Insights from Lithium Stripping Dynamics on Fast Charging

Safe and reliable fast charging of lithium-ion batteries is contingent upon the development of facile methods of detection and quantification of lithium plating. Among the leading candidates for online lithium plating detection is analysis of the voltage plateau observed during the rest or discharge phase ensuing a charge. In this work, an operando metric, ‘S-factor,’ is developed from electrochemical data to quantitatively analyze the severity of lithium plating over a range of charge rates and temperatures. An in-situ visualization method is employed to study the physical mechanisms and phase transitions occurring at the graphite electrode during the voltage plateau.

Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research.

An Efficient Interpretable Visualization Method of Multidimensional Structural Data Matching Based on Job Seekers and Positions

With the rapid development of Internet technology, millions of small, medium, and microenterprises are using Internet recruitment platforms to host their recruitment information. They have different job requirements and benefits positions. It is important to understand them for job seekers when choosing a position. Existing Internet recruitment platforms do not provide a detailed analysis of positions and visual methods for multidimensional matching of positions and job applicants. Candidates need to spend a lot of energy to screen out suitable positions. In this paper, we propose an efficient interpretable visualization method of multidimensional structural data matching based on job seekers and positions. First, we extract the keywords of the job seeker’s ability and benefits based on personal information, and we generate a job seeker ability table and a job seeker demand table. After that, we calculate the degree of the support, confidence, and promotion of each rule through the association rules generated by each frequent itemset of recruitment data to obtain the association rule table. We further explore the relationship between the skills required for the three types of positions based on the association rule. Finally, we use the regression method to build a salary forecasting model. On this basis, we predict the salary of job seekers based on the work experience, education, and work city provided by the job seeker. Simulation results show that our method has better performance on the job analysis and recommendation.

An Advanced Dynamic Visualization Method of Global Ocean Tide with Multi-core Processor Based on OpenGL

In terms of ocean tide visualization, to meet the requirement of both display range and operational efficiency, an advanced method is proposed, in which the tide height is rapidly computed with global tide model EOT10a, and dynamically displayed by OpenGL. Aiming at the large amounts of calculation of global tide height, the feature of multicore processor is integrated into the method. The experiment shows that, compared to a single-core processor, when using a 6-core processor, the speedup ratio is about 5.4, parallel efficiency reaches 90%, and 880 000 tide heights can be calculated per second. Eventually, the result would be output as a tide height graph by OpenGL. This method could be a useful tool for marine cartography due to the large display range and the high efficiency.

Systematic Analysis of Power Dispatching: Using Machine Learning

With the proposal of the concept of carbon neutrality in China, the market will continue to pay more attention to sustainable energy and energy conversion. The management of the power system is a very important part in this field due to the discontinuity of wind energy and solar energy, which is also called power dispatching. It is particularly important in the process of power system conversion and management, so it is very helpful to understand the development and bottleneck of power system to understand the main research content of power dispatching through literature. Based on machine learning and text mining, this paper analyses the related research of power dispatching. The results show that the related papers of power dispatching mainly include safe operation, power dispatching strategy, power dispatching automation, power dispatching technology analysis and so on. This paper also shows the results by a clear visualization method.

Measuring of Ionizing Radiation and CO2 Gas Concentration in Air of the Falluja City in Iraq

In this work, large nuclear radiation and CO2 readings have been achieved in Falluja city; hundreds of measurements have been collected in many places and streets. The vast data was processed by a new data visualization method, which makes all the data appear on the map using Google Earth Pro software. The lowest average exposure of ionizing radiation in the air is 1.314mSv/y for the first part of Falluja sector1, while the highest one is 1.5768mSv/y in sector2. The average radiation exposure in the air for people in Falluja city is 0.9732 mSv/y.