TD-SCDMA/GSM/GPRS双模终端CELL CHANGE ORDER过程研究

随着TD-SCDMA系统的商用,同时需兼容已非常成熟运营的GSM系统,TD-SCDMA/GSM/GPRS双模终端已是市场的主流。本文针对双模单待终端(协议控制)CELL CHANGE ORDER过程进行研究,该过程是双模终端实现PS域切换的一种重要方式。首先,以TD-SCDMA/GSM/GPRS系统高层协议为基础介绍了双模单待自动切换终端的CELL CHANGE ORDER过程的各个阶段:系统间测量、网络判决及小区改变执行;然后详细地设计了小区改变执行的正常及异常处理流程,并对如何实现数据平面切换过程进行了重点描述;最后搭建板级测试环境,进行协议一致性测试,验证了CELL CHANGE ORDER过程的实现。

Distributed event-triggered consensus tracking of second-order multi-agent systems with a virtual leader

This paper investigates the consensus tracking problems of second-order multi-agent systems with a virtual leader via event-triggered control. A novel distributed event-triggered transmission scheme is proposed, which is intermittently examined at constant sampling instants. Only partial neighbor information and local measurements are required for event detection. Then the corresponding event-triggered consensus tracking protocol is presented to guarantee second-order multi-agent systems to achieve consensus tracking. Numerical simulations are given to illustrate the effectiveness of the proposed strategy.

A Novel Secure Data Transmission Scheme in Industrial Internet of Things

The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.

数据产权刑法保护模式的构建

数据产权是一种具有财产权属性的新型权利,该权利与虚拟财产权和知识产权具有明显差异。数据产权属于刑法保护的公法益范畴,其应归属于市场经济秩序法益之中。现行刑法有关财产犯罪、知识产权犯罪和数据犯罪的规定均无法实现对数据产权的全面保护。刑法对数据产权的保护应以促进数据流通为主要目标,且应当覆盖数据处理的各流程阶段。对侵犯数据产权行为进行刑法规制时,应对“未经同意”获取数据行为审慎入罪。应增设妨害数据流通管理秩序罪,对“情节严重的”妨害数据流通管理秩序行为予以刑法规制。

基于邻域优势粗糙集的区分度动态属性约简算法

为解决动态环境下数值型偏序关系数据的属性约简问题,利用优势粗糙集的区分度提出一种增量式属性约简算法。在数值型信息系统环境下,定义邻域优势区分度度量,通过邻域优势区分度设出一种非增量式属性约简算法;研究和分析对象变化场景下邻域优势区分度进行增量式更新的原理;分别提出数据对象增加和减少情形下数据集属性约简的增量式更新算法。在多个UCI数据集上进行实验验证,实验结果表明,该增量式算法能够有效完成动态数据的属性约简任务。

数据错误的法律治理

大数据时代,数据错误普遍存在。数据错误贯穿数据的全生命周期,是数据质量低下的表现,主要包含缺乏时效、记录重复、难被理解、难以访问、可信度低、不成体系、不一致等特性,表现为数据损失、篡改、造假、偏差、混淆等形式。数据错误既包括客观实际层面的错误,也包括主观行为层面的错误,其成因在于数治制度、数治体系与数治能力存在缺陷。数据错误可能会损害公民的正当权利,破坏社会的运行秩序以及降低国家的治理效能。因此,要确定数据错误规制的基本原则,厘清规制数据错误的主要路径,构建规制数据错误的具体制度,包括设立必要的数据容错法律机制,建构维护数据质量的法律制度以及打造全链条协同共治的法律制度,从而更好地进行数据治理。

Fourth-Order Predictive Modelling: II. 4th-BERRU-PM Methodology for Combining Measurements with Computations to Obtain Best-Estimate Results with Reduced Uncertainties

This work presents a comprehensive fourth-order predictive modeling (PM) methodology that uses the MaxEnt principle to incorporate fourth-order moments (means, covariances, skewness, kurtosis) of model parameters, computed and measured model responses, as well as fourth (and higher) order sensitivities of computed model responses to model parameters. This new methodology is designated by the acronym 4th-BERRU-PM, which stands for “fourth-order best-estimate results with reduced uncertainties.” The results predicted by the 4th-BERRU-PM incorporates, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizes the results produced by extant data assimilation and data adjustment procedures.

Second-Order MaxEnt Predictive Modelling Methodology. I: Deterministically Incorporated Computational Model (2nd-BERRU-PMD)

This work presents a comprehensive second-order predictive modeling (PM) methodology designated by the acronym 2nd-BERRU-PMD. The attribute “2nd” indicates that this methodology incorporates second-order uncertainties (means and covariances) and second-order sensitivities of computed model responses to model parameters. The acronym BERRU stands for “Best- Estimate Results with Reduced Uncertainties” and the last letter (“D”) in the acronym indicates “deterministic,” referring to the deterministic inclusion of the computational model responses. The 2nd-BERRU-PMD methodology is fundamentally based on the maximum entropy (MaxEnt) principle. This principle is in contradistinction to the fundamental principle that underlies the extant data assimilation and/or adjustment procedures which minimize in a least-square sense a subjective user-defined functional which is meant to represent the discrepancies between measured and computed model responses. It is shown that the 2nd-BERRU-PMD methodology generalizes and extends current data assimilation and/or data adjustment procedures while overcoming the fundamental limitations of these procedures. In the accompanying work (Part II), the alternative framework for developing the “second- order MaxEnt predictive modelling methodology” is presented by incorporating probabilistically (as opposed to “deterministically”) the computed model responses.

Second-Order MaxEnt Predictive Modelling Methodology. II: Probabilistically Incorporated Computational Model (2nd-BERRU-PMP)

This work presents a comprehensive second-order predictive modeling (PM) methodology based on the maximum entropy (MaxEnt) principle for obtaining best-estimate mean values and correlations for model responses and parameters. This methodology is designated by the acronym 2nd-BERRU-PMP, where the attribute “2nd” indicates that this methodology incorporates second- order uncertainties (means and covariances) and second (and higher) order sensitivities of computed model responses to model parameters. The acronym BERRU stands for “Best-Estimate Results with Reduced Uncertainties” and the last letter (“P”) in the acronym indicates “probabilistic,” referring to the MaxEnt probabilistic inclusion of the computational model responses. This is in contradistinction to the 2nd-BERRU-PMD methodology, which deterministically combines the computed model responses with the experimental information, as presented in the accompanying work (Part I). Although both the 2nd-BERRU-PMP and the 2nd-BERRU-PMD methodologies yield expressions that include second (and higher) order sensitivities of responses to model parameters, the respective expressions for the predicted responses, for the calibrated predicted parameters and for their predicted uncertainties (covariances), are not identical to each other. Nevertheless, the results predicted by both the 2nd-BERRU-PMP and the 2nd-BERRU-PMD methodologies encompass, as particular cases, the results produced by the extant data assimilation and data adjustment procedures, which rely on the minimization, in a least-square sense, of a user-defined functional meant to represent the discrepancies between measured and computed model responses.

数字经济环境下数据犯罪规制和认定模式的演变

在数字经济环境下,保证数据安全和保障数据共享活力同样重要,数据犯罪的规制和认定应当同时满足这两方面的需求。现有数据犯罪规制和认定采用的是权利保护模式,即通过保护数据权利主体的利益进行数据犯罪规制和认定。权利保护模式不能满足数字经济发展的需求;以非法获取行为为规制重点的前置化保护不当可能导致数据流通受阻;现行刑法规制数据犯罪行为方式的局限可能导致数据安全保护不全面。数据犯罪规制和认定应当采用秩序维护模式,关注数据价值实现过程中各方主体的利益,看重一般数据的公共产品属性。为实现数据犯罪规制和认定的秩序维护模式,立法者应当增设维护数据管理秩序的新罪名。在数据犯罪的司法认定上,也需要及时调整思路,做好保护数据安全和保障数据共享活力之间的利益平衡。

Fourth-Order Predictive Modelling: I. General-Purpose Closed-Form Fourth-Order Moments-Constrained MaxEnt Distribution

This work (in two parts) will present a novel predictive modeling methodology aimed at obtaining “best-estimate results with reduced uncertainties” for the first four moments (mean values, covariance, skewness and kurtosis) of the optimally predicted distribution of model results and calibrated model parameters, by combining fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters. Underlying the construction of this fourth-order predictive modeling methodology is the “maximum entropy principle” which is initially used to obtain a novel closed-form expression of the (moments-constrained) fourth-order Maximum Entropy (MaxEnt) probability distribution constructed from the first four moments (means, covariances, skewness, kurtosis), which are assumed to be known, of an otherwise unknown distribution of a high-dimensional multivariate uncertain quantity of interest. This fourth-order MaxEnt distribution provides optimal compatibility of the available information while simultaneously ensuring minimal spurious information content, yielding an estimate of a probability density with the highest uncertainty among all densities satisfying the known moment constraints. Since this novel generic fourth-order MaxEnt distribution is of interest in its own right for applications in addition to predictive modeling, its construction is presented separately, in this first part of a two-part work. The fourth-order predictive modeling methodology that will be constructed by particularizing this generic fourth-order MaxEnt distribution will be presented in the accompanying work (Part-2).

考虑载客状态的改进孤立森林浮动车异常数据检测算法

为提高浮动车数据中异常数据检测能力及不同载客状态下的模型检测分析能力,提出基于S-DTA-IIForest(Summation&Difference Third Order Average&Improvement-Isolation Forest)的浮动车数据异常检测算法。构建由相邻两项求和(S)、三阶求和平均差分(DTA)的二维度空间SDTA特征向量;提出差额累计更新和动态区分辨识的改进孤立森林IIForest算法,通过设置停止阈值参数,避免当出现新样本异常值分数大于停止阈值时,仅更新样本不更新孤立森林模型的问题,设计每个二叉树区分辨识度参数,区分辨识度位于停止区间时停止二叉树生长,提高算法收敛性能,以ROC(Receiver Operating Characteristic)曲线下面积AUC(Area Under ROC Cure)、F1-score为指标对模型精度进行对比分析,并以重庆市中心城区学府大道开展实例验证。结果表明:本文S-DTA-IIForest组合算法AUC、F1-score分别为86.63%、0.89,AUC较传统孤立森林IForest(Isolation Forest)提高32.4%,运行效率提高1.29%,具有收敛速度更快、精度更高的优势,载客条件下模型AUC、F1-score较未载客分别提高7.7%、10.8%,组合算法对载客数据有更高的检测精度,且未载客状态数据异常率较载客状态增加71.4%,未载客数据异常率更高。

数据不正当竞争行为判定的反思与完善

准确判定数据不正当竞争行为是规制该类行为的关键。实证考察2012-2023年的数据不正当竞争案件裁判文书后发现,对数据不正当竞争行为判定,普遍适用权益侵害判定范式,这误读了反不正当竞争法的法律属性;对竞争关系的认定存在拓宽化的倾向,其在数字时代反不正当竞争法适用中的现实价值和改进进路尚待厘清;既有的以“搭便车”原则、互联网行业惯例和法官创制性细则为标准具体化商业道德的进路皆无法化解商业道德的不确定性难题。对此,为促进数据健康有序流动,维护数字市场的竞争秩序,应实现数据不正当竞争行为判定路径的“系统性”变革。首先,应实现权益侵害判定范式向行为正当判定范式的有效转变,确保法院裁判结果符合反不正当竞争法的法益保护目标和契合数字经济发展的需求;其次,纠正“竞争关系决定论”的误区,调整竞争关系在数据不正当竞争案件中的角色定位,将其作为认定原告资格的重要标准和评测损害程度的因素;最后,认定商业道德应兼顾公平竞争价值与自由竞争价值,遵循“由事实到价值”的商业道德内涵的确定步骤,肯定模仿自由并慎用“搭便车”裁判标准,并且在援引互联网行业惯例时应对其是否符合法律法规和有助于维护竞争秩序予以考察,应让创设的商业道德具体细则符合反不正当竞争法的价值目标。

Advanced derivative ratio filters for edge detection of potential field data

Edge location is an important information of the source,and can be obtained by the potential field data. Most edge detection methods of potential field data are the functions of horizontal and vertical derivatives.The authors provide a new strategy to establish edge detection filters that can improve the resolution to identify small bodies,which use the ratio functions of different-order derivatives to recognize the edges of the sources.The new filter is named as advanced derivative ratio( ADR) filter and balanced outputs can be produced for different forms of ADR filters. The ADR filters are tested on synthetic data and real potential field data. The advantage of the ADR filters is that they can detect the edges of the causative sources more precisely and clearly,and the model testing results show that the resolution of ADR filters is higher than other existing filters. The ADR filters were applied to real data,with more subtle details obtained.

科学数据共享伦理秩序建构研究

[目的/意义]科学数据共享伦理秩序建构,旨在强化共享参与主体行为的正当性与合理性,规范共享过程与规约主体间际关系。科学数据共享是新型数据赋权场域,数据共享风险及不确定性增强,为避免数据共享及重用伦理失序问题,科学数据共享伦理秩序建构亟不可待。[方法/过程]在阐释科学数据伦理秩序内涵与属性的基础上,论证科学数据共享伦理秩序建构的实然基础与应然要求,系统论述科学数据共享伦理秩序的建构进路。[结果/结论]科学数据共享伦理秩序建构需要遵循理念公平、过程公正与结果正义的基本价值准则,以制度契约保障有效性、以激励机制确保可实施性、以平台互惠共生治理逻辑实现可控性。

考虑新能源多重相关性的柔性配电网分布鲁棒优化策略

高比例分布式新能源与全控型柔性电力电子元器件的大量接入,给传统配电网带来更多清洁电能与调控选择的同时,其出力的时空分布不均衡性与海量器件调节的复杂性,亦使得配电网的运行面临严峻挑战。对此,提出了一种考虑新能源多重相关性的柔性配电网分布鲁棒优化策略。首先,以配电网有功损耗与电压偏移最小为目标,推导并构建含多种源网荷协同调控措施的柔性配电网最优潮流模型。然后,计及新能源在时间空间与功率维度上的多重相关性,建立了基于数据驱动的柔性配电网两阶段分布鲁棒优化模型,采用1-范数与∞-范数进行源荷不确定性集合描述,并采用二阶锥将其线性化与凸松弛。最后,采用列与约束生成算法对该模型进行求解,并以改进的IEEE 33节点测试系统为例进行仿真分析,验证了该方法的有效性和实用性。

含有输入时滞的非线性系统的输出反馈采样控制

针对含有输入时滞和低阶非线性项的非线性系统,提出一种基于采样机制的无记忆输出反馈控制方法.该方法移除了传统预测控制方法预测映射难以确定的限制,同时避免了时滞依赖方法对过去时刻状态信息的依赖性,在实际中更易实现.首先,根据系统输出在采样时刻的信息,利用加幂积分技术和齐次占优思想设计了无记忆输出反馈采样控制器.然后,利用齐次系统理论提出了闭环系统的稳定性条件.最后,仿真结果验证了所提方法的有效性和优越性.

元宇宙时代法律秩序的风险挑战与制度回应

元宇宙是运用区块链、人工智能、大数据等高新数字技术创造出的虚拟世界,其本质是对现实社会生活的映射。元宇宙的“数字技术化”“技术数字化”以及类似于“数字社会”的技术特征,这些都对现行法律秩序产生了重大冲击。对此予以回应的法治路径,存在“重构”与“调整”之争。基于元宇宙时代法律秩序的本质内涵而言,会发现元宇宙对于现行法律秩序只是“新瓶装旧酒”。人们虽然可以在“元宇宙社会”中进行各种活动,但并不意味这就是人们未来的生活方式,故尚无必要为其重构法律秩序。而是应基于元宇宙的技术特征进行制度回应,从重视数字基础设施的建设、规范数据的收集与处理、确立良性算法的价值导向、落实数字平台主体的责任层面出发,以有效应对元宇宙时代带来的风险挑战。

基于Visual Studio下MES系统开发与应用

针对自动化罐装产线存在工序间实时信息无法互享互通,生产数据滞后,订单、制造、仓储模块间不协同的问题,基于Visual Studio软件,在C/S架构模式下,设计开发了自动化罐装产线的MES系统。可实现订单排产功能对生产订单全周期管理、数据监控经S7协议实时采集产线数据、SQL Server数据库对信息储存和分析、仓储管控实现自动化、精益化产品库存管理。MES系统产线运行表明,订单准时交付率100%,采集产线数据完整精确,仓储管控智能精益。为产业“智改数转”提供了典型的工程应用范例和借鉴。

“组态软件技术”课程教学设计与实践

在工程教育专业认证持续深入推进的背景下,结合电气工程专业特色,对“组态软件技术”课程教学进行重新设计与教学实践。引入高阶思维临场认知对教学内容进行重构,应用课堂多源数据建立教学评测一体化的教学新模式。实践表明该课程的教学设计有着良好的沉浸式体验感,学生主动建构、解决问题的高阶思维能力得到提升,新的教学模式促进了课程教学的高质量发展。