Compositional Scene Modeling with Global Object-Centric Representations

The appearance of the same object may vary in different scene images due to perspectives and occlusions between objects. Humans can easily identify the same object, even if occlusions exist, by completing the occluded parts based on its canonical image in the memory. Achieving this ability is still a challenge for machine learning, especially under the unsupervised learning setting. Inspired by such an ability of humans, this paper proposes a compositional scene modeling method to infer global representations of canonical images of objects without any supervision. The representation of each object is divided into an intrinsic part, which characterizes globally invariant information (i.e. canonical representation of an object), and an extrinsic part, which characterizes scene-dependent information (e.g., position and size). To infer the intrinsic representation of each object, we employ a patch-matching strategy to align the representation of a potentially occluded object with the canonical representations of objects, and sample the most probable canonical representation based on the category of object determined by amortized variational inference. Extensive experiments are conducted on four object-centric learning benchmarks, and experimental results demonstrate that the proposed method not only outperforms state-of-the-arts in terms of segmentation and reconstruction, but also achieves good global object identification performance

Design, purification and assessment of GRP78 binding peptide-linked Subunit A of Subtilase cytotoxic for targeting cancer cells

The sequence of primers for GBP-SubA and optimization of E. coli strain and vector of GBP-SubA expression. (DOC 710 kb

Cultural Differences in Humor Perception, Usage, and Implications

Humor is a universal phenomenon but is also culturally tinted. In this article, we reviewed the existing research that investigates how culture impacts individuals’ humor perception and usage as well as humor’s implications for psychological well-being. Previous research has substantiated evidence that Easterners do not hold as positive an attitude toward humor as their Western counterparts do. This perception makes Easterners less likely to use humor as a coping strategy in comparison with Westerners. Despite this difference, Westerners and Easterners have similar patterns in the relationship between their humor and psychological well-being index, though the strength of the relationship varies across cultures. Implications and potential future research avenues discussed

OCTScenes: A Versatile Real-World Dataset of Tabletop Scenes for Object-Centric Learning

Humans possess the cognitive ability to comprehend scenes in a compositional manner. To empower AI systems with similar abilities, object-centric representation learning aims to acquire representations of individual objects from visual scenes without any supervision. Although recent advancements in object-centric representation learning have achieved remarkable progress on complex synthesis datasets, there is a huge challenge for application in complex real-world scenes. One of the essential reasons is the scarcity of real-world datasets specifically tailored to object-centric representation learning methods. To solve this problem, we propose a versatile real-world dataset of tabletop scenes for object-centric learning called OCTScenes, which is meticulously designed to serve as a benchmark for comparing, evaluating and analyzing object-centric representation learning methods. OCTScenes contains 5000 tabletop scenes with a total of 15 everyday objects. Each scene is captured in 60 frames covering a 360-degree perspective. Consequently, OCTScenes is a versatile benchmark dataset that can simultaneously satisfy the evaluation of object-centric representation learning methods across static scenes, dynamic scenes, and multi-view scenes tasks. Extensive experiments of object-centric representation learning methods for static, dynamic and multi-view scenes are conducted on OCTScenes. The results demonstrate the shortcomings of state-of-the-art methods for learning meaningful representations from real-world data, despite their impressive performance on complex synthesis datasets. Furthermore, OCTScenes can serves as a catalyst for advancing existing state-of-the-art methods, inspiring them to adapt to real-world scenes. Dataset and code are available at https://huggingface.co/datasets/Yinxuan/OCTScenes

Research on Flexible HVDC Transmission Technology and Strategies for Improving the Operational Stability of IGBT Components

[Introduction] With the continuous improvement of the strategic position of clean energy, more and more new energy power generation equipment is connected to the power grid, but its power quality is unstable, which has a great impact on the AC (Alternating-Current) transmission grid. Flexible DC (Direct-Current) transmission networks can effectively isolate AC and the DC networks, and have good development prospects. The key component of flexible DC power transmission is the converter valve. The key component of flexible DC power transmission is the converter valve with fully controlled IGBT components as the core. Therefore, the safe and stable operation of IGBT (Insulate-Gate Bipolar Transistor) components plays an important role in the stability of the entire flexible DC system. In order to improve the safety and operational stability of IGBT components, it is necessary to control their operating current and voltage to avoid overcurrent and overvoltage damage. At the same time, it is necessary to control the temperature and humidity of the environment, equipment corrosion resistance to improve operating conditions. [Method] Therefore, both internal and external strategies were adopted. Starting resistors, reactors, lightning arresters, etc. were installed internally to control the current and voltage of the circuit. Externally, air conditioners were set, the room tightness was improved, and equipment anti-corrosion treatment was equipped to ensure a good working environment. [Result] By configuring starting resistors, reactors, lightning arresters and other facilities in the internal circuit, the circuit current and voltage are limited, and then the overcurrent multiple and overvoltage multiple acting on the IGBT components are controlled under extreme conditions. By controlling the temperature and humidity of the room where the IGBT is located and the corrosion resistance of the equipment, a suitable environment is provided for the operation of the IGBT components, which is helpful to improve the safety and operational reliability of the IGBT components. [Conclusion] Flexible DC transmission can well solve the power transmission problem of new energy power generation facilities with poor power quality. And by optimizing the internal strategy of the flexible DC transmission system circuit and the external strategy to improve the suitability of the operating environment of the IGBT components, the safety and operational reliability of the IGBT components and even the entire flexible direct current system are improved

Statistical modeling of spatially stratified heterogeneous data

Spatial statistics is an important methodology for geospatial data analysis. It has evolved to handle spatially autocorrelated data and spatially (locally) heterogeneous data, which aim to capture the first and second laws of geography, respectively. Examples of spatially stratified heterogeneity (SSH) include climatic zones and land-use types. Methods for such data are relatively underdeveloped compared to the first two properties. The presence of SSH is evidence that nature is lawful and structured rather than purely random. This induces another “layer” of causality underlying variations observed in geographical data. In this article, we go beyond traditional cluster-based approaches and propose a unified approach for SSH in which we provide an equation for SSH, display how SSH is a source of bias in spatial sampling and confounding in spatial modeling, detect nonlinear stochastic causality inherited in SSH distribution, quantify general interaction identified by overlaying two SSH distributions, perform spatial prediction based on SSH, develop a new measure for spatial goodness of fit, and enhance global modeling by integrating them with an SSH q statistic. The research advances statistical theory and methods for dealing with SSH data, thereby offering a new toolbox for spatial data analysis

DISTRIBUTED NOSQL STORAGE FOR EXTREME-SCALE SYSTEM SERVICES IN CLOUDS AND SUPERCOMPUTERS

As supercomputers gain more parallelism at exponential rates, the storage infrastructure performance is increasing at a significantly lower rate due to relatively centralized management. This implies that the data management and data flow between the storage and compute resources is becoming the new bottleneck for large-scale applications. Similarly, cloud based distributed systems introduce other challenges stemming from the dynamic nature of cloud applications. This dissertation addresses several challenges on storage systems at extreme scales for supercomputers and clouds by designing and implementing a zero-hop distributed NoSQL storage system (ZHT), which has been tuned for the requirements of high-end computing systems. ZHT aims to be a building block for scalable distributed systems. The goals of ZHT are delivering high availability, good fault tolerance, light-weight design, persistence, dynamic joins and leaves, high throughput, and low latencies, at extreme scales (millions of nodes). We have evaluated ZHT’s performance under a variety of systems, ranging from a Linux cluster with 64-nodes, an Amazon EC2 virtual cluster up to 96-nodes, to an IBM Blue Gene/P supercomputer with 8K-nodes. This work also presents several real systems that have adopted ZHT as well as other NoSQL systems, namely ZHT/Q, FusionFS, IStore, MATRIX, Slurm++, Fabriq, FREIDAState, and WaggleDB, all of these real systems have been significantly simplified due to NoSQL storage systems, and have been shown to outperform other leading systems by orders of magnitude in some cases. Through our work, we have shown how NoSQL storage systems can help on both performance and scalability at large scales in such a variety of environments.Ph.D. in Computer Science, December 201