Detection of Turbulence Anomalies Using a Symbolic Classifier Algorithm in Airborne Quick Access Record(QAR)Data Analysis

As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.

A Blind Batch Encryption and Public Ledger-Based Protocol for Sharing Sensitive Data

For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.

Big Data Access Control Mechanism Based on Two-Layer Permission Decision Structure

Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access controlmechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policymanagement efficiency and difficulty in accurately describing the access control policy. To overcome theseproblems, this paper proposes a big data access control mechanism based on a two-layer permission decisionstructure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes areintroduced in the ABAC model as business constraints between entities. The proposed mechanism implementsa two-layer permission decision structure composed of the inherent attributes of access control entities and thebusiness attributes, which constitute the general permission decision algorithm based on logical calculation andthe business permission decision algorithm based on a bi-directional long short-term memory (BiLSTM) neuralnetwork, respectively. The general permission decision algorithm is used to implement accurate policy decisions,while the business permission decision algorithm implements fuzzy decisions based on the business constraints.The BiLSTM neural network is used to calculate the similarity of the business attributes to realize intelligent,adaptive, and efficient access control permission decisions. Through the two-layer permission decision structure,the complex and diverse big data access control management requirements can be satisfied by considering thesecurity and availability of resources. Experimental results show that the proposed mechanism is effective andreliable. In summary, it can efficiently support the secure sharing of big data resources.

Blockchain-Enabled Privacy Protection and Access Control Scheme Towards Sensitive Digital Assets Management

With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.

Cross-Domain Bilateral Access Control on Blockchain-Cloud Based Data Trading System

Data trading enables data owners and data requesters to sell and purchase data.With the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of attention.Particularly,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform.Moreover,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace.In the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple domains.In this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading systems.We consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud provider.The proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic techniques.In the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature scheme.Therefore,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each other.To demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.

A comparative study on characteristics of retracted publications across different open access levels

Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Optimizing Memory Access Efficiency in CUDA Kernel via Data Layout Technique

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale computing. Despite these advancements, efficiently programming GPUs remains a daunting challenge, often relying on trial-and-error optimization methods. This paper introduces an optimization technique for CUDA programs through a novel Data Layout strategy, aimed at restructuring memory data arrangement to significantly enhance data access locality. Focusing on the dynamic programming algorithm for chained matrix multiplication—a critical operation across various domains including artificial intelligence (AI), high-performance computing (HPC), and the Internet of Things (IoT)—this technique facilitates more localized access. We specifically illustrate the importance of efficient matrix multiplication in these areas, underscoring the technique’s broader applicability and its potential to address some of the most pressing computational challenges in GPU-accelerated applications. Our findings reveal a remarkable reduction in memory consumption and a substantial 50% decrease in execution time for CUDA programs utilizing this technique, thereby setting a new benchmark for optimization in GPU computing.

基于TOE框架的公共数据开放利用水平影响因素及提升路径分析

[目的/意义]揭示公共数据开放利用多重影响因素耦合下的多元路径,有助于深化理解公共数据利用联动效应,促进数据价值释放。[方法/过程]以27个省份为研究对象,基于TOE框架构建公共数据开放利用影响因素框架,通过模糊集定性比较分析和必要条件分析的方法进行组态路径分析,最终基于组态分析结果提出相应路径提升对策。[结果/结论]高与非高公共数据开放利用均存在4类组态路径,为其他地区因地制宜提升公共数据开放利用水平提供了路径借鉴。我国各地方应遵循国家公共数据开放指导思想,结合地方优势和特点选择适宜的路径以提升公共数据开放利用水平。

Identifying the uneven distribution of health and education services in China using open geospatial data

Growing attention has been directed to the use of satellite imagery and open geospatial data to understand large-scale sustainable development outcomes.Health and education are critical domains of the Unites Nations’Sus-tainable Development Goals(SDGs),yet existing research on the accessibility of corresponding services focused mainly on detailed but small-scale studies.This means that such studies lack accessibility metrics for large-scale quantitative evaluations.To address this deficiency,we evaluated the accessibility of health and education ser-vices in China's Mainland in 2021 using point-of-interest data,OpenStreetMap road data,land cover data,and WorldPop spatial demographic data.The accessibility metrics used were the least time costs of reaching hospital and school services and population coverage with a time cost of less than 1 h.On the basis of the road network and land cover information,the overall average time costs of reaching hospital and school were 20 and 22 min,respectively.In terms of population coverage,94.7%and 92.5%of the population in China has a time cost of less than 1 h in obtaining hospital and school services,respectively.Counties with low accessibility to hospitals and schools were highly coupled with poor areas and ecological function regions,with the time cost incurred in these areas being more than twice that experienced in non-poor and non-ecological areas.Furthermore,the cumulative time cost incurred by the bottom 20%of counties(by GDP)from access to hospital and school services reached approximately 80%of the national total.Low-GDP counties were compelled to suffer disproportionately increased time costs to acquire health and education services compared with high-GDP counties.The accessibil-ity metrics proposed in this study are highly related to SDGs 3 and 4,and they can serve as auxiliary data that can be used to enhance the evaluation of SDG outcomes.The analysis of the uneven distribution of health and education services in China can help identify areas with backward public services and may contribute to targeted and efficient policy interventions.

Scientific Value Weights more than Being Open or Toll Access:An analysis of the OA advantage in Nature and Science

Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries.Design/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA advantages.First,according to the OA classification of the Web of Science(WoS),we collect data from the WoS by downloading OA and TA articles,letters,and reviews published in Nature and Science during 2010–2019.These papers are divided into three broad disciplines,namely biomedicine,physics,and others.Then,taking a discipline in a journal and using the classical Latent Dirichlet Allocation(LDA)to cluster 100 topics of OA and TA papers respectively,we apply the Pearson correlation coefficient to match the topics of OA and TA,and calculate the hot-degree and R-index of every OA-TA topic pair.Finally,characteristics of the discipline can be presented.In qualitative comparison,we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs,and analyze the relations between OA/TA and citation numbers.Findings:The result shows that OA hot-degree in biomedicine is significantly greater than that of TA,but significantly less than that of TA in physics.Based on the R-index,it is found that OA advantages exist in biomedicine and TA advantages do in physics.Therefore,the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or TA.However,OA promotes the spread of important scientific discoveries in high-quality papers.Research limitations:We lost some citations by ignoring other open sources such as arXiv and bioArxiv.Another limitation came from that Nature employs some strong measures for access-promoting subscription-based articles,on which the boundary between OA and TA became fuzzy.Practical implications:It is useful to select hot topics in a set of publications by the hotdegree index.The finding comprehensively reflects the differences of OA and TA in different disciplines,which is a useful reference when researchers choose the publishing way as OA or TA.Originality/value:We propose a new method,including two indicators,to explore and measure OA or TA advantages.

How does a data strategy enable customer value?The case of FinTechs and traditional banks under the open finance framework

The coupling of data and digital innovation opens the way for new business in the financial services sector,where customers are placed at the centre of decisions and data can help to develop customer knowledge.To carry out our research,we adopted a multi-case study approach to explore how a data strategy is developed in the retail banking industry,together with its relationship with customer value,paying particular attention to the heterogeneity between traditional banks and financial technology companies(FinTechs).Two main points emerged from the study.Firstly,there are three possible approaches to Open Finance,which are mainly defined by their different corporate cultures,organisational configurations,technological architecture and data value.Secondly,it is not enough to be a FinTech to be best placed to exploit the market,as some traditional banks share the FinTechs’approach to Open Finance.Designing new tailored products,customising their prices and offering them over the right channels through targeted communication are all data-driven initiatives that stem from cross-or up-selling potential,core to the retail banking industry for turning a customer into a cash flow,thus enabling value to be created for customers.Our findings additionally revealed that there is a form of external information asymmetry between the customer and the bank,and that there is also an internal asymmetry between bank departments,as their visibility on information about the same customer may differ.

HiLog:OpenHarmony的高性能日志系统

日志是计算机系统中记录事件状态信息的的重要载体,日志系统负责计算机系统的日志生成、收集和输出.OpenHarmony是新兴的、面向全设备、全场景的开源操作系统.在所述工作之前,包括日志系统在内OpenHarmony有许多关键子系统尚未构建,而OpenHarmony的开源特性使第三方开发者可以为其贡献核心代码.为了解决Open Harmony日志系统缺乏的问题,主要开展如下工作:(1)分析当今主流日志系统的技术架构和优缺点;(2)基于OpenHarmony操作系统的异构设备互联特性设计HiLog日志系统模型规范;(3)设计并实现第1个面向OpenHarmony的日志系统HiLog,并贡献到OpenHarmony主线;(4)对HiLog日志系统的关键指标进行测试和对比试验.实验数据表明,在基础性能方面,HiLog和Log的日志写入阶段吞吐量分别为1500 KB/s和700 KB/s,相比Android日志系统吞吐量提升114%;在日志持久化方面,HiLog可以3.5%的压缩率进行持久化,并且丢包率小于6‰,远低于Log.此外,HiLog还具备数据安全、流量控制等新型实用能力.

Ensuring Security, Confidentiality and Fine-Grained Data Access Control of Cloud Data Storage Implementation Environment

With the development of cloud computing, the mutual understandability among distributed data access control has become an important issue in the security field of cloud computing. To ensure security, confidentiality and fine-grained data access control of Cloud Data Storage (CDS) environment, we proposed Multi-Agent System (MAS) architecture. This architecture consists of two agents: Cloud Service Provider Agent (CSPA) and Cloud Data Confidentiality Agent (CDConA). CSPA provides a graphical interface to the cloud user that facilitates the access to the services offered by the system. CDConA provides each cloud user by definition and enforcement expressive and flexible access structure as a logic formula over cloud data file attributes. This new access control is named as Formula-Based Cloud Data Access Control (FCDAC). Our proposed FCDAC based on MAS architecture consists of four layers: interface layer, existing access control layer, proposed FCDAC layer and CDS layer as well as four types of entities of Cloud Service Provider (CSP), cloud users, knowledge base and confidentiality policy roles. FCDAC, it’s an access policy determined by our MAS architecture, not by the CSPs. A prototype of our proposed FCDAC scheme is implemented using the Java Agent Development Framework Security (JADE-S). Our results in the practical scenario defined formally in this paper, show the Round Trip Time (RTT) for an agent to travel in our system and measured by the times required for an agent to travel around different number of cloud users before and after implementing FCDAC.

政府数据开放平台效率评估及影响因素实证研究——基于无导向SBM-Malmquist-Tobit模型

[目的/意义]效率评估有利于掌握平台开放效率情况。将SBM、Malmquist和Tobit模型结合起来,形成一个综合评估框架,不仅可以评估当前效率,还可以分析效率变化趋势和影响因素,为政府数据开放平台效率评估提供新的方法借鉴。[方法/过程]以2019-2022年中国10个省市政府数据开放平台的“投入-产出”面板数据作为数据来源,利用无导向SBM模型不需要预设生产可能性边界方向的特性,使平台效率评估更加灵活和全面;利用Malmquist指数可衡量时间序列数据效率变化的特性,帮助平台识别效率演变趋势;利用Tobit模型适用于分析截尾数据的特性,帮助识别效率背后各影响因素的作用机理。[结果/结论]省市政府数据开放平台效率水平整体呈上升趋势,平均增长率为17.1%,其中深圳、广东表现较为突出,平台通过优化流程、提高服务质量、增强用户体验、提升运营模式等措施,使整体效率得到了显著提升,为其他平台促进开放效率和成效提供了可借鉴的经验;平台的全要素生产率(M指数)平均增长率为17.1%,表明技术进步,但技术效率平均值下降,存在浪费或无效率问题。规模效率平均增长率为14.5%,但纯技术效率下降,表明平台需更注重提升纯技术效率;政府数据开放平台受到平台数据综合水平、数据平台建设水平、组织准备度、财政支持水平和公众外部需求的交叉正向影响。数据的多样性、质量及可用性,以及平台的功能设计、用户体验等方面是提升效率的关键因素,政府的重视程度、财政支持和社会公众的需求直接影响平台的综合效率水平。

Research on Data Tampering Prevention Method for ATC Network Based on Zero Trust

The traditional air traffic control information sharing data has weak security characteristics of personal privacy data and poor effect,which is easy to leads to the problem that the data is usurped.Starting from the application of the ATC(automatic train control)network,this paper focuses on the zero trust and zero trust access strategy and the tamper-proof method of information-sharing network data.Through the improvement of ATC’s zero trust physical layer authentication and network data distributed feature differentiation calculation,this paper reconstructs the personal privacy scope authentication structure and designs a tamper-proof method of ATC’s information sharing on the Internet.From the single management authority to the unified management of data units,the systematic algorithm improvement of shared network data tamper prevention method is realized,and RDTP(Reliable Data Transfer Protocol)is selected in the network data of information sharing resources to realize the effectiveness of tamper prevention of air traffic control data during transmission.The results show that this method can reasonably avoid the tampering of information sharing on the Internet,maintain the security factors of air traffic control information sharing on the Internet,and the Central Processing Unit(CPU)utilization rate is only 4.64%,which effectively increases the performance of air traffic control data comprehensive security protection system.

LSTM-based lane change prediction using Waymo open motion dataset: The role of vehicle operating space

Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.

Contribution of the Open Access Modality to the Impact of Hybrid Journals Controlling by Field and Time Effects

Purpose:Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain.Thus,the objective of this work is to analyze the contribution of the Open Access(OA)modality to the impact of hybrid journals.Design/methodology/approach:The“research articles”in the year 2017 from 200 hybrid journals in four subject areas,and the citations received by such articles in the period 2017-2020 in the Scopus database,were analyzed.The hybrid OA papers were compared with the paywalled ones.The journals were randomly selected from those with share of OA papers higher than some minimal value.More than 60 thousand research articles were analyzed in the sample,of which 24%under the OA modality.Findings:We obtain at journal level that cites per article in both hybrid modalities(OA and paywalled)strongly correlate.However,there is no correlation between the OA prevalence and cites per article.There is OA citation advantage in 80%of hybrid journals.Moreover,the OA citation advantage is consistent across fields and held in time.We obtain an OA citation advantage of 50%in average,and higher than 37%in half of the hybrid journals.Finally,the OA citation advantage is higher in Humanities than in Science and Social Science.Research limitations:Some of the citation advantage is likely due to more access allows more people to read and hence cite articles they otherwise would not.However,causation is difficult to establish and there are many possible bias.Several factors can affect the observed differences in citation rates.Funder mandates can be one of them.Funders are likely to have OA requirement,and well-funded studies are more likely to receive more citations than poorly funded studies.Another discussed factor is the selection bias postulate,which suggests that authors choose only their most impactful studies to be open access.Practical implications:For hybrid journals,the open access modality is positive,in the sense that it provides a greater number of potential readers.This in turn translates into a greater number of citations and an improvement in the position of the journal in the rankings by impact factor.For researchers it is also positive because it increases the potential number of readers and citations received.Originality/value:Our study refines previous results by comparing documents more similar to each other.Although it does not examine the cause of the observed citation advantage,we find that it exists in a very large sample.

Open Access to Geological Research of China——"Geoscience Periodical Network of China"

＂Geoscience Periodical Network of China＂ is composed of 233 Chinese geological journals, which covers all kinds of geological research fields of China. All papers of this site comprise English abstract, and some papers have figures with English description. Papers present as the PDF format with two types： （1） papers can be downloaded for opening access; and （2） the others provide both Chinese and English abstract, which can be downloaded after registration. Welcome to visit our website： http：//www.geojournals.cn/

Open Access to Geological Research of China——“Geoscience Periodical Network China”

＂Geoscience Periodical Network of China＂ is composed of 233 Chinese geological journals, which covers all kinds of geological research fields of China. All papers of this site comprise English abstract, and some papers have figures with English description. Papers present as the PDF format with two types： （1） papers can be downloaded for opening access; and （2） the others provide both Chinese and English abstract, which can be downloaded after registration. Welcome to visit our website： http：//www.geojournals.cn/