Evaluating I/O Scheduling in Virtual Machines Based on Application Load

In recent years, cloud computing services and virtualization technology have been widely used. Virtualization requires the access to underlying resources to go through a virtualization layer, which reduces the operation efficiency, especially the access to disk I/O will easily become the bottleneck of the whole system. Therefore, how to improve the I/O performance of virtualization applications has become a hot spot in current researches, especially on I/O scheduling algorithm. While the design and selection of traditional I/O scheduling algorithms are greatly restricted by the seek time and latency of the underlying disks, the virtualization layer in a virtual environment to some extent shields the perception of the scheduling algorithm of virtual machines on the characteristics of the underlying hardware. Whether the traditional algorithms are applicable and how the multi-layer I/O scheduling system in virtualization collaborates to better meet the I/O performance requirements have become pressing issues. In this paper, the authors will explain how the I/O scheduler in Linux system works under different application loads in two scenarios (real machine and virtual machine), and take open-source Xen as examples to test and evaluate the influence of combination of the Dom0 scheduling algorithm and the virtual domain scheduling algorithm on I/O performance under different application loads, and then put forward the preferred proposals of I/O scheduler in virtual domains

NeRF-VINS: A Real-time Neural Radiance Field Map-based Visual-Inertial Navigation System

Achieving accurate, efficient, and consistent localization within an a priori environment map remains a fundamental challenge in robotics and computer vision. Conventional map-based keyframe localization often suffers from sub-optimal viewpoints due to limited field of view (FOV), thus degrading its performance. To address this issue, in this paper, we design a real-time tightly-coupled Neural Radiance Fields (NeRF)-aided visual-inertial navigation system (VINS), termed NeRF-VINS. By effectively leveraging NeRF's potential to synthesize novel views, essential for addressing limited viewpoints, the proposed NeRF-VINS optimally fuses IMU and monocular image measurements along with synthetically rendered images within an efficient filter-based framework. This tightly coupled integration enables 3D motion tracking with bounded error. We extensively compare the proposed NeRF-VINS against the state-of-the-art methods that use prior map information, which is shown to achieve superior performance. We also demonstrate the proposed method is able to perform real-time estimation at 15 Hz, on a resource-constrained Jetson AGX Orin embedded platform with impressive accuracy.Comment: 6 pages, 7 figure

General Place Recognition Survey: Towards Real-World Autonomy

In the realm of robotics, the quest for achieving real-world autonomy, capable of executing large-scale and long-term operations, has positioned place recognition (PR) as a cornerstone technology. Despite the PR community's remarkable strides over the past two decades, garnering attention from fields like computer vision and robotics, the development of PR methods that sufficiently support real-world robotic systems remains a challenge. This paper aims to bridge this gap by highlighting the crucial role of PR within the framework of Simultaneous Localization and Mapping (SLAM) 2.0. This new phase in robotic navigation calls for scalable, adaptable, and efficient PR solutions by integrating advanced artificial intelligence (AI) technologies. For this goal, we provide a comprehensive review of the current state-of-the-art (SOTA) advancements in PR, alongside the remaining challenges, and underscore its broad applications in robotics. This paper begins with an exploration of PR's formulation and key research challenges. We extensively review literature, focusing on related methods on place representation and solutions to various PR challenges. Applications showcasing PR's potential in robotics, key PR datasets, and open-source libraries are discussed. We also emphasizes our open-source package, aimed at new development and benchmark for general PR. We conclude with a discussion on PR's future directions, accompanied by a summary of the literature covered and access to our open-source library, available to the robotics community at: https://github.com/MetaSLAM/GPRS.Comment: 20 pages, 12 figures, under revie

Variable-Permeability Well-Testing Models and Pressure Response in Low-Permeability Reservoirs with non-Darcy Flow

This paper proposes the concept of variable-permeability effect and sets up the one-dimensional and two-dimensional non-Darcy well testing models. The finite difference algorithm is employed to solve the differential equations of the variable-permeability model, and the non-convergence of the numerical solutions is solved by using the geometric mean of permeability. The type curves of pressure and pressure derivative with variable-permeability effect are obtained, and sensitivity analysis is conducted. The results show that the type curves upturn in the middle and late sections, and the curves turn more upward with the severer of the variable-permeability effect. The severer the non-Darcy effect is, the less obviously the curve upturns caused by boundary effect. Furthermore, the boundary effect is increased by increasing the number of impermeable boundaries or decreasing the distance between the well and boundary

A HISTORY OF THE STEREOLOGY IN CHINA

This review article introduces the formation and development of stereology in China under the background of the development of international stereology. In the early 1970s, some stereological monographs and collections were introduced into China, and Chinese scholars began to understand, study and promote stereology knowledge. Meanwhile, the widespread use of image analysis systems has contributed to the spread of stereology in China. On the other hand, academic exchanges and personnel training have played a catalytic role in the formation of stereology in China. According to China National Knowledge Infrastructure (CNKI) statistics, the number and impact of Chinese papers in stereology continues to grow during the past 30 years. After in-depth discussion, Chinese scholars have adopted a broader definition of stereology. With economic development and technological progress, China has great potential to develop, promote and apply the stereological methods and the related technologies

Preparation and Application of Starch/Polyvinyl Alcohol/Citric Acid Ternary Blend Antimicrobial Functional Food Packaging Films

Ternary blend films were prepared with different ratios of starch/polyvinyl alcohol (PVA)/citric acid. The films were characterized by field emission scanning electron microscopy (FE-SEM), thermogravimetric analysis, as well as Fourier transform infrared (FTIR) analysis. The influence of different ratios of starch/polyvinyl alcohol (PVA)/citric acid and different drying times on the performance properties, transparency, tensile strength (TS), water vapor permeability (WVP), water solubility (WS), color difference (ΔE), and antimicrobial activity of the ternary blends films were investigated. The starch/polyvinyl alcohol/citric acid (S/P/C1:1:0, S/P/C3:1:0.08, and S/P/C3:3:0.08) films were all highly transparent. The S/P/C3:3:0.08 had a 54.31 times water-holding capacity of its own weight and its mechanical tensile strength was 46.45 MPa. In addition, its surface had good uniformity and compactness. The S/P/C3:1:0.08 and S/P/C3:3:0.08 showed strong antimicrobial activity to Listeria monocytogenes and Escherichia coli, which were the food-borne pathogenic bacteria used. The freshness test results of fresh figs showed that all of the blends prevented the formation of condensed water on the surface of the film, and the S/P/C3:1:0.08 and S/P/C3:3:0.08 prevented the deterioration of figs during storage. The films can be used as an active food packaging system due to their strong antibacterial effect

LEARNING-BASED AUTOMATIC BREAST TUMOR DETECTION AND SEGMENTATION IN ULTRASOUND IMAGES

Ultrasound (US) images have been widely used in the diagnosis of breast cancer in particular. While experienced doctors may locate the tumor regions in a US image manually, it is highly desirable to develop algorithms that automatically detect the tumor regions in order to assist medical diagnosis. In this paper, we propose a novel algorithm for automatic detection of breast tumors in US images. We formulate the tumor detection as a two step learning problem: tumor localization by bounding box and exact boundary delineation. Specifically, the proposed method uses an AdaBoost classifier on Harr-like features to detect a preliminary set of tumor regions. The preliminarily detected tumor regions are further screened with a support vector machine using quantized intensity features. Finally, the random walk segmentation algorithm is performed on the US image to retrieve the boundary of each detected tumor region. The proposed method has been evaluated on a data set containing 112 breast US images, including histologically confirmed 80 diseased ones and 32 normal ones. The data set contains one image from each patient and the patients are from 31 to 75 years old. Experiments demonstrate that the proposed algorithm can automatically detect breast tumors, with their locations and boundary shapes retrieved with high accuracy

effectsoftheoxidationextentofthesicsurfaceontheperformanceofnisicmethanationcatalysts

采用等体积浸渍法制备了Ni/SiC甲烷化催化剂,研究了SiC载体表面氧化程度对催化剂低温活性和高温稳定性的影响,并采用热重-差示扫描量热、N2物理吸附、傅立叶变换红外光谱、氨程序升温脱附、X射线衍射、氢程序升温还原和氢化学吸附技术对样品进行了表征.结果表明,随着载体氧化温度的提高,催化剂的比表面积和镍分散度降低,但还原性和反应稳定性提高.未氧化载体所负载催化剂的高温稳定性最差,其原因在于载体对镍粒子的固定作用最弱.负载于500和700℃处理的SiC载体上的催化剂具有较好的低温活性和高温稳定性,这是因为适度氧化后的载体能较好地分散并固定镍粒子.900℃处理的载体因过度氧化形成了低活性的氧化层,使负载的镍粒子变大,因而催化剂的低温活性最差

effectsoftheoxidationextentofthesicsurfaceontheperformanceofnisicmethanationcatalysts

采用等体积浸渍法制备了Ni/SiC甲烷化催化剂,研究了SiC载体表面氧化程度对催化剂低温活性和高温稳定性的影响,并采用热重-差示扫描量热、N2物理吸附、傅立叶变换红外光谱、氨程序升温脱附、X射线衍射、氢程序升温还原和氢化学吸附技术对样品进行了表征.结果表明,随着载体氧化温度的提高,催化剂的比表面积和镍分散度降低,但还原性和反应稳定性提高.未氧化载体所负载催化剂的高温稳定性最差,其原因在于载体对镍粒子的固定作用最弱.负载于500和700℃处理的SiC载体上的催化剂具有较好的低温活性和高温稳定性,这是因为适度氧化后的载体能较好地分散并固定镍粒子.900℃处理的载体因过度氧化形成了低活性的氧化层,使负载的镍粒子变大,因而催化剂的低温活性最差