An Angle Structure Descriptor for Image Retrieval

This paper presents an efficient image feature representation method, namely angle structure descriptor(ASD), which is built based on the angle structures of images. According to the diversity in directions, angle structures are defined in local blocks. Combining color information in HSV color space, we use angle structures to detect images. The internal correlations between neighboring pixels in angle structures are explored to form a feature vector. With angle structures as bridges, ASD extracts image features by integrating multiple information as a whole, such as color, texture, shape and spatial layout information. In addition, the proposed algorithm is efficient for image retrieval without any clustering implementation or model training. Experimental results demonstrate that ASD outperforms the other related algorithms.

Performance-based global reliability assessment of a high-rise frame-core tube structure subjected to multi-dimensional stochastic earthquakes

When evaluating the seismic safety and reliability of complex engineering structures,it is a critical problem to reasonably consider the randomness and multi-dimensional nature of ground motions.To this end,a proposed modeling strategy of multi-dimensional stochastic earthquakes is addressed in this study.This improved seismic model has several merits that enable it to better provide seismic analyses of structures.Specifically,at first,the ground motion model is compatible with the design response spectrum.Secondly,the evolutionary power spectrum involved in the model and the design response spectrum are constructed accordingly with sufficient consideration of the correlation between different seismic components.Thirdly,the random function-based dimension-reduction representation is applied,by which seismic modeling is established,with three elementary random variables.Numerical simulations of multi-dimensional stochastic ground motions in a specific design scenario indicate the effectiveness of the proposed modeling strategy.Moreover,the multi-dimensional seismic response and the global reliability of a high-rise frame-core tube structure is discussed in detail to further illustrate the engineering applicability of the proposed method.The analytical investigations demonstrate that the suggested stochastic model of multi-dimensional ground motion is available for accurate seismic response analysis and dynamic reliability assessment of complex engineering structures for performance-based seismic resistance design.

SEQUENTIAL RETRIEVAL OF B-TREES AND A FILE STRUCTURE WITH A DENSE B-TREE INDEX

A simple fast method is given for sequentially retrieving all the records in a B tree. A file structure for database is proposed. The records in its primary data file are sorted according to the key order. A B tree is used as its dense index. It is easy to insert, delete or search a record, and it is also convenient to retrieve records in the sequential order of the keys. The merits and efficiencies of these methods or structures are discussed in detail.

Analysis of multi-dimensional SAR for determining the thickness of thin sea ice in the Bohai Sea

Flat thin ice (<30 cm thick) is a common ice type in the Bohai Sea, China. Ice thickness detection is important to offshore exploration and marine transport in winter. Synthetic aperture radar (SAR) can be used to acquire sea ice data in all weather conditions, and it is a useful tool for monitoring sea ice conditions. In this paper, we combine a multi-layered sea ice electromagnetic (EM) scattering model with a sea ice thermodynamic model to assess the determination of the thickness of flat thin ice in the Bohai Sea using SAR at different frequencies, polarization, and incidence angles. Our modeling studies suggest that co-polarization backscattering coefficients and the co-polarized ratio can be used to retrieve the thickness of flat thin ice from C- and X-band SAR, while the co-polarized correlation coefficient can be used to retrieve flat thin ice thickness from L-, C-, and X-band SAR. Importantly, small or moderate incidence angles should be chosen to avoid the effect of speckle noise.

Coverless Information Hiding Based on the Molecular Structure Images of Material

The traditional information hiding methods embed the secret information by modifying the carrier,which will inevitably leave traces of modification on the carrier.In this way,it is hard to resist the detection of steganalysis algorithm.To address this problem,the concept of coverless information hiding was proposed.Coverless information hiding can effectively resist steganalysis algorithm,since it uses unmodified natural stego-carriers to represent and convey confidential information.However,the state-of-the-arts method has a low hidden capacity,which makes it less appealing.Because the pixel values of different regions of the molecular structure images of material(MSIM)are usually different,this paper proposes a novel coverless information hiding method based on MSIM,which utilizes the average value of sub-image’s pixels to represent the secret information,according to the mapping between pixel value intervals and secret information.In addition,we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the method.And the histogram of the Bag of words model(BOW)is used to determine the number of subimages in the image that convey secret information.Moreover,to improve the retrieval efficiency,we built a multi-level inverted index structure.Furthermore,the proposed method can also be used for other natural images.Compared with the state-of-the-arts,experimental results and analysis manifest that our method has better performance in anti-steganalysis,security and capacity.

STRUCTURE OF MESO-β AND –γ-SCALE ON SOUTH CHINA HEAVY RAINFALL ON 12～13 JUNE 2005 USING DUAL-DOPPLER RADAR

The three-dimensional wind fields of the heavy rain on 12-13 June 2005 in Guangdong province are retrieved and studied with the volume scan data of the dual-Doppler radar located in the cities of Meizhou and Shantou. It is shown that the meso-β-scale and meso-γ-scale convergence lines located in the convective system at the low and middle layer play an important role in the heavy rainfall. The convergence line is the initiating and maintaining mechanism of the rain. A three dimensional kinematic structure model is also given.

Similar Video Retrieval via Order-Aware Exemplars and Alignment

In this paper, we present machine learning algorithms and systems for similar video retrieval. Here, the query is itself a video. For the similarity measurement, exemplars, or representative frames in each video, are extracted by unsupervised learning. For this learning, we chose the order-aware competitive learning. After obtaining a set of exemplars for each video, the similarity is computed. Because the numbers and positions of the exemplars are different in each video, we use a similarity computing method called M-distance, which generalizes existing global and local alignment methods using followers to the exemplars. To represent each frame in the video, this paper emphasizes the Frame Signature of the ISO/IEC standard so that the total system, along with its graphical user interface, becomes practical. Experiments on the detection of inserted plagiaristic scenes showed excellent precision-recall curves, with precision values very close to 1. Thus, the proposed system can work as a plagiarism detector for videos. In addition, this method can be regarded as the structuring of unstructured data via numerical labeling by exemplars. Finally, further sophistication of this labeling is discussed.

长江上游卫星反演与再分析降水数据的适用性评估

为评估不同降水数据在长江上游的适用性,基于气象站点观测数据,采用多种评价指标,定量评估了卫星反演降水数据(IMERG-Final、GSMaP-Gauge)及再分析降水数据(ERA5-Land)在长江上游的应用精度,并分析了各降水数据在不同等级降水的误差结构。结果表明:3套降水数据均能准确捕捉流域降水东高西低的空间格局,与观测降水有着良好的相关性,且2015—2019年表现平稳,有可长期应用的潜力;各降水数据时间分辨率越高,误差相对越大,在流域地形变化剧烈的中部误差更大;对弱降水易错报高估,对强降水的低估随降水强度上升而加剧;两套卫星反演降水数据总体误差较小,适用性良好,IMERG-Final有更好的误差控制能力,GSMaP-Gauge对降水发生的识别更为准确;ERA5-Land明显高估流域降水,尤其在西南部地区。

无序无人机影像的并行化SfM三维重建方法

增量式运动恢复结构(ISfM)已成为无人机影像三维重建的关键技术。然而,大数据量、大重叠度和高分辨率的无序无人机影像导致的匹配对检索代价大、迭代优化误差累积和效率低的问题,使其难以满足大场景ISfM处理需求。本文提出联合全局描述子和图索引的无人机影像并行化SfM方法。针对影像特征数量大、影像检索编码本尺寸增加导致的匹配对检索效率低的问题,设计了联合全局描述子和图索引的高效影像检索方法,从而加速影像匹配。针对分块并行化SfM子场景合并存在同名点搜索效率低、内存消耗大、合并解算精度低的问题,设计了基于按需匹配图和双向重投影误差的子场景合并方法,实现无人机影像的并行化SfM重建。利用不同场景、不同采集方式获取的真实无人机影像进行试验,结果表明本文方法能够实现36~108倍加速比的匹配对检索,ISfM重建效率达到30倍加速,且相对定向和绝对定向精度与传统方法相当。

Alignment efficient image-sentence retrieval considering transferable cross-modal representation learning

Traditional image-sentence cross-modal retrieval methods usually aim to learn consistent representations of heterogeneous modalities,thereby to search similar instances in one modality according to the query from another modality in result.The basic assumption behind these methods is that parallel multi-modal data(i.e.,different modalities of the same example are aligned)can be obtained in prior.In other words,the image-sentence cross-modal retrieval task is a supervised task with the alignments as ground-truths.However,in many real-world applications,it is difficult to realign a large amount of parallel data for new scenarios due to the substantial labor costs,leading the non-parallel multi-modal data and existing methods cannot be used directly.On the other hand,there actually exists auxiliary parallel multi-modal data with similar semantics,which can assist the non-parallel data to learn the consistent representations.Therefore,in this paper,we aim at“Alignment Efficient Image-Sentence Retrieval”(AEIR),which recurs to the auxiliary parallel image-sentence data as the source domain data,and takes the non-parallel data as the target domain data.Unlike single-modal transfer learning,AEIR learns consistent image-sentence cross-modal representations of target domain by transferring the alignments of existing parallel data.Specifically,AEIR learns the image-sentence consistent representations in source domain with parallel data,while transferring the alignment knowledge across domains by jointly optimizing a novel designed cross-domain cross-modal metric learning based constraint with intra-modal domain adversarial loss.Consequently,we can effectively learn the consistent representations for target domain considering both the structure and semantic transfer.Furthermore,extensive experiments on different transfer scenarios validate that AEIR can achieve better retrieval results comparing with the baselines.

全文检索技术在图书检索中的应用

现有的图书检索方法多是对馆藏图书进行编目、分类、标注等处理后形成书目数据库,用户根据书名、作者和出版社等信息来检索图书。这种方式不能满足用户根据任意关键词来检索图书的需求,效率较低。全文检索是基于倒排索引技术对文本中的所有词组和关键词进行索引,支持快速检索到文本中任何一个单词和关键词。若将全文检索技术应用于图书检索中,可使用户根据任意关键词检索图书,可根据检索量和用户习惯推荐热门图书。文章介绍了如何在图书检索过程中应用全文检索技术,分析了全文检索引擎选择、图书文本解析、图书文本分词、图书索引设计、图书文档提交等主要过程,并给出了全文检索技术的最终实现效果,以期对提升图书检索系统的易用性提供一定借鉴。

基于树结构的代码检索方法

随着软件项目规模的不断增大和开源代码库的日益丰富,快速、准确的代码检索变得至关重要。传统基于关键词的搜索方法存在效率低和准确性不高等问题,因此文章提出了一种基于树结构的项目源代码检索方法,结合代码和注释构建多层次树结构,以帮助开发者更好地理解代码关系,进而准确定位所需代码。通过汇聚相似代码元素、过滤非相关代码,该方法可有效提高代码检索的准确性。实验结果显示,基于树结构的代码检索方法在准确率、召回率和F1值方面显著优于传统的文本匹配和图嵌入方法,可提供高效、准确的代码检索工具,从而提高开发效率和代码重用质量,有望在软件开发中产生积极影响。

数据结构在大数据存储与检索中的性能优化研究

随着大数据时代的到来,数据结构在大数据存储和检索中的性能优化显得尤为重要。文章旨在探讨和分析不同数据结构在大数据环境下的存储与检索性能,并提出相应的优化策略。首先介绍大数据的基本概念和特征,以及数据结构在大数据应用中的重要性。其次分析常见数据结构,如树形结构、图结构、哈希结构等在大数据存储与检索中的应用及其局限性。再次,文章提出几种针对特定数据结构的优化方法,包括改进算法、数据压缩、并行处理等,以提高存储效率,加快检索速度。最后,通过实验验证这些优化策略的有效性。

Remote Sensing of Tropical Cyclone Thermal Structure from Satellite Microwave Sounding Instruments: Impacts of Background Profiles on Retrievals

A variational retrieval system often requires background atmospheric profiles and surface parameters in its minimization process. This study investigates the impacts of specific background profiles on retrievals of tropical cyclone(TC) thermal structure. In our Microwave Retrieval Testbed(MRT), the K-means clustering algorithm is utilized to generate a set of mean temperature and water vapor profiles according to stratiform and convective precipitation in hurricane conditions. The Advanced Technology Microwave Sounder(ATMS) observations are then used to select the profiles according to cloud type. It is shown that the cloud-based background profiles result in better hurricane thermal structures retrieved from ATMS observations. Compared to the Global Positioning System(GPS) dropsonde observations, the temperature and specific humidity errors in the TC inner region are less than 3 K and 2.5 g kg^(–1), respectively, which are significantly smaller than the retrievals without using the cloud-based profiles. Further experiments show that all the ATMS observations could retrieve well both temperature and humidity structures, especially within the inner core region. Thus, both temperature and humidity profiles derived from microwave sounding instruments in hurricane conditions can be reliably used for evaluation of the storm intensity with a high fidelity.

Carbon Fiber Supported Binary Metal Sulfide Catalysts with Multi-Dimensional Structures for Electrocatalytic Nitrogen Reduction Reactions Over a Wide pH Range

Green and environmentally friendly electrocatalytic nitrogen(N_(2))fixation to synthesize ammonia(NH3)is recognized as an effective method to replace the traditional Haber-Bosch process.However,the difficulties in N_(2) adsorption and fracture of hard N≡N bond still remain major challenges in electrocatalytic N_(2) reduction reactions(NRR).From the perspectives of enhancing N_(2) adsorption and providing more catalytic sites,two-dimensional(2D)FeS_(2) nanosheets and three-dimensional(3D)metal organic framework-derived ZnS embedded within N-doped carbon polyhedras are grown on the carbon cloth(CC)template in this work.Thus,a composite NRR catalyst with multi-dimensional structures,which is signed as FeS_(2)/ZnS-NC@CC,is obtained for using over a wide pH range.The uniform distribution of hollow ZnS-NC frameworks and FeS_(2) nanosheets on the surface of CC largely increase the N_(2) enrichment efficiency and offer more active sites,while the CC skeleton acts as an independent conductive substrate and S-doping helps promote the fracture of N≡N bond during the NRR reaction.As a result,the FeS_(2)/ZnS-NC@CC electrode achieves a high Faraday efficiency of 46.84%and NH3 yield of 58.52μg h^(−1) mg^(−1) at-0.5 V vs.Ag/AgCl in 0.1 M KOH.Furthermore,the FeS_(2)/ZnS-NC@CC electrode displays excellent NRR catalytic activity in acidic and neutral electrolytes as well,which outperforms most previously reported electrocatalysts including noble metals.Therefore,this work provides a new way for the design of multi-dimensional electrocatalysts with excellent electrocatalytic efficiency and stability for NRR applications.

A Comprehensive Review on Multi-Dimensional Heat Conduction of Multi-Layer and Composite Structures:Analytical Solutions

Heat conduction in multi-layer and composite materials is one of the fundamental heat transfer problems in many industrial applications.Due to different materials types,interface conditions,and various geometries of these laminates,the heat conduction mechanism is more complicated than that of one-layer isotropic media.Analytical solutions are the best ways to study and understand such problems in depth.In this study,different existing analytical solutions for heat conduction in multi-layer and composite materials are reviewed and classified in rectangular,cylindrical,spherical,and conical coordinates.Applied boundary conditions,internal heat source,and thermal contact resistance as the most critical parameters in the solution complexity investigated in the literature,are discussed and summarized in different tables.Various types of multi-layer structures such as isotropic,anisotropic,orthotropic,and reinforced laminates are included in this study.It is found that although more than half a century has passed since the beginning of the research on heat transfer in multi-layer composites,new researches that can help with a better understanding in this area are still being offered.The challenges and shortcomings in this area are also discussed to guide future researches.

The organizational structure of post-coordinate retrieval systems

Addressing the limitations of previous studies,the authors suggest that the organizational structure of post-coordinate retrieval systems should be speculated according to the characteristics of the coordination methods and their basic components.Taking keyword search engines as an example,the authors analyse their components and features,examine retrieval-related factors and research issues,and point out that professionals in the field of information organization should play an important role in the study of post-coordinate systems by taking advantage of their rich experiences in research and practice.

基于ThinkPHP的农业机械化科研信息服务平台设计

为了提高农业机械化领域科研信息检索服务工作效率,更好地满足科研工作者需求,设计开发农业机械化科研信息服务系统(AMISP)具有重要意义。在明确农业机械化科研信息检索实际需求及设计与开发AMISP可行性的基础上,设计了基于B/S结构的4层ThinkPHP体系结构,以MySQL5.0为数据库服务器的AMISP平台,包括网站信息浏览、信息服务和后台信息管理3个主体功能模块,并设计了支撑平台运行的3个数据库及其14个数据表间的实体关系。平台不但具有专业领域网站的一般功能,且具有一站式学术信息检索服务功能,界面友好,信息交互功能强,可为农业机械化领域科技工作者提供高效、精准的专业化科研信息检索服务功能。

联合模态语义相似度修正的无监督跨模态哈希

基于哈希编码的无监督跨模态检索方法以其存储代价低、检索速度快、无需人工标注信息的优点受到了广泛的关注.最近的方法通过融合各模态的相似度信息构建联合模态相似度矩阵,用以指导哈希编码网络的学习.然而,这些方法未考虑数据特征空间的流形结构差异对相似度的影响而引入了噪声降低了模型的检索性能.本文提出了一种基于联合模态语义相似度修正的无监督跨模态哈希方法(JSSR),引入特征空间中的流形结构信息修正相似度矩阵中的噪声信息,同时增强语义相关样本的亲和力,使得生成的哈希码更具判别性和区分度.在典型的公开数据集NUS-WIDE和MIR Flickr上的实验结果表明,JSSR在跨模态检索精度上超越了现有的方法.