Spectrum Prediction Based on GAN and Deep Transfer Learning:A Cross-Band Data Augmentation Framework

This paper investigates the problem of data scarcity in spectrum prediction.A cognitive radio equipment may frequently switch the target frequency as the electromagnetic environment changes.The previously trained model for prediction often cannot maintain a good performance when facing small amount of historical data of the new target frequency.Moreover,the cognitive radio equipment usually implements the dynamic spectrum access in real time which means the time to recollect the data of the new task frequency band and retrain the model is very limited.To address the above issues,we develop a crossband data augmentation framework for spectrum prediction by leveraging the recent advances of generative adversarial network(GAN)and deep transfer learning.Firstly,through the similarity measurement,we pre-train a GAN model using the historical data of the frequency band that is the most similar to the target frequency band.Then,through the data augmentation by feeding the small amount of the target data into the pre-trained GAN,temporal-spectral residual network is further trained using deep transfer learning and the generated data with high similarity from GAN.Finally,experiment results demonstrate the effectiveness of the proposed framework.

Incorporating Domain Knowledge into Data Mining Process:An Ontology Based Framework

With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then au tonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to in corporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data ,source by ontology. Experiments suggest that the framework should be useful in guiding the continuous mining process.

Towards a Comprehensive Security Framework of Cloud Data Storage Based on Multi Agent System Architecture

The tremendous growth of the cloud computing environments requires new architecture for security services. Cloud computing is the utilization of many servers/data centers or cloud data storages (CDSs) housed in many different locations and interconnected by high speed networks. CDS, like any other emerging technology, is experiencing growing pains. It is immature, it is fragmented and it lacks standardization. Although security issues are delaying its fast adoption, cloud computing is an unstoppable force and we need to provide security mechanisms to ensure its secure adoption. In this paper a comprehensive security framework based on Multi-Agent System (MAS) architecture for CDS to facilitate confidentiality, correctness assurance, availability and integrity of users' data in the cloud is proposed. Our security framework consists of two main layers as agent layer and CDS layer. Our propose MAS architecture includes main five types of agents: Cloud Service Provider Agent (CSPA), Cloud Data Confidentiality Agent (CDConA), Cloud Data Correctness Agent (CDCorA), Cloud Data Availability Agent (CDAA) and Cloud Data Integrity Agent (CDIA). In order to verify our proposed security framework based on MAS architecture, pilot study is conducted using a questionnaire survey. Rasch Methodology is used to analyze the pilot data. Item reliability is found to be poor and a few respondents and items are identified as misfits with distorted measurements. As a result, some problematic questions are revised and some predictably easy questions are excluded from the questionnaire. A prototype of the system is implemented using Java. To simulate the agents, oracle database packages and triggers are used to implement agent functions and oracle jobs are utilized to create agents.

Evolution of corporate environmental information disclosure framework of “knowledge and action”: Based on big data background

Cloud accounting is based on the traditional financial work process, the context of big data, and the necessary trend of future corporate accounting development. Its emergence and rapid development will have a fundamental impact on corporate environmental information disclosure. In the big data era of information sharing, companies will have a new understanding of the emergence, balance, and final consideration of social responsibility, and will have new changes in their overall decision-making and information disclosure methods. "Knowing" and "behavior" will be combined on the basis of rational judgment, so that corporate environmental information disclosure is more in line with the overall social development requirements. Based on the background of big data, this article starts with the disclosure of impact factors, footholds, and path choices. It describes the evolution of corporate environmental information disclosure and provides reference suggestions for enterprises to disclose environmental information truthfully and perform social responsibilities.

Proof of Activity Protocol for IoMT Data Security

The Internet of Medical Things(IoMT)is an online device that senses and transmits medical data from users to physicians within a time interval.In,recent years,IoMT has rapidly grown in the medicalfield to provide healthcare services without physical appearance.With the use of sensors,IoMT applications are used in healthcare management.In such applications,one of the most important factors is data security,given that its transmission over the network may cause obtrusion.For data security in IoMT systems,blockchain is used due to its numerous blocks for secure data storage.In this study,Blockchain-assisted secure data management framework(BSDMF)and Proof of Activity(PoA)protocol using malicious code detection algorithm is used in the proposed data security for the healthcare system.The main aim is to enhance the data security over the networks.The PoA protocol enhances high security of data from the literature review.By replacing the malicious node from the block,the PoA can provide high security for medical data in the blockchain.Comparison with existing systems shows that the proposed simulation with BSD-Malicious code detection algorithm achieves higher accuracy ratio,precision ratio,security,and efficiency and less response time for Blockchain-enabled healthcare systems.

Security Framework for Managing Data Security within Point of Care Tests

Point of Care (PoC) devices and systems can be categorized into three broad classes (CAT 1, CAT 2, and CAT 3) based on the context of operation and usage. In this paper, the categories are defined to address certain usage models of the PoC device. PoC devices that are used for PoC testing and diagnostic applications are defined CAT 1 devices;PoC devices that are used for patient monitoring are defined as CAT 2 devices (PoCM);PoC devices that are used for as interfacing with other devices are defined as CAT 3 devices (PoCI). The PoCI devices provide an interface gateway for collecting and aggregating data from other medical devices. In all categories, data security is an important aspect. This paper presents a security framework concept, which is applicable for all of the classes of PoC operation. It outlines the concepts and security framework for preventing security challenges in unauthorized access to data, unintended data flow, and data tampering during communication between system entities, the user, and the PoC system. The security framework includes secure layering of basic PoC system architecture, protection of PoC devices in the context of application and network. Developing the security framework is taken into account of a thread model of the PoC system. A proposal for a low-level protocol is discussed. This protocol is independent of communications technologies, and it is elaborated in relation to providing security. An algorithm that can be used to overcome the threat challenges has been shown using the elements in the protocol. The paper further discusses the vulnerability scanning process for the PoC system interconnected network. The paper also presents a four-step process of authentication and authorization framework for providing the security for the PoC system. Finally, the paper concludes with the machine to machine (M2M) security viewpoint and discusses the key stakeholders within an actual deployment of the PoC system and its security challenges.

基于DataV的气象可视化数据平台设计与实现

综合分析了传统气象数据展示的缺陷,针对气象数据量大、展示直观度低、分析研判少、智能演示弱等问题,提出将DataV技术引入可视化展示平台的解决方案,结合气象业务现状,将气象预警、预报、站点、服务产品等海量信息分析后集中展示,给决策机构提供可靠的数据展示;平台总体框架设计过程中,引入数据中台技术,使用了多线程B/S架构录入数据,后台采用了MySQL数据库存储服务,数据接口使用了Mybatis框架,前端使用DataV平台进行演示;阐述了系统各项技术设计方案,并给出具体设计方法。实际运行效果表明,该技术方案可以直观反映气象大数据分析的结果,极大地提高了气象数据的交互性、实时性、灵活性,更清晰地辅助于决策。

A Quality Assurance Reference Framework for Assessing Educational Data

Digital educational content is gaining importance as an incubator of pedagogical methodologies in formal and informal online educational settings. Its educational efficiency is directly dependent on its quality, however educational content is more than information and data. This paper presents a new data quality framework for assessing digital educational content used for teaching in distance learning environments. The model relies on the ISO2500 series quality standard and beside providing the mechanisms for multi-facet quality assessment it also supports organizations that design, create, manage and use educational content with the quality tools (expressed as quality metrics and measurement methods) to provide a more efficient distance education experience. The model describes the quality characteristics of the educational material content using data and software quality characteristics.

Preliminary study of Chinese Antarctic data management in accordance with the international framework

Antarctic data management is the research focus, which the international Antarctic organizations, e.g. Antarctic Treaty Consultative Meeting(ATCM) , Scientific Committee on Antarctic Research(SCAR), and Council of Managers of National Antarctic Programmes(COMNAP) have been paying close attention to and promoting actively. Through the co effort of international Antarctic organizations and member countries concerned in recent years, Antarctic Data Directory Syatem(ADDS) is established as the most important basic programme for development of the international Antarctic data management system. At present, Joint Committee on Antarctic Data Management(JCADM) is responsible for organizing and coordinating the international Antarctic data management, and implementing the project ADDS.In this paper the background on Antarctic data management in time sequence and the structure of international framework are introduced, meanwhile, it is necessary to develop ADDS first of all. The ADDS mainly consists of the two principal parts: National Antarctic Data Center(NADCs) of all the party members and Antarctic Main Directory(AMD), the best available technology for creating ADDS is to make full use of International Directory Network(IDN) and adopt its Directory Interchange Formats(DIF). In the light of the above requirements, combined with Chinese specific situation, the contents, technical and administrative methods on Chinese Antarctic data management are discussed to promote our related work.

从“数据隐私框架”看欧美数据跨境流动的规则博弈

欧美《隐私盾协议》失效后,双方为了恢复数据跨境流动秩序,于2022年底达成了“数据隐私框架”。该框架旨在回应欧盟法院在“《隐私盾协议》无效案”中提出的主要关切。2023年7月,欧盟委员会基于该框架对美国的个人数据保护水平发布了充分性认定决议。然而,该框架并未对美国情报机构大规模收集数据与窥探隐私的行为施加实质性限制。此外,框架建立的双层救济机制由于缺乏独立性,也无法给数据隐私权益受损的欧盟公民提供充分有效的救济。与《隐私盾协议》相比,该框架在本质上并没有明显的突破。欧盟和美国在双方数据跨境流动制度安排上的博弈,表面上是两种数据保护理念和治理模式的碰撞,实际上反映出了欧盟实施“数字主权”战略与美国维护“数字霸权”地位之间存在的根本利益冲突。欧美凭借各自优势,在数字经济时代争夺全球数字治理话语权。通过深入研究欧美之间关于“数据隐私框架”的规则博弈,可以为我国在选择适合本土的数据监管模式和提升数据治理规则话语权方面提供重要的思考和启示。

Development of the Data Processing and Analysis System Framework for ICF Experiments

An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.

数据伦理框架:国际对话与中国化的构建路径

数据伦理框架作为国外数据治理体系的重要组成部分,在提升数据治理效能、优化数据治理模式等方面具有重要作用。欧美国家已经建立了相对成熟的数据伦理框架,对其基本架构和深层逻辑的探讨可以为我国数据伦理框架的构建提供重要参考,对我国数据治理体系的现代化也具有重要意义。通过文献调研法和内容分析法,对8个国外数据伦理框架进行比较,研究国外数据伦理通用的框架、结构和运行模式,借鉴国外数据伦理框架的模式及实践经验,对我国数据伦理框架参与国际数据伦理对话以及中国化构建路径进行了探索性研究。国外数据伦理框架相对稳定,并具有规律性,确立了以法律体系为支撑、以基本原则为核心、以行动方案为指南的数据伦理逻辑框架,形成了“法律体系—伦理框架—伦理说明”为一体的以伦理问题为中心的运行机制。

基于多模态数据的智慧课堂学生学习行为研究

新兴技术赋能下的智慧课堂为学生学习行为监测、评价、反馈、预警提供丰富的教育多模态数据,充分采集、处理和分析教育多模态数据能够为教育研究和实践提供参考。首先,梳理已有智慧课堂学习行为分析和多模态数据教学研究,借鉴学习行为分类系统,构建基于多模态数据类型的“声音数据—图像数据—文本数据”三维的多模态数据分析框架,从言语学习活动、位置移动、身体动作、技术使用四个方面呈现智慧课堂下学生学习行为变化;其次,将体现学生学习行为特征的多模态数据编码,并进行质性表征形成编码体系;最后,从情境和时序行为分析视角出发,对课例中的学习行为多模态数据进行频度变化及周期性变化分析。研究得出,在智慧课堂环境下,学生课堂学习参与性、主动性、专注度均在不断提升,课堂学习氛围朝着积极的方向发展,无效及无关学习行为逐渐减少。此外,通过对学生学习行为多模态数据的剖析,以期为学生了解自身学习行为及状态、教师进行个性化教学,以及研究者构建学习评价体系提供数据来源、科学依据。

面向高等教育教师的数据素养分析框架开发和评估:结构方程建模方法

随着信息和通信技术的快速发展,教师数据素养已成为现代教育领域的一个重要趋势.该文基于高等教育教师数据素养的现状和需求,提出一种基于结构方程建模方法的教师数据素养分析框架,旨在探索一种可行的方法来提高教师数据素养水平.通过研究教师的技术整合自我效能感、技术知识水平、对技术的态度以及使用社交网络的目的与他们数据素养水平之间的关系,阐明和分析了数据素养水平与这些变量之间的关系.使用结构方程模型对来自415名教师的数据进行分析,查看变量之间的相关性,并确定哪些预测因素对教师数据素养能力影响最大.同时,通过对定量数据结果进行分析,验证和评估该文所提出的分析框架.采用关系筛选模型,在研究结果审查的模型中检测到教师的技术整合自我效能感是最重要的变量,对数据素养水平的预测具有重要影响.该文结果有助于指导并提升教师数据素养水平,达到提高教育教学质量和效果的目的.

基于多方法的中医体质动态变化因素分析

目的基于一般统计学、Apriori-DEMATEL算法、DoWhy因果推理框架等方法探究中医体质动态变化影响因素。方法对18-60岁人群进行中医体质识别数据的动态采集,包括采集时间、体质类型以及饮食习惯、睡眠习惯、睡眠时间、运动习惯、情绪状态、压力情况、生活环境、工作/生活变故、家庭氛围、出差频次、加班情况11个体质影响因素。采用一般统计分析分析不同类型体质变化对应影响因素的相对百分比,采用Apriori-DEMATEL算法分析饮食习惯等11种体质影响因素与体质变化之间的相关性,采用DoWhy因果推理框架分析饮食习惯、睡眠习惯、睡眠时间、运动习惯、情绪状态、压力情况之间的因果关系。探讨构成类型转换变化因素的频率,确定构成类型动态变化的关键影响因素。结果经过预处理后形成13536条有效数据,基于Apriori-DEMATEL算法将因素划分成饮食习惯、睡眠习惯、睡眠时间、运动习惯、情绪状态和压力情况这6个原因因素及居住环境、工作/生活变故、家庭氛围、出差频次和加班情况这5个结果因素。结合一般统计学分析发现,在原因因素中饮食习惯、睡眠习惯、睡眠时间和压力情况这4个因素的变化对其他因素的影响程度大,在体质调摄过程中,应对上述4个因素重点关注,保持体质的平衡;在5个结果因素里面,工作/生活变故和家庭氛围这两个因素的数值绝对值较大,说明这两个因素易受其他因素的影响。饮食习惯、睡眠习惯、睡眠时间、运动习惯、情绪状态和压力情况这六个因素变化的中心度较高,说明这六个因素的变化是体质发生改变的重要性因素。根据各因素对应体质变化频数统计发现以上六个因素的变化在气虚质、平和质和特禀质间的体质转变频数占比较大,说明这六个因素的改变对这三种体质类型的变化发挥重要作用。结合Apriori-DEMATEL算法和DoWhy因果推理框架分析的结果,推断饮食习惯和睡眠时间通过影响其他因素的变化间接导致体质变化。结论本文从动态数据和多种分析方法入手,探讨了中医体质动态变化的影响因素,结果表明饮食习惯、睡眠习惯、睡眠时间、运动习惯、情绪状态和压力情况的变化对气虚质、平和质和特秉质的转化有较大影响。在日常生活中要注意这六个因素的变化,并制定相应的改善方案,减少转化为偏体质的概率。本研究也为中医体质类型动态变化的影响因素分析提供了数据支持和客观化分析参考。

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。

基于虚拟网关的交通基础设施监测点位数据接入方法

针对交通基础设施点位监测数据来源多样、结构各异、协议不一的特点,分析具体接入需求,提出一种基于Netty架构的交通基础设施监测点位数据接入虚拟网关。阐述网关接入监测点位的配置方法及集群分配策略,定义超文本传输协议(HTTP)、传输控制协议(TCP)、用户数据报协议(UDP)下的数据传输格式,设计一种数据传输消息的编码和校验机制。在真实监测数据样本增强的基础上,利用分布式消息模拟工具对虚拟网关性能进行测试,结果表明,该虚拟网关实现了多点位多协议的交通基础设施监测数据统一接入,每亿条数据接入时间、存储时间分别达到8.14 s和9.75 s,平均数据溯源时间为2.96 s,具有亿级规模点位监测数据的接入能力,可为交通基础设施数字化监测的研究和应用提供理论支撑。

数智经济时代财会人才培养模式的构建

随着大数据时代的到来,财会人员的作用正在被重新定义。财务人的角色已逐步从提供报告演变为业务合作伙伴。基于我国2019年《中国管理会计职业能力框架》,同时借鉴IMA《2022管理会计能力素质框架》,构建具有成长型特色的财会人才培养模式。该模式以培养职业适应力和可持续发展力为引擎,设置业财融合、技财融合、人财融合的专业课程体系,明确知识、能力、素质和元学习四个维度的培养规格和四级递增的专业能力水平,为我国财会专业的人才培养和职业发展规划提供了参考。

基于重采样和混合集成学习的不平衡窃电检测

针对电力用户类别不平衡导致窃电检测具有偏向性问题,该文提出一种基于重采样和混合集成学习的不平衡窃电检测模型。首先以Easy-ensemble混合集成学习框架为基础确定最佳采样子集数;然后通过重采样自适应策略,即根据用户用电数据集的不平衡度以及最佳采样子集数确定检测模型的重采样方式,使用电数据达到平衡;最后按照先串行集成减小偏差、后并行集成降低方差的混合集成方式,对重采样后的均衡样本进行窃电检测。算例对比分析表明所提检测模型通过重采样和混合集成有效解决了传统集成算法在不平衡窃电检测中的偏向问题,降低了由于用电数据的不平衡性对集成结果的影响,提高了用户类别不平衡的窃电检测效果,在多种不平衡度下模型的准确率、F1值和G均值均表现优异。