Using a Discrete-Event System Specifications (DEVS) for designing a Modelica compiler

We introduce a new architecture for the design of a tool for modeling and simulation of continuous and hybrid systems. The environment includes a compiler based on Modelica, a modular and a causal standard specification language for physical systems modeling (the tool supports models composed using certain component classes defined in the Modelica Standard Library, and the instantiation, parameterization and connection of these MSL components are described using a subset of Modelica). Models are defined in Modelica and are translated into DEVS models. DEVS theory (originally defined for modeling and simulation of discrete event systems) was extended in order to permit defining these of models. The different steps in the compiling process are show, including how to model these dynamic systems under the discrete event abstraction, including examples of model simulation with their execution results.     

一种基于深度森林的恶意代码分类方法

针对当前恶意代码静态分析方法精度不足的问题，将恶意代码映射为无压缩的灰度图像，然后根据图像变换方法将图像变换为恒定大小的图像，使用方向梯度直方图提取图像的特征，最后提出一种基于深度森林的恶意代码分类方法.实验中选择不同家族的多个恶意代码样本进行分类，验证了该方法的有效性，并且实验结果优于近期提出的SPAM-GIST方法.     

工程教育认证背景下设计模式课程教学研究

工程教育是我国高等教育的重要组成部分,工程教育认证已成为中国高校新的风向标,也成为高考生选择报考专业的一项重要指标。设计模式是计算机科学与技术专业的一门核心课程,包含了面向对象的精髓,是软件体系结构的基础,在工程教育认证所评估的课程设置中起着承上启下的关键作用。本文基于工程教育专业认证理念,以及山东农业大学申请认证所用的《计算机科学与技术专业培养方案》,从教学内容、教学方式、课程目标与毕业要求对应关系、解决复杂工程问题能力、教学进度安排等方面,对设计模式课程开展了教学研究,并将该教学方案应用于本科教学。     

Bi-projection for 360°image object detection bridged by RoI Searcher

Object detection on 360°images is a vital component of 3D environment perception. The existing methods either treat panoramic images (usually represented in equirectangular projection—ERP) as normal FoV images and endure the distortions or project them into the less-distortion format and narrow the FoV, leading to unsatisfactory performance in practical applications. To solve this problem, we propose a dual-projection 360°object detection network named Bip R-CNN, consisting of three modules: a bi-projection feature extractor, a cross-projection region-of-interest (RoI) searcher, and a classification and regression predictor. Specifically, we extract the equirectangular and corresponding dual-cubemap features simultaneously from the input images. Besides, Projection-Inter Feature Fusion and Projection-Intra Feature Fusion are designed to allow the mutual interaction between the bi-projective features and promote the integration of features at different scales, respectively. In the proposed cross-projection RoI Searcher, we search for the bounding box (BBox) locations on cubemap from the corresponding ERP spherical proposals, bridging the RoIs of two different projection formats at feature level. Finally, the cube proposals are used to detect objects in the last predictor module. Considering the scarceness of the existing panoramic dataset (only indoor scenes), we propose an efficient approach to convert conventional datasets into annotated panoramic datasets without manual intervention, increasing the diversity of panoramic datasets. Extensive experiments are conducted on the synthetic and real-world datasets with spherical criteria, demonstrating our superiority to other state-of-the-art solutions.     

宝钢低铁损取向硅钢在变压器新能效标准下的应用

随着变压器新能效标准GB 20052-2020的正式实施，变压器各能效等级普遍提升，也推动取向硅钢产品等级的提高。本文结合新能效标准，针对宝钢低铁损取向硅钢产品应用实绩，给出选材建议，并针对产品使用过程中存在的问题进行剖析，以期对变压器制造厂家选材和使用起到参考作用。     

Unsupervised regions based segmentation using object discovery

We present a new unsupervised algorithm to discovery and segment out common objects from multiple images. Compared with previous cosegmentation methods, our algorithm performs well even when the appearance variations in the foregrounds are more substantial than those in some areas of the backgrounds. Our algorithm mainly includes two parts: the foreground object discovery scheme and the iterative region allocation algorithm. Two terms, a region-saliency prior and a region-repeatness measure, are introduced in the foreground object discovery scheme to detect the foregrounds without any supervisory information. The iterative region allocation algorithm searches the optimal solution for the final segmentation with the constraints from a maximal spanning tree, and an effective color-based model is utilized during this process. The comparative experimental results show that the proposed algorithm matches or outperforms several previous methods on several standard datasets.     

应用型人才培养下化学实验教学改革

为进一步贯彻国家教育改革和发展纲要的要求,培养应用型人才,本文依据化学学科是一门以实验为基础的学科特点,结合化学实验教学,对其体系进行整合,探索新时期应用型人才培养下化学实验教学的课改方向,在传统化学实验教学的基础之上,培养学生的创新能力、实践能力和应用能力,以达到培养现代社会所需要的复合应用型人才的需求。     

民族地区院校中药应用型人才培养模式研究

针对少数民族地区医药院校的特点,对培养面向基层经济建设需要的中药应用型人才的培养目标及培养模式进行了探索,初步总结中药应用型人才的培养模式,从人才培养模式的定位、课程体系构建、多元化的人才评价体系的构建,突出实验技能培训,改革教学方法手段,强化科研实习等方面的改革,培养以能力为本位的应用型人才。     

高磁感取向硅钢27QG090的常化退火工艺

采用中试试验平台完成高磁感取向硅钢27QG090实验室常化退火工艺过程,利用光学显微镜、X射线衍射仪、透射电镜和能谱仪分析常化退火处理后试样的显微组织和宏观织构。结果表明,高磁感取向硅钢27QG090常化退火后的显微组织为铁素体,宏观织构主要是以α织构、α^*织构、铜型织构为主,兼有微弱的高斯织构,常化退火后的析出物主要是AlN,其平均尺寸约为40 nm。综合分析得出最优的常化退火工艺为1120℃×3 min+920℃×3 min, 100℃水淬。