Stability of Multi-Dimensional Switched Systems with an Application to Open Multi-Agent Systems

Extended from the classic switched system, themulti-dimensional switched system (MDSS) allows for subsystems(switching modes) with different state dimensions. In this work,we study the stability problem of the MDSS, whose state transi-tion at each switching instant is characterized by the dimensionvariation and the state jump, without extra constraint imposed.Based on the proposed transition-dependent average dwell time(TDADT) and the piecewise TDADT methods, along with the pro-posed parametric multiple Lyapunov functions (MLFs), sufficientconditions for the practical and the asymptotical stabilities of theMDSS are respectively derived for the MDSS in the presenceof unstable subsystems. The stability results for the MDSS areapplied to the consensus problem of the open multi-agent system(MAS) which exhibits dynamic circulation behaviors. It is shownthat the (practical) consensus of the open MAS with disconnectedswitching topologies can be ensured by (practically) stabilizingthe corresponding MDSS with unstable switching modes via theproposed TDADT and parametric MLF methods.Comment: 12 pages, 9 figure

Is ProtoPNet Really Explainable? Evaluating and Improving the Interpretability of Prototypes

ProtoPNet and its follow-up variants (ProtoPNets) have attracted broad research interest for their intrinsic interpretability from prototypes and comparable accuracy to non-interpretable counterparts. However, it has been recently found that the interpretability of prototypes can be corrupted due to the semantic gap between similarity in latent space and that in input space. In this work, we make the first attempt to quantitatively evaluate the interpretability of prototype-based explanations, rather than solely qualitative evaluations by some visualization examples, which can be easily misled by cherry picks. To this end, we propose two evaluation metrics, termed consistency score and stability score, to evaluate the explanation consistency cross images and the explanation robustness against perturbations, both of which are essential for explanations taken into practice. Furthermore, we propose a shallow-deep feature alignment (SDFA) module and a score aggregation (SA) module to improve the interpretability of prototypes. We conduct systematical evaluation experiments and substantial discussions to uncover the interpretability of existing ProtoPNets. Experiments demonstrate that our method achieves significantly superior performance to the state-of-the-arts, under both the conventional qualitative evaluations and the proposed quantitative evaluations, in both accuracy and interpretability. Codes are available at https://github.com/hqhQAQ/EvalProtoPNet

A Survey of Neural Trees

Neural networks (NNs) and decision trees (DTs) are both popular models of machine learning, yet coming with mutually exclusive advantages and limitations. To bring the best of the two worlds, a variety of approaches are proposed to integrate NNs and DTs explicitly or implicitly. In this survey, these approaches are organized in a school which we term as neural trees (NTs). This survey aims to present a comprehensive review of NTs and attempts to identify how they enhance the model interpretability. We first propose a thorough taxonomy of NTs that expresses the gradual integration and co-evolution of NNs and DTs. Afterward, we analyze NTs in terms of their interpretability and performance, and suggest possible solutions to the remaining challenges. Finally, this survey concludes with a discussion about other considerations like conditional computation and promising directions towards this field. A list of papers reviewed in this survey, along with their corresponding codes, is available at: https://github.com/zju-vipa/awesome-neural-treesComment: 35 pages, 7 figures and 1 tabl

Analysis of the Spatial Differentiation and Development Optimization of Towns’ Livable Quality in Aksu, China

With the proposal of the United Nations Sustainable Development Goals (SDGs), how to effectively improve the quality of human settlements has become a hot spot. Governments and scholars around the world pay attention to reasonable improvement of livability, which is conducive to improving the happiness level of residents and is closely related to human well-being. Due to the lack of rural statistical data in Xinjiang, this study established a new comprehensive evaluation system, which selected 21 indicators from the natural and humanistic aspects. The results show that the overall ecological security of Aksu prefecture is good, and Kuche city has the best humanistic livability performance. In terms of the livable quality of towns, Kuche Urban Area performs best. The towns with excellent and good livable quality are concentrated, but their spatial connections are weak. Based on the analysis and survey results, we put forward zoning optimization suggestions for the livable quality in Aksu prefecture. The results of this study would provide directional guidance for the improvement of livable quality in Aksu prefecture. At the same time, we expect that it can provide a methodological supplement for the relevant evaluation in other similar regions

A Survey of Deep Learning for Low-Shot Object Detection

Object detection has achieved a huge breakthrough with deep neural networks and massive annotated data. However, current detection methods cannot be directly transferred to the scenario where the annotated data is scarce due to the severe overfitting problem. Although few-shot learning and zero-shot learning have been extensively explored in the field of image classification, it is indispensable to design new methods for object detection in the data-scarce scenario since object detection has an additional challenging localization task. Low-Shot Object Detection (LSOD) is an emerging research topic of detecting objects from a few or even no annotated samples, consisting of One-Shot Object Detection (OSOD), Few-Shot Object Detection (FSOD) and Zero-Shot Object Detection (ZSD). This survey provides a comprehensive review of LSOD methods. First, we propose a thorough taxonomy of LSOD methods and analyze them systematically, comprising some extensional topics of LSOD (semi-supervised LSOD, weakly-supervised LSOD and incremental LSOD). Then, we indicate the pros and cons of current LSOD methods with a comparison of their performance. Finally, we discuss the challenges and promising directions of LSOD to provide guidance for future works

Spatial Characteristics of Land Use Multifunctionality and Their Trade-Off/Synergy in Urumqi, China: Implication for Land Space Zoning Management

Identifying and exploring the spatial characteristics of land use multifunctionality (LUMF) and their trade-off/synergy are the basis for promoting the coordinated development of LUMF, and have significant implications for land space zoning management. In this study, we integrated multi-source data to construct a multi-functional identification system of land use, and quantitatively identified agricultural production function (APF), urban life function (ULF), and ecological function (EF) from grid units. We used the mechanical equilibrium model and Spearman correlation variable analysis to explore the trade-off/synergy between the primary and secondary function of land use. The results show that LUMF has obvious spatial differentiation characteristics and significant composite characteristics. Functionality interweaves and overlaps spatially, creating trade-off/synergy between LUMF. Urumqi as a whole was at a coordinated level (73%). High urban life–low agricultural production and high ecology–low agricultural production were the main types of trade-off/synergy. APF and EF were dominant functions, and there was a significant synergistic relationship. APF and urban life-bearing function had a trade-off relationship. Based on the research results, zoning attempts were made as a reference. Finally, under the framework of regional function theory, we considered the sequential selection process and competition process of LUMF, and put forward proposals for land space zoning management

Spatial Characteristics of Land Use Multifunctionality and Their Trade-Off/Synergy in Urumqi, China: Implication for Land Space Zoning Management

Identifying and exploring the spatial characteristics of land use multifunctionality (LUMF) and their trade-off/synergy are the basis for promoting the coordinated development of LUMF, and have significant implications for land space zoning management. In this study, we integrated multi-source data to construct a multi-functional identification system of land use, and quantitatively identified agricultural production function (APF), urban life function (ULF), and ecological function (EF) from grid units. We used the mechanical equilibrium model and Spearman correlation variable analysis to explore the trade-off/synergy between the primary and secondary function of land use. The results show that LUMF has obvious spatial differentiation characteristics and significant composite characteristics. Functionality interweaves and overlaps spatially, creating trade-off/synergy between LUMF. Urumqi as a whole was at a coordinated level (73%). High urban life–low agricultural production and high ecology–low agricultural production were the main types of trade-off/synergy. APF and EF were dominant functions, and there was a significant synergistic relationship. APF and urban life-bearing function had a trade-off relationship. Based on the research results, zoning attempts were made as a reference. Finally, under the framework of regional function theory, we considered the sequential selection process and competition process of LUMF, and put forward proposals for land space zoning management

Additional file 2 of The role of proteoglycan form of DMP1 in cranial repair

Additional file 2

Spatial and Temporal Evolution of Land Use and the Response of Habitat Quality in Wusu, China

Understanding land use change and its impact on habitat quality (HQ) is conducive to land use management and ecological protection. We used the InVEST model and the GeoDetector model to explore the land use and HQ of Wusu from 1980 to 2020. We found that the spatial distribution of land use in Wusu had the most dramatic change from 2000 to 2010, and accordingly, the habitat quality deteriorated seriously from 2000 to 2010. Via correlation analysis, the response of HQ to land use change is obvious, among which the negative effect of forest land to construction land is the largest, and the positive effect of construction land to water is the largest. However, the overall HQ had the largest negative response to the change of grassland to arable land, and the largest positive response to the change of unused land to grassland. Of the driving factors that cause land use change and thus affect HQ, the human factors are the strongest, and the negative impact on HQ is more irreversible. This study can provide a scientific basis for land use management and ecological protection in Wusu, and can help to further promote the exploration of human activities and ecological responses in arid and semi-arid areas