An Improved Parameter Dimensionality Reduction Approach Based on a Fast Marching Method for Automatic History Matching

History matching is a critical step in reservoir numerical simulation algorithms.It is typically hindered by difficulties associated with the high-dimensionality of the problem and the gradient calculation approach.Here,a multi-step solving method is proposed by which,first,a Fast marching method(FMM)is used to calculate the pressure propagation time and determine the single-well sensitive area.Second,a mathematical model for history matching is implemented using a Bayesian framework.Third,an effective decomposition strategy is adopted for parameter dimensionality reduction.Finally,a localization matrix is constructed based on the single-well sensitive area data to modify the gradient of the objective function.This method has been verified through a water drive conceptual example and a real field case.The results have shown that the proposed method can generate more accurate gradient information and predictions compared to the traditional analytical gradient methods and other gradient-free algorithms.

Integration of Lab model and EHOG for human appearance matching across disjoint camera views

The integration of the Lab model with the extended histogram of oriented gradients （EHOG） is proposed to improve the accuracy of human appearance matching across disjoint camera views under perturbations such as illumination changes and different viewing angles. For the Lab model that describes the global information of observations, a sorted nearest neighbor clustering method is proposed for color clustering and then a partitioned color matching method is used to calculate the color similarity between observations. The Bhattacharya distance is employed for the textural similarity calculation of the EHOG which describes the local information. The global information, which is robust to different viewing angles and scale changes, describes the observations well. Meanwhile, the use of local information, which is robust to illumination changes, can strengthen the discriminative ability of the method. The integration of global and local information improves the accuracy and robustness of the proposed matching approach. Experiments are carried out indoors, and the results show a high matching accuracy of the proposed method.

A reliable algorithm for image matching based on SIFT

A novel algorithm is presented to make the results of image matching more reliable and accurate based on SIFT (Scale Invariant Feature Transform). SIFT algorithm has been identified as the most resistant matching algorithm to common image deformations; however, if there are similar regions in images, SIFT algorithm still generates some analogical descriptors and provides many mismatches. This paper examines the local image descriptor used by SIFT and presents a new algorithm by integrating SIFT with two-dimensional moment invariants and disparity gradient to improve the matching results. In the new algorithm, decision tree is used, and the whole matching process is divided into three levels with different primitives. Matching points are considered as correct ones only when they satisfy all the three similarity measurements. Experiment results demonstrate that the new approach is more reliable and accurate.

Hollow Gradient-Structured Iron-Anchored Carbon Nanospheres for Enhanced Electromagnetic Wave Absorption

In the present paper,a microwave absorber with nanoscale gradient structure was proposed for enhancing the electromagnetic absorption performance.The inorganic-organic competitive coating strategy was employed,which can effectively adjust the thermodynamic and kinetic reactions of iron ions during the solvothermal process.As a result,Fe nanoparticles can be gradually decreased from the inner side to the surface across the hollow carbon shell.The results reveal that it offers an outstanding reflection loss value in combination with broadband wave absorption and flexible adjustment ability,which is superior to other relative graded distribution structures and satisfied with the requirements of lightweight equipment.In addition,this work elucidates the intrinsic microwave regulation mechanism of the multiscale hybrid electromagnetic wave absorber.The excellent impedance matching and moderate dielectric parameters are exhibited to be the dominative factors for the promotion of microwave absorption performance of the optimized materials.This strategy to prepare gradient-distributed microwave absorbing materials initiates a new way for designing and fabricating wave absorber with excellent impedance matching property in practical applications.

Robust key point descriptor for multi-spectral image matching

Histogram of collinear gradient-enhanced coding （HCGEC）, a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detailed textural information, which is desirable in multi-spectral image matching. Experiments on two multi-spectral data sets demonstrate that the proposed descriptor can yield significantly better results than some state-of- the-art descriptors.

Multi-scale Graph-matching Based Kernel for Character Recognition from Natural Scenes

认出从自然景色图象提取的字符由于 intraclass 变化的高度是相当挑战性的。在这份报纸，我们为景色特性识别建议一个多尺度的匹配图的基于的核。以便捕获人物的内在地特殊的结构，每幅图象被与多尺度的图象格子联系的几张图代表。当也越过邻近的节点保存空间一致性时，二幅图象的类似被匹配二张图(图象) 因此定义为最佳精力，它在图为每个节点发现最好的火柴。计算类似是合适的为支持向量机器(SVM ) 构造一个核。与多尺度的格子匹配图获得的多重核被联合以便最后的核是更柔韧的。挑战性的 Chars74k 和 ICDAR03-CH 数据集上的试验性的结果证明建议方法比现状方法更好表现。

A novel model for extending international co-operation in science and education

In September 1994 the University of Twente, the Netherlands, and Zhejiang University, China, decided to cooperate in the field of science, education and management. After several visits of delegations from both sides it was considered worthwhile to explore further opportunities for mutual cooperation. The directors of international cooperation on each side jointly commissioned a project to investigate the potential in a systematic way and to establish further contacts where appropriate. This paper reports on the results of the research cum matching project. To reveal promising matches between multiple departments of both academic institutions a matching model for uni-versities was designed. The study was carried out along two parallel lines. In the research line the theoretical framework was developed into a model for international university co-operation. Moreover, an analysis was carried out on internal, external and cultural aspects resulting in a set of thirty four influencing factors. In the matching line a total of seventy interviews were held in order to identify promising matches between units at both universities. This line resulted in eleven promising matches for further co-operation. The novel model appeared useful in analyzing the variety of factors and in developing matches between both univer-sities. In the further implementation of the model the issues of 搇evel of co-operation?and 搕op-down versus bottom-up?need to be addressed in more detail.

Integrating Research Analytic Framework and Personality Matching for Supervisor Recommendation

Supervisor selection is important for research students in their future studies and careers.Currently,students rely on information search or friends recommendation to find potential research supervisors.However,due to the challenges of incomplete and asymmetric information,students can hardly find suitable supervisors that match their research interests as well as personalities.Existing methods mainly consider topic-relevance and candidate-quality,and overlook the significance of connectivity consideration and two-sided matching degree of individuals personality styles.It proposes a novel supervisor recommendation approach that integrates relevance,connectivity,quality and personality-matching dimensions.The results of user-based evaluations demonstrate that the proposed approach generates more satisfactory recommendations as compared to that of all baseline methods.The present solution has been implemented as a social network recommendation service on ScholarMate.

A Method for Rapid Matching Based on Second Order Partial Derivative

Our goal is to enhance matching speed which is important for image engineering. Second Partial Derivative operator in Harris corner detector is directly used to compute the similarity between corners. Then initial matches are obtained. The algorithm is contrasted with normalized cross-correlation and method based on horizontal and vertical gradient. Its computational complexity is reduced and matching speed is improved effectively because this method only adopts the addition and subtraction operations. Experiments on several real images test the matching speed, the matching precision and matching rate of the algorithm. The results demonstrate that the algorithm not only have higher speed but also get higher matching precision and correct matching rate. Even though the stereo image pairs have brightness differences, it still performs rather well.

中国婚姻市场的教育匹配模式及收益测度

婚姻匹配是择偶双方追求婚姻收益最大化的结果,中国高等教育事业的快速发展促使婚姻市场的教育匹配模式出现相应调整,映射出不同教育匹配模式下婚姻收益以及收益差距的双重转变。现有研究主要关注婚姻教育匹配带来的经济与社会效应,在一定程度上忽略了教育及教育匹配模式在微观个体层面对婚姻收益产生的影响,以及由婚姻收益反映出的教育匹配模式的特征和变化。从婚姻收益的角度验证中国婚姻市场中个体搜寻潜在配偶的选择依据,并对过去、当前和未来教育匹配模式的特征差异和发展趋势进行经济解释已成为婚姻匹配研究领域中的一个深层次问题。因此,本文基于第五次、第六次全国人口普查微观数据和第七次全国人口普查长表数据资料分析中国婚姻市场的受教育现状、教育匹配现状及变化特征,同时通过微观数据构建婚姻匹配数据库,使用CS模型对婚姻收益进行测算,考察各受教育水平人口在不同教育匹配模式下的婚姻收益和收益差距,从而解读中国婚姻市场在教育及教育匹配模式层面呈现出的新特征和新趋势。研究发现:第一,我国高等教育普及程度不断加深,适婚年龄人口在高等教育获得方面的性别差异逐渐缩小,近10年来已出现教育性别差异逆转现象。第二,在高等教育事业不断推进的背景下,中国婚姻市场的教育匹配模式也出现相应变化,在教育同质匹配保持主导地位的同时,“男高女低”教育匹配模式的比例下降,“女高男低”的教育匹配模式成为婚姻教育匹配的新趋势。第三,婚姻收益测算结果表明整体上女性婚姻收益高于男性。分受教育水平来看,在低、中学历人口中,女性婚姻收益高于男性;在高学历人口中,男性婚姻收益高于女性。在低、高学历人口中,与配偶的受教育水平差异越大,婚姻收益越低。第四,教育同质匹配模式下的婚姻收益最高,“男高女低”教育匹配模式下的婚姻收益次之,但“女高男低”与“男高女低”教育匹配模式下的婚姻收益差距正逐渐缩小。为提高居民婚姻收益、缩小收益差距,政府和教育部门在积极推进高等教育事业发展的同时,应加强教育差异群体的婚姻辅导工作;家庭内部也应树立夫妻家庭地位平等的观念,淡化家庭分工中的性别因素;此外,婚姻市场中的个体需转变传统的婚姻教育匹配观念,提倡多元化的择偶标准,这将有利于社会整体婚姻收益的提升以及社会不平等现象的改善。

车载激光点云道路标线分类提取方法

利用车载激光道路点云提取道路标线的难度较大。针对此问题,文章采用一种改进的基于点云特征图像的道路标线分类提取方法。首先将道路点云投影生成点云特征图像,通过结合图像梯度分析、图像二值化和连通域分析等操作,进一步进行道路标线像素提取;然后反投影到三维点云后,利用高斯混合模型对道路标线精细优化,从而提取出完整的道路标线点云;最后通过模板匹配分类,对道路标线点云进行分类提取。实验结果表明,该方法对不同道路环境下道路标线提取的准确度、完整度以及综合评价都超过90%。

经济欠发达地区职业技能人才供给与需求协调状况分析——以甘肃省为例

职业教育作为欠发达地区技能人才培养的基石,把握专业设置和技能人才供给与需求匹配成为各方关注的焦点。通过测算甘肃职业技能人才供需匹配度发现,多数专业供需不协调,专业供不应求,专业设置和市场脱钩,专业更新慢等状况明显。由此提出以市场为导向的优化甘肃职业教育专业设置方向。提出欠发达地区在政府层面做好现代职业教育规划、放松专业设置权限、鼓励校企合作、加快职业教育专业教师队伍建设、构建科学的质量评价制度,在职业院校层面把握为地方经济、社会发展服务的宗旨,探索实施“订单式”技能人才培养模式,建立技能人才培训基地等对策建议。

基于几何矩特征与纹理度量的图像匹配算法

为提高多种几何内容变化下的特征点匹配准确度,引入双边滤波器,设计了几何矩特征耦合纹理度量的图像匹配算法。引入双边滤波器,对图像进行预处理,以去除图像中噪声,接着利用Hessian算子,准确检测图像特征。利用图像灰度信息,计算图像特征圆域内的几何矩,以形成鲁棒性较强的特征向量。通过平均梯度模型,对特征点邻域的纹理特征进行度量,并将其联合欧氏测量结果,对图像特征实施匹配。借助互相关模型,对匹配特征的相关程度进行测量,以检测特征点的匹配正确性,优化特征匹配结果。实验数据表明:较当前特征匹配方法而言,在多种几何内容变化下,所提技术具有更高的匹配准确度与鲁棒性。

基于系统理论的校企协同育人项目管理——以湖北水职院实施的教育部供需对接就业育人项目为例

教育部供需对接育人项目涉及到学校、企业、学生、行业及教育主管部门等多方的不同需求,涉及教育部发布项目指南、企业和学校的项目申请,校企供需对接,以及协议签订,项目实施、结题等多个环节,还涉及到安全、资金、管理、法律、教学等多种影响因素,呈现出项目的系统化特征。基于系统思维的供需对接育人项目管理是项目有效实施的根本保证。特别在新冠疫情背景下,实施供需对接育人项目需要加大项目管理力度,有效满足各方需求,从全过程全环节全因素方面实施管控,保障项目可持续发展。以某职业技术学院实施供需对接育人项目为例,分析了项目实施的环节、影响因素,以及采取的举措。

基于多源数据的县域小学教育设施供需匹配评价——以广州市增城区为例

教育设施的供需均衡性对实现教育公平具有重要意义。以广州市增城区为例,基于多源数据类型,综合人口空间化和小学可达性分析结果,对小学教育设施的供需匹配度进行评价。结果表明:(1)增城区小学可达性整体水平有待提升,各镇街可达性差异较大;车行可达性自南向北圈层递减,步行可达性点状空间集聚特征显著。(2)车行出行方式下供需匹配较均衡,基本符合“核心-边缘”空间分布规律;步行出行方式下供需失衡严重且单中心集聚特征显著,增城区小学教育设施存在一定的空间错配现象。针对不同类型地区的小学教育设施供需匹配情况,应从区际均衡、校际均衡及政策保障多角度出发,采取差异化配置策略,以应对未来学龄人口就学的不同需求。

公共文化服务融入学前教育的可及性研究——基于广州市的样本

公共文化服务已经成为我国文化建设的重要内容和战略工程,而可及性是评价公共文化服务体系与其服务对象“适合度”的概念。本研究基于737名广州市幼儿园教师和行政人员的调研数据,建构了包含可获得性、可接近性、可接受性和可适合性四个维度的可及性评价框架,分析和评价公共文化服务体系与幼儿园师生需求及文化服务利用行为间的适合性。研究发现:公共文化服务机构与幼儿园供需双方均认可公共文化服务的教育价值,但公共文化服务职能未得到充分发挥,公共文化服务融入学前教育的可及性总体有待提升。其中,可获得性和可接近性是现阶段影响公共文化服务融入学前教育的基础条件;检索公共文化服务资源能力弱、缺乏实践运用能力成为制约幼儿园运用公共文化服务的重要原因。公共文化服机构扩能提质增效且提供精准供给,推动幼儿园常态化关注与运用公共文化服务,是提升公共文化服务与幼儿园师生需求间适合性的可选路径。

基于极限梯度提升的完美匹配单层智能算法实现航空瞬变电磁问题高效吸收

对于航空瞬变电磁的低频探地问题,除了精度和效率需要考虑,深地探测问题的复杂度也不容忽视,特别是对于低频复杂问题存在异常体与背景间的多尺度效应.为了模拟开域问题,有限厚度区域的完全匹配层被用于截断计算域,然而这也无形中增大了整个模型,造成计算复杂度增加.鉴于此,提出了一种新的基于极限梯度提升(extreme gradient boosting,XGB)的完美匹配单层模型,并将该模型集成到时域有限差分求解器中,以进一步提高时域有限差分仿真的性能.所提出的基于XGB的完美匹配单层模型通过特征注意力集成学习方法可以获得更高的精度,同时占用更少的内存、消耗更少的时间.此外,由于该模型依托于传统机器学习模型,因此它在模型训练的稳定性和轻量级方面具有显著的优势.最后,通过对航空瞬变电磁应用进行三维数值模拟,验证了该方法的有效性和稳定性.该模型不仅在精度、效率和问题复杂性方面具有优势,而且还可以成功地集成到时域有限差分求解器中,解决低频航空瞬变电磁问题.

人工智能时代高校思想政治教育主题活动课程化建设的内涵、价值及路径

人工智能在教育数字化实践中的广泛应用直接推动了高校思想政治教育的重塑。人工智能时代高校思想政治教育主题活动课程化转型,既是高校实现从思政课程到课程思政的现代化转型升级,也是全面建设现代化高校思想政治教育的现实诉求。构建新时代高校思想政治教育主题活动课程化建设体系应紧扣高校大思政的格局,形成三位一体的推进模式;创新数智融合课程体系,打造全要素互动共同体;加强现代思政队伍建设,建立健全评价反馈体系。

能力增值影响本科生就业匹配的模型建构与路径分析

结构性矛盾是制约高校毕业生高质量就业的关键性因素。从能力视角出发,基于人力资本理论和人职匹配理论,通过建构计量模型,定量分析本科毕业生在高等教育期间所获得的能力增值对就业匹配的影响及教育类型差异。研究发现,在专业匹配上,能力增值越高,毕业生的专业匹配度越高,且这一影响主要通过认知能力体现;在教育匹配上,能力增值显著影响毕业生的教育匹配状况,与教育匹配的学生相比,教育不足的学生依赖相对更高的认知能力弥补教育水平上的欠缺,教育过度的学生则通过更高的学历层次弥补非认知能力上的欠缺。对此,高等教育人才培养要兼顾认知能力与非认知能力,不同类型的教育主体还应结合自身的培养目标和定位,在学生能力塑造方面有所侧重与提升。

水下重力匹配导航适配性评价方法比较研究

重力匹配导航精度受重力适配区选取的影响。针对如何有效筛选最优适配区,采用信息熵的单特征准则与多属性决策的多特征准则评价重力底图的适配性。选择重力标准差、相关系数、粗糙度、坡度、重力特征丰度与累加梯度均值6种参数,利用单/多特征两种准则筛选同一海域适配/非适配区,通过地形轮廓匹配(terrain contour matching, TERCOM)算法在所筛选区域进行重力匹配导航验证,对比分析两者的匹配导航精度。结果表明,单特征准则在适配/非适配区的导航误匹配率分别为30%和20%;多特征准则在适配区无明显误匹配,误差在百米级,在非适配区出现多次误匹配。分析表明,多特征分析准则与单特征分析准则相比,可更准确有效地评价重力匹配区的适配性。