A Systematic Evaluation and Benchmark for Embedding-Aware Generative Models: Features, Models, and Any-shot Scenarios

Embedding-aware generative model (EAGM) addresses the data insufficiency problem for zero-shot learning (ZSL) by constructing a generator between semantic and visual feature spaces. Thanks to the predefined benchmark and protocols, the number of proposed EAGMs for ZSL is increasing rapidly. We argue that it is time to take a step back and reconsider the embedding-aware generative paradigm. The main work of this paper is two-fold. First, the embedding features in benchmark datasets are somehow overlooked, which potentially limits the performance of EAGMs, while most researchers focus on how to improve EAGMs. Therefore, we conduct a systematic evaluation of ten representative EAGMs and prove that even embarrassedly simple modifications on the embedding features can improve the performance of EAGMs for ZSL remarkably. So it's time to pay more attention to the current embedding features in benchmark datasets. Second, based on five benchmark datasets, each with six any-shot learning scenarios, we systematically compare the performance of ten typical EAGMs for the first time, and we give a strong baseline for zero-shot learning (ZSL) and few-shot learning (FSL). Meanwhile, a comprehensive generative model repository, namely, generative any-shot learning (GASL) repository, is provided, which contains the models, features, parameters, and scenarios of EAGMs for ZSL and FSL. Any results in this paper can be readily reproduced with only one command line based on GASL

李善《文選注》引書義例考

李善《文選注》徵引浩繁，引書義例複雜。本文依據其引用文獻之實際情況，參考注中隨文標示之相關義例，從引用目的、書名標舉、引文處理三個方面系統、深入地考察了李善《文選注》引書之義例系統。把握李善注引書義例，有益於把握李善注及其所引文獻，乃至《文選》本文。 This article provides a systematic and comprehensive analysis of the numerous citations and their complex principles in Li Shan’s 李善 Wenxuan zhu 文選注 (Annotations to Selections of Refined Literature) through their purpose, title, and text. The article contributes to a deeper understanding of Li Shan’s annotations and citations, and moreover, the texts in Wenxuan文選 (Selections of Refined Literature)

Addressing Domain Shift via Knowledge Space Sharing for Generalized Zero-Shot Industrial Fault Diagnosis

Fault diagnosis is a critical aspect of industrial safety, and supervised industrial fault diagnosis has been extensively researched. However, obtaining fault samples of all categories for model training can be challenging due to cost and safety concerns. As a result, the generalized zero-shot industrial fault diagnosis has gained attention as it aims to diagnose both seen and unseen faults. Nevertheless, the lack of unseen fault data for training poses a challenging domain shift problem (DSP), where unseen faults are often identified as seen faults. In this article, we propose a knowledge space sharing (KSS) model to address the DSP in the generalized zero-shot industrial fault diagnosis task. The KSS model includes a generation mechanism (KSS-G) and a discrimination mechanism (KSS-D). KSS-G generates samples for rare faults by recombining transferable attribute features extracted from seen samples under the guidance of auxiliary knowledge. KSS-D is trained in a supervised way with the help of generated samples, which aims to address the DSP by modeling seen categories in the knowledge space. KSS-D avoids misclassifying rare faults as seen faults and identifies seen fault samples. We conduct generalized zero-shot diagnosis experiments on the benchmark Tennessee-Eastman process, and our results show that our approach outperforms state-of-the-art methods for the generalized zero-shot industrial fault diagnosis problem

Analysis of the impact on the gravity field determination from the data with the ununiform noise distribution using block-diagonal least squares method

AbstractThe block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field determination. On the basis of block-diagonal least squares method, three data processing strategies are employed to determine the gravity field models using three kinds of simulated global grid data with different noise spatial distribution in this paper. The numerical results show that when we employed the weight matrix corresponding to the noise of the observation data, the model computed by the least squares using the full normal matrix has much higher precision than the one estimated only using the block part of the normal matrix. The model computed by the block-diagonal least squares method without the weight matrix has slightly lower precision than the model computed using the rigorous least squares with the weight matrix. The result offers valuable reference to the using of block-diagonal least squares method in ultra-high gravity model determination

A comparison of pitting susceptibility of Q235 and HRB335 carbon steels used for reinforced concrete

The phase structure and the pitting susceptibility of two carbon steels, Q235 and HRB335, used for reinforced concrete, are investigated by phase observation, polarization curve measure-ments, electrochemical impedance spectroscopy, and Mott-Schottky analysis. It is found that Q235 is ferrite and HRB335 is pearlite. Q235 is more susceptible to chloride ions leading to pit-ting than HRB335. The polarization curves show that the breakdown potential of the passive film in saturated Ca(OH)2 solution containing 0.4 M NaCl is 0 V for Q235 and 0.34 V for HRB335. The Mott-Schottky analyses show that passive films formed on Q235 and HRB335 in saturated Ca(OH)2 solution containing chloride ions behave like an n-type semiconductor. The passive film formed on Q235 has a higher donor density, which explains why Q235 is more susceptible to pitting than HRB335

Effects of physiological integration on nitrogen use efficiency of moso bamboo in homogeneous and heterogeneous environments

IntroductionMoso bamboo is one of the important clonal plants with complex underground rhizome-root system. Ramets connected by rhizome can translocate and share nitrogen (N), which may affect the nitrogen use efficiency (NUE) of moso bamboo. The aims of this study were to investigate the mechanisms of N physiological integration and its relationship with NUE of moso bamboo.MethodsA pot experiment was conducted to trace the movement of 15N between the connected ramets of moso bamboo in both homogeneous and heterogeneous N environments.ResultsResults showed that N translocation within clonal fragments of moso bamboo was detected in both homogeneous and heterogeneous environments. The intensity of physiological integration (IPI) was significantly lower in homogeneous environments than that in heterogeneous environments. 15N translocation between the connected ramtes of moso bamboo was determined by the source-sink relationship in heterogeneous environments, and the 15N allocation of the fertilized ramet was higher than that of the connected unfertilized ramet. The NUE of connected treatment was significantly higher than that of severed treatment, which suggested that physiological integration significantly improved the NUE of moso bamboo. In addition, the NUE of moso bamboo was significantly higher in heterogeneous environments than that in homogeneous environments. The contribution rate of physiological integration (CPI) on NUE in heterogeneous environments was significantly higher than that in homogenous environments.DiscussionThese results will provide theoretical basis for precision fertilization in moso bamboo forests

Evaluation and comparison of the processing methods of airborne gravimetry concerning the errors effects on downward continuation results: Case studies in Louisiana (USA) and the Tibetan Plateau (China)

Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3–5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems

A Global Path Planning Algorithm Based on Bidirectional SVGA

For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by A⁎). This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning

A Simplified All-ZVS Strategy for High-Frequency Triple Active Bridge Converters with Designed Magnetizing Inductance

The triple active bridge (TAB) converters that integrates the on-board charger and the auxiliary power module is ideally suited for producing a high-power density electric vehicle (EV) charger. As the power coupling among each port complicates the TAB's mode analysis, it is challenging to avoid a compromise with high-efficient operation and the wide-applicability of soft-switching operation in the TAB modulation technique. In this work, the influence of the transformer's magnetizing inductance is introduced into the analysis of the TAB converter for simplifying the realization of zero voltage switching (ZVS), and in this way, the power conversion efficiency of TAB operating in high-frequency can be improved. Drawing on the working principles of a single dual active bridge (DAB) converter and the linear superposition theorem, a simplified four-phase modulation (FPM) scheme for the TAB converter is proposed in this article, which is computationally stress-free, featuring low switching and conduction loss characteristics. By combining the FPM scheme with the tuning of the magnetizing inductance value, the ZVS operation of all switches can be readily achieved without imposing extra computational burden. This is particularly advantageous for time-intensive scenarios such as those found in the application of EVs. In addition, the ZVS process of the TAB converter is thoroughly studied and unified to simplify the calculation of ZVS current and required dead time, enabling the identification of the optimal magnetizing inductance value. The proposed optimization solution is introduced, studied, validated, and benchmarked in a 2.5 kW/100 kHz SiC-based TAB prototype, whose operating parameters are tailored to EVs application and peak efficiency reaches 96.3% at a partial load.</p