Artificial intelligence implication on energy sustainability in Internet of Things: A survey     

《Information processing & management》2023,60(2):103212

The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.  相似文献   

Directed collaboration patterns in funded teams: A perspective of knowledge flow     

《Information processing & management》2023,60(2):103237

Collaborations in funded teams are essential for understanding funded research and funding policies, although of high interest, are still not fully understood. This study aims to investigate directed collaboration patterns from the perspective of the knowledge flow, which is measured based on the academic age. To this end, we proposed a project-based team identification approach, which gives particular attention to funded teams. The method is applicable to other funding systems. Based on identified scientific teams, we detected recurring and significant subgraph patterns, known as network motifs, and under-represented patterns, known as anti-motifs. We found commonly occurred motifs and anti-motifs are remarkably characterized by different structures matching certain functions in knowledge exchanges. Collaboration patterns represented by motifs favor hierarchical structures, supporting intensive interactions across academic generations. Anti-motifs are more likely to show chain-like structures, hindering potentially various knowledge activities, and are thus seldom found in real collaboration networks. These findings provide new insights into the understanding of funded collaborations and also the funding system. Meanwhile, our findings are helpful for researchers, the public and policymakers to gain knowledge on research(ers) evolution, particularly in terms of primordial collaboration patterns.  相似文献   

Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis     

《Information processing & management》2023,60(3):103260

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一种基于图卷积自编码模型的多维度学科知识网络融合方法     

李慧  胡吉霞 《图书情报工作》2020,64(18):114-125

[目的/意义] 针对包含单一类型知识单元的知识网络难以全面反映学科知识结构的问题，提出一种从多维度进行知识网络结构融合的方法，为学科领域知识结构挖掘提供借鉴。[方法/过程] 利用LDA及TF-IDF方法抽取学科知识单元，然后运用语义相似度和关键词共现分析方法构建3个学科知识子网络：主题网络、关键词网络和实体网络，并采用空间节点传递对齐方法对齐子网络节点，接着设计基于图卷积操作的自编码模型对知识节点进行表示，最后通过计算余弦相似度重构学科知识网络。[结果/结论] 实验部分以人工智能领域为例，构建融合主题、关键词和实体的学科知识网络并展开分析，实验结果表明，本文所提方法能有效地揭示学科领域研究内容和知识结构，为学科知识发现与组织研究提供有益参考。  相似文献   

知识融合研究的现状分析及建议     

李广建  陈瑜 《图书情报工作》2019,63(1):41-51

[目的/意义]人类社会在从信息社会向后信息时代过渡的进程中，正在经历从"信息"向"智能"的跨越。在大数据环境和人工智能技术发展的双重因素作用下，知识融合作为知识化和智能化过程中的关键环节，为完善知识服务、智慧服务、催生高级智能形态提供了重要的理论和技术支撑。开展基于全学科视角的知识融合调研，扩展知识融合研究视域，为全面阐释知识融合研究现状，构建统一的知识融合理论研究框架提供借鉴。[方法/过程]本文采用定量与定性结合的文献分析方法，分析不同学科视角下知识融合研究现状，归纳知识融合在不同学科中的主要研究内容和关注的问题、知识融合涉及到的因素、知识融合的应用场景等。[结果/结论]知识融合研究属于多交叉学科领域，概念边界模糊，研究领域分散，目前尚未形成统一的研究框架。本文通过文献调研，在充分总结既往知识融合研究成果的基础上，划分知识融合的研究取向，为知识融合研究提出合理建议。  相似文献   

基于极化特征和纹理特征的PolSAR影像建筑物提取方法     

马肖肖  程博  刘岳明  崔师爱  梁琛彬 《中国科学院大学学报》2019,36(5):682-693

极化合成孔径雷达（PolSAR）以其多参数、多通道、多极化、信息记录更加完整等特点，在城市地物提取领域中发挥着重要作用，并已成为遥感影像研究领域的热点。选择覆盖苏州市的Radarsat2影像，利用极化非相干分解法和灰度共生矩阵法分别提取19种极化特征和8种纹理特征，通过分析建筑物、植被和水体的极化特征和纹理特征进行特征组合，结合主成分分析法（PCA）和支持向量机法（SVM）对城市建筑物进行提取，并定量评估精度。结果表明：基于极化特征的建筑物提取精度最高为92.4%；基于纹理特征的提取精度最高为88.9%；极化特征与纹理特征相结合可以提高精度，最高精度为93.7%；PCA特征融合算法具有较高的运算效率，同时提高了精度。  相似文献   

Applying artificial intelligence technique to predict knowledge hiding behavior     

《International Journal of Information Management》2019

Drawing on psychological ownership and social exchange theories, this study suggests theoretical arguments and empirical evidence for understanding employee reactions to distributive, procedural, and interactional (in)justice — three crucial bases of employees’ feelings of social self-worth. Utilizing field data and artificial intelligence technique, this paper reveals that distributive, procedural, and interactional (in)justice contribute to higher levels of knowledge hiding behavior among employees and that this impact is non-linear (asymmetric). By reuniting the discourses of organizational justice and knowledge management, this study indicates that feelings of psychological ownership of knowledge and the degree of social interaction are mechanisms that work with organizational (in)justice to influence knowledge hiding behavior. The current research may inform contemporary theories of business research and provide normative guidance for managers.  相似文献   

Cognitive-inspired domain adaptation of sentiment lexicons     

Frank Z. Xing  Filippo Pallucchini  Erik Cambria 《Information processing & management》2019,56(3):554-564

Sentiment lexicons are essential tools for polarity classification and opinion mining. In contrast to machine learning methods that only leverage text features or raw text for sentiment analysis, methods that use sentiment lexicons embrace higher interpretability. Although a number of domain-specific sentiment lexicons are made available, it is impractical to build an ex ante lexicon that fully reflects the characteristics of the language usage in endless domains. In this article, we propose a novel approach to simultaneously train a vanilla sentiment classifier and adapt word polarities to the target domain. Specifically, we sequentially track the wrongly predicted sentences and use them as the supervision instead of addressing the gold standard as a whole to emulate the life-long cognitive process of lexicon learning. An exploration-exploitation mechanism is designed to trade off between searching for new sentiment words and updating the polarity score of one word. Experimental results on several popular datasets show that our approach significantly improves the sentiment classification performance for a variety of domains by means of improving the quality of sentiment lexicons. Case-studies also illustrate how polarity scores of the same words are discovered for different domains.  相似文献   

Contemporary school knowledge democracy: possible meanings,promising perspectives and necessary prerequisites     

Eleni Katsarou  Konstantinos Sipitanos 《Educational Action Research》2019,27(1):108-124

ABSTRACT

The basic aim of this paper is to discuss the concept ‘Knowledge Democracy’ (KD) and what it can mean in the school context, its implications on knowledge production and dissemination and on the educational practices. We try to enrich this discussion by presenting action research projects to provide case studies of how thinking about KD can reshape educational practice. We consider that the discussion on KD has to be enriched as the concept seems very promising with good prospects towards school’s democratization. On the other hand, as it is quite new, it can encompass internal contradictions that can cause problems at the level of practice. So, we consider very important any contribution to this discussion not as another theoretical sample of the debate on the ‘politics of knowledge’, but because any improvement at the thinking of the issue can be reflected on school practices. Any challenge to traditional politics of knowledge can lead to a deeper understanding of the world of schooling and to transformations through new discourses and new approaches to teaching and learning in school.  相似文献   

图书情报学领域学科交叉及其国家差异的动态分析     

王思茗  滕广青 《图书情报知识》2020,(3):109-118,F0003

[目的/意义]领域知识的跨学科交叉研究能够打破学科间的壁垒,有助于发现重大科学问题的解决方案。[研究设计/方法]基于图书情报学领域文献题录信息构建轻量级领域知识图谱,从中提取学科信息、国家信息、时间信息及其关联,采用时间与空间相结合的多维度分析方法,对学科交叉的演化进程以及国家差异进行跟踪与分析。[结论/发现]图书情报学领域内学科交叉现象日渐显著,各国家的学科交叉程度与倾向存在差异,一些目前尚不突出的交叉学科方向值得关注。[创新/价值]采用多维度视角分析学科交叉现象,相关结论可以为国家科技战略制定及学科发展规划提供有益参考。  相似文献