A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row-column confusion and closed-loop bi-directional diffusion

Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.

Confusing Object Detection:A Survey

Confusing object detection(COD),such as glass,mirrors,and camouflaged objects,represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds,leveraging deep learning methodologies.Despite garnering increasing attention in computer vision,the focus of most existing works leans toward formulating task-specific solutions rather than delving into in-depth analyses of methodological structures.As of now,there is a notable absence of a comprehensive systematic review that focuses on recently proposed deep learning-based models for these specific tasks.To fill this gap,our study presents a pioneering review that covers both themodels and the publicly available benchmark datasets,while also identifying potential directions for future research in this field.The current dataset primarily focuses on single confusing object detection at the image level,with some studies extending to video-level data.We conduct an in-depth analysis of deep learning architectures,revealing that the current state-of-the-art(SOTA)COD methods demonstrate promising performance in single object detection.We also compile and provide detailed descriptions ofwidely used datasets relevant to these detection tasks.Our endeavor extends to discussing the limitations observed in current methodologies,alongside proposed solutions aimed at enhancing detection accuracy.Additionally,we deliberate on relevant applications and outline future research trajectories,aiming to catalyze advancements in the field of glass,mirror,and camouflaged object detection.

Candidate Expansion Algorithm Based on WeightedSyllable Confusion Matrix for Mandarin LVCSR

The inclusion of more potentially correct words in the candidate sets is important to improve the accuracy of Large Vocabulary Continuous Speech Recognition （LVCSR）. A candidate expansion algorithm based on the Weighted Syllable Confusion Matrix （WSCM） is proposed. First, WSCM is derived from a confusion network. Then, the reeognised candidates in the confusion network is used to conjeeture the most likely correct words based on WSCM, after which, the conjectured words are combined with the recognised candidates to produce an expanded candidate set. Finally, a combined model having mutual information and a trigram language model is used to rerank the candidates. The experiments on Mandarin film data show that an improvement of 9.57% in the character correction rate is obtained over the initial recognition performance on those light erroneous utterances.

Confusion of Life in The Catcher in the Rye:Viewed From Holden's Inner World

The Catcher in the Rye is a novel published in 1951.Since its publication,it has been listed as one of the world greatest masterpieces.The story in the novel deals with a rebellious teenage schoolboy Holden and his quixotic experiences in New York,taking place in December.Through the tone of a middle schoolboy,the author shows the deepest confusion of teenagers during 1950 s in their lives.It also exposes a clearer understanding of adolescents' particular psychology.This article gives a discussion of Holden's confusion of life viewed from his inner world.

Text retrieval algorithm that decreases confusion

To overcome the problem that the confusion between texts limits the precision in text re- trieval, a new text retrieval algorithm that decrease confusion （DCTR） is proposed. The algorithm constructs the searching template to represent the user＇ s searching intention through positive and negative training. By using the prior probabilities in the template, the supported probability and anti- supported probability of each text in the text library can be estimated for discrimination. The search- ing result can be ranked according to similarities between retrieved texts and the template. The com- plexity of DCTR is close to term frequency and mversed document frequency （TF-IDF）. Its distin- guishing ability to confusable texts could be advanced and the performance of the result would be im- proved with increasing of training times.

Meige Syndrome: An Eternal Diagnostic Confusion

Meige syndrome is an idiopathic dystonia characterized by combination of blepharospasm and involuntary movements of the lower facial and/or masticatory (jaw) muscles. The condition is rare and has a variety of clinical presentations which often lead to its misdiagnosis. We report a case of Meige syndrome repeatedly misdiagnosed and treated unsuccessfully as conversion disorder.

Centroids analysis for circle of confusion in reverse Hartmann test

The point spread function（PSF） is investigated in order to study the centroids algorithm in a reverse Hartmann test（RHT） system. Instead of the diffractive Airy disk in previous researches, the intensity of PSF behaves as a circle of confusion（CoC） and is evaluated in terms of the Lommel function in this paper. The fitting of a single spot with the Gaussian profile to identify its centroid forms the basis of the proposed centroid algorithm. In the implementation process, gray compensation is performed to obtain an intensity distribution in the form of a two-dimensional（2D） Gauss function while the center of the peak is derived as a centroid value. The segmental fringe is also fitted row by row with the one-dimensional（1D） Gauss function and reconstituted by averaged parameter values. The condition used for the proposed method is determined by the strength of linear dependence evaluated by Pearson＇s correlation coefficient between profiles of Airy disk and CoC. The accuracies of CoC fitting and centroid computation are theoretically and experimentally demonstrated by simulation and RHTs. The simulation results show that when the correlation coefficient value is more than 0.9999, the proposed centroid algorithm reduces the root-mean-square error（RMSE） by nearly one order of magnitude, thus achieving an accuracy of - 0.01 pixel or better performance in experiment. In addition, the 2D and 1D Gaussian fittings for the segmental fringe achieve almost the same centroid results, which further confirm the feasibility and advantage of the theory and method.

US STRATEGY TOWARD MIDDLE EAST:CONFUSION IN TRANSFORMATION

During the Cold War,the United States implemented an"offshore balance"policy in the Middle East,on the one hand,competing with the Soviet Union for a sphere of influence,and on the other hand,not directly engaging in the war.After the end of the Cold War,the US,as the sole super power,switched to the strategy of direct intervention in the Middle East.

Iatrogenic Horner's syndrome: A cause for diagnostic confusion in the emergency department

Horner＇s syndrome （HS） results from interruption of sympathetic nervous supply to the eye and manifests clinically with partial ptosis, miosis and enophthalmos, along with anhidrosis of face on the affected side.

The Reflection on Spiritual Confusion and the Desire for Return to Humanity in T.S.Eliot's The Love Song of J.Alfred Prufrock

Although in the name of love,The Love Song is actually a middle-aged man's internal monologue of his courage and cowardice.This essay will analyze the stream of consciousness of Prufrock and the world in which he lives,the author's ruthless exposure to society's emptiness and ultimate concern for human development,and poetic techniques he utilizes including metaphor,repetition,and allusion,to express his reflection on spiritual confusion and desire for return to human nature.

A Brief Discussion on the Causes and Countermeasures of College Students'Psychological Confusion and Mental Health Problems

College period is one of the most critical periods of one person’s life for it is an important period of establishing world concept,outlook on life and values.Various challenges and pressures have had a great impact on the mental health of college students.In that case,college students’psychological confusion and mental health problems occur frequently and the overall condition of college students’psychological problems is worrying.The mental health of college students has also attracted the attention of colleges and the society.Besides,the mental health education courses have been adopted to guide college students.This article aims to analyze the causes of college students’psychological confusion and mental health problems and also the obstacles or difficulties in solving them from the perspective of college students'cultivation of positive psychological quality and mental health education.And corresponding solutions from both the outside and personal perspectives.

Instance Reweighting Adversarial Training Based on Confused Label

Reweighting adversarial examples during training plays an essential role in improving the robustness of neural networks,which lies in the fact that examples closer to the decision boundaries are much more vulnerable to being attacked and should be given larger weights.The probability margin(PM)method is a promising approach to continuously and path-independently mea-suring such closeness between the example and decision boundary.However,the performance of PM is limited due to the fact that PM fails to effectively distinguish the examples having only one misclassified category and the ones with multiple misclassified categories,where the latter is closer to multi-classification decision boundaries and is supported to be more critical in our observation.To tackle this problem,this paper proposed an improved PM criterion,called confused-label-based PM(CL-PM),to measure the closeness mentioned above and reweight adversarial examples during training.Specifi-cally,a confused label(CL)is defined as the label whose prediction probability is greater than that of the ground truth label given a specific adversarial example.Instead of considering the discrepancy between the probability of the true label and the probability of the most misclassified label as the PM method does,we evaluate the closeness by accumulating the probability differences of all the CLs and ground truth label.CL-PM shares a negative correlation with data vulnerability:data with larger/smaller CL-PM is safer/riskier and should have a smaller/larger weight.Experiments demonstrated that CL-PM is more reliable in indicating the closeness regarding multiple misclassified categories,and reweighting adversarial training based on CL-PM outperformed state-of-the-art counterparts.

复杂地质条件下多级高边坡组合支护方案与稳定性预测研究

以镇赫高速陈贝屯至煤灰堡段为例,根据工程地质、边坡等级和边坡特性等因素对边坡不同剖面采用衡重式挡墙、俯斜式挡墙、桩+锚索、锚杆+面板等支护形式。从病害原因分析和处治手段出发,研究了多级高边坡支护的质量保证措施。基于LightGBM算法建立边坡稳定性预测模型,验证模型精确性后给出预测模型的特征相对重要性结果和预测结果。结果表明:建立预测模型可较好地预测边坡稳定性;影响边坡稳定性最关键的因素为中土体粘聚力,其次为边坡角β,孔隙压力比和土体重度对边坡稳定性影响不大;镇赫高速K2+051~K2+340段边坡稳定概率为0.9,失稳概率为0.1。本项目运营经验表明,组合支护方案及质量保障措施有效提高了项目施工质量、减少了返工现象,保证了项目的经济效益。

面向工业缺陷分类的交互式易混淆缺陷分离方法研究

在工业生产中会根据严重程度对缺陷做不同处理,所以需要对缺陷进行分类。但是,实际生产中经常因为存在一些易混淆缺陷而导致分类精度不够,使得在生产实践中只能对所有缺陷进行保守处理,带来很大人力成本和经济代价。为解决该问题,提出一种交互式易混淆缺陷分离方法,将少量易混淆缺陷从其他缺陷中分离出来,从而保证剩下的绝大部分缺陷的分类结果能被直接使用。首先,将训练数据中的易混淆缺陷挑选出来作为一个或多个新缺陷类别,称之为虚缺陷,从而使得训练所得网络能区分虚缺陷和其它类缺陷。其中,还设计了一套可视化界面辅助用户交互地挑选易混淆缺陷以构建虚类别。使用实际工业现场的CMOS缺陷数据进行有效性验证,结果表明所提方法能快速分类出易混淆缺陷,并保证剩余缺陷的分类精度满足工业应用要求。

计算机辅助下自体荧光图像定量结果与口腔白斑病上皮异常增生等级的相关性

目的·探究计算机辅助下自体荧光图像定量结果与口腔白斑病上皮异常增生等级的相关性。方法·纳入2016年4月—2024年1月于上海交通大学医学院附属第九人民医院口腔黏膜病科就诊的口腔白斑病患者357例。利用手持自体荧光仪器获取患者病损的自体荧光图像,将自体荧光图像转为灰度图像,获得量化指标。在Python中拟合有序多元Logistic回归模型,绘制累积概率图。将数据集划分训练集和测试集,生成决策树,调整不同的超参数,获得最佳的模型效果。计算准确度、精确度和F1分值。利用混淆矩阵对模型性能进行可视化呈现。结果·随着上皮异常增生程度的增加,相对色阶平均值呈现下降趋势。在上皮异常增生二分类中累积概率图不同类别曲线之间无重叠,在四分类中仅上皮重度异常增生与其他类别曲线有重叠,说明模型的区分能力较好。在二分类病理等级中,当训练集和测试集比例为4∶1、决策树最大深度为2时,准确度、精确度、F1分值可达到较高,分别为0.792、0.801和0.795。在四分类病理等级中,当训练集和测试集比例为9∶1、决策树最大深度为4时,准确度、精确度、F1分值可达到较高,分别为0.611、0.537和0.569。结论·口腔黏膜病专科医师可将计算机辅助下自体荧光图像定量结果作为参考依据,预测口腔白斑病患者上皮异常增生程度,监控患者癌变风险。

移动群智感知中基于网格混淆的位置隐私保护

针对现有移动群智感知(mobile crowd sensing,MCS)面临的隐私泄露问题,引入一种混合式区块链架构来构建系统,实现MCS的去中心化,并通过私有区块链保护工人隐私记录。采用无证书签密实现用户数据传输过程中的机密性和完整性,保证用户信息的安全性。为了降低位置隐私暴露的风险,提出一种基于网格混淆的位置隐私保护方案(location privacy protection scheme based on grid obfuscation,LPPSGO)。该方案通过H3索引系统划分多精度六边形网格,实现工人位置的空间隐匿,工人可以根据个性化隐私需求扰动自身位置,无须担心真实位置的暴露。仿真实验结果表明,LPPSGO能有效提高MCS系统的任务分配成功率,减少时间开销,与其他位置保护方案相比,安全性更强,覆盖性能更好。

基于优化极限学习机模型的边坡稳定性预测研究

边坡稳定性预测对工程安全及地质灾害防治极其重要,目前机器学习在边坡稳定性预测较广泛,例如BP神经网络、支持向量机(SVM)、极限学习机(ELM)等。但传统的ELM模型在预测边坡稳定性时存在易陷入局部最小值、难以选择合适学习率的问题,针对此问题,提出了一种基于主成分分析法(PCA)和爬行动物搜索法(RSA)并行优化极限学习机(ELM)的边坡稳定性预测模型。此模型利用PCA算法对数据进行降维,减少数据的冗余性,并利用RSA算法优化ELM模型的输入层权值和隐含层偏置,极大地提高了模型的预测精度和预测效率。将传统的ELM模型、RSA-ELM模型、PCA-SVM模型及PCA-RSA-ELM 4种模型进行对比,从而得到PCA-RSA-ELM模型在边坡稳定性预测这类问题上的精确性更高,为边坡稳定性预测分析提供新的思路,对防灾减灾及保护国民经济安全具有重大意义。

基于分层的边折叠节点链接法

为兼顾网络结构地理空间特征的同时,减轻视觉混乱和密度位置信息丢失的问题,文中对节点链接方法进行改进,给出基于分层的边折叠网络可视化方法。首先,在对节点位置布局时,采用位置固定的节点链接法保证地理空间特征;其次,结合用户交互,从边折叠的角度改进节点链接法,从而缓解常规节点链接法的遮挡交叉和信息丢失问题;最后,以中国航线网络进行实例验证。结果表明,与节点位置固定的节点链接法和基于力引导的节点链接法相比,改进的节点链接法极大地降低了交叉点数量,能够有效缓解边遮挡引起的视觉混乱问题,提高网络可视化的效果和准确性。

基于智能优化算法的边坡稳定性预测方法研究

针对边坡稳定性预测中数据分析片面、模型预测精度低的问题,基于302个边坡案例,选取6个变量特征,利用麻雀搜索算法(SSA)更新BP神经网络的敏感因子,建立SSA-BP边坡稳定性预测模型。采用混淆矩阵、受试者工作特征(ROC)曲线及曲线下面积A_(UC)值作为衡量指标,通过五折交叉验证法提高模型的泛化能力并与RF、BP、SVM、PSO-BP、GA-BP和LSTM 6种机器学习算法进行预测效果对比。结果表明,SSA-BP模型的A_(UC)值、准确率和F_1分数均最高,分别为91.90%、85.81%和85.87%,相较于优化前的BP网络A_(UC)值提高了23%。经典算例证明SSA-BP预测模型与ABAQUS计算的安全系数相近,并可给出可靠的预测结果,为岩土工程中边坡稳定性预测提供了一种新方法。

国家队运动员身份混同引发的商业代言法律争议

近年来,随着社会经济的不断发展,国家队运动员身份发生了重大变化,产生了身份混同这一复杂的问题,进而可能导致对身份法律性质的认识谬误、多重身份规范适用冲突等诸多法律问题。运用文献分析法,结合国家队队员参与商业代言活动所引发的相关法律争议,提出相关治理建议,以期为完善我国体育纠纷解决机制和落实保障运动员合法身份权益建言献策。具体来说,应坚持确立身份规则这一出发点和落脚点,在此基础上明确国家队运动员身份权利的内容与边界,以及试行运动员商业开发活动招标制度。