Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles.Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions.However,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world applications.In this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway driving.Within this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step.Thus,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical events.To construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy.Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data.The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios.The proposed risk assessment framework is promising for real-world applications.

Low-Carbon Dispatch of an Integrated Energy System Considering Confidence Intervals for Renewable Energy Generation

Addressing the insufficiency in down-regulation leeway within integrated energy systems stemming from the erratic and volatile nature of wind and solar renewable energy generation,this study focuses on formulating a coordinated strategy involving the carbon capture unit of the integrated energy system and the resources on the load storage side.A scheduling model is devised that takes into account the confidence interval associated with renewable energy generation,with the overarching goal of optimizing the system for low-carbon operation.To begin with,an in-depth analysis is conducted on the temporal energy-shifting attributes and the low-carbon modulation mechanisms exhibited by the source-side carbon capture power plant within the context of integrated and adaptable operational paradigms.Drawing from this analysis,a model is devised to represent the adjustable resources on the charge-storage side,predicated on the principles of electro-thermal coupling within the energy system.Subsequently,the dissimilarities in the confidence intervals of renewable energy generation are considered,leading to the proposition of a flexible upper threshold for the confidence interval.Building on this,a low-carbon dispatch model is established for the integrated energy system,factoring in the margin allowed by the adjustable resources.In the final phase,a simulation is performed on a regional electric heating integrated energy system.This simulation seeks to assess the impact of source-load-storage coordination on the system’s low-carbon operation across various scenarios of reduction margin reserves.The findings underscore that the proactive scheduling model incorporating confidence interval considerations for reduction margin reserves effectively mitigates the uncertainties tied to renewable energy generation.Through harmonized orchestration of source,load,and storage elements,it expands the utilization scope for renewable energy,safeguards the economic efficiency of system operations under low-carbon emission conditions,and empirically validates the soundness and efficacy of the proposed approach.

China Continues to Bring Confidence to Global Economy Recovery

Looking forward to 2024,what opportunities and challenges will global development face?In particular,how can the global economy get rid of the“sequelae”of the pandemic?At the 170th“Monthly Talk on the Economy”held recently by the China Center for International Economic Exchange,experts analyzed the world’s economy since the outbreak of COVID-19,and made clear the context of and provided suggestions for global development in 2024.

Analysis of the Reform of Ideological and Political Education in College English Curriculum from the Perspective of“Cultural Confidence”

With the rapid development of the education industry,higher requirements have been put forward for college English education and teaching,accelerating the pace of college English reform.Issues such as how to integrate knowledge transmission,language expression skill improvement,cultural element extraction,and ideological and political education,and present the role of curriculum education function have attracted attention.In the era of informatization,college students’thinking has undergone certain changes and gradually developed towards diversification.Therefore,universities should start from the perspective of cultural confidence,extract valuable ideological and political elements,and explore effective tourism ideological and political teaching methods.While helping college students enhance their cultural confidence,it is also beneficial for them to better inherit traditional Chinese culture.This article conducts an in-depth exploration of ideological and political education in college English courses from the perspective of“cultural confidence”and uses scientific and effective measures to solve the problems encountered,aiming to provide valuable guidelines for relevant researchers.

Ministry of Commerce:Full of confidence,clear direction,strong motivation

On March 12,the official account of the International Business Daily of the Ministry of Commerce published an article titled“Foreign trade enterprises:full of confidence,clear direction,strong motivation”.The content is as follows:This year,China is still facing a tough foreign trade situation.On the one hand,many international organizations predict that global economic growth in 2024 will still be lower than the historical average and the pressure on external demand will increase;on the other hand,trade protectionism and unilateralism are on the rise,geopolitical conflicts,the global“super election year”and other spillover factors have created many uncertainties.

Prediction of Uncertainty Estimation and Confidence Calibration Using Fully Convolutional Neural Network

Convolution neural networks(CNNs)have proven to be effective clinical imagingmethods.This study highlighted some of the key issues within these systems.It is difficult to train these systems in a limited clinical image databases,and many publications present strategies including such learning algorithm.Furthermore,these patterns are known formaking a highly reliable prognosis.In addition,normalization of volume and losses of dice have been used effectively to accelerate and stabilize the training.Furthermore,these systems are improperly regulated,resulting in more confident ratings for correct and incorrect classification,which are inaccurate and difficult to understand.This study examines the risk assessment of Fully Convolutional Neural Networks(FCNNs)for clinical image segmentation.Essential contributions have been made to this planned work:1)dice loss and cross-entropy loss are compared on the basis of segment quality and uncertain assessment of FCNNs;2)proposal for a group model for assurance measurement of full convolutional neural networks trained with dice loss and group normalization;And 3)the ability of the measured FCNs to evaluate the segment quality of the structures and to identify test examples outside the distribution.To evaluate the study’s contributions,it conducted a series of tests in three clinical image division applications such as heart,brain and prostate.The findings of the study provide significant insights into the predictive ambiguity assessment and a practical strategies for outside-distribution identification and reliable measurement in the clinical image segmentation.The approaches presented in this research significantly enhance the reliability and accuracy rating of CNNbased clinical imaging methods.

Monocular 3D object detection with Pseudo-LiDAR confidence sampling and hierarchical geometric feature extraction in 6G network

The high bandwidth and low latency of 6G network technology enable the successful application of monocular 3D object detection on vehicle platforms.Monocular 3D-object-detection-based Pseudo-LiDAR is a low-cost,lowpower solution compared to LiDAR solutions in the field of autonomous driving.However,this technique has some problems,i.e.,(1)the poor quality of generated Pseudo-LiDAR point clouds resulting from the nonlinear error distribution of monocular depth estimation and(2)the weak representation capability of point cloud features due to the neglected global geometric structure features of point clouds existing in LiDAR-based 3D detection networks.Therefore,we proposed a Pseudo-LiDAR confidence sampling strategy and a hierarchical geometric feature extraction module for monocular 3D object detection.We first designed a point cloud confidence sampling strategy based on a 3D Gaussian distribution to assign small confidence to the points with great error in depth estimation and filter them out according to the confidence.Then,we present a hierarchical geometric feature extraction module by aggregating the local neighborhood features and a dual transformer to capture the global geometric features in the point cloud.Finally,our detection framework is based on Point-Voxel-RCNN(PV-RCNN)with high-quality Pseudo-LiDAR and enriched geometric features as input.From the experimental results,our method achieves satisfactory results in monocular 3D object detection.

Aggregation operators and CRITIC-VIKOR method for confidence complex q-rung orthopair normal fuzzy information and their applications

Supply chain management is an essential part of an organisation's sustainable programme.Understanding the concentration of natural environment,public,and economic influence and feasibility of your suppliers and purchasers is becoming progressively familiar as all industries are moving towards a massive sustainable potential.To handle such sort of developments in supply chain management the involvement of fuzzy settings and their generalisations is playing an important role.Keeping in mind this role,the aim of this study is to analyse the role and involvement of complex q-rung orthopair normal fuzzy(CQRONF)information in supply chain management.The major impact of this theory is to analyse the notion of confidence CQRONF weighted averaging,confidence CQRONF ordered weighted averaging,confidence CQRONF hybrid averaging,confidence CQRONF weighted geometric,confidence CQRONF ordered weighted geometric,confidence CQRONF hybrid geometric operators and try to diagnose various properties and results.Furthermore,with the help of the CRITIC and VIKOR models,we diagnosed the novel theory of the CQRONF-CRITIC-VIKOR model to check the sensitivity analysis of the initiated method.Moreover,in the availability of diagnosed operators,we constructed a multi-attribute decision-making tool for finding a beneficial sustainable supplier to handle complex dilemmas.Finally,the initiated operator's efficiency is proved by comparative analysis.

Validity and reliability of the evaluation tool of TCM confidence in students with TCM learning experience

Objective:This study aimed to design an evaluation scale of traditional Chinese medicine(TCM)confidence and then evaluate its validity and reliability.Methods:Three parallel samples with TCM learning experience were included in this current study.Randomly selected 500 nursing students were included factor analysis and reliability and validity analyses.After 4 weeks,200 nursing students were recruited to retest the reliability.The evaluation tool of TCM confidence included 6 dimensions and 25 entries.Results:Cronbach's a coefficient of the evaluation scale was 0.95 and that of the 6 observed aspects were higher than 0.90,and splithalf reliability was 0.81.For the retest reliability,Cronbach's a coefficient of the evaluation scale was 0.93 and that of the 6 examined aspects was all over 0.80.The index of content validity Scale Content Validity Index(S-CVI)was 0.92 and Item Content Validity Index(I-CVI)was 0.83–1.00.Conclusions:Observed results may indicate that the designed tool can be used to assess the TCM confidence level of students with TCM studied experience and also can evaluate results of TCM education during studying TCM lectures.

Constructing Confidence Regions for Autoregressive-Model Parameters

We discuss formulas and techniques for finding maximum-likelihood estimators of parameters of autoregressive (with particular emphasis on Markov and Yule) models, computing their asymptotic variance-covariance matrix and displaying the resulting confidence regions;Monte Carlo simulation is then used to establish the accuracy of the corresponding level of confidence. The results indicate that a direct application of the Central Limit Theorem yields errors too large to be acceptable;instead, we recommend using a technique based directly on the natural logarithm of the likelihood function, verifying its substantially higher accuracy. Our study is then extended to the case of estimating only a subset of a model’s parameters, when the remaining ones (called nuisance) are of no interest to us.

Exploration on Ideological and Political Construction of Higher Vocational English Course in Southern Xinjiang from the Perspective of "Cultural Confidence"

At present,the lack of Chinese culture in higher vocational English teaching in southern Xinjiang is serious.The existing English curriculum system is not enough to support the goal of cultivating ethnic minority college students cultural confidence,and its curriculum ideological and political construction is still in the initial stage of exploration.The combination of the Chinese national culture and the ethnic culture of Xinjiang and the ideological and political elements organically integrated into cultural confidence have endowed the vocational English education in Xinjiang with the characteristics of the times.In this paper,from the perspective of China s"cultural confidence",ideological and political elements were explored,and the background of ideological and political construction in higher vocational English teaching course in southern Xinjiang was analyzed;it is expounded that the ideological and political construction is an inevitable requirement for the high-quality development of vocational English education in southern Xinjiang,and the content design and implementation path of higher vocational English course was explored to provide new ideas and new ways for the curriculum ideological and political construction of higher vocational English teaching in southern Xinjiang.

Entry-Level Forward Surgical Team Training Is Associated with Increased Confidence of Primary Combat Surgeons

Background: In recent years, we have established an entry-level Forward Surgical Team (FST) training program in a Chinese military medical university for the 5th grade undergraduates, who would be deployed to different military medical services as primary combat surgeons. This study aimed to assess the role of this pre-service training in improving their confidence with combat medical skills, after several years since they received the training. Methods: We conducted a nationwide survey of 239 primary combat surgeons who have ever participated in an entry-level FST training program before deployment between June 2016 and June 2020, which was for evaluating on a 5-point Likert scale the benefits of entry-level FST training and conventional surgery training in improving their confidence with combat medical skills. The difference in scores was compared using the student t-test. Significance was considered as P Results: The total score was significantly higher for entry-level FST training than that for conventional surgery training (30.76 ± 4.33 vs. 28.95 ± 4.80, P There was no significant difference between the training for surgical skills confidence scores (18.03 ± 8.04 vs. 17.51 ± 8.30, P = 0.098), but for non-technical skills, the score of entry-level FST training was significantly higher than that of conventional surgery training (12.73 ± 5.39 vs. 11.44 ± 5.62, P The distributions of confidence scores were different under various subgroups by demographics. There were no significant differences in scores between the two training in all specific surgical skill sets except “life-saving surgery” (P = 0.011). Scores of all 4 non-technical skill sets were significantly higher for entry-level FST than those for conventional surgery training (P Conclusions: The training should be considered as an essential strategy to improve confidence in combat medical skills, especially life-saving surgery and non-technical skills, for primary combat surgeons.

Full Confidence in China’s Development

Roberta Lipson,a pioneering U.S.entrepreneur in China,speaks of the CIIE’s role in international cooperation,healthcare in China,and her own experience in this exclusive interview.

Growing Confidence in China's High-Quality Development

The new philosophy of innovative, coordinated, green, open,and shared development runs through the entire development process and is implemented in all fields of Beijing’s practice of building the “Two Zones.”

Miracle of Civilization,Assurance of Confidence

The"Hemudu Special Exhibition"is the first comprehensive display of Hemudu archaeological achievements in 50 years.This exhibition showcases a large number of artifacts for the first time in Beijing.It includes not only a concentrated display of classic archaeological artifacts but also presentations of the latest archaeological findings.

“三融入,一反哺”:植物生理学课程思政探索与实践

课程思政是立德树人的根本任务,针对植物生理学教学中课程思政元素融入不够,育智重于育人的不足。以文化自信为切入点,采取“三融入,一反哺”策略,即将处于世界领先地位的中国古代传统农业思想、近现代中国植物生理学家的成就、西南联合大学(简称“西南联大”)的卓越贡献和科研反哺教学融入植物生理学教学。激发学生的学习热情,提高创新能力;增强文化自信,提升专业认同感。

非对称自信水平下突发事件响应等级研判方法——基于自信度调整视角

新形势下我国社会安全事件系统性风险凸显造成应急响应等级研判难度跃升,针对专家非对称自信水平下突发事件响应等级研判难题,建立基于信任的专家自信度调整策略,提出专家自信水平影响的应急响应等级研判方法。该方法利用专家提供的信任度和熟悉度构成二元函数描述专家间信任关系,构建基于信任机制的专家自信度调整策略,通过分析非对称自信水平中蕴含的专家研判不确定性,基于证据理论提出应急响应等级研判问题建模方法。在此基础上,综合证据的来源重要度和自身可信度,提出考虑决策者风险偏好的证据可靠度计算方法,赋予证据不同重要性以实现专家研判信息的准确融合,为突发事件应急响应等级综合研判提供决策支持。最后,利用算例验证了方法的实用性与先进性。结果表明:相比投票、权威等常用决策方法,本文所提方法适用性更广、可信性更高、实用性更强。

基于熵和置信度的非平衡问题欠采样Boosting框架

为了解决传统方法中存在的边界过拟合、泛化性能差、重要信息丢失问题,提出一种基于熵和置信度的非平衡问题欠采样Boosting框架。将动态重采样方法与Boosting集成在一起,以解决边界过拟合问题,提高泛化性能;在Ecuboost中使用置信度和熵作为基准,以保证欠采样过程中大多数样本的有效性和结构分布,提出的基于置信度的Boosting框架使动态采样方法进一步提升方法的泛化能力。用两个大型数据集上的实验对比结果验证了该方法的有效性。

融合尺度与信心指数的三维表面重建算法

针对包含细小结构场景的三维表面重建精度和完整度难以提高的问题,提出一种融合三维点云尺度与信心指数的三维表面重建算法。构建了一个表面隐函数,采用高斯函数为其基函数,三阶贝塞尔函数为其权重函数,并根据点云尺度与信心指数大小自适应调整基函数覆盖范围与权重函数取值。采用八叉树存储与处理数据,根据点云尺度大小自适应划分八叉树结构,从而自适应调整表面隐函数三维采样密度。通过无约束等值面提取方法,提取隐函数等值面,从而得到三维表面。与几种典型表面重建算法对比实验,结果表明所提算法重建三维表面细节清晰,整体重建精度与完整度均有提高。

教育强国背景下的基础教育变革:可为、应为与何为

建设教育强国是国家重大战略,标志着一个崭新教育时代的开启。基础教育是教育强国建设的基点,基础教育变革必然是教育强国建设的内在要义和必由之路,这要从可为、应为与何为三个逻辑向度加以认识和把握:教育强国战略为基础教育变革提供方向引领、生成动力和实践基础,此乃可为;基础教育变革推动儿童健康成长、时代新人培养、文化传承创新和人类文明赓续,以达成教育强国目标,此乃应为;系统把握基础教育变革的价值之向、思维之度、创生之基,以落实立德树人任务为着力点,以增强基础教育适应性为切入点,以坚定中国特色教育自信为支撑点,通过基础教育变革更好推动各级各类教育协同发展,最终为教育强国建设奠基赋能,此乃何为。