检索结果-南通市图书馆

同方期刊数据库

A General Linguistic Steganalysis Framework Using Multi-Task Learning

在线全文

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 2383-2399页

作者： lingyun xiang Rong Wang Yuhang Liu Yangfan Liu Lina Tan School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Computer Science and Electronic Engineering University of EssexColchesterCO43SQUK School of Computer Science Hunan University of Technology and BusinessChangsha410205China

Prevailing linguistic steganalysis approaches focus on learning sensitive features to distinguish a particular category of steganographic texts from non-steganographic texts,by performing binary *** it remains an unsolved problem and poses a significant threat to the security of cyberspace when various categories of non-steganographic or steganographic texts *** this paper,we propose a general linguistic steganalysis framework named LS-MTL,which introduces the idea of multi-task learning to deal with the classification of various categories of steganographic and non-steganographic ***-MTL captures sensitive linguistic features from multiple related linguistic steganalysis tasks and can concurrently handle diverse tasks with a constructed *** the proposed framework,convolutional neural networks(CNNs)are utilized as private base models to extract sensitive features for each steganalysis ***,a shared CNN is built to capture potential interaction information and share linguistic features among all ***,LS-MTL incorporates the private and shared sensitive features to identify the detected text as steganographic or *** results demonstrate that the proposed framework LS-MTL outperforms the baseline in the multi-category linguistic steganalysis task,while average Acc,Pre,and Rec are increased by 0.5%,1.4%,and 0.4%,*** ablation experimental results show that LS-MTL with the shared module has robust generalization capability and achieves good detection performance even in the case of spare data.

关键词： Linguistic steganalysis multi-task learning convolutional neural network(CNN) feature extraction detection performance

灭活植物乳杆菌对仔猪生长性能、血液生化指标及腹泻率的影响

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

饲料工业 2024年第10期45卷 26-31页

作者：胡虹刘德海冯菲马焕向凌云刘丽胡宜亮张秀江河南省科学院生物研究所有限责任公司河南郑州450008 河南省工业酶工程技术研究中心河南郑州450008 河南豫科检测有限公司河南郑州450008

试验主要研究灭活植物乳杆菌对仔猪生长性能、血液生化指标及腹泻率的影响。选用45头28日龄的健康杜×长×大三元杂交断奶仔猪,对照组饲喂基础饲粮,试验Ⅰ组在基础饲粮中添加0.3 g/kg天蚕素抗菌肽,试验Ⅱ组在基础饲粮中添加0.3 g/kg灭... 详细信息

试验主要研究灭活植物乳杆菌对仔猪生长性能、血液生化指标及腹泻率的影响。选用45头28日龄的健康杜×长×大三元杂交断奶仔猪,对照组饲喂基础饲粮,试验Ⅰ组在基础饲粮中添加0.3 g/kg天蚕素抗菌肽,试验Ⅱ组在基础饲粮中添加0.3 g/kg灭活植物乳杆菌。结果表明,试验Ⅰ组与对照组相比平均日增重(ADG)提高了15.56%(P0.05);试验Ⅱ组与对照组相比ADG提高了26.67%(P0.05);与对照组相比,试验Ⅱ组与对照组相比血样中葡萄糖含量提高了15.70%(P<0.05),尿素氮含量降低了42.70%(P<0.05)。由此可见,在基础日粮中添加灭活植物乳杆菌,对于仔猪具有良好的饲喂效果,可改善仔猪生长性能,降低仔猪腹泻率,改善仔猪健康。

关键词：灭活植物乳杆菌仔猪生长性能血液生化指标腹泻率

在线全文

学校读者我要写书评

暂无评论

激光雷达和相机的决策级融合目标检测方法

长沙理工大学学报（自然科学版） 2024年第1期21卷 133-140页

作者：龙科军余娟费怡向凌云骆嫚杨双辉长沙理工大学交通运输工程学院湖南长沙410114 长沙理工大学智能道路与车路协同湖南省重点实验室湖南长沙410114 长沙理工大学计算机与通信工程学院湖南长沙410114 东风悦享科技有限公司湖北武汉430058

【目的】激光雷达与相机这两类传感器检测数据格式不统一、分辨率不同,且数据级和特征级的融合计算复杂度高,故提出一种决策级的目标融合检测方法。【方法】对激光雷达与相机的安装位置进行联合标定,实现这两类传感器检测结果的坐标系转... 详细信息

【目的】激光雷达与相机这两类传感器检测数据格式不统一、分辨率不同,且数据级和特征级的融合计算复杂度高,故提出一种决策级的目标融合检测方法。【方法】对激光雷达与相机的安装位置进行联合标定,实现这两类传感器检测结果的坐标系转换;利用匈牙利算法将激光雷达点云检测目标框和相机图像检测目标框进行匹配,设定目标框重合面积阈值,检测获得目标物的位置、类型等。【结果】实车测试结果表明,根据检测目标检测框长宽比选取不同交并比阈值的方法使得车辆和行人的目标识别准确率分别提升了3.3%和5.3%。利用公开数据集KITTI对所提融合方法进行验证,结果表明,在3种不同难度等级场景下,所提融合方法的检测精度分别达到了75.42%、69.71%、63.71%,与现有常用的融合方法相比,检测精度均有所提升。【结论】这两类传感器的检测目标框重合面积阈值对决策级融合检测结果影响较大,根据检测目标检测框长宽比选取不同阈值可有效提升车辆和行人的目标识别准确率。决策级融合方法能准确匹配雷达和相机的检测目标,有效提升目标检测精度。

关键词：目标检测决策级融合匈牙利算法激光雷达相机环境感知

Instant Edit Propagation on Images Based on Bilateral Grid

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2019年第8期61卷 643-656页

作者： Feng Li Chaofeng Ou Yan Gui lingyun xiang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore639798Singapore

The ability to quickly and intuitively edit digital content has become increasingly important in our everyday ***,existing edit propagation methods for editing digital images are typically based on optimization with high computational cost for large ***,existing edit propagation methods are generally inefficient and highly ***,to improve edit efficiency,this paper proposes a novel edit propagation method using a bilateral grid,which can achieve instant propagation of sparse image ***,given an input image with user interactions,we resample each of its pixels into a regularly sampled bilateral grid,which facilitates efficient mapping from an image to the bilateral *** a result,all pixels with the same feature information(color,coordinates)are clustered to the same grid,which can achieve the goal of reducing both the amount of image data processing and the cost of *** then reformulate the propagation as a function of the interpolation problem in bilateral space,which is solved very efficiently using radial basis *** results show that our method improves the efficiency of color editing,making it faster than existing edit approaches,and results in excellent edited images with high quality.

关键词： Instant edit propagation bilateral grid radial basis function image editing

An Online Chronic Disease Prediction System Based on Incremental Deep Neural Network

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第4期67卷 951-964页

作者： Bin Yang lingyun xiang Xianyi Chen Wenjing Jia School of Design Jiangnan UniversityWuxi214122China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Electrical and Data Engineering University of Technology SydneySydney2000Australia

Many chronic disease prediction methods have been proposed to predict or evaluate diabetes through artificial neural ***,due to the complexity of the human body,there are still many challenges to face in that *** of them is how to make the neural network prediction model continuously adapt and learn disease data of different patients,*** paper presents a novel chronic disease prediction system based on an incremental deep neural *** propensity of users suffering from chronic diseases can continuously be evaluated in an incremental *** time,the system can predict diabetes more and more accurately by processing the feedback *** diabetes prediction studies are based on a common dataset,the Pima Indians diabetes dataset,which has only eight input *** order to determine the correlation between the pathological characteristics of diabetic patients and their daily living resources,we have established an in-depth cooperation with a hospital.A Chinese diabetes dataset with 575 diabetics was ***’data collected by different sensors were used to train the network *** evaluated our system using a real-world diabetes dataset to confirm its *** experimental results show that the proposed system can not only continuously monitor the users,but also give early warning of physiological data that may indicate future diabetic ailments.

关键词： Deep learning incremental learning network architecture design chronic disease prediction

An Encrypted Image Retrieval Method Based on SimHash in Cloud Computing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2020年第4期63卷 389-399页

作者： Jiaohua Qin Yusi Cao Xuyu xiang Yun Tan lingyun xiang Jianjun Zhang College of Computer Science and Information Technology Central South University of Forestry&TechnologyChangsha410004China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China College of Engineering and Design Hunan Normal UniversityChangsha410012China

With the massive growth of images data and the rise of cloud computing that can provide cheap storage space and convenient access,more and more users store data in cloud ***,how to quickly query the expected data with privacy-preserving is still a challenging in the encryption image data *** this goal,this paper proposes a ciphertext image retrieval method based on SimHash in cloud ***,we extract local feature of images,and then cluster the features by *** on it,the visual word codebook is introduced to represent feature information of images,which hashes the codebook to the corresponding ***,the image feature vector is generated by SimHash searchable encryption feature algorithm for similarity *** experiments on two public datasets validate the effectiveness of our ***,the proposed method outperforms one popular searchable encryption,and the results are competitive to the state-of-the-art.

关键词： Cloud computing SimHash encryption image retrieval K-means

Reversible Natural Language Watermarking Using Synonym Substitution and Arithmetic Coding

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2018年第6期55卷 541-559页

作者： lingyun xiang Yan Li Wei Hao Peng Yang Xiaobo Shen Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha 410114HunanChina School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha 410114HunanChina School of Traffic&Transportation Engineering Changsha University of Science&TechnologyChangsha 410114HunanChina Hunan Branch of CNCERT/CC Changsha 410004HunanChina School of Computer Science and Engineering Nanyang Technological University639798Singapore

For protecting the copyright of a text and recovering its original content harmlessly,this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution *** analyzing relative frequencies of synonymous words,synonyms employed for carrying payload are quantized into an unbalanced and redundant binary *** quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional ***,the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible *** the receiver side,the watermark and compressed data can be extracted by decoding the values of synonyms in the watermarked text,as a result of which the original context can be perfectly recovered by decompressing the extracted compressed data and substituting the replaced synonyms with their original *** results demonstrate that the proposed method can extract the watermark successfully and achieve a lossless recovery of the original ***,it achieves a high embedding capacity.

关键词： Arithmetic coding synonym substitution lossless compression reversible watermarking.

A Fast and Effective Multiple Kernel Clustering Method on Incomplete Data

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第4期67卷 267-284页

作者： lingyun xiang Guohan Zhao Qian Li Gwang-Jun Kim Osama Alfarraj Amr Tolba Changsha Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha410114China Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems Changsha University of Science and TechnologyChangsha410114China Faculty of Engineering and Information Technology Global Big Data Technologies CentreUniversity of Technology SydneyUltimoNSW2007Australia Department of Computer Engineering Chonnam National UniversityGwangju61186Korea Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Mathematics and Computer Science Faculty of ScienceMenoua UniversityShebin-El-kom32511Egyp

Multiple kernel clustering is an unsupervised data analysis method that has been used in various scenarios where data is easy to be collected but hard to be ***,multiple kernel clustering for incomplete data is a critical yet challenging *** the existing absent multiple kernel clustering methods have achieved remarkable performance on this task,they may fail when data has a high value-missing rate,and they may easily fall into a local *** address these problems,in this paper,we propose an absent multiple kernel clustering(AMKC)method on incomplete *** AMKC method rst clusters the initialized incomplete ***,it constructs a new multiple-kernel-based data space,referred to as K-space,from multiple sources to learn kernel combination ***,it seamlessly integrates an incomplete-kernel-imputation objective,a multiple-kernel-learning objective,and a kernel-clustering objective in order to achieve absent multiple kernel *** three stages in this process are carried out simultaneously until the convergence condition is *** on six datasets with various characteristics demonstrate that the kernel imputation and clustering performance of the proposed method is signicantly better than state-of-the-art ***,the proposed method gains fast convergence speed.

关键词： Multiple kernel clustering absent-kernel imputation incomplete data kernel k-means clustering

饲用凝结芽孢杆菌益生机理及发酵制备工艺研究进展

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

饲料工业 2022年第23期43卷 55-60页

作者：张秀江胡虹向凌云张志龙孙小玉河南省科学院生物研究所有限责任公司河南郑州450008 郑州市现代农业科技服务中心河南郑州450000

凝结芽孢杆菌是一种产乳酸的芽孢杆菌,除具有乳酸菌和芽孢杆菌共同的功效和良好的安全性外,还具备高抗逆性、强黏附性、分泌消化酶、产抑菌物质、易于发酵培养和贮藏稳定性好等优势。作为饲料添加剂,凝结芽孢杆菌具有促进动物生长、增... 详细信息

凝结芽孢杆菌是一种产乳酸的芽孢杆菌,除具有乳酸菌和芽孢杆菌共同的功效和良好的安全性外,还具备高抗逆性、强黏附性、分泌消化酶、产抑菌物质、易于发酵培养和贮藏稳定性好等优势。作为饲料添加剂,凝结芽孢杆菌具有促进动物生长、增强抗病能力等作用。文章对凝结芽孢杆菌的益生机理、发酵制备工艺进行了综述,以期为凝结芽孢杆菌的产品开发及其在畜禽养殖生产中更加合理的应用提供技术支持。

关键词：凝结芽孢杆菌益生机理菌种选育发酵工艺后处理工艺