Intelligent 3D garment system of the human body based on deep spiking neural network

Background Intelligent garments,a burgeoning class of wearable devices,have extensive applications in domains such as sports training and medical rehabilitation.Nonetheless,existing research in the smart wearables domain predominantly emphasizes sensor functionality and quantity,often skipping crucial aspects related to user experience and interaction.Methods To address this gap,this study introduces a novel real-time 3D interactive system based on intelligent garments.The system utilizes lightweight sensor modules to collect human motion data and introduces a dual-stream fusion network based on pulsed neural units to classify and recognize human movements,thereby achieving real-time interaction between users and sensors.Additionally,the system incorporates 3D human visualization functionality,which visualizes sensor data and recognizes human actions as 3D models in real time,providing accurate and comprehensive visual feedback to help users better understand and analyze the details and features of human motion.This system has significant potential for applications in motion detection,medical monitoring,virtual reality,and other fields.The accurate classification of human actions contributes to the development of personalized training plans and injury prevention strategies.Conclusions This study has substantial implications in the domains of intelligent garments,human motion monitoring,and digital twin visualization.The advancement of this system is expected to propel the progress of wearable technology and foster a deeper comprehension of human motion.

Exploring the Association between Climate Change and Human Development: A Visual Analytics Study

This study explores the complex relationship between climate change and human development. The aim is to understand how climate change affects human development across countries, regions, and the global population. Visual analytics were used to examine the impact of various climate change indicators on different aspects of human development. The study highlights the urgent need for climate change action and encourages policymakers to make decisive moves. Climate change adversely affects numerous aspects of daily life, leading to significant consequences that must be addressed through policy changes and global governance recommendations. Key findings include that regions with higher CO2 emissions experience a significantly higher incidence of life-threatening diseases compared to regions with lower emissions. Additionally, higher CO2 emissions correlate with consistent death rates. Increased pollution exposure is associated with a higher prevalence of life-threatening diseases and higher rates of malnutrition. Moreover, greater mineral depletion is linked to more frequent life-threatening diseases, suggesting that industrialization contributes to adverse health effects. These results provide valuable insights for policy and decision-making aimed at mitigating the impact of climate change on human development.

Magnetic resonance diffusion tensor imaging and diffusion tensor tractography of human visual pathway

AIM: To investigate the visual pathway in normal subjects and patients with lesion involved by diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT). METHODS: Thirty normal volunteers, 3 subjects with orbital tumors involved the optic nerve (ON) and 33 subjects with occipital lobe tumors involved the optic radiation (OR) (10 gliomas, 6 meningiomas and 17 cerebral metastases) undertook routine cranium magnetic resonance imaging (MRI), DTI and DTT. Visual pathway fibers were analyzed by DTI and DTT images. Test fractional anisotropy (FA) and mean diffusivity (MD) values in different part of the visual pathway. RESULTS: The whole visual pathway but optic chiasm manifested as hyperintensity in FA maps and homogenous green signal in the direction encoded color maps. The optic chiasm did not display clearly. There was no significant difference between the bilateral FA values and MD values of normal visual pathway but optic chiasm, which the FA values tested were much too low (all P>0.05). The ONs of subjects with orbital tumors were compressed and displaced. Only one subject had lower FA values and higher MD values. OR of 9 gliomas subjects were infiltrated, with displacement in 2 and disruption in 7 subjects. All OR in 6 meniongiomas subjects were displaced. OR in 17 cerebral metastases subjects all developed displacement while 7 of them had disruption also. CONCLUSION: MR-DTI is highly sensitive in manifesting visual pathway. Visual pathway can be analyzed quantitatively in FA and MD values. DTT supplies accurate three dimensional conformations of visual pathway. But optic chiasm's manifestation still needs to improve.

Human melanopsin-AAV2/8 transfection to retina transiently restores visual function in rd1 mice

AIM： To explore whether ectopic expression of human melanopsin can effectively and safely restore visual function in rd1 mice.· METHODS： Hematoxylin-eosin staining of retinal sections from rd1 mice was used to detect the thickness of the outer nuclear layer to determine the timing of surgery. We constructed a human melanopsinAAV2/8 viral vector and injected it into the subretinal space of rd1 mice. The Phoenix Micron IV system was used to exclude the aborted injections, and immunohistochemistry was used to validate the ectopic expression of human melanopsin. Furthermore, visual electrophysiology and behavioral tests were used to detect visual function 30 and 45 d after the injection. The structure of the retina was compared between the human melanopsin-injected group and phosphate buffer saline（PBS）-injected group.·RESULTS： Retinas of rd1 mice lost almost all of their photoreceptors on postnatal day 28（P28）. We therefore injected the human melanopsin-adeno-associated virus（AAV） 2/8 viral vector into P30 rd1 mice. After excluding aborted injections, we used immunohistochemistry of the whole mount retina to confirm the ectopic expression of human melanopsin by co-expression of human melanopsin and YFP that was carried by a viral vector. At30 d post-injection, visual electrophysiology and the behavioral test significantly improved. However,restoration of vision disappeared 45 d after human melanopsin injection. Notably, human melanopsin-injected mice did not show any structural differences in their retinas compared with PBS-injected mice.·CONCLUSION： Ectopic expression of human melanopsin effectively and safely restores visual function in rd1

Adaptive image enhancement algorithm based on fuzzy entropy and human visual characteristics

To overcome the shortcomings of the Lee image enhancement algorithm and its improvement based on the logarithmic image processing(LIP) model, this paper proposes what we believe to be an effective image enhancement algorithm. This algorithm introduces fuzzy entropy, makes full use of neighborhood information, fuzzy information and human visual characteristics.To enhance an image, this paper first carries out the reasonable fuzzy-3 partition of its histogram into the dark region, intermediate region and bright region. It then extracts the statistical characteristics of the three regions and adaptively selects the parameter αaccording to the statistical characteristics of the image’s gray-scale values. It also adds a useful nonlinear transform, thus increasing the ubiquity of the algorithm. Finally, the causes for the gray-scale value overcorrection that occurs in the traditional image enhancement algorithms are analyzed and their solutions are proposed.The simulation results show that our image enhancement algorithm can effectively suppress the noise of an image, enhance its contrast and visual effect, sharpen its edge and adjust its dynamic range.

New algorithm for infrared small target image enhancement based on wavelet transform and human visual properties

The key to the wavelet based denoising teehniquea is how to manipulate the wavelet coefficients. By referring to the idea of Inclusive-OR in the design of circuits, this paper proposes a new algorithm called wavelet domain Inclusive-OR denoising algorithm（WDIDA）, which distinguishes the wavelet coefficients belonging to image or noise by considering their phases and modulus maxima simultaneously. Using this new algorithm, the denoising effects are improved and the computation time is reduced. Furthermore, in order to enhance the edges of the image but not magnify noise, a contrast nonlinear enhancing algorithm is presented according to human visual properties. Compared with traditional enhancing algorithms, the algorithm that we proposed has a better noise reducing performanee , preserving edges and improving the visual quality of images.

A ROBUST ADAPTIVE VIDEO ENCODER BASED ON HUMAN VISUAL MODEL

A Robust Adaptive Video Encoder (RAVE) based on human visual model is proposed. The encoder combines the best features of Fine Granularity Scalable (FGS) coding, framedropping coding, video redundancy coding, and human visual model. According to packet loss and available bandwidth of the network, the encoder adjust the output bit rate by jointly adapting quantization step-size instructed by human visual model, rate shaping, and periodically inserting key frame. The proposed encoder is implemented based on MPEG-4 encoder and is compared with the case of a conventional FGS algorithm. It is shown that RAVE is a very efficient robust video encoder that provides improved visual quality for the receiver and consumes equal or less network resource. Results are confirmed by subjective tests and simulation tests.

Human Visual Attention Mechanism-Inspired Point-and-Line Stereo Visual Odometry for Environments with Uneven Distributed Features

Visual odometry is critical in visual simultaneous localization and mapping for robot navigation.However,the pose estimation performance of most current visual odometry algorithms degrades in scenes with unevenly distributed features because dense features occupy excessive weight.Herein,a new human visual attention mechanism for point-and-line stereo visual odometry,which is called point-line-weight-mechanism visual odometry(PLWM-VO),is proposed to describe scene features in a global and balanced manner.A weight-adaptive model based on region partition and region growth is generated for the human visual attention mechanism,where sufficient attention is assigned to position-distinctive objects(sparse features in the environment).Furthermore,the sum of absolute differences algorithm is used to improve the accuracy of initialization for line features.Compared with the state-of-the-art method(ORB-VO),PLWM-VO show a 36.79%reduction in the absolute trajectory error on the Kitti and Euroc datasets.Although the time consumption of PLWM-VO is higher than that of ORB-VO,online test results indicate that PLWM-VO satisfies the real-time demand.The proposed algorithm not only significantly promotes the environmental adaptability of visual odometry,but also quantitatively demonstrates the superiority of the human visual attention mechanism.

Human Visual Acuity in Analysis of Intervention in the Landscape of Coxilha Rica/Brazil

The Drovers’ Paths are remnants of important land access roads from Rio Grande do Sul to São Paulo at the time of Colonial Brazil. They were built and used between the 18th and 20th centuries, particularly in the region of Coxilha Rica. The main objective of this research is to develop a method for decision-making applied to the territorial landscape management in the Coxilha Rica. The method consisted of generating criteria to map the visibility spot reached from the main selected points;define the human visual acuity, realize bibliographic research, use cartographic and historical documents, inter-views, as well as field surveys that enabled the identification, characterization and mapping of historical farms and drovers’ paths. After data processing, the information was entered into the cartographic database;the data were cross-checked and analysis was made of the visibility of the surrounding farms and stone-walled corridors. Quality assessments showed that, with the visibility polygons, and through the use of cartographic tools, we could cross-check between different levels of information and analyze landscape intervention alternatives in order to minimize environmental impacts. When applying the method in the Coxilha Rica it was possible mapping the visibility polygon, taking human visual acuity into consideration, based on historical farms and stone-walled corridors;and making spatial analyses to explore alternatives to intervention (installation of power transmission systems) in order to preserve the scenic environment of the region. In the end, the decision was by does not construct the system.

Evaluating Methods of Visual Assistance for Workers to Improve Quality and Usability in Individualized Kitchen Cabinet Assembly

In times of digitalisation, visual assistance systems in assembly are increasingly important. The design of these assembly systems needs to be highly complex to meet the requirements. Due to the increasing number of variants in production processes, as well as shorter innovation and product life cycles, assistance systems should improve quality and reduce complexity of assembly processes. However, many large kitchen manufacturers still assemble kitchen cabinets manually, due to the high variety of components, such as rails and fittings. This paper focuses on the analysis and evaluation of virtual assistance systems to improve quality and usability in individualised kitchen cabinet assembly processes at a large German manufacturer. A solution is identified and detailed.

基于文献计量学对我国护理人力资源研究的可视化分析

目的:分析护理人力资源研究热点及变化趋势,为后续研究提供参考依据。方法:检索2012-2024年中国知网、万方数据、维普、中国生物医学文献数据库中护理人力资源相关文献,应用CiteSpace 6.2.R4、VOSviewer 1.6.18对纳入文献进行可视化分析。结果:纳入分析的文献共2203篇,发文量呈现阶段波动,成果主要集中在护理领域且价值较高,各研究团队、机构间缺乏紧密合作。关键词分析发现,以人力资源、护理、护理管理等出现频率较高,共产生16个聚类和24个突现词。结论:护理人力资源研究是近几年来护理管理领域的研究热点,利用人工智能及大模型等进行护理人力需求预测、建立符合护理人力劳动价值的绩效考核优化制度及推进中医护理人才职称体系构建等将成为未来的发展趋势。

基于Visualization Toolkit的数字化人体骨骼系统的重建与可视化

在人体骨骼系统的三维可视化过程中 ,将二维CT数据重建生成理想的三维骨骼数据是非常重要的一环。作者应用可视化工具VisualizationToolkit (VTK)和VC ++实现了二维数据的三维重建、面片削减、连通性检测、三维平滑等一系列功能。与利用OpenGL等工具重建得到的骨骼数据相比 ,不但准确度和视觉效果有了显著改善 ,数据量也大大减小。VTK在人体骨骼系统的重建及处理工作中取得的良好效果表明 ,它是医学图像重建和处理的有力工具之一 ,具有使用灵活 ,功能强大的优点 ,值得推广。

基于Agent的Visual Basic人性化软件编程技术

Agent具有自治性、交互性、协作性、可通信性等特性,MicrosoftAgent可提供人性化编程技术,可使计算机具有更好的人机交互性,其应用前景相当广阔。论文将介绍VB6.0调用AgentActiveX控件进行编程的基本方法,如Word文语转换、语音识别等,并给出编程实例,希望能够起到抛砖引玉的作用。

基于知识图谱的国内Human Library研究现状可视化分析

本文以2005-2014年CNKI数据库中收录的主题为Human Library的文献为数据源,借助信息可视化软件——Cite SpaceⅡ绘制相应的知识图谱,通过对发文作者及研究机构知识图谱的分析,确定了该领域的代表作者、核心研究机构及其相互关系;通过对高频关键词聚类知识图谱的分析,识别出Human Library研究的4个热点研究主题,最后,本文通过对突现关键词的解读探析了该领域的前沿研究趋势。

基于Web GIS的非遗数据管理研究——以皮影GIS系统为例

文章在结合皮影Web GIS系统建设实践的基础上,探索基于Web GIS技术的非遗数据管理路径与方法。在传统关系型数据库的基础上,将空间元素进行经纬度元素的对应扩展,并添加到元数据方案中,使之与时间元素、属性元素一并构成新的元数据方案。通过网络地图提供的API接口,调用本地服务器中的数据,即可在网络地图中实现数据管理。利用大型网络地图对非遗数据进行管理具有使用简便、易维护、成本低、数据可移植等优势;同时,能有效实现数据可视化呈现、可视化挖掘、可视化分析,以及非遗项目的可视化濒危预警等功能。

基于Visual Foxpro 6.0的人事管理系统设计

根据企事业单位人力资源管理的需要,利用Visual Foxpro 6.0数据库应用软件,在对职工各方面情况进行详细分类的基础上,经过系统分析与设计,开发了某单位的人事管理系统;该系统可对人员信息进行采集、存储、加工、维护和使用,并通过信息录入、查询、打印、更新等功能的运用,实现人员信息的计算机化管理,提高信息的准确性和工作效率。

基于知识检索的多模态人物交互检测

人物交互(human-object interaction,HOI)检测在复杂场景理解中发挥着至关重要的作用。目前的大多数方法都以一阶段的方式将参数交互查询直接映射到一组HOI预测中,这导致丰富的交互结构没有被充分挖掘和利用。对此可以通过多模态数据获取更多维度的信息,从而更全面地理解人物之间的交互行为。为此设计了一种Transformer风格的HOI检测器,该检测器基于查询的方式检索对比语言图像预训练(CLIP)知识,然后执行交互建议生成,通过结构感知网络将非参数交互建议转换为HOI预测。本文创新性地将CLIP知识迁移到HOI检测中,并通过对整体语义结构和局部空间结构进行额外编码提高了预测结果的准确性。实验结果表明,所提模型在公共数据集V-COCO上的准确率达到了64.83%,在HICO-DET数据集上的准确率达到了28.78%,与现有的HOI检测算法相比展现出优越的性能,证明了该算法的有效性。

Visualizing Association Rules Using Linked Matrix,Graph, and Detail Views

Although association rule mining is an important pattern recognition and data analysis technique, extracting and finding significant rules from a large collection has always been challenging. The ability of information visualization to enable users to gain an understanding of high dimensional and large-scale data can play a major role in the exploration, identification, and interpretation of association rules. In this paper, we propose a method that provides multiple views of the association rules, linked together through a filtering mechanism. A visual inspection of the entire association rule set is enabled within a matrix view. Items of interest can be selected, resulting in their corresponding association rules being shown in a graph view. At any time, individual rules can be selected in either view, resulting in their information being shown in the detail view. The fundamental premise in this work is that by providing such a visual and interactive representation of the association rules, users will be able to find important rules quickly and easily, even as the number of rules that must be inspected becomes large. A user evaluation was conducted which validates this premise.

Rate Control Algorithm of Wireless Video Based on Visual Saliency Map Model

In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.