Women in visual neural regeneration research

The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).

A Survey of Time Series Data Visualization Methods

In the era of big data,the general public is more likely to access big data,but they wouldn’t like to analyze the data.Therefore,the traditional data visualization with certain professionalism is not easy to be accepted by the general public living in the fast pace.Under this background,a new general visualization method for dynamic time series data emerges as the times require.Time series data visualization organizes abstract and hard-to-understand data into a form that is easily understood by the public.This method integrates data visualization into short videos,which is more in line with the way people get information in modern fast-paced lifestyles.The modular approach also facilitates public participation in production.This paper summarizes the dynamic visualization methods of time series data ranking,studies the relevant literature,shows its value and existing problems,and gives corresponding suggestions and future research prospects.

DAViS:a unified solution for data collection, analyzation,and visualization in real‑time stock market prediction

The explosion of online information with the recent advent of digital technology in information processing,information storing,information sharing,natural language processing,and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content.For example,a typical stock market investor reads the news,explores market sentiment,and analyzes technical details in order to make a sound decision prior to purchasing or selling a particular company’s stock.However,capturing a dynamic stock market trend is challenging owing to high fluctuation and the non-stationary nature of the stock market.Although existing studies have attempted to enhance stock prediction,few have provided a complete decision-support system for investors to retrieve real-time data from multiple sources and extract insightful information for sound decision-making.To address the above challenge,we propose a unified solution for data collection,analysis,and visualization in real-time stock market prediction to retrieve and process relevant financial data from news articles,social media,and company technical information.We aim to provide not only useful information for stock investors but also meaningful visualization that enables investors to effectively interpret storyline events affecting stock prices.Specifically,we utilize an ensemble stacking of diversified machine-learning-based estimators and innovative contextual feature engineering to predict the next day’s stock prices.Experiment results show that our proposed stock forecasting method outperforms a traditional baseline with an average mean absolute percentage error of 0.93.Our findings confirm that leveraging an ensemble scheme of machine learning methods with contextual information improves stock prediction performance.Finally,our study could be further extended to a wide variety of innovative financial applications that seek to incorporate external insight from contextual information such as large-scale online news articles and social media data.

Measurement Analysis and Evaluation of Twenty- Five Years of Chinese Mathematics Textbooks: Visual Analysis Based on CiteSpace Knowledge Graph (1999-2024)

At present,textbooks based on core literacy have become the inevitable demands of China’s curriculum reform,and the literacy of textbook goal construction is the key to the implementation of core literacy requirements,which is a huge challenge for textbook compilers.In this paper,we use the visual metrology of the CiteSpace knowledge graph to analyze Chinese mathematics textbooks(1999-2024),hoping to guide the future direction of Chinese mathematics textbook research.

Real-Time Data and Visualization Monitoring of Computer Numerical Control Machine Tools Based on Hyper Text Markup Language 5

In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.

Real-Time Grouting Monitoring and Visualization Analysis System for Dam Foundation Curtain Grouting

A real-time monitoring and 3D visualization analysis system is proposed for dam foundation curtain grouting. Based on the real-time control technology, the optimization method and the set theory, a mathematical model of the system is established. The real-time collection and transmission technology of the grouting data provides a data foundation for the system. The real-time grouting monitoring and dynamic alarming method helps the system control the grouting quality during the grouting process, thus, the abnormalities of grouting, such as jacking and hydraulic uplift, can be effectively controlled. In addition, the 3D grouting visualization analysis technology is proposed to establish the grouting information model(GIM). The GIM provides a platform to visualize and analyze the grouting process and results. The system has been applied to a hydraulic project of China as a case study, and the application results indicate that the real-time grouting monitoring and 3D visualization analysis for the grouting process can help engineers control the grouting quality more efficiently.

Real-time Visualization of Urban with Gigantic Amount of Detailed Buildings

Complex urban scenery is generally composed of gigantic amount of detailed buildings, efficient representation and rendering are essential for its visualization. We present an accelerating method for urban visualization. Our approach can optimize the organization of models in accordance with the quadtree based terrain, which makes the parallelization easier. Through minimizing the draw call within one rendering process, our approach can reduce the time cost of each frame and improve the framerate greatly. Hereby, our system can handle large-scale detailed models with high diversity and also can afford the ability to adjust the rendering strategy automatically according to the state of the hardware.

Association between tear film break up time and blink interval in visual display terminal users

AIM：To investigate the association between tear film break up time（TBUT）and blinking interval in visual display terminal（VDT）users.METHODS：Nine hundred and thirty VDT users underwent dry eye testing,and functional visual acuity（FVA）test.The blinking interval during FVA was compared with TBUT.Subjects with longer blinking interval than TBUT were considered as unstable tear film.Logistic regression analysis revealed the risk factors for unstable tear group.RESULTS：Among 930 workers,858 subjects（92.3%）participated in this study.Almost 80% of the subjects were categorized into the unstable tear group.Unstable tear group has significantly lower Schirmer values and TBUT（17.5±11.6 vs 21.1±11.5 mm,3.7±2.6 vs 5.7±2.7s,both P〈0.001）.There were no significant differences in epithelial staining or severity of symptoms.Logistic regression showed that over 40y was a risk for being unstable tear group[odds ratio（OR）=1.53;95%confidence interval（CI）=1.06-2.20].Contact lens use was protective factor for being in the unstable tear group（OR=0.37;95%CI=0.26-0.53）.CONCLUSION：Subjects with shorter TBUT than blinking interval are prevalent among VDT users.Subjects over the age of 40 shows an increased risk for unstable tear film.

Comparison between Auditory and Visual Simple Reaction Times

Objective: The purpose of this study was to find out whether the simple reaction time was faster for auditory or visual stimulus and the factors responsible for improving the performance of the athlete. Methodology: 14 subjects were as- signed randomly into groups consisting of 2 members. Both the members from each group performed both the visual and auditory tests. The tests were taken from the DirectRT software program from a laptop. The DirectRT software consists of Testlabvisual and Testlabsounds to test the reaction times to visual and auditory stimuli. The 2 members from each group completed both the visual and auditory reaction times, the data was taken and the mean reaction time was calculated excluding the first and last values. Results: The results show that the mean visual reaction time is around 331 milliseconds as compared to the mean auditory reaction time of around 284 milliseconds. Conclusion: This shows that the auditory reaction time is faster than the visual reaction time. And also males have faster reaction times when compared to females for both auditory as well as visual stimuli.

VISUALIZATION OF FLOW STRUCTURES IN A TURBULENT BOUNDARY LAYER USING A NEW TECHNIQUE

In this paper, an experimental investigation on the flow structures in a turbulent bounda- ry layer employing a special laser light sheet-Hydrogen bubble flow visualization technique is described. It is observed that the high/low speed streaks are directly related to the hairpin or horseshoe-like vortices. This observation can give a better understanding of the physical mechanism in the turbulent boundary layer.

Study of real-time LWD data visual interpretation and geo-steering technology

LWD（logging while drilling） data has been used to explore complex subtle reservoirs by realtime visual interpretation and geo-steering.The method comprises of computer communication,well log data processing,formation recognition,reservoir modeling and model updating in real time.We studied the key technologies related to real-time LWD data visual interpretation and geo-steering and developed computer software with Chinese intellectual property rights covering the following important aspects： 1） real-time computer communication of well site LWD data;2） visualization of geological model and borehole information;3） real-time interpretation of LWD data;4） real-time geological model updating and geo-steering technology.We use field application examples to demonstrate the feasibility and validity of the proposed technologies.

An improved smoke-wire flow visualization technique using capacitor as power source

An improved smoke-wire flow visualization technique using a large capacitor as the power source was proposed. Electric current discharged from capacitors was used to heat a fine metal wire suspended in the flow field. The oil droplets attached to the wire were vaporized and smoke filaments followed the flow motions. A digital camera was used to record the images of the smoke filaments. The actions of discharging and camera shutter were triggered by signals from a microcontroller to ensure the accurate timing. Clear images of the streaklines were captured at a freestream velocity up to 12.9 m/s, much higher than the limits of the existing techniques.

Bifurcation analysis of visual angle model with anticipated time and stabilizing driving behavior

In the light of the visual angle model(VAM),an improved car-following model considering driver's visual angle,anticipated time and stabilizing driving behavior is proposed so as to investigate how the driver's behavior factors affect the stability of the traffic flow.Based on the model,linear stability analysis is performed together with bifurcation analysis,whose corresponding stability condition is highly fit to the results of the linear analysis.Furthermore,the time-dependent Ginzburg–Landau(TDGL)equation and the modified Korteweg–de Vries(m Kd V)equation are derived by nonlinear analysis,and we obtain the relationship of the two equations through the comparison.Finally,parameter calibration and numerical simulation are conducted to verify the validity of the theoretical analysis,whose results are highly consistent with the theoretical analysis.

Dynamic Terrain Visualization Based on ROAM and OGRE

Terrain Visualization is an important part of visualization systems of battlefield,and the visualization of dynamic terrain is also important for dynamic battle environment.In this paper,special attention has been paid on real-time optimally adapting meshes (ROAM) algorithm,which is a candidate for dynamic terrain,and its mesh representation,mesh continuity algorithm and error metrics are discussed.The DEXTER-ROAM algorithm is discussed and analyzed.By revising the mesh representation of ROAM,a dynamic ROAM algorithm based on partial-regular grid is established.By introducing transition region,mesh discontinuity of dynamic partial-regular grid is resolved.Error metric blocks are removed for computation complexity and culling blocks are introduced to accelerate view frustum culling.The algorithm is implemented in a 3D rendering engine called OGRE.In the end,an example of dynamic crater is given to examine the dynamic ROAM algorithm.

A New Method for Visual Real-Time Monitoring of Low Frequency Oscillation

Visual real-time monitoring is the premise of low frequency oscillation control in power grids. This paper showed a visual method for the control center of power grids to monitor low frequency oscillation. It processed the PMU real-time data with incomplete S-transform, and converted the waveforms to two-dimensional time-frequency figures which showed the initial time, frequency and amplitude of each low frequency oscillation mode directly. GPU was used to show figures and calculate FFT with the purpose of improving calculation efficiency. The results of practical cases show that the real-time characters of low frequency oscillation can be identified availably by this visualization real-time monitoring method which is helpful and suitable for practical application.

Visualization aided system of hydropower engineering management

For the purpose of realizing the information visualization of hydropower engineering management,we constructed three kinds of graphics models sorted by hierarchy for system modelling,employed the construction simulation system to simulate the real-time construction behaviours,introduced the graphics rendering system to organize and update the virtual scene,and designed the interaction system to respond to the user-initiated and simulation-initiated events.So,the real-time,interactive visualization aided system of hydropower engineering management is developed.Eventually,the effectiveness and capabilities of the system are showed through the application examples in China.

时序数据的因果关系交互式可视分析

针对时序数据中因果关系检测算法效率低、错误率高、可解释性低的问题,本文提出一种新颖的用于时序数据的因果关系检测模型。该模型整合了泛函贪婪等价搜索(F-GES)模型与格兰杰(Granger)因果关系模型,展开因果关系的抽取和推断,并提出了因果关系可视分析方法,以交互式地分析时序数据中变量间的因果关系。可视分析方法形成了参数视图用于提高因果关系探索效率、因果关系树图用于直观有效地展示变量之间的因果关系、时间视图用于比较原始时序数据、堆叠流图用于帮助用户探索时序数据的层次演变以及平行坐标图用于进行相关性分析。基于真实数据形成的原型系统交互式地验证和总结时序数据中的因果关系,从而更高效地挖掘和理解时序数据中变量之间蕴含的因果规律以帮助决策。

动态场景下基于3D多目标追踪的实时视觉SLAM方法研究

近年来一些解决动态场景下的SLAM技术被提出,其中SLAM与MOT结合的技术路线不仅可解决动态场景问题,还可以提高系统对周围场景的理解,获得了更大关注。本文介绍了一种高效的实时在线视觉SLAMMOT融合系统,以双目视觉或RGBD作为输入,只须借助2D目标检测网络,便能高效、准确、鲁棒地跟踪相机以及动态目标的位姿,并生成稀疏点云地图。为提高多动态目标追踪的精度与准确度,引入了级联匹配与IOU匹配结合的策略;利用阿克曼转向模型来简化追踪目标的运动,减少求解动态目标位姿所需匹配点的数量;利用因子图将相机与动态目标的追踪结果进行联合优化,同时提高相机、追踪目标的位姿和地图点的精度。最后在KITTI跟踪数据集上与其他方法进行比较。结果表明,在满足实时性要求的前提下,该方法仍能准确地追踪相机以及动态目标位姿。

面向流程制造的数字孪生车间可视化监控系统研究

为了解决流程制造过程监控实时性差、准确性不足的问题,在数字孪生技术迅速发展且与制造业结合愈发紧密的背景下,提出基于生产要素数据、生产工艺流程与多工序设备实体对象的数字孪生车间可视化监控系统架构。从要素、状态、运行逻辑等多个维度对多工序耦合生产线实体对象进行孪生建模,基于OPC UA统一架构的数据采集传输,虚拟车间的实时驱动等关键技术,实现了流程制造设备状态、生产要素工艺全流程三维可视化监控。基于某流程制造企业制丝生产试验线开展了应用验证,为提升流程制造过程中全生产要素的预见性、联动性、自治性提供了方法和实现途径。