基于Flink的海量医学图像检索系统设计与实现

医学图像检索是有效利用医学资源的基础，而医学图像的海量性和增量性为图像检索带来了新的挑战和要求。为了提高医学图像检索过程的效率，设计并实现一种基于Flink的海量医学图像检索系统。首先，系统通过Web应用作为用户操作入口，在后端搭建数据平台和业务集群；其次，系统通过HBase对医学图像数据进行分布式存储，利用深度卷积神经网络模型提取医学图像特征；然后，将所提取的医学图像特征数据进行乘积量化编码，并通过HBase进行存储；最后，通过基于Flink的内存计算对接Kafka进行实时图像检索，以及对批量导入图像的特征索引编码。系统在4个节点的服务器上部署分布式集群，使用真实医学图像数据集进行测试，通过在MapReduce和Spark两种不同技术模块下的对比实验表明本系统具有更好的检索效率表现。     

区域供水安全指标体系构建及短板要素甄别

根据区域供水特点和供水安全内涵,构建区域供水安全评价指标体系,并辨识了2010~2017年江苏省区域供水安全状态;根据短板要素理论,采用均衡度指标计算不同指标之间的差异,将指标分为短板要素、限制性要素和优势要素。从纵向(年际)和横向(指标)两个方面分析江苏省区域供水的发展状态和原因。结果表明,江苏省区域供水安全状态一直在稳步提高,除去随机性较大的水源子系统,其余三个子系统都在向安全的方向发展。     

An application of metadata-based image retrieval system for facility management

For facility management, photography is an efficient and accurate method of recording the physical state of infrastructure. However, without an effective organizational scheme, the difficulty of retrieving relevant photos from historical databases can become overly burdensome for highly complex or long-lived assets. To make strategic decisions, it is crucial to retrieve the right information from a plurality of sources in a timely manner. The main objective of this paper is to present a method for organizing and retrieving photos from massive facility management photo databases using photo-metadata: photographed location, camera perspective, and image semantic content information. Indoor localization experiments were performed using Bluetooth technology to infer the location information. Perspective is inferred from the device’s on-board inertial measurement unit (IMU). Image semantic content is inferred using a Convolutional Neural Network (CNN)-based deep learning algorithm. Fusing these three features, seven query options were provided for the user when retrieving images. Leveraging Building Information Modeling (BIM) as a process and Geographic Information Systems (GIS) as a framework, this paper also envisions a federated information management by connecting 2D and 3D facility assets with our real-world map which can be smoothly bridged with our image retrieval system. The realization of the integrated application with BIM and GIS is significantly beneficial for the facility management domain by advancing the understanding of projects in a broader view with a federated data platform. In this research, the framework is illustrated with 21 institutional buildings within the University of Texas at Austin’s main campus, and the authors conclude that the proposed metadata-based image retrieval system can ultimately enhance the better-informed decision-making process through rapid information retrieval.     

Collaborative Distribution Alignment for 2D image-based 3D shape retrieval

Retrieving 3D shapes with 2D images has become a popular research area nowadays, and a great deal of work has been devoted to reducing the discrepancy between 3D shapes and 2D images to improve retrieval performance. However, most approaches ignore the semantic information and decision boundaries of the two domains, and cannot achieve both domain alignment and category alignment in one module. In this paper, a novel Collaborative Distribution Alignment (CDA) model is developed to address the above existing challenges. Specifically, we first adopt a dual-stream CNN, following a similarity guided constraint module, to generate discriminative embeddings for input 2D images and 3D shapes (described as multiple views). Subsequently, we explicitly introduce a joint domain-class alignment module to dynamically learn a class-discriminative and domain-agnostic feature space, which can narrow the distance between 2D image and 3D shape instances of the same underlying category, while pushing apart the instances from different categories. Furthermore, we apply a decision boundary refinement module to avoid generating class-ambiguity embeddings by dynamically adjusting inconsistencies between two discriminators. Extensive experiments and evaluations on two challenging benchmarks, MI3DOR and MI3DOR-2, demonstrate the superiority of the proposed CDA method for 2D image-based 3D shape retrieval task.     

电力工程项目管理的三要素分析

现今社会经济正在迅速发展中，电力工程领域也得到了较为良好的发展。但在此领域发展中，项目管理问题较为突显。文章主要是对电力工程项目管理的三要素进行了分析研究，以此帮助有效提升电力项目的管理工作效率及质量。     

Fast retrieval of hidden data using enhanced hidden Markov model in video steganography

In the digital world, secure data communication has an important role in mass media and Internet technology. With the increase in modern malicious technologies, confidential data are exposed at a greater risk during data communication. For secured communication, recent technologies and the Internet have introduced steganography, a new way to hide data. Steganography is the growing practice of concealing data in multimedia files for secure data transfer. Nowadays, videos are more commonly chosen as cover media than other multimedia files because of the moving sequence of images and audio files. Despite its popularity, video steganography faces a significant challenge, which is a lack of a fast retrieval system of the hidden data. This study proposes a novel video steganography technique in which an enhanced hidden Markov model (EHMM) is employed to improve the speed of retrieving hidden data. EHMM mathematical formulations are used to enhance the speed of embedding and extracting secret data. The data embedding and retrieving operations were performed using the conditional states and the state transition dynamics between the video frames. The proposed EHMM is extensively evaluated using three benchmark functions, and experimental evaluations are conducted to test the speed of data retrieval using differently sized cover-videos. Results indicate that the proposed EHMM yields better results by reducing the data hiding time by 3–50%, improving the data retrieval rate by 22–77% with a minimum computational cost of 20–91%, and improving the security by 4–77% compared with state-of-the-art methods.     

A numerical investigation of the connection between state of dispersion and percolation and its effect on the elastic properties of 2D random microstructures

The present work is dedicated to a numerical investigation of the connection between state of dispersion and percolation and its effect on the elastic properties of 2D random microstructures. The main objective consists in checking out the link between percolation and mechanical response in the context of a heterogeneous medium the reinforcements of which are not homogeneously dispersed. Besides, the influence of the stiffness of inclusions is also investigated since this could impact on the percolation effects. For these purposes, large samples of volume elements are generated according to the Monte Carlo method. We consider the low cost framework of 2D random grids which enables large and in-depth investigations. Besides, the spatial distribution of heterogeneities is simulated with the help of the 2-scale Boolean scheme of disks which is a powerful tool for modelling and studying several states of dispersion. The numerical results highlight beneficial mechanical reinforcements for a heterogeneous dispersion when the percolation phenomenon is enhanced. This improvement is highly sensitive to the stiffness of heterogeneities.     

电镀污泥中铜镍锌元素的检测

对电镀污泥的样品采集、样品制备以及电镀污泥中铜、镍、锌元素的检测方法进行了研究和优化改进。对铜、镍和锌的分析方法的精密度进行了加标回收实验,加标回收率为97%~105%。对方法的准确度与先进的电感耦合等离子体原子发射光谱法检测结果进行对比,结果显示,该方法操作较为简单,检测成本较低,可准确判断电镀污泥中铜、镍和锌含量。