Adaversarial Issue of Machine Learning Approaches Applied in Smart Grid: A Survey

The machine learning (ML) sees an increasing prevalence of being used in the internet-of-things enabled smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid applications (MLsgAPPs). The adversarial distortion injected into the power signal will greatly affect the system's normal control and operation. Therefore, it is imperative to conduct vulnerability assessment for MLsgAPPs applied in the context of safety-critical power systems. In this paper, we provide a comprehensive review of the recent progress in designing attack and defense methods for MLsgAPPs. Unlike the traditional survey about ML security, this is the first review work about the security of MLsgAPPs that focuses on the characteristics of power systems. The survey is organized from the aspects of adversarial assumptions, targeted applications, evaluation metrics, defending approaches, physics-related constraints, and applied datasets. We also highlight future directions on this topic to encourage more researchers to conduct further research on adversarial attacks and defending approaches for MLsgAPPs

DEVELOPMENT OF CONCEPTUAL MODEL FOR SOCIAL COMMERCE RESEARCH THROUGH INTEGRATION WITH BIG DATA ANALYSIS

Information systems designers face great opportunities and challenges in developing a holistic big data research approach for the new analytics savvy generation. In addition business intelligence is largely utilized in the business community and thus can leverage the opportunities from the abundant data and domain-specific analytics in many critical areas. The aim of this paper is to assess the relevance of these trends in the current business context through evidence-based documentation of current and emerging applications as well as their wider business implications. In this paper, we use BigML to examine how the two social information channels (i.e., friends-based opinion leaders-based social information) influence consumer purchase decisions on social commerce sites. We undertake an empirical study in which we integrate a framework and a theoretical model for big data analysis. We conduct an empirical study to demonstrate that big data analytics can be successfully combined with a theoretical model to produce more robust and effective consumer purchase decisions. The results offer important and interesting insights into IS research and practice

A Sliding Mode Control Based Stabilization Method for Directional Rotary Steering Tool-Face

When the directional rotary steering system works in the state of maintaining the tool face angle, the use of PID control mode will lead to a large swing angle of the tool face angle of the directional rotary steering system. In order to reduce the swing amplitude of the tool face angle, based on the PID position control and the angle position error sliding mode control strategy, the exponential synovial control function is established. The simulation results show that the fast and accurate tool face angle tracking is achieved through the closed-loop control of the angle position. The paper provides an implementation method for the research of directional rotary steering system

Sustainable Food and Fuel on Yongxing Island by Conversing the Carbon Captured from Ambient Air

AbstractSynthetic hydrocarbon fuel, derived from renewable energy and captured carbon dioxide from ambient air, can thoroughly close its carbon cycle and is a promising option for CCU and an important approach to sustainable energy. We investigate the Yongxing island in south China sea, which offers steady wind resources to provide continuous energy supply for plant factory and fuel synthesis. The energy consumption of MSAC and TSAC is compared and conversion of the captured CO2 to food and fuel are calculated. Powered by wind energy, 200 ton vegetables and 5.2*103 ton diesel will be produced per year, so self-sufficiency of vegetable and fuel demand can be achieved on Yongxing island. Our methodology could provide a new utilization mode for islands like Yongxing island

3D Interacting Hand Pose Estimation by Hand De-occlusion and Removal

Estimating 3D interacting hand pose from a single RGB image is essential for understanding human actions. Unlike most previous works that directly predict the 3D poses of two interacting hands simultaneously, we propose to decompose the challenging interacting hand pose estimation task and estimate the pose of each hand separately. In this way, it is straightforward to take advantage of the latest research progress on the single-hand pose estimation system. However, hand pose estimation in interacting scenarios is very challenging, due to (1) severe hand-hand occlusion and (2) ambiguity caused by the homogeneous appearance of hands. To tackle these two challenges, we propose a novel Hand De-occlusion and Removal (HDR) framework to perform hand de-occlusion and distractor removal. We also propose the first large-scale synthetic amodal hand dataset, termed Amodal InterHand Dataset (AIH), to facilitate model training and promote the development of the related research. Experiments show that the proposed method significantly outperforms previous state-of-the-art interacting hand pose estimation approaches. Codes and data are available at https://github.com/MengHao666/HDR.Comment: ECCV202

Enhancing Cyber-Resiliency of DER-based SmartGrid: A Survey

The rapid development of information and communications technology has enabled the use of digital-controlled and software-driven distributed energy resources (DERs) to improve the flexibility and efficiency of power supply, and support grid operations. However, this evolution also exposes geographically-dispersed DERs to cyber threats, including hardware and software vulnerabilities, communication issues, and personnel errors, etc. Therefore, enhancing the cyber-resiliency of DER-based smart grid - the ability to survive successful cyber intrusions - is becoming increasingly vital and has garnered significant attention from both industry and academia. In this survey, we aim to provide a systematical and comprehensive review regarding the cyber-resiliency enhancement (CRE) of DER-based smart grid. Firstly, an integrated threat modeling method is tailored for the hierarchical DER-based smart grid with special emphasis on vulnerability identification and impact analysis. Then, the defense-in-depth strategies encompassing prevention, detection, mitigation, and recovery are comprehensively surveyed, systematically classified, and rigorously compared. A CRE framework is subsequently proposed to incorporate the five key resiliency enablers. Finally, challenges and future directions are discussed in details. The overall aim of this survey is to demonstrate the development trend of CRE methods and motivate further efforts to improve the cyber-resiliency of DER-based smart grid.Comment: Submitted to IEEE Transactions on Smart Grid for Publication Consideratio

Effect of Salicylic Acid and Methyl Jasmonate on Growth and Pigment Production in Monascus purpureus

681-685The influence of salicylic acid (SA) and methyl jasmonate (MeJa) on the biomass and pigments production in Monascus purpureus was investigated. With 100 μmol/L SA- and 10 μmol/L MeJa-treated cultures, the maximum biomass were 4.70 and 4.33 g/L and significantly higher than the control, respectively. Supplemented with 10 μmol/L SA or MeJa, extracellular yellow, orange and red pigments increased, respectively, compared to the control. Supplemented with 10 μmol/L SA or 30 μmol/L MeJa, intracellular yellow, orange and red pigment production increased mostly compared to the control. AP activity was significant induction with SA and MeJa supplementation and the most significant at the 8th day of induction. These results indicate that proper concentration SA or MeJa enhance the biomass and pigment production in Monascus purpureus. Salicylic acid improved biomass and pigment production significantly more than MeJa

Observation of spin-tensor induced topological phase transitions of triply degenerate points with a trapped ion

Triply degenerate points (TDPs), which correspond to new types of topological semimetals, can support novel quasiparticles possessing effective integer spins while preserving Fermi statistics. Here by mapping the momentum space to the parameter space of a three-level system in a trapped ion, we experimentally explore the transitions between different types of TDPs driven by spin-tensor--momentum couplings. We observe the phase transitions between TDPs with different topological charges by measuring the Berry flux on a loop surrounding the gap-closing lines, and the jump of the Berry flux gives the jump of the topological charge (up to a $2\pi$ factor) across the transitions. For the Berry flux measurement, we employ a new method by examining the geometric rotations of both spin vectors and tensors, which lead to a generalized solid angle equal to the Berry flux. The controllability of multi-level ion offers a versatile platform to study high-spin physics and our work paves the way to explore novel topological phenomena therein.Comment: 9 pages, 10 figure

Effect of heat treatment on microstructure and mechanical behaviours of 18Ni-300 maraging steel manufactured by selective laser melting

Selective laser melting (SLM) of 18Ni-300 maraging steel is an important research area in view of its numerous applications in the automotive domain. Heat treatment plays a significant role in the microstructure and mechanical behaviour of maraging steels and is a major area of interest. This paper investigated the effect of heat treatment on microstructure and mechanical behaviour of SLM-built 18Ni-300 maraging steel. The experimental results showed that the densest parts with the smallest number of defects were fabricated at optimum laser energy density of 70 J/mm3 and laser power of 275 W. When the laser power was fixed at 275 W, lower laser energy density resulted in the formation of balling and irregular pores, while higher laser energy density induced spherical pores and microcracks. The as-built samples consisted of cellular and columnar microstructures due to the fast cooling and solidification rates during SLM. However, solution treatment led to changes in the typical microstructure and massive lath martensite phase. The tensile strength and microhardness decreased slightly due to grain growth and residual stress relief upon solution treatment; an opposite effect was observed when the samples were subjected to solution treatment followed by aging at 490 °C for 2 h. With regard to the tensile anisotropy, yield strength and ultimate tensile strength of the horizontally-built samples slightly exceeded those vertically-built. These findings are significant as they allow an informed prediction about the effect of various heat treatments on the microstructure and mechanical behaviour of components manufactured from 18Ni-300 maraging steel using the SLM process