SUMMARY: Multimodal single-cell sequencing data provide detailed views into the molecular biology of cells. To allow for interactive analyses of such rich data and to readily derive insights from it, new analysis solutions are required. In this work, we present Cellenium, our new scalable visual analytics web application that enables users to semantically integrate and organize all their single-cell RNA-, ATAC-, and CITE-sequencing studies. Users can then find relevant studies and analyze single-cell data within and across studies. An interactive cell annotation feature allows for adding user-defined cell types. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are freely available under an MIT license and are available on GitHub (https://github.com/Bayer-Group/cellenium). The server backend is implemented in PostgreSQL, Python 3, and GraphQL, the frontend is written in ReactJS, TypeScript, and Mantine css, and plots are generated using plotlyjs, seaborn, vega-lite, and nivo.rocks. The application is dockerized and can be deployed and orchestrated on a standard workstation via docker-compose.

In this article, a generic virtual prototyping tool to optimize Modular Multilevel Converters (MMCs) is proposed. The aim is to optimize the components of MMC. Moreover, the geometry of the arm inductor is proposed and its geometric variables are optimized. A generic model of MMC and an optimization tool, implemented in MATLAB/Simulink, are presented. Maximize the converter efficiency and minimize its overall volume define a bi-objective optimization problem. A bi-objective Genetic Algorithm (GA) is used and optimization results are presented in Pareto fronts. To validate the generic virtual prototyping tool, two converters are optimized: 13.85 kVA and 398 kVA. Analysis and discussions to choose suitable solutions on Pareto fronts are performed.

The design of power converters that have both high efficiency and high power density performance while maintaining the lowest possible cost and highest possible reliability is a challenge for power electronics engineers. Therefore, optimization techniques are often used to obtain the optimal solution for a given set of specified objectives. As a result, engineers must devise the correct methodology to solve multi-variant problems arising from these fixed objectives. The aim of this paper is to investigate PFC rectifier performance as a function of design variables and temperature impact using a bi-objective optimization algorithm. A methodology based on a Pareto-Front analysis to find the optimal design variable is described and a design model including electro-thermal modeling and power loss calculations is presented. Subsequently, the optimization result of a single-phase boost PFC converter operating in continuous conduction mode (CCM) for input power levels of 3kW is analyzed, and then the methodology to evaluate cost and reliability variables for design optimization is presented. FEM simulations and experimental results are shown to demonstrate the effectiveness of the proposed models.

Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment systems (toll payment, parking fee payment), and freeway and arterial monitoring systems for traffic surveillance. The ALPR uses either a color, black and white, or infrared camera to take images. The quality of the acquired images is a major factor in the success of the ALPR. ALPR as a real-life application has to quickly and successfully process license plates under different environmental conditions, such as indoors, outdoors, day or night time. It should also be generalized to process license plates from different nations, provinces, or states. These plates usually contain different colors, are written in different languages, and use different fonts; some plates may have a single color background and others have background images. The license plates can be partially occluded by dirt, lighting, and towing accessories on the car. In this paper, we present a comprehensive review of the state-of-the-art techniques for ALPR. We categorize different ALPR techniques according to the features they used for each stage, and compare them in terms of pros, cons, recognition accuracy, and processing speed. Future forecasts of ALPR are given at the end.