[目的/意义]信息素养是数字素养、科学素养等"+素养"的基础素养,是数字化时代的公民在学习、生活、工作中所必备的核心素养.[方法/过程]通过对中国、美国、英国等国的 18 份信息素养标准进行分析及解读,总结各国信息素养标准的特征及其对我国全民信息素养提升方面的启示.[结果/结论]我国应强化顶层设计作用,倡导多部门主导、教育领域专家参与的信息素养标准的制定,编撰信息素养学习素材,举办丰富的信息素养主题活动,以加速全民信息素养水平的提升进程.

数字化时代对公民科学素质提出了新的要求,即具备能够适应数字社会的核心能力.基于对数字社会典型特征及其对公民科学素质新要求的分析,提出以数字素养提升促进科学素质的提升,并结合数字素养的研究与实践提出三个方面的建议:以具体情境下的技能习得促进能力提升;以数字环境下的积极态度促进科学精神培育;以数字化相关知识为基础拓展科学认知.

新时代我国科普事业的发展需要高质量科普人才的支撑,高层次科普人才培养是提升我国科普人才队伍质量的重要手段之一.基于对我国高层次科普人才培养存在问题的分析,发现缺乏专业硕士学位是严重制约高层次科普人才培养的重要因素,指出设立科普专业硕士学位是落实《科学素质纲要(2021—2035年)》的重要举措,同时提出设立科普专业硕士学位的具体建议.

基因疗法是全球突破性技术之一,在单基因遗传疾病治疗中已取得突破性进展.阐述了不同的基因疗法策略、载体和基因编辑技术的特点,综述了脊髓性肌萎缩症、Leber先天性黑蒙2型、血友病、β-地中海贫血的发病机理、临床表现、基因疗法的开发进程以及临床试验情况.目前,上述4种单基因疾病的9种基因疗法已分别取得美国食品药品监督管理局突破性疗法资格、欧洲药品管理局的优先药物资格或者已经批准上市.基因疗法的研究还面临着许多挑战,但随着科学研究的深入和科学技术的不断发展,将有更多的患者获得治疗.

慕课作为"互联网+教育"的产物,历经几年的发展,已经具备了一定的建设积累.如何有效推进这批技术成果的转化,创新应用模式是慕课后续发展面临的首要问题.在分析慕课核心特性的基础上,总结慕课在科普领域的成果转化及其运营服务流程,并指出,慕课核心特征中的一部分固有属性与科普特性具有共通之处,慕课资源向科普领域的技术转化创新了慕课的应用模式,无论从慕课的应用推进还是提升全民科学素养都具有积极意义.

针对场景应用于科普虚拟现实的具体需求,研发了大型场景的航空采集技术和地面采集方法,实现了全套面向科普虚拟现实展示的大型场景的数据采集技术,为多数据源采集数据融合奠定了基础,为三维重建和场景展示提供了可靠的数据来源.

调研了目前网络流量计量的发展状况,列举了常用的流量指标和应用特点,分析了Alexa网站排名的机制和提供的流量数据,并使用实际数据验证了Alexa的排名.提出了数据的估算方式来分析中国地区的排名情况,对Alexa中国排名75～125名的流量指标数据进行归纳处理,提出排名处于该区间的网站的特点,给出提升排名在数据指标上应达到的目标和改进建议,为新闻、门户网站建设及网站评价提供参考,为网站提升Alexa排名提出建议.

This paper proposes an approach based on Ordinal Optimization (OO) to solve trajectory planning for automated driving. As most planning approaches based on candidate curves optimize the trajectory curve and the velocity profile separately, this paper formulates the problem as an unified Non-Linear Programming (NLP) model, optimizing the trajectory curve and the acceleration profile (acceleration is the derivative of velocity) simultaneously. Then a hybrid optimization algorithm named OODE, developed by combining the idea of OO and Differential Evolution (DE), is proposed to solve the NLP model. With the acceleration profile optimized "roughly", OODE computes and compares "rough" (biased but computationally-easier) curve evaluations to select the best curve from candidates, so that a good enough curve can be obtained very efficiently. Then the acceleration profile is optimized again "accurately" with the selected curve. Simulation results show that good enough solutions are ensured with a high probability and our method is capable of working in real time.

In this paper, on-road trajectory planning is solved by introducing intelligent computing budget allocation (ICBA) into a candidate-curve-based planning algorithm, namely, ordinal-optimization-based differential evolution (OODE). The proposed algorithm is named IOODE with ‘I’ representing ICBA. OODE plans the trajectory in two parts: trajectory curve and acceleration profile. The best trajectory curve is picked from a set of candidate curves, where each curve is evaluated by solving a subproblem with the differential evolution (DE) algorithm. The more iterations DE performs, the more accurate the evaluation will become. Thus, we intelligently allocate the iterations to individual curves so as to reduce the total number of iterations performed. Meanwhile, the selected best curve is ensured to be one of the truly top curves with a high enough probability. Simulation results show that IOODE is 20% faster than OODE while maintaining the same performance in terms of solution quality. The computing budget allocation framework presented in this paper can also be used to enhance the efficiency of other candidate-curve-based planning methods.

为提高科普展品的使用效率和开放共享水平,提出了一种基于互联网的科普展品远程操作和体验系统.系统硬件主要包括直播设备、流媒体服务器、远程控制模块、Web服务器;软件主要包括用户操作、浏览界面和远程实验管理程序.以声驻波展品为例说明科普展品远程操作和体验的实现.此系统以互联网为媒介,几乎无限制地延伸了展品的操作、体验范围,同时提供了一个不断丰富体验内容和形式的基础平台.

This paper presents an algorithm named OCBA_OODE for on-road trajectory planning by using optimal computing budget allocation (OCBA) in a candidate-curve-based planning algorithm named OODE.OODE picks the best trajectory by comparing rough (biased but computationally inexpensive) evaluations of a set of candidate curves.The curve evaluation converges to the real value as the computing budget increases.OODE allocates the equal parts of the computing budget to each curve,while OCBA OODE repeatedly allocates the budget according to the latest curve evaluations to improve the planning efficiency.OCBA_OODE is 20％ faster than OODE while maintaining the same solution quality.

In this paper, on-road trajectory planning is solved by introducing intelligent computing budget allocation (ICBA) into a candidate-curve-based planning algorithm, namely, ordinal-optimization-based differential evolution (OODE). The proposed algorithm is named IOODE with ‘I’ representing ICBA. OODE plans the trajectory in two parts: trajectory curve and acceleration profile. The best trajectory curve is picked from a set of candidate curves, where each curve is evaluated by solving a subproblem with the differential evolution (DE) algorithm. The more iterations DE performs, the more accurate the evaluation will become. Thus, we intelligently allocate the iterations to individual curves so as to reduce the total number of iterations performed. Meanwhile, the selected best curve is ensured to be one of the truly top curves with a high enough probability. Simulation results show that IOODE is 20% faster than OODE while maintaining the same performance in terms of solution quality. The computing budget allocation framework presented in this paper can also be used to enhance the efficiency of other candidate-curve-based planning methods.

With the trajectory modeled in two parts: trajectory curve and acceleration profile, the problems of decisionmaking and trajectory planning for intelligent vehicles are formulated as a non-linear programming(NLP) model to optimize the efficiency, safety, comfort and economy of trajectory. To solve this model, a hybrid intelligent optimization algorithm OODE is developed. With a two-layer framework applied, OODE optimizes the acceleration profile and trajectory curve in the inner and outer layers, respectively. By “roughly” evaluating the candidate trajectory curves, the optimal curve is determined very efficiently. The simulation results show that, the proposed method is capable of handling complicated traffic scenarios with multiple dynamic obstacles, and also can meet the demands of real-time applications. Compared with traditional methods, the model accuracy of the proposed method is higher, and the planning speed is obviously faster.

As hypersonic flight vehicle flying at a high altitude where aerodynamic forces and moments are not enough for steady flight, reaction control system is widely used due to its effectiveness and agility. This paper describes two main approaches to studying the effect of reaction control system. The first approach is the method by measuring the pressure near the thrusters and then estimating the gas-jet interaction. The second one is the method by using moment system identification to identify the aerodynamic force caused by reaction control system. The second approach can be easily used without adding extra measurements. And identification method of the time parameters in the reaction control system is also discussed.

In order to provide the function of vehicle position and driving assistance in micro traffic environment as that of GPS for primal size vehicle,an indoor position system is built for autonomous micro-vehicle using RFID and network communication technology. In the system,Kalman filter is introduced to track and position the target and micro-vehicle can be shown in real-time. Experiment results show that the system can track the position of micro-vehicle with an error smaller than 0. 07 m in real time,which meets the position demands of micro-vehicle in micro traffic environment.

针对车辆跟随系统中每辆车只能获得局部信息的情况,给出了一种控制器设计方法,并利用李雅普诺夫方法分析了系统的稳定性,给出了保证系统能够稳定运行的充分条件.为增强系统的可扩展性,在原有控制器基础上加入了速度限制,以避免系统位置偏差的逐级放大.在缩微交通环境下实现了5辆缩微车的车辆跟随系统,以验证控制方案的可行性.通过仿真和缩微车实验表明,运用所设计的控制方案,车辆跟随系统能够稳定行驶,避免了系统位置偏差的传播.

提出一种基于注意力动力学的新的视觉认知计算模型,并应用于缩微智能车的自主驾驶.该模型通过上层驾驶任务、底层对象显著性和先验知识,共同驱动视觉注意关注区域的选择.首先由上层驾驶任务确定任务相关区域;然后在任务相关区域内通过基于改进的Itti-Koch显著图的底层对象显著性检测方法和基于先验知识的注意力跟踪转移机制,确定注意关注区域;最后根据在注意关注区域内进行识别认知的结果,完成自主驾驶控制决策和先验知识保存,并通过反馈机制实现驾驶任务切换.实验结果表明,新模型能够有效减少智能车图像计算处理的时间,极大提高智能车环境感知的能力和智能决策的效率.

The multivariable aircraft control system probably becomes unstable caused by those perturbations occurred in all control loops simultaneously or only one of the loops. This paper presents a method to evaluate the stability margin of multivariable aircraft control system under single-loop perturbations by using the structured singular value. By introducing the diagonal multiplicative perturbation matrix at the system input node, system stability margin under single-loop perturbations can be calculated. The evaluation method can handle with three types of the single-loop perturbations, including complex perturbation, amplitude perturbation and phase angle perturbation. The method can evaluate more accurately the stability margin of the multivariable closed-loop system under single-loop perturbations. Simulations on a typical lateral-loop simulation model of a kind of aircraft and an F16 simulation model are given, and the results show the effectiveness.

Sizes of wheel hub are difficult to be measured directly, and a new image measurement method for the wheel hub is proposed in this paper. After images of wheel hub are captured and dealt with, useful information of wheel hub is extracted. Then the 3D-model of wheel hub which is composed of 4 circles is rebuilt accurately. Therefore, inner and outer sizes of wheel hub are measured indirectly. Some experiments have been done by the new method. The experiment results show that this new method is very effective and accurate sizes of wheel hub are obtained.

The basis of the autonomous driving system of the micro-vehicles based on simple visual is the road element detection.Based on the lack of the micro-vehicles processing capacity and the real-time requirements of the detection and control algorithms , the paper proposed a new feature extraction and tracking algorithm based on the pixel data blocks.We use the fixed OTSU threshold image binarization to reduce the impact of light.The detection experiments show that the rapid structural road elements detection ( RSRED ) algorithm can extract the lane markings , road signs , zebra crossings and other road elements against the interference of light , shelter , pollution and the vehicle speed definitely influence over detection rate of road elements.Finally the Lane-kepping and Overtaking experiments show that the algorithm is efficient and stable.