matching score by the expert’s judgment.

A generalized model of TiOx-based memristive devices and its application for image processing

Memristive technology has been widely explored, due to its distinctive properties, such as nonvolatility, high density,versatility, and CMOS compatibility. For memristive devices, a general compact model is highly favorable for the realization of its circuits and applications. In this paper, we propose a novel memristive model of TiOx-based devices, which considers the negative differential resistance（NDR） behavior. This model is physics-oriented and passes Linn＇s criteria. It not only exhibits sufficient accuracy（IV characteristics within 1.5% RMS）, lower latency（below half the VTEAM model）,and preferable generality compared to previous models, but also yields more precise predictions of long-term potentiation/depression（LTP/LTD）. Finally, novel methods based on memristive models are proposed for gray sketching and edge detection applications. These methods avoid complex nonlinear functions required by their original counterparts. When the proposed model is utilized in these methods, they achieve increased contrast ratio and accuracy（for gray sketching and edge detection, respectively） compared to the Simmons model. Our results suggest a memristor-based network is a promising candidate to tackle the existing inefficiencies in traditional image processing methods.

Contrast Enhancement Based Image Detection Using Edge Preserved Key Pixel Point Filtering

In existing methods for segmented images,either edge point extraction or preservation of edges,compromising contrast images is so sensitive to noise.The Degeneration Threshold Image Detection(DTID)framework has been proposed to improve the contrast of edge filtered images.Initially,DTID uses a Rapid Bilateral Filtering process for filtering edges of contrast images.This filter decomposes input images into base layers in the DTID framework.With minimal filtering time,Rapid Bilateral Filtering handles high dynamic contrast images for smoothening edge preservation.In the DTID framework,Rapid Bilateral Filtering with Shift-Invariant Base Pass Domain Filter is insensitive to noise.This Shift-Invariant Filtering estimates value across edges for removing outliers(i.e.,noise preserving base layers of the contrast image).The intensity values are calculated in the base layer of the contrast image for accurately detecting nearby spatial locations using Shift-Invariant base Pass Domain Filter(SIDF).At last,Affine Planar Transformation is applied to detect edge filtered contrast images in the DTID framework for attaining a high quality of the image.It normalizes the translation and rotation of images.With this,Degeneration Threshold Image Detection maximizes average contrast enhancement quality and performs an experimental evaluation of factors such as detection accuracy,rate,and filtering time on contrast images.Experimental analysis shows that the DTID framework reduces the filtering time taken on contrast images by 54%and improves average contrast enhancement quality by 27%compared to GUMA,HMRF,SWT,and EHS.It provides better performance on the enhancement of average contrast enhancement quality by 28%,detection accuracy rate by 26%,and reduction in filtering time taken on contrast images by 30%compared to state-of-art methods.

Particle Size Estimation Based on Edge Density

Given image sequences of closely packed particles, the underlying aim is to estimate diameters without explicit segmentation. In a way, this is similar to the task of counting objects without directly counting them. Such calculations may, for example, be useful）Cast estimation of particle size in different application areas. The topic is that of estimating average size （=average diameter） of packed particles, from formulas involving edge density, and the edges from moment-based thresholding are used. An average shape factor is involved in the calculations, obtained for some frames from crude partial segmentation. Measurement results from about 80frames have been analyzed.

EDGE-DETECTION BASED ON THE LOCAL VARIANCE IN ANGIOGRAPHIC IMAGES

This paper presents a new method for detection of edges in digital angiographic images. It is found that variances of local regions across edges of images are statistically different from that of those where no edge is crossed. This difference can be utilized for the detection of edges of angiographic images. An algorithm based on local variance is proposed. As a result, the edge-detection algorithm is not sensitive to noise and low-level textures of images. A computer program based on the new algorithm has been developed and used by several hospitals.

EFFECT OF Mg AND Zr ADDITION ON CREEP CRACK GROWTH BEHAVIOUR OF A Ni-BASE SUPERALLOY

The creep crack growth(CCG)and the time to carck initiation and rupture of specimen (t_(rc)and t_r)were measured by means of electrical potential method on single edge notched specimens at 700℃.The field near the crack tip under steady-state creep was represented by energy rate integral(C~*),and the CCG rate as a function of C~* has been obtained.The agreement between the predicted and observed t_(rc)values is quite good.It was found that the addition of small amount of Mg and Zr in the alloys causes t_(rc)and t_r of the specimens to in- crease significantly.

Reinforcing a Matroid to Have k Disjoint Bases

Let denote the maximum number of disjoint bases in a matroid . For a connected graph , let , where is the cycle matroid of . The well-known spanning tree packing theorem of Nash-Williams and Tutte characterizes graphs with . Edmonds generalizes this theorem to matroids. In [1] and [2], for a matroid with , elements with the property that have been characterized in terms of matroid invariants such as strength and -partitions. In this paper, we consider matroids with , and determine the minimum of , where is a matroid that contains as a restriction with both and . This minimum is expressed as a function of certain invariants of , as well as a min-max formula. These are applied to imply former results of Haas [3] and of Liu et al. [4].

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

This paper presents a corner-based image alignment algorithm based on the procedures of corner-based template matching and geometric parameter estimation. This algorithm consists of two stages: 1) training phase, and 2) matching phase. In the training phase, a corner detection algorithm is used to extract the corners. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. A parabolic function is further applied to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against non-liner light changes. The accuracy and precision of the corner-based image alignment are competitive to that of edge-based image alignment under the same environment. In practice, the proposed algorithm demonstrates its precision, efficiency and robustness in image alignment for real world applications.

Modeling Notch Wear of Ceramic Tool in High Speed Machining of Nickel-based Superalloy

On the basis of theoretical analyses and calculations of high speed continuous impact force and tool notch surface temperature acted upon by burr and serrated chip edge, a notch wear model of low stress value and temperature impact fatigue was established. Saw-tooth-shaped burr and fin-shaped chip edge continuously impacts the rake face and flank face at high speed and high fre-quency, which results in a V-shaped notch wear. An experiment was done to validate that the saw-tooth-shaped burr does affect the notch wear. This model can be utilized to solve reasonably many problems that cannot be explained by any other theoretical assumptions.

内蒙古白云鄂博主东矿三维地电模型与短偏移距瞬变电磁三维正演分析

内蒙古白云鄂博大型稀土-铌-铁矿床历经近70年开采,浅部铁矿资源已开发殆尽,亟需寻找深部资源.利用电磁法摸清主矿和东矿深部矿体连接状态及赋存特征对进一步认识白云鄂博成矿模式和寻找深部接替资源意义重大.然而,该区复杂的构造、地层、岩性、地形等条件给电磁法勘探带来极大挑战.采用数值建模与模拟手段对关键观测要素进行分析有助于勘探设计和数据解释.本文以白云鄂博主东矿及其结合部位为主要研究区域,基于已有地质、钻孔等资料,构建了主东矿三维地电模型,利用时域矢量有限元算法开展了电性源短偏移距瞬变电磁法(SOTEM)三维数值模拟,并重点分析了矿坑地形对观测数据的影响程度以及不同收发装置下的深部矿体的三维电磁学响应特征和探测能力.结果表明矿坑地形会导致SOTEM电磁场响应值升高,在主矿西侧布置发射源,更有助于实现对连接部位下方铁矿体的有效探测.该工作可为今后野外实际观测中工作参数优选和数据解释提供依据.

科研反哺教学在林木育种学教学中的探索与实践

林木育种学是高等农林院校林学专业的一门骨干课程,是以遗传进化理论为指导,研究林木优良品种选育、繁殖原理和技术的学科。其最高目标是选育林木优良品种,为林业生产提供最基本、最优质、最高效的生产资料,是林业的命脉和促进林业产业发展的原动力,在生态文明和美丽中国建设中发挥着越来越重要的作用。为了使学生更容易理解和掌握林木育种学的理论知识,深化科教融合,推进创新型人才培养,完善协同育人机制,在林木育种学授课过程中,通过将理论知识与生产实践相联系,将科技前沿贯穿于课堂教学,并以科研平台辅助实验教学的方式进行教学改革,不仅丰富了教学内容,激发了学生的学习热情,加深了对理论知识的理解,而且还利于学生良好科研素养的培养及创新能力的提高。

教育工学知识体系的组织和表达——指向“教育工程师”培养的思考

教育工学是未来教育工程师培养的重要理论基础,该领域的知识组织和表达是需要解决的一个基础性问题。教育工学知识的组织就是建构教育工学的知识体系,以教育工学的基本理论为核心,在认识的方向理清人类教育工学思想的历史脉络,在行动的方向求索教育工学的应用方略,从而构成以史、论、用为基本要素的知识结构。教育工学知识的表达则着眼于教育工程师的培养,需要遵循概念界定的操作性原则、原理陈述的工作性原则、方法表现的情境性原则和整体表达的理论与经验合参原则。

职业本科教材的开发和使用:影响因素、问题表征与行动路径

职业本科教育的人才培养目标、教材的本体特征、职业教育教材的类型特征,这三个因素影响职业本科教材的内容选择、组织逻辑及其呈现方式。目前职业本科教材开发和使用存在的问题包括:高质量教材供应不足;教材开发缺乏方法论指导,教材的职业本科特色不足;政府层面缺乏有效的职业本科教材开发激励机制,企业参与职业本科教材开发深度不够。未来应明确职业本科专业课程建设方向;开展职业院校有组织教研,集中力量攻关量大面广和重点领域教材开发;同步推动职业本科教材形态创新,扩大教材配套资源数量。

移动边缘计算场景下基于身份的安全认证密钥协商协议

移动边缘计算的快速发展推动了对新型安全技术的研究。认证密钥协商协议作为保障安全通信的重要方法之一,得到了广泛的关注,但现有的面向移动边缘计算的认证密钥协商协议并不能很好地同时满足移动边缘计算的安全性和性能需求。针对这一问题,提出了移动边缘计算场景下的认证密钥协商协议。首先,协议方案根据移动用户和边缘计算服务器的身份构建身份认证的凭证,双方通过该凭证完成相互认证并构建会话密钥,保证了通信安全;其次,通过形式化分析和非形式化分析证明了方案具有良好的安全性能;最后,由于所提方案避免使用包括双线性对在内的计算开销较大的密码学运算,在计算和通信开销方面的表现也较优。

基于模型阶数选择准则的稳健杂波边缘检测方法

在雷达目标自适应检测问题当中,辅助数据存在杂波边缘的情况将导致杂波协方差矩阵(CCM)的估计性能出现严重下降,极大地影响目标检测性能。为了解决这一问题,该文提出一种杂波边缘检测方法,能够对辅助数据中杂波边缘数量与位置进行自适应判别。首先,假定辅助数据中存在杂波边缘,采用模型阶数选择算法和最大似然估计方法完成杂波参数估计,其中杂波边缘位置由循环搜索方法得到。之后将杂波参数估计结果应用到检测算法中,通过广义似然比检验方法来判断杂波边缘是否存在。此外为了进一步提升算法在小样本条件下的稳健性,引入CCM的特殊结构作为先验知识,将算法推广至CCM为斜对称、谱对称以及中心对称3种结构的情况。仿真及实测数据均表明该文所提算法能够高效地识别雷达辅助数据中的杂波边缘数量和位置,先验知识的引入更能进一步改善算法在辅助数据量较小时的性能。