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Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload the computing tasks to nearby Roadside Units (RSUs) that deploy computing capabilities. However, the highly dynamic network topology, strict low-delay constraints, and massive data of tasks of VEC pose significant challenges for implementing efficient offloading. Digital Twin-based VEC is emerging as a promising solution that enables real-time monitoring of the state of the VEC network through mapping and interaction between the physical and virtual worlds, thus assisting in making sound offload decisions in the physical world. Thus, this paper proposes an intelligent partial offloading scheme, namely, Digital Twin-Assisted Intelligent Partial Offloading (IGNITE). First, to find the optimal offloading space in advance, we combine the improved clustering algorithm with the Digital Twin (DT) technique, in which unreasonable decisions can be avoided by reducing the size of the decision space. Second, to reduce the overall cost of the system, Deep Reinforcement Learning (DRL) algorithm is employed to train the offloading strategy, allowing for automatic optimization of computational delay and vehicle service price. To improve the efficiency of cooperation between digital and physical spaces, a feedback mechanism is established. It can adjust the parameters of the clustering algorithm based on the final offloading results in this clustering. To the best of our knowledge, this is the first study on DT-assisted vehicle offloading that proposes a feedback mechanism, forming a complete closed loop as prediction-offloading-feedback. Extensive experiments demonstrate that IGNITE has significant advantages in terms of total system computational cost, total computational delay, and offloading success rate compared with its counterparts.

Collaborative machine learning, especially Federated Learning (FL), is widely used to build high-quality Machine Learning (ML) models in the Internet of Vehicles (IoV). In this paper, we study the performance evaluation problem in an inherently heterogeneous IoV, where the final models across the network are not identical and are computed on different standards. Previous studies assume that local agents are receiving data from the same phenomenon, and a same final model is fitted to them. However, this “one model fits all” approach leads to a biased performance evaluation of individual agents. We propose a general approach to measure the performance of individual agents, where the common knowledge and correlation between different agents are explored. Experimental results indicate that our evaluation scheme is efficient in these settings.

ABSTRACTMobilizing Foucault’s genealogy, this article investigates how an “ethics event”—the involvement by some sell-side financial analysts in the United States and United Kingdom across the past two decades in corporate governance—emerged. It is found that the complex relations formed between specific historical precedents, normative discourses, and fields of power rendered certain issues in financial markets morally problematic and constructed analysts’ corporate governance work as a potential solution. Contributing to research in finance ethics, this article develops a novel perspective to conceptualize the rise of ethically relevant practices in financial markets, focusing on how ethical problems and their solutions are outcomes of discursive construction and power relations. This article also revises our understanding of the boundary between technical norms and moral norms in financial markets. When ethical crises occur, it is argued, transforming technical practices and revising the technical norms adopted by financial professionals has the potential to tackle ethical concerns.

Purpose: The purpose of this paper is to contribute to scholarly work on the role of sell-side financial analysts in corporate governance (CG). It examines the more recent work products pertaining specifically to CG that analysts based in the USA and UK have generated in the past two decades, namely, their CGCG reports. Specifically, this paper focusses on analysing how analyst CG reports constitute a comparative space in which the governance procedures of companies are evaluated and “best practices” are created. Design/methodology/approach: This study involves a social constructivist textual analysis of 48 CG reports produced by analysts based in the USA and UK between 1998 and 2009. Findings: Analyst CG reports textually construct a comparative space comprising four dimensions. First, the space is constructed for some carefully edited users to evaluate the governance of companies. Second, the construction of this space requires the selection of “building materials”, i.e., governance issues included in the space that render companies amenable to evaluation and comparison. Third, by linking the range of governance issues chosen to formal regulations, firms are rendered governable and regulatory requirements reinterpreted. Lastly, by using different types of inscriptions, such as narratives and tables, the space highlights “winners”, i.e., those companies which do better than others, and constructs their governance procedures as “best practices”. Research limitations/implications: This research provides a first step towards an in-depth understanding of analyst CG reports. The insights from this paper generate a range of areas for future research, including how these reports are produced and used. Originality/value: This paper adds to the existing literature focussing on the role of analysts in CG. It extends previous studies by examining the more recent and debatable work products generated by analysts, namely, their CG reports, and suggests an extended CG role for them. Theoretically, analyst CG reports are conceptualised as “inscriptions” that construct “documentary reality”. The notion of “editing” is also drawn upon, to analyse a particular way in which documentary reality is constructed. Accordingly, this paper broadens the theoretical perspectives used in CG research.

The increasing demand for portable electronic devices and hybrid electric vehicles stimulates the development of supercapacitors as an advanced energy storage system. Here, we demonstrate a binder-free nickel hydroxide@nanoporous gold/Ni foam (Ni(OH)2@NPG/Ni foam) electrode for high-performance supercapacitors, which is prepared by a facile three-step fabrication route including electrodeposition of Au-Sn alloy on Ni foam, chemical dealloying of Sn and electrodepostion of Ni(OH)2on NPG/Ni foam. Such Ni(OH)2@NPG/Ni foam electrode is composed of a thin layer of conformable Ni(OH)2nanoflakes supported on three-dimensional (3D) hierarchically porous NPG/Ni foam substrate. The resulting Ni(OH)2@NPG/Ni foam electrode can offer highways for both electron transfer and ion transport and lead to an excellent electrochemical performance with an ultrahigh specific capacitance of 3380 F g-1 at a current density of 2 A g−1. Even when the current density was increased to 50 A g−1, it still retained a high capacitance of 1927 F g−1. The promising performance of the Ni(OH)2@NPG/Ni foam electrode is mainly ascribed to the 3D hierarchical porosity and the highly conductive network on the NPG/Ni foam composite current collector, as well as the conformal electrodeposition of Ni(OH)2active material on the NPG/Ni foam, which induces the formation of interconnected porosity both on the top surface and on the inner surface of the electrode. This inspiring electrochemical performance would make the as-designed electrode material become one of the most promising candidates for future electrochemical energy storage systems. 人们对便携式电子器件和混合动力汽车的需求不断增长, 激发了超级电容器等先进储能体系的发展. 本文通过三步法, 包括电化学沉积金-锡合金、 化学去合金除锡以及电化学沉积氢氧化镍等, 制备了无需粘结剂的氢氧化镍@纳米多孔金/泡沫镍电极用作超级电容器电极材料. 该电极材料由支撑在三维分级多孔的纳米多孔金/泡沫镍基底表面的氢氧化镍纳米片薄层组成, 能够为电子传导与离子输运提供快速通道, 在2 A g−1的充放电电流密度下比电容值高达 3380 F g−1, 当充放电电流密度增大到50 A g−1时, 其比电容值仍能保持为1927 F g−1, 表现出优异的电化学性能. 氢氧化镍@纳米多孔金/泡沫镍电极材料具有优良电化学性能的原因在于其所拥有的三维分级多孔结构、 纳米多孔金/泡沫镍复合集流体的高导电网络以及氢氧化镍活性材料在纳米多孔金/泡沫镍表面的保形电沉积使整个电极的内外表面均形成互连的多孔结构. 氢氧化镍@纳米多孔金/泡沫镍电极材料所展现出的优异电化学性能令其有望成为未来最有前景的电化学储能材料之一.

Cyber crimes and malicious network activities have posed serious threats to the entire internet and its users. This issue is becoming more critical, as network-based services, are more widespread and closely related to our daily life. Thus, it has raised a serious concern in individual internet users, industry and research community. A significant amount of work has been conducted to develop intelligent anomaly-based intrusion detection systems (IDSs) to address this issue. However, one technical challenge, namely reducing false alarm, has been along with the development of anomaly-based IDSs since 1990s. In this paper, we provide a solution to this challenge. A nonlinear correlation coefficient-based (NCC) similarity measure is proposed to help extract both linear and nonlinear correlations between network traffic records. This extracted correlative information is used in our proposed IDS to detect malicious network behaviours. The effectiveness of the proposed NCC-based measure and the proposed IDS are evaluated using NSL-KDD dataset. The evaluation results demonstrate that the proposed NCC-based measure not only helps reduce false alarm rate, but also helps discriminate normal and abnormal behaviours efficiently.