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构建中国特色刑法观应当关注的五大关系

学习论坛 2025年第1期 126-136页

作者：郑延谱曾钜中北京师范大学法学院北京100091

构建中国特色现代刑法观,应当关注其与中国传统刑法观、外来刑法理论、中国自主知识体系、中国刑事立法、中国刑事司法之间的五大关系。在传统刑法观的基础上,需建立“一体两翼三联结”的结构,目的在于以法治为灵魂,以三大刑法基本原则... 详细信息

构建中国特色现代刑法观,应当关注其与中国传统刑法观、外来刑法理论、中国自主知识体系、中国刑事立法、中国刑事司法之间的五大关系。在传统刑法观的基础上,需建立“一体两翼三联结”的结构,目的在于以法治为灵魂,以三大刑法基本原则为支柱,以中国特色社会主义理论为行动指南,建立具有中国特色的刑法观。外来刑法理论为刑法原则、刑罚目的、法益平衡、犯罪治理的研究切入视角,同时为社会主义精神文明建设领域内新型犯罪活动的治理等方面提供启示。一方面,中国特色现代刑法观的自主性需要以高质量学术人才培养体系作支撑;另一方面,刑法观的独特价值体现于文化中所承载的公平、正义。中华传统法律文化缺乏权利平等的实质,在构建中国刑法自主话语体系的过程中,成为应当着力修补的短板。习近平法治思想是引领中国刑法观进而构建中国刑法自主话语体系的指导思想,体现为刑法基本原则的刑法观应作为构建中国刑法观自主话语体系的三大支柱。

关键词：刑法观中国特色自主知识体系构建关系

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基于语料库的朝鲜语命名实体结构特征研究

外语学刊 2025年第1期 9-18页

作者：黄政豪金光洙延边大学工学院延吉133002 延边大学外国语学院延吉133002

本文统计Klue⁃ner和Kochet⁃ner两个命名实体语料库中的新闻、评论和文化遗产文本数据包含的不同类别朝鲜语命名实体。根据统计结果分析朝鲜语命名实体的音节长度特征分布和格词尾结合率。分析结果表明,音节长度和格词尾的使用在命名实... 详细信息

本文统计Klue⁃ner和Kochet⁃ner两个命名实体语料库中的新闻、评论和文化遗产文本数据包含的不同类别朝鲜语命名实体。根据统计结果分析朝鲜语命名实体的音节长度特征分布和格词尾结合率。分析结果表明,音节长度和格词尾的使用在命名实体分类中具有一定的规律可循。本文的研究成果可用于命名实体分类工作,同时也可以为朝鲜语命名实体语料库构建提供分布结构建议。

关键词：朝鲜语格词尾命名实体识别特征提取名词分类

铝在N,N-二甲基丁胺-氯化铝熔盐中的低温电沉积

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有色金属（冶炼部分） 2025年第1期 72-76,98页

作者：郑勇王倩罗家还李玲郑永军田大勇安阳工学院化学与环境工程学院安阳市低温电解铝与节能减排重点实验室河南安阳455000 中国科学院过程工程研究所离子液体清洁过程北京市重点实验室北京100190

开发新型的电解质以及低温电解铝技术是促进铝工业改革创新的重要途径之一。采用N,N-二甲基丁胺、无水氯化铝为原料,混合制备得到了新型低温熔盐。结果证明,该熔盐为氯铝酸型离子液体,可以在其中实现铝的低温电沉积。在此基础上,系统考... 详细信息

开发新型的电解质以及低温电解铝技术是促进铝工业改革创新的重要途径之一。采用N,N-二甲基丁胺、无水氯化铝为原料,混合制备得到了新型低温熔盐。结果证明,该熔盐为氯铝酸型离子液体,可以在其中实现铝的低温电沉积。在此基础上,系统考察了试验温度、电解电位、反应时间对铝的电沉积、表面形貌和化学组成的影响规律,获得了纯度较高的金属铝。有关研究为低温电解铝技术的发展及其在铝精炼和电镀铝中的应用提供了一定的科学依据。

关键词：铝低温熔盐离子液体电沉积电解

Homotopy based optimal configuration space reduction for anytime robotic motion planning

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Chinese journal of Aeronautics 2021年第1期34卷 364-379页

作者： Yang LIU zheng zheng Fangyun QIN School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191083China

Anytime sampling-based motion planning algorithms are widely used in practical applications due to limited real-time computing *** algorithm quickly finds feasible paths and incrementally improves them to the optimal ***,anytime sampling-based algorithms bring a paradox in convergence speed since finding a better path helps prune useless candidates but also introduces unrecognized useless candidates by *** on the words of homotopy classes,we propose a Homotopy class Informed Preprocessor(HIP)to break the paradox by providing extra *** comparing the words of path candidates,HIP can reveal wasteful edges of the sampling-based graph before finding a better *** experimental results obtained in many test scenarios show that HIP improves the convergence speed of anytime sampling-based algorithms.

关键词： Collision avoidance Homotopy Motion planning Rapidly-exploring Random Tree(RRT) Robots

Energy-aware deployment of dense heterogeneous cellular networks with QoS constraints

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Science China(Information Sciences) 2017年第4期60卷 148-165页

作者： Qimei CUI Zhiyan CUI Wei zheng Riku jNTTI Weiliang XIE National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications Department of Communications and Networking Aalto University China Telecom Corporation Limited

The base station(BS) configuration is a key factor to improve energy efficiency(EE). In this paper,we focus on designing the network deployment parameters(i.e., BS densities) for biased K-tier heterogeneous cellular network(HCN) with quality of service(Qo S) provisioning. Using appropriate approximations, we derive the closed-form expressions of optimal BS density across all tiers to minimize the area power consumption(APC) by applying the stochastic geometry theory, while satisfying the users’ Qo S requirements. These results are used to obtain some new insights into the EE performance of biased HCN deployment. With the aid of this approach, the best type of BSs to be deployed or switched off for energy saving purposes can be identified from the perspectives of BS transmission power. More precisely, if the BS transmission power ratio between an arbitrary pair of tiers of K-tier HCN, e.g., the small cell BS and macro BS tiers, is higher than a threshold which is a function of path loss exponent, bias factor and power consumption, the small cell BSs are *** opposite situation takes place otherwise. Furthermore, it is also shown that, compared to the unbiased HCN scenario, significant energy savings are possible by appropriately biasing the HCN and optimizing the BS density, subject to the Qo S constraints among all tiers.

关键词： heterogeneous cellular networks stochastic geometry energy efficiency BS density energy saving

Exploiting multi-channels deep convolutional neural networks for multivariate time series classification

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Frontiers of Computer Science 2016年第1期10卷 96-112页

作者： Yi zheng QiLIU Enhong CHEN Yong GE j. Leon ZHAO School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Department of Computer Science University of North Carolina at Charlotte Charlotte 28223 USA Department of Information Systems City University of Hong Kong Hong Kong China

Time series classification is related to many dif- ferent domains, such as health informatics, finance, and bioinformatics. Due to its broad applications, researchers have developed many algorithms for this kind of tasks, e.g., multivariate time series classification. Among the classifi- cation algorithms, k-nearest neighbor （k-NN） classification （particularly 1-NN） combined with dynamic time warping （DTW） achieves the state of the art performance. The defi- ciency is that when the data set grows large, the time con- sumption of 1-NN with DTW will be very expensive. In con- trast to 1-NN with DTW, it is more efficient but less ef- fective for feature-based classification methods since their performance usually depends on the quality of hand-crafted features. In this paper, we aim to improve the performance of traditional feature-based approaches through the feature learning techniques. Specifically, we propose a novel deep learning framework, multi-channels deep convolutional neu- ral networks （MC-DCNN）, for multivariate time series classi- fication. This model first learns features from individual uni- variate time series in each channel, and combines information from all channels as feature representation at the final layer. Then, the learnt features are applied into a multilayer percep- tron （MLP） for classification. Finally, the extensive experi- ments on real-world data sets show that our model is not only more efficient than the state of the art but also competitive in accuracy. This study implies that feature learning is worth to be investigated for the problem of time series classification.

关键词： convolutional neural networks time series clas-sification feature learning deep learning

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基于SIR模型的城市路网拥堵传播分析

郑州大学学报（工学版） 2025年第1期46卷 51-58页

作者：郑长江周思达郑树康马庚华张博戴津雯河海大学土木与交通学院江苏南京210098 河海大学环境学院江苏南京210098 河海大学港口海岸与近海工程学院江苏南京210098

研究城市道路交通拥堵传播规律对缓解交通拥堵问题有着积极作用,为此建立了基于SIR的城市道路交通拥堵传播模型,用以分析城市道路交通拥堵传播过程。首先,基于城市实际路网构建路网对偶拓扑网络,并依据SIR建立交通拥堵传播模型。其次,... 详细信息

研究城市道路交通拥堵传播规律对缓解交通拥堵问题有着积极作用,为此建立了基于SIR的城市道路交通拥堵传播模型,用以分析城市道路交通拥堵传播过程。首先,基于城市实际路网构建路网对偶拓扑网络,并依据SIR建立交通拥堵传播模型。其次,结合道路网络的复杂网络特征和道路自身的相关属性,引入随机森林算法计算相关权重,确定拥堵模型中的传播速率等关键参数。最后,以南京市秦淮区某区域路网为例,构建有69个节点,163条连线的城市路网对偶拓扑网络进行仿真实验。结果表明:道路节点度和道路饱和度是影响道路拥堵传播的关键因素,道路节点度的影响相对较小,传播范围增长在5%以内,恢复时间影响在10%左右;道路饱和度的影响相对较大,随着道路饱和度的增长,传播范围增长最大可至40%,恢复时间影响在20%左右。

关键词： SIR模型城市交通拥堵传播道路节点度道路饱和度

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Convexification of Hybrid AC-DC Optimal Power Flow with Line-Commutated Converters

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CSEE journal of Power and Energy Systems 2024年第2期10卷 617-628页

作者： Hongyuan Liang Zhigang Li j.H.zheng Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Line-commutated converter (LCC)-based high-voltage DC (HVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.

关键词： AC-DC power system convex relaxation linecommutated converter optimal power flow second-order cone programming

Dispatchable Region for Active Distribution Networks Using Approximate Second-order Cone Relaxation

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CSEE journal of Power and Energy Systems 2023年第6期9卷 1999-2007页

作者： Zhigang Li Wenjing Huang j.H.zheng Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

Uncertainty in distributed renewable generation threatens the security of power distribution *** concept of dispatchable region is developed to assess the ability of power systems to accommodate renewable generation at a given operating *** DC and linearized AC power flow equations are typically used to model dispatchable regions for transmission systems,these equations are rarely suitable for distribution *** achieve a suitable trade-off between accuracy and efficiency,this paper proposes a dispatchable region formulation for distribution networks using tight convex *** cone relaxation is adopted to reformulate AC power flow equations,which are then approximated by a polyhedron to improve ***,an efficient adaptive constraint generation algorithm is employed to construct the proposed dispatchable *** studies on distribution systems of various scales validate the computational efficiency and accuracy of the proposed method.

关键词： Dispatchable region distribution system renewable power generation second-order cone relaxation uncertainty