The Impact of Strategic Leadership on Innovation Ambidexterity:The Mediating Effect of Social Capital

This study focused on the strategic leadership in the organization and the internal and external social capital can be seen as the ambidexterity innovation assets for building organization capability.The research selected 500 top managers and 385 ones were returned,using purposive sampling in Southern Tainan Real Estate firms as subjects to explore the interactions and relationships among strategic leadership,social capital,innovation ambidexterity,and contextual ambidexterity,and examines the fitness of model in this study.The data were analyzed by a variety of statistical methods,such as regression analysis,hierarchical regression analysis,ANOVA,and SEM to test the hypotheses of this study and model fitness.The conclusions are as follows:(1)Strategic leadership has significant positive influence on social capital and innovation ambidexterity.(2)Social capital has significant positive influence on innovation ambidexterity.(3)Good model fitness of relationship exists among each construct,and the social capital has significant mediating effects between strategic leadership and innovation ambidexterity.(4)The relationship between social capital and innovation ambidexterity has a moderating influence of contextual ambidexterity.

Blockchain-Based Certificateless Cross-Domain Authentication Scheme in the Industrial Internet of Things

The Industrial Internet of Things(IIoT)consists of massive devices in different management domains,and the lack of trust among cross-domain entities leads to risks of data security and privacy leakage during information exchange.To address the above challenges,a viable solution that combines Certificateless Public Key Cryptography(CL-PKC)with blockchain technology can be utilized.However,as many existing schemes rely on a single Key Generation Center(KGC),they are prone to problems such as single points of failure and high computational overhead.In this case,this paper proposes a novel blockchain-based certificateless cross-domain authentication scheme,that integrates the threshold secret sharing mechanism without a trusted center,meanwhile,adopts blockchain technology to enable cross-domain entities to authenticate with each other and to negotiate session keys securely.This scheme also supports the dynamic joining and removing of multiple KGCs,ensuring secure and efficient cross-domain authentication and key negotiation.Comparative analysiswith other protocols demonstrates that the proposed cross-domain authentication protocol can achieve high security with relatively lowcomputational overhead.Moreover,this paper evaluates the scheme based on Hyperledger Fabric blockchain environment and simulates the performance of the certificateless scheme under different threshold parameters,and the simulation results show that the scheme has high performance.

A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles

The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the network.However,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain interactions.During such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication process.Additionally,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency issues.To mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for IoV.This scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree structures.It divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and security.Finally,we evaluate the performance of CAIoV.Experimental results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%.

A Post-Quantum Cross-Domain Authentication Scheme Based on Multi-Chain Architecture

Due to the rapid advancements in network technology,blockchain is being employed for distributed data storage.In the Internet of Things(IoT)scenario,different participants manage multiple blockchains located in different trust domains,which has resulted in the extensive development of cross-domain authentication techniques.However,the emergence of many attackers equipped with quantum computers has the potential to launch quantum computing attacks against cross-domain authentication schemes based on traditional cryptography,posing a significant security threat.In response to the aforementioned challenges,our paper demonstrates a post-quantum cross-domain identity authentication scheme to negotiate the session key used in the cross-chain asset exchange process.Firstly,our paper designs the hiding and recovery process of user identity index based on lattice cryptography and introduces the identity-based signature from lattice to construct a post-quantum cross-domain authentication scheme.Secondly,our paper utilizes the hashed time-locked contract to achieves the cross-chain asset exchange of blockchain nodes in different trust domains.Furthermore,the security analysis reduces the security of the identity index and signature to Learning With Errors(LWE)and Short Integer Solution(SIS)assumption,respectively,indicating that our scheme has post-quantum security.Last but not least,through comparison analysis,we display that our scheme is efficient compared with the cross-domain authentication scheme based on traditional cryptography.

SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer

This study proposes a novel general image fusion framework based on cross-domain long-range learning and Swin Transformer,termed as SwinFusion.On the one hand,an attention-guided cross-domain module is devised to achieve sufficient integration of complementary information and global interaction.More specifically,the proposed method involves an intra-domain fusion unit based on self-attention and an interdomain fusion unit based on cross-attention,which mine and integrate long dependencies within the same domain and across domains.Through long-range dependency modeling,the network is able to fully implement domain-specific information extraction and cross-domain complementary information integration as well as maintaining the appropriate apparent intensity from a global perspective.In particular,we introduce the shifted windows mechanism into the self-attention and cross-attention,which allows our model to receive images with arbitrary sizes.On the other hand,the multi-scene image fusion problems are generalized to a unified framework with structure maintenance,detail preservation,and proper intensity control.Moreover,an elaborate loss function,consisting of SSIM loss,texture loss,and intensity loss,drives the network to preserve abundant texture details and structural information,as well as presenting optimal apparent intensity.Extensive experiments on both multi-modal image fusion and digital photography image fusion demonstrate the superiority of our SwinFusion compared to the state-of-theart unified image fusion algorithms and task-specific alternatives.Implementation code and pre-trained weights can be accessed at https://github.com/Linfeng-Tang/SwinFusion.

Context Information and Fragments Based Cross-Domain Word Segmentation

A new joint decoding strategy that combines the character-based and word-based conditional random field model is proposed.In this segmentation framework,fragments are used to generate candidate Out-of-Vocabularies(OOVs).After the initial segmentation,the segmentation fragments are divided into two classes as "combination"(combining several fragments as an unknown word) and "segregation"(segregating to some words).So,more OOVs can be recalled.Moreover,for the characteristics of the cross-domain segmentation,context information is reasonably used to guide Chinese Word Segmentation(CWS).This method is proved to be effective through several experiments on the test data from Sighan Bakeoffs 2007 and Bakeoffs 2010.The rates of OOV recall obtain better performance and the overall segmentation performances achieve a good effect.

FedCDR:Privacy-preserving federated cross-domain recommendation

Cross-Domain Recommendation(CDR)aims to solve data sparsity and cold-start problems by utilizing a relatively information-rich source domain to improve the recommendation performance of the data-sparse target domain.However,most existing approaches rely on the assumption of centralized storage of user data,which undoubtedly poses a significant risk of user privacy leakage because user data are highly privacy-sensitive.To this end,we propose a privacy-preserving Federated framework for Cross-Domain Recommendation,called FedCDR.In our method,to avoid leakage of user privacy,a general recommendation model is trained on each user's personal device to obtain embeddings of users and items,and each client uploads weights to the central server.The central server then aggregates the weights and distributes them to each client for updating.Furthermore,because the weights implicitly contain private information about the user,local differential privacy is adopted for the gradients before uploading them to the server for better protection of user privacy.To distill the relationship of user embedding between two domains,an embedding transformation mechanism is used on the server side to learn the cross-domain embedding transformation model.Extensive experiments on real-world datasets demonstrate that ourmethod achieves performance comparable with that of existing data-centralized methods and effectively protects user privacy.

Achieving Consistence for Cross-Domain WAN Control in Software-Defined Networks

When applying Software-Defined Networks(SDN) to WANs,the SDN flexibility enables the cross-domain control to achieve a better control scalability.However,the control consistence is required by all the cross-domain services,to ensure the data plane configured in consensus for different domains.Such consistence process is complicated by potential failure and errors of WANs.In this paper,we propose a consistence layer to actively and passively snapshot the cross-domain control states,to reduce the complexities of service realizations.We implement the layer and evaluate performance in the PlanetLab testbed for the WAN emulation.The testbed conditions are extremely enlarged comparing to the real network.The results show its scalability,reliability and responsiveness in dealing with the control dynamics.In the normalized results,the active and passive snapshots are executed with the mean times of 1.873 s and 105 ms in135 controllers,indicating its readiness to be used in the real network.

Cross-Domain Authentication Scheme Based on Blockchain and Consistent Hash Algorithm for System-Wide Information Management

System-wide information management(SWIM)is a complex distributed information transfer and sharing system for the next generation of Air Transportation System(ATS).In response to the growing volume of civil aviation air operations,users accessing different authentication domains in the SWIM system have problems with the validity,security,and privacy of SWIM-shared data.In order to solve these problems,this paper proposes a SWIM crossdomain authentication scheme based on a consistent hashing algorithm on consortium blockchain and designs a blockchain certificate format for SWIM cross-domain authentication.The scheme uses a consistent hash algorithm with virtual nodes in combination with a cluster of authentication centers in the SWIM consortium blockchain architecture to synchronize the user’s authentication mapping relationships between authentication domains.The virtual authentication nodes are mapped separately using different services provided by SWIM to guarantee the partitioning of the consistent hash ring on the consortium blockchain.According to the dynamic change of user’s authentication requests,the nodes of virtual service authentication can be added and deleted to realize the dynamic load balancing of cross-domain authentication of different services.Security analysis shows that this protocol can resist network attacks such as man-in-the-middle attacks,replay attacks,and Sybil attacks.Experiments show that this scheme can reduce the redundant authentication operations of identity information and solve the problems of traditional cross-domain authentication with single-point collapse,difficulty in expansion,and uneven load.At the same time,it has better security of information storage and can realize the cross-domain authentication requirements of SWIM users with low communication costs and system overhead.KEYWORDS System-wide information management(SWIM);consortium blockchain;consistent hash;cross-domain authentication;load balancing.

Exploration on the Frontiers of Flexible and Deformable Cross-Domain Intelligent Flight

As human aeronautic and aerospace technology continues to prosper and the aerial flight space domain further expands,traditional fixed-shape air vehicles have been confronted with difficulties in satisfying complex missions in cross-domain scenarios.Owing to their flexible and deformable appearance,morphing air vehicles are expected to realize cross-domain intelligent flight,thus emerging as the most subversive strategic development trend and research focus in aeronautic and aerospace fields.This paper primarily reviews the research background and challenges of flexible and deformable cross-domain intelligent flight,proposing a corresponding research framework and mode as well as exploring the scientific issues and state-of-the-art solutions,where key research progress is introduced.The explorations covered in this paper also provide ideas and directions for the study of deformable cross-domain intelligent flight,which has critical scientific significance in promoting the study itself.

Cross-Domain Data Traceability Mechanism Based on Blockchain

With the application and development of blockchain technology,many problems faced by blockchain traceability are gradually exposed.Such as cross-chain information collaboration,data separation and storage,multisystem,multi-security domain collaboration,etc.To solve these problems,it is proposed to construct trust domains based on federated chains.The public chain is used as the authorization chain to build a cross-domain data traceability mechanism applicable to multi-domain collaboration.First,the architecture of the blockchain cross-domain model is designed.Combined with the data access strategy and the decision mechanism,the open and transparent judgment of cross-domain permission and cross-domain identity authentication is realized.And the public chain consensus node election mechanism is realized based on PageRank.Then,according to the characteristics of a nonsingle chain structure in the process of data flow,a data retrievalmechanism based on a Bloom filter is designed,and the cross-domain traceability algorithm is given.Finally,the safety and effectiveness of the traceability mechanism are verified by security evaluation and performance analysis.

A Cross-Domain Trust Model of Smart City IoT Based on Self-Certification

Smart city refers to the information system with Intemet of things and cloud computing as the core tec hnology and government management and industrial development as the core content,forming a large scale,heterogeneous and dynamic distributed Internet of things environment between different Internet of things.There is a wide demand for cooperation between equipment and management institutions in the smart city.Therefore,it is necessary to establish a trust mechanism to promote cooperation,and based on this,prevent data disorder caused by the interaction between honest terminals and malicious temminals.However,most of the existing research on trust mechanism is divorced from the Internet of things environment,and does not consider the characteristics of limited computing and storage capacity and large differences of Internet of hings devices,resuling in the fact that the research on abstract trust trust mechanism cannot be directly applied to the Internet of things;On the other hand,various threats to the Internet of things caused by security vulnerabilities such as collision attacks are not considered.Aiming at the security problems of cross domain trusted authentication of Intelligent City Internet of things terminals,a cross domain trust model(CDTM)based on self-authentication is proposed.Unlike most trust models,this model uses self-certified trust.The cross-domain process of internet of things(IoT)terminal can quickly establish a trust relationship with the current domain by providing its trust certificate stored in the previous domain interaction.At the same time,in order to alleviate the collision attack and improve the accuracy of trust evaluation,the overall trust value is calculated by comprehensively considering the quantity weight,time attenuation weight and similarity weight.Finally,the simulation results show that CDTM has good anti collusion attack ability.The success rate of malicious interaction will not increase significantly.Compared with other models,the resource consumption of our proposed model is significantly reduced.

BLECA: A Blockchain-Based Lightweight and Efficient Cross-Domain Authentication Scheme for Smart Parks

Smart parks serve as integral components of smart cities,where they play a pivotal role in the process of urban modernization.The demand for cross-domain cooperation among smart devices from various parks has witnessed a significant increase.To ensure secure communication,device identities must undergo authentication.The existing cross-domain authentication schemes face issues such as complex authentication paths and high certificate management costs for devices,making it impractical for resource-constrained devices.This paper proposes a blockchain-based lightweight and efficient cross-domain authentication protocol for smart parks,which simplifies the authentication interaction and requires every device to maintain only one certificate.To enhance cross-domain cooperation flexibility,a comprehensive certificate revocation mechanism is presented,significantly reducing certificate management costs while ensuring efficient and secure identity authentication.When a park needs to revoke access permissions of several cooperative partners,the revocation of numerous cross-domain certificates can be accomplished with a single blockchain write operation.The security analysis and experimental results demonstrate the security and effectiveness of our scheme.

创业叙事对创业绩效的影响研究——组织双元性、资源获取与修辞策略的作用

企业是有机资源综合体,其成长与发展离不开相关利益者的资源支持,对创业企业而言,捉襟见肘的资源匮乏是常态问题,尤其需要得到相关利益者的支持,而对创业企业的认可是其资源投入的先决条件。创业叙事是创业者构建组织双元性、满足相关利益者诉求预期及吸引和说服其资源投入的关键手段。而创业叙事对创业成功的影响效应、黑箱机制与边界条件如何等,既有研究尚未揭示。基于此,本研究旨在科学界定创业叙事修辞策略内涵构成,合理开发相应测量工具,探究创业叙事对创业绩效的影响效应,揭示组织双元性与资源获取的中介作用机理,同时考察修辞策略在其间的边界条件作用。实证研究得出如下结论:(1)创业修辞策略即为达到某种创业表述目的而刻意使用的劝服性话语,其量表包括行业共性描述和独特优势阐述两维13题项;(2)创业叙事显著正向影响创业绩效;(3)组织双元性与资源获取在创业叙事对创业绩效的影响中起链式中介作用;(4)行业共性描述修辞策略强化创业叙事对组织合法性的影响,而独特优势阐述修辞策略强化创业叙事对组织竞争性的影响。

知识产权保护、创业导向与双元创新

创新型经济以保护知识产权为着力点,以创业企业作为推动经济创新的重要载体。突破创新者困境的关键在于双元创新,因此探究知识产权保护的正负效应对双元创新的差异化影响,以及不同类型创业导向的中介机制具有实践价值。结果发现:①知识产权保护对创业企业探索式创新具有正效应,而对利用式创新具有负效应;②基于战略认知观发现,知识产权保护能够强化自主研发型导向,而抑制技术引进型导向;③知识产权保护通过激发自主研发型导向对探索式创新产生正效应,通过抑制技术引进型导向对利用式创新产生负效应。由此,构建差异化创新路径,以期为创业企业持续创新发展提供有益的洞见。

基于悖论认知框架的团队双元之演化趋势及影响过程研究

基于悖论认知框架,探讨团队悖论认知变化对团队双元变化的影响,以及团队社会整合与任务整合发挥的作用。通过对145个研发团队为期4个月的追踪调查获取数据,并构建潜变量增长模型假设。研究发现:随着时间推移,团队双元呈现出显著的向上增长趋势;团队悖论认知的变化正向影响团队双元的变化;团队任务整合正向影响团队悖论认知的变化,从而间接影响团队双元的变化;团队社会整合负向影响团队悖论式认知的变化,从而间接影响团队双元的变化。

组态视角下高校双元创新驱动策源能力建设的路径研究——基于中国31个省份的QCA分析

基于组态分析视角,以我国31个省市为案例样本,运用模糊集定性比较法(fsQCA)探讨高校双元创新行为、要素和能力相互组合的“化学反应”,实现创新策源浓度、潜力和效率提升的有效路径。研究发现:高校双元创新促进创新策源能力建设具有“多重并发”和“殊途同归”的特点,存在探索式创新驱动型、融合式创新驱动型和要素协同驱动型3种组态类型,共计5条具体路径。不同地区高校在提升创新策源能力建设水平时,要充分把握创新人才这一关键要素的支撑作用,将局部优化的单一思维及时转变为组态协调的系统思维,真正做到统筹推进、把握关键、因地制宜,做出具有前瞻性和针对性的策略设计。

智能制造企业的双元创新路径研究

在高质量发展的背景下,智能制造企业如何通过双元创新来提高企业绩效已成为学术界和实践界关注的话题。动态能力凭借其兼顾探索式与利用式双元创新平衡的特质,成为智能制造企业应对环境变化的重要因素,而服务化也是提高智能制造企业创新绩效的重要因素,但现有研究却较少将两者纳入同一个创新路径研究体系。基于双元创新、服务化与动态能力等基础理论,构建了“服务化、动态能力—双元创新—企业绩效”理论模型,并参考借鉴了国内外比较成熟的量表设计问卷,通过Credamo平台搜集我国387家智能制造企业的样本数据,运用结构方程模型(SEM),实证研究服务化产品和客户导向、整合重构能力、组织和技术柔性能力等核心要素对双元创新的影响,以及双元创新对企业绩效的影响路径。研究结果表明:在智能制造企业中,服务化客户导向对探索式创新的影响更为显著,服务化产品导向对利用式创新的影响更为显著;整合重构能力对利用式创新的促进作用更为显著,组织和技术柔性能力对探索式创新的促进作用更为显著;相较于利用式创新,探索式创新对企业绩效的影响更为显著;在双元驱动下智能制造企业的创新模型中存在两条路径,其中一条创新路径为“组织和技术柔性能力、服务化客户导向—探索式创新—企业绩效”,另一条创新路径为“整合重构能力、服务化产品导向—利用式创新—企业绩效”。最后,就智能制造企业如何培育发展服务化和动态能力,促进双元创新并有效提升企业绩效提供了理论指导和对策建议:智能制造企业的创新发展亟须培育服务化新业态;智能制造企业的创新发展亟须培育动态能力,包括整合重构能力、组织和技术柔性能力;智能制造企业要从自身发展的核心痛点出发,通过双元创新提高企业绩效。

A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

高技术企业利用大数据能力实现创新双元性的多元路径——基于知识动态能力的组态分析

立足于数字经济背景,研究采用fsQCA方法,以236家高技术企业为对象,探讨多维度大数据分析能力与内部动态能力联动实现创新双元性的组态路径。研究发现:(1)大数据人员能力是创新双元性的核心条件。(2)存在两类驱动路径,即基础决策型、管理优化型的时间双元模式与分析协同型的结构双元模式。(3)知识协同辅助下,大数据管理及人员能力是实现创新双元性的关键;大数据基础设施与管理能力存在驱动与抑制效应的替代关系。研究结论有助于厘清如何在数字化背景下整合利用不同类型数字能力,帮助高技术企业兼顾探索式创新与利用式创新。