智能网联汽车数据跨境流动的法律问题研究

数据是自动驾驶技术发展的核心，数据跨境流动是智能网联汽车行业发展中的常见场景。数据出境可能涉及国家安全、产业发展和个人信息保护等多方利益。我国在构建智能网联汽车数据跨境流动的法律规制时，必须立足本国利益，创新监管模式，平衡数据安全与产业发展的关系。     

全球主要经济体数据跨境流动规则研究

数据跨境流动在给全球经济体带来新的发展机遇的同时也带来了新的安全困境。全球主要经济体基于自身实际情况选择数据跨境路径,维护自身数据权利与数据安全。美国主张有限例外的自由流动规则,欧盟对外构建充分性认定规则框架,东盟施行“示范合同条款”机制,而中国则构建起严格的数据跨境流动的安全规则体系。为促进数据跨境流动的安全发展,应尊重各国数据主权,完善数据跨境流动安全规则,探索基于典型应用场景的数据跨境流动实践。     

跨境数据流动治理：框架、实践困境与启示

数字经济时代对传统的地缘政治格局和现有的国家网络治理体系提出了挑战,其中,跨境数据流动成为具体典型性的问题之一。跨境数据流动在促进全球化的同时也给国家的安全和发展带来了新问题与新挑战。如何在跨境数据流动中创造社会价值,如何提升政府数据战略思维和治理能力,成为各国数据治理的重要考虑。在全球数据治理和网络安全的背景下,从动因视角出发,本文着重探究跨境数据流动治理背后的理论和制度逻辑,进而提出中国的因应策略。     

美欧数据跨境流动立法情况概述

近年来,数据跨境流动问题成为国际社会广泛关注的话题,也成为各方矛盾焦点和监管难题。数据跨境监管经过多年发展,逐步形成由欧盟和美国主导的两套规制体系。美国采取服务于贸易的宽松政策,欧盟设立较为严格的制度,同时通过设置多种场景寻求个人信息保护与数据自由流动的平衡。文章表述我国应建立重要数据分级分类管理制度,针对不同场景设置多样化的数据跨境流动机制,推动建立数据跨境流动行业自律制度,强化国际合作,积极参与国际规则的制定。     

数据跨境流动治理与对策研究

数据是信息时代重要的国家战略资源,合理的数据流动在促进经济增长、加速创新、推动全球化方面发挥着重要作用。当前全球跨境数据流动监管体系处在形成关键期。我国作为全球数据资源大国,面临数字经济快速发展机遇,需要妥善规制处理数据跨境流动问题,在保障数据安全的基础上促进数据有序高效流动,为数字经济高质量发展提供有力支撑。在梳理美国、欧盟以及国际组织等主要国家和地区数据跨境流动研究最新进展的基础上,分析了各自特点,并结合我国数据跨境流动实际提出对策建议。     

比例原则视域下个人数据跨境流动规制中的利益权衡

目前,全球性的个人数据跨境流动规制尚未形成,虽然区域全面经济伙伴关系协定(RCEP)已对以美欧为主导的两大格局之价值“漏洞”予以填补,将国家安全上升为可与个人数据权利、经济利益相提并论的第三大利益,但隐私盾协议的失效却也意味着“严格型”与“宽松型”规制之间仍存在激烈矛盾,而这源于不同国家对这三大利益的不同考量。但这一冲突并非不可弥合。比例原则这一科学方法论的指引,有助于尽可能平衡三大利益,探寻出全球规制之理想路径——“平衡点”,扭转“分而治之”的局面。虽然受制于推进构建全球性规制之困难,目前我国域内立法仍然偏向于“数据本地化”立场,但我国仍应当以“平衡点”为奋斗目标,完善国内立法框架的同时,期待多元共治之美好愿景的实现。     

统筹推进数据跨境流动监管与数字贸易发展

数据跨境流动在推动数字贸易快速发展的同时,也必然存在数据跨境带来的安全风险,处理好两者关系对于统筹“发展”与“安全”至关重要。梳理数据跨境流动监管与数字贸易发展的关系,分析主要经济体在协调数据跨境流动监管与数字贸易发展的经验做法,分析中国协调推进数据跨境流动监管与数字贸易发展的成效与问题,可以提出相应建议。     

跨境数据流动时代个人信息安全的立法保护

跨境数据流动导致个人信息安全问题的原因在于各国立法的分散和缺陷。数字经济时代,数据流动交换进入爆发式增长阶段。文章通过梳理跨境数据流动时代国外个人信息保护规范的发展现状,以及跨境数据流动背景下我国个人信息保护状况,分析了目前全球在跨境数据流动方面的问题,并依据问题从设立个人信息专员制度、统一立法标准、确立数据主权归属主体等方面进行了立法对策建议,力图提出可行性措施。     

数据跨境流动的法治挑战与应对

数据跨境流动正在成为连接全球数字经济的纽带,我国应积极融入并引领数字经济全球化。然而,“‘滴滴出行’赴美上市”事件却暴露出了数据跨境流动在国家安全和个人数据保护层面提出的法治挑战。我国针对挑战采取了一系列立法活动,但是在法治实践当中仍面临两大困难,即重要数据目录的动态管理和个人数据保护与经济发展的协调平衡。综合当前立法与相关理论发现,引入区块链技术,用技术监管技术的法治思维是解决这两大实践难点的有效途径。     

探索数字贸易视阈下跨境数据流动治理体系

较早探索跨境数据流动治理的国家和地区已经积累了丰富的经验,我国应取其所长,加强与其他主要经济体在这一领域的合作。中国应在恪守“数据主权”利益的基础上,在实践中不断完善我国跨境数据流动治理体系,推进WTO提高规制跨境数据流动治理水平,为共同构建和平、安全、开放、合作、有序的网络空间命运共同体贡献中国智慧。     

Cross border railway operations: improving safety at cultural interfaces

Organizations with different cultures will interface with each other as legislation is introduced to ensure the interoperability of railway systems across Europe. To approach the safety challenges related to interfaces between cultures, the International Union of Railways (UIC) initiated the project Safety Culture at Interfaces. The project covers the development of a method for assessing and trying to improve safety cultural interfaces. The project was performed by SINTEF. This paper presents the method, which is called SafeCulture. The project has piloted the method in three railway organizations with positive evaluations from the participants, identifying several issues that could improve safety at interfaces. It is not possible to isolate safety culture at interfaces from the whole system, embracing environment, infrastructure, organization, individual and teamwork. Safety culture at interfaces is an integrated part of the “whole picture”. Building safety culture at interfaces has been seen as a learning process that requires involvement and commitment between organizations. This is a difficult challenge. One of the first challenges is to motivate and get involvement from the relevant parties in the process. The next challenge is to develop real commitment from the organizations that are involved to agree on common solutions. Our approach to these challenges has been to establish a qualitative method, consisting of questionnaires and exploration of scenarios where the involved parties feel confident of their knowledge and can be motivated to share experience. Involvement and participation from the workforce and management, from the beginning of the learning loop, will create ownership and commitment to the problems and their solutions.

全太阳能数据中心整体技术方案与实践

如何在提高数据中心数据处理能力的同时又降低用电量,成为数据中心行业进一步发展的瓶颈问题。为此,提出全太阳能数据中心整体技术方案,以微服务器集群构架为核心,以太阳能光伏发电为主供电源,在此基础上,再配合高压直流配电系统和分布式内嵌UPS系统。首个全太阳能数据中心已经建成投入使用,根据实际运行结果表明,能耗减少到常规数据中心的1/4,节能减排效果十分显著。同时,机房运行成本下降50%,利润率提高400%,一次性建设费用只有常规同等规模数据中心的60%,社会效益和经济效益同样明显。     

Control flow and data flow oriented integration testing methods

The testing of modular software systems can be divided into a module testing phase and an integration testing phase. While module testing checks the modules separately, integration testing examines the use of interfaces in a modular system. Integration testing allows errors to be found which cannot be found by module testing. The aim of this paper is to propose a new approach to integration testing. The main principle is to transfer and adapt module testing methods to the level of integration testing. The approach is described for control flow and data flow oriented testing methods. To decrease the testing effort and increase the probability of finding errors, integration testing can be limited to statically detectable anomalous applications of interfaces. This is accomplished by the combination of static analysis with dynamic execution and by the possibility of using information already provided by the module tests. To find further test data to execute interfaces, symbolic execution is applied. One great advantage here is to prove whether statically determined interface anomalies can be dynamically executed and can therefore occur at all.     

Cross the data desert: generating textual-visual summary on the evolutionary microblog stream

Effectively and efficiently summarizing social media is crucial and non-trivial to analyze social media. On social streams, events which are the main concept of semantic similar social messages, often bring us a firsthand story of daily news. However, to identify the valuable news, it is almost impossible to plough through millions of multi-modal messages one by one with traditional methods. Thus, it is urgent to summarize events with a few representative data samples on the streams. In this paper, we provide a vivid textual-visual media summarization approach for microblog streams, which exploits the incremental latent semantic analysis (LSA) of detected events. Firstly, with a novel weighting scheme for keyword relationship, we can detect and track daily sub-events on a keyword relation graph (WordGraph) of microblog streams effectively. Then, to summarize the stream with representative texts and images, we use cross-modal fusion to analyze the semantics of microblog texts and images incrementally and separately, with a novel incremental cross-modal LSA algorithm. The experimental results on a real microblog dataset show that our method is at least 1.31% better and 23.67% faster than existing state-of-the-art methods, and cross-modal fusion can improve the summarization performance by 4.16% on average.

     

Optic flow regulation: the key to aircraft automatic guidance

We have developed a visually based autopilot which is able to make an air vehicle automatically take off, cruise and land, while reacting appropriately to wind disturbances (head wind and tail wind). This autopilot consists of a visual control system that adjusts the thrust so as to keep the downward optic flow (OF) at a constant value. This autopilot is therefore based on an optic flow regulation loop. It makes use of a sensor, which is known as an elementary motion detector (EMD). The functional structure of this EMD was inspired by that of the housefly, which was previously investigated at our Laboratory by performing electrophysiological recordings while applying optical microstimuli to single photoreceptor cells of the insect's compound eye.

We built a proof-of-concept, tethered rotorcraft that circles indoors over an environment composed of contrasting features randomly arranged on the floor. The autopilot, which we have called OCTAVE (Optic flow based Control sysTem for Aerial VEhicles), enables this miniature (100 g) rotorcraft to carry out complex tasks such as ground avoidance and terrain following, to control risky maneuvers such as automatic take off and automatic landing, and to respond appropriately to wind disturbances. A single visuomotor control loop suffices to perform all these reputedly demanding tasks. As the electronic processing system required is extremely light-weight (only a few grams), it can be mounted on-board micro-air vehicles (MAVs) as well as larger unmanned air vehicles (UAVs) or even submarines and autonomous underwater vehicles (AUVs). But the OCTAVE autopilot could also provide guidance and/or warning signals to prevent the pilots of manned aircraft from colliding with shallow terrain, for example.     

BiFlowLISA: Measuring spatial association for bivariate flow data

Spatial flow data are often used to represent spatial interaction phenomena such as daily commuting trips, human or animal migrations, and the exchanges of commodities, capital, or even information between regions. With the increasingly available large volume of flow data in fine spatiotemporal resolution, exploratory spatial data analysis (ESDA) has become more important than ever to gain understanding of the data and the story behind it. A major group of flow-related ESDA methods focus on measuring spatial associations, which proves useful in improving the prediction power and interpretability of spatial interaction model (SIM), as well as in identifying local clusters and outliers of flow events. This paper introduces a new spatial statistical method called BiFlowLISA—a local indicator of spatial association of bivariate flow data. BiFlowLISA evaluates the association between two types of flows in close proximity, in other words, how the value of type-I flows associate with the value of nearby type-II flows. We develop BiFlowLISA by extending the local bivariate Moran's I to the flow context. We also put forth its global version to measure the global patterns, and another variant of BiFlowLISA to measure both spatial and in-situ correlations at the same time. Several flow-specific issues are discussed and solved, including flow neighbor definition, OD matrix sparsity, and conditional permutation. We experiment with synthetic datasets to verify its functionality and to summarize its characteristics. A case study of taxi and ride-hailing services in New York City demonstrates its usefulness in the comparative analysis of the spatial patterns of two types of travel flows. More applications of BiFlowLISA await to be explored in the future.     

A storage and retrieval plan for data on head and neck cancer patients

A system for storing comprehensive data on patients with head and neck tumours, using a microprocessor, is described. Methods for updating the data and extracting and manipulating data about specified groups are also outlined.