Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

Testing method of rock structural plane using digital drilling

The rock mass consists of rock blocks and structural planes,which can reduce its integrity and strength.Therefore,accurately obtaining the characteristics of the rock mass structural plane is a prerequisite for evaluating stability and designing supports in underground engineering.Currently,there are no effective testing methods for the characteristic parameters of the rock mass structural plane in underground engineering.The paper presents the digital drilling technology as a new testing method of rock mass structural planes.Flawed rock specimens with cracks of varying widths and angles were used to simulate the rock mass structural planes,and the multifunctional rock mass digital drilling test system was employed to carry out the digital drilling tests.The analysis focuses on the variation laws of drilling parameters,such as drilling pressure and drilling torque,affected by the characteristics of prefabricated cracks,and clarifies the degradation mechanism of rock equivalent compressive strength.Additionally,an identification model for the characteristic parameters of rock mass structural planes during drilling is established.The test results indicate that the average difference of the characteristics of prefabricated cracks identified by the equivalent compressive strength is 2.45°and 0.82 mm,respectively.The identification model while drilling is verified to be correct due to the high identification accuracy.Based on this,a method for testing the characteristic parameters of the surrounding rock structural plane while drilling is proposed.The research offers a theoretical and methodological foundation for precise in situ identification of structural planes of the surrounding rock in underground engineering.

The Impact of Music Education on Children’s Cognitive Development:From Traditional Classrooms to Modern Digital Platforms

Music education has long been debated for its influence on children’s cognitive development,particularly regarding their thinking methods and adaptability.This article synthesizes research data to examine the cognitive benefits of music instruction,including increased IQ,language proficiency,memory,and attention.Traditional face-to-face training,while personalized and socially interactive,faces limitations such as budget constraints and accessibility.Modern digital platforms offer individualized learning paths with AI-driven feedback but may lack necessary interpersonal interaction.This paper proposes a hybrid approach to music education,integrating traditional and digital methods to maximize cognitive gains.Further research is recommended to explore the implementation of these integrated learning strategies in varied educational settings.

A Mechanism for Digital Finance to Drive Green and Low-Carbon Development

Given the global focus on green and low-carbon development and the increasing prominence of digital finance,it is particularly important to explore how to leverage digital finance to achieve these environmental goals.This study,through mechanism analysis,deeply examines how China’s digital finance promotes green and low-carbon development and elucidates the positive interaction between digital finance and the green industry.The study found that digital finance,through more flexible and efficient financial functions,alters the cost structure of carbon emissions,and reduces the risks and costs of green investments,thereby creating a cooperative green mechanism benefiting all parties,and guiding social groups toward a green and low-carbon transformation.Additionally,the rapid development of digital finance has strengthened the implementation of environmental protection policies,effectively promoted the expansion of the environmental protection industry,and established the green ethos as a mainstream concept in financial development.This study aims to provide reference perspectives and suggestions,assist policymakers in promoting the green and lowcarbon development of digital finance,and offer insights into the integrated development of digital finance and the green environmental protection industry.

Resolution analysis of thermal neutron radiography based on accelerator-driven compact neutron source

Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applications.Recently,thermal neutron radiography experiments based on a D-T neutron generator performed by Hefei Institutes of Physical Science indicated a significant resolution deviation between the experimental results and the values calculated using the traditional resolution model.The experimental result was up to 23%lower than the calculated result,which hinders the achievement of the design goal of a compact neutron radiography system.A GEANT4 Monte Carlo code was developed to simulate the CTNR process,aiming to identify the key factors leading to resolution deviation.The effects of a low collimation ratio and high-energy neutrons were analyzed based on the neutron beam environment of the CTNR system.The results showed that the deviation was primarily caused by geometric distortion at low collimation ratios and radiation noise induced by highenergy neutrons.Additionally,the theoretical model was modified by considering the imaging position and radiation noise factors.The modified theoretical model was in good agreement with the experimental results,and the maximum deviation was reduced to 4.22%.This can be useful for the high-precision design of CTNR systems.

Toward Data-Driven Digital Therapeutics Analytics:Literature Review and Research Directions

With the advent of digital therapeutics(DTx),the development of software as a medical device(SaMD)for mobile and wearable devices has gained significant attention in recent years.Existing DTx evaluations,such as randomized clinical trials,mostly focus on verifying the effectiveness of DTx products.To acquire a deeper understanding of DTx engagement and behavioral adherence,beyond efficacy,a large amount of contextual and interaction data from mobile and wearable devices during field deployment would be required for analysis.In this work,the overall flow of the data-driven DTx analytics is reviewed to help researchers and practitioners to explore DTx datasets,to investigate contextual patterns associated with DTx usage,and to establish the(causal)relationship between DTx engagement and behavioral adherence.This review of the key components of datadriven analytics provides novel research directions in the analysis of mobile sensor and interaction datasets,which helps to iteratively improve the receptivity of existing DTx.

Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

Digital仿真测试在改进数字逻辑课程教学中的应用探究--基于与Logisim软件的比较

针对数字逻辑课程教材中的一处错误,提出使用Digital仿真软件进行测试的改进方案。分析表明:Digital仿真软件能用于组合逻辑电路与时序逻辑电路的测试;其不仅可使用真值表实现测试,还可用测试语句构建大规模的复杂测试用例,更适用于数字逻辑课程教学中设计题目的测试。进一步与Logisim软件比较表明:Digital软件测试功能更强,波形观察方便,更有助于实验和测试;考虑了电源和接地、外接端子均为双向连接,Digital软件所构建和仿真的电路更加符合实际;其RAM器件类型更多,有助于仿真完整的计算机系统。据此提出,在数字电路和计算机组成原理等硬件课程教学中推广使用Digital软件。

Does digitalization mitigate regional inequalities?Evidence from China

Regional inequality significantly influences sustainable development and human well-being.In China,there exists pronounced regional disparities in economic and digital advancements;however,scant research delves into the interplay between them.By analyzing the economic development and digitalization gaps at regional and city levels in China,extending the original Cobb-Douglas production function,this study aims to evaluate the impact of digitalization on China's regional inequality using seemingly unrelated regression.The results indicate a greater emphasis on digital inequality compared to economic disparity,with variable coefficients of 0.59 for GDP per capita and 0.92 for the digitalization index over the past four years.However,GDP per capita demonstrates higher spatial concentration than digitalization.Notably,both disparities have shown a gradual reduction in recent years.The southeastern region of the Hu Huanyong Line exhibits superior levels and rates of economic and digital advancement in contrast to the northwestern region.While digitalization propels economic growth,it yields a nuanced impact on achieving balanced regional development,encompassing both positive and negative facets.Our study highlights that the marginal utility of advancing digitalization is more pronounced in less developed regions,but only if the government invests in the digital infrastructure and education in these areas.This study's methodology can be utilized for subsequent research,and our findings hold the potential to the government's regional investment and policy-making.

Digital signal acquisition system for complex nuclear reaction experiments

A digital data-acquisition system based on XIA LLC products was used in a complex nuclear reaction experiment using radioactive ion beams.A flexible trigger system based on a field-programmable gate array(FPGA)parametrization was developed to adapt to different experimental sizes.A user-friendly interface was implemented,which allows converting script language expressions into FPGA internal control parameters.The proposed digital system can be combined with a conventional analog data acquisition system to provide more flexibility.The performance of the combined system was veri-fied using experimental data.

Alexa,let's train now!——A systematic review and classification approach to digital and home-based physical training interventions aiming to support healthy cognitive aging

Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.

Children’s Health, Parent-Child Activities, Using Digital Devices, and Social Competence: Serial Mediation

Background: Studies have pointed out the influence of different children’s activities and prolonged use of digital products on their social development. However, whether the parent-child activities and using digital devices were serial mediators of the relationship between children’s health and social development needs further verification. Purpose: This study explored how parent-child activities and children’s use of digital devices influence the relationship between children’s health and their social competence. Method: This study used data from Kids in Taiwan: National Longitudinal Study of Child Development and Care. A total sample of 2164 participants was used in this study. Serial mediation analyses were performed using model six of Hayes’ PROCESS (2012). Results: This study found that parent-child activities and the use of digital devices can serially mediate the relationship between children’s health and social competence. Children’s health could directly improve their social competence, but it could also serially mediate social competence by increasing parent-child activities and reducing the use of digital devices. Conclusion: Childcare policy planners and parenting educators should not only call on parents to reduce the use of electronic products for their children, but also encourage parents to spend more time interacting with their children, so that children can learn social skills by interacting with others in their daily lives.

Method for evaluation of geological strength index of carbonate cliff rocks:Coupled hyperspectral-digital borehole image technique

The deterioration of unstable rock mass raised interest in evaluating rock mass quality.However,the traditional evaluation method for the geological strength index(GSI)primarily emphasizes the rock structure and characteristics of discontinuities.It ignores the influence of mineral composition and shows a deficiency in assessing the integrity coefficient.In this context,hyperspectral imaging and digital panoramic borehole camera technologies are applied to analyze the mineral content and integrity of rock mass.Based on the carbonate mineral content and fissure area ratio,the strength reduction factor and integrity coefficient are calculated to improve the GSI evaluation method.According to the results of mineral classification and fissure identification,the strength reduction factor and integrity coefficient increase with the depth of rock mass.The rock mass GSI calculated by the improved method is mainly concentrated between 40 and 60,which is close to the calculation results of the traditional method.The GSI error rates obtained by the two methods are mostly less than 10%,indicating the rationality of the hyperspectral-digital borehole image coupled evaluation method.Moreover,the sensitivity of the fissure area ratio(Sr)to GSI is greater than that of the strength reduction factor(a),which means the proposed GSI is suitable for rocks with significant fissure development.The improved method reduces the influence of subjective factors and provides a reliable index for the deterioration evaluation of rock mass.

A deep-reinforcement learning approach for optimizing homogeneous droplet routing in digital microfluidic biochips

Over the past two decades,digital microfluidic biochips have been in much demand for safety-critical and biomedical applications and increasingly important in point-of-care analysis,drug discovery,and immunoassays,among other areas.However,for complex bioassays,finding routes for the transportation of droplets in an electrowetting-on-dielectric digital biochip while maintaining their discreteness is a challenging task.In this study,we propose a deep reinforcement learning-based droplet routing technique for digital microfluidic biochips.The technique is implemented on a distributed architecture to optimize the possible paths for predefined source–target pairs of droplets.The actors of the technique calculate the possible routes of the source–target pairs and store the experience in a replay buffer,and the learner fetches the experiences and updates the routing paths.The proposed algorithm was applied to benchmark suitesⅠand Ⅲ as two different test benches,and it achieved significant improvements over state-of-the-art techniques.

全范围头面部DR辅助摆位系统设计与实现

为了辅助放射技师减少摆位错误,提出了一套完整的全范围头面部DR(digital radiography)智能辅助摆位系统.该系统以嵌入式计算平台为基础,利用RGB-D相机捕获的图像准确估计患者头部姿态,并针对不同的拍摄体位需求提供精确的摆位指导.采用六维向量描述头部姿态,并开发了一个深度神经网络Effi6DNet,其能够实时从RGB图像中估计全范围的头部姿态;同时,通过三维可塑模型(3DMM)和3D头部重建技术优化头部姿态估计,达到更高的准确度.该系统结合这2种技术,并融入具体摆位要求,实现了在嵌入式平台上实时和高精度的辅助摆位功能.在多个数据集上的验证结果表明,该系统能够实时和准确识别头部姿态,提供合理的摆位指导.该系统为提高头面部DR的效率和准确性提供了一种新的智能化解决方案.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

HYDRO:Optimizing interactive hybrid images for digital signage content

Background In modern society,the digital signage installed in many large-scale facilities supports daily life.However,owing to their limited screen size,it is difficult to simultaneously provide different types of information to many viewers at varying distances from the screen.Therefore,in this study,we extend the existing research on the use of hybrid images for tiled displays.Methods To facilitate smoother information selection,a new interactive display method is proposed that incorporates touch-activated widgets as high-frequency parts of hybrid images.These widgets are novel because they are more visible to viewers near the display.We developed an authoring tool called the hybrid image display resolution optimizer(HYDRO),which features two types of control functions to optimize the visibility of touch-activated widgets in terms of placement and resolution.Conclusion The effectiveness of the proposed method is demonstrated empirically through a quantitative user study and an eyetracking-based qualitative evaluation.

DRFM干扰在OFDM新体制雷达中的研究

新体制雷达以正交频分复用(OFDM)数字调制方式作为雷达信号源,具有高频谱效率、高分辨能力等优点。本文首先介绍了新体制雷达系统的基本组成部分,主要包括OFDM信号源、发射模块、环境模块、接收模块和信号处理模块。其次介绍了数字射频存储器(DRFM)干扰的主要组成部分以及工作原理,其中主要包括假目标干扰。最后将DRFM干扰与新体制雷达结合,在加干扰和不加干扰两种情况下对仿真目标进行测距和测速,结果验证了新体制雷达测量目标的准确性以及DRFM干扰的可行性。对新体制雷达及DRFM干扰研究具有参考意义。

DR设备利用信号传递特性得出准确剂量指示质量控制方法的研究

目的:探究数字X射线摄影(DR)设备利用信号传递特性(STP)得出准确探测器剂量指示(DDI)的质量控制方法。方法:通过STP绘制拟合回归曲线,得出剂量与DDI值或像素值的计算公式,计算得出影像接收器入射空气比释动能10μGy对应的基线值。结果:SYNTHESIS型DR摄影机的剂量与像素值对数相关公式为y=-1455ln(x)+7311.1,回归到剂量x=10μGy,得出像素值y=3961。Brivo XR515型DR摄影机的剂量与像素值线性响应公式为y=140.33x-2.3445,回归到剂量x=10μGy,得出准确的像素值y=1401。结论:此方法可以准确地完成DR设备验收检测和状态检测的DDI项目,并得到客观准确的评价。