Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture

Supporting the current trend in the AI community, we present the AI Journey 2021 Challenge called Fusion Brain, the first competition which is targeted to make the universal architecture which could process different modalities (in this case, images, texts, and code) and solve multiple tasks for vision and language. The Fusion Brain Challenge combines the following specific tasks: Code2code Translation, Handwritten Text recognition, Zero-shot Object Detection, and Visual Question Answering. We have created datasets for each task to test the participants' submissions on it. Moreover, we have collected and made publicly available a new handwritten dataset in both English and Russian, which consists of 94,128 pairs of images and texts. We also propose a multimodal and multitask architecture - a baseline solution, in the center of which is a frozen foundation model and which has been trained in Fusion mode along with Single-task mode. The proposed Fusion approach proves to be competitive and more energy-efficient compared to the task-specific one

geonetworking: Vehicle Adapter

The first release of the Vehicle Adapter developed for the GCDC2016 competition. Built on top of Alexey Voronov's geonetworking library

A Method for Optimum Placement of Access Points in Indoor Positioning Systems

When designing and installing Indoor Positioning Systems, several interrelated tasks have to be solved to find an optimum placement of the Access Points. For this purpose, a mathematical model for a predefined number of access points indoors is presented. Two iterative algorithms for the minimization of localization error of a mobile object are described. Both algorithms use local search technique and signal level probabilities. Previously registered signal strengths maps were used in computer simulation

Improving the Accuracy for Radio-Based Positioning in Mines Using SLAM

During the day-to-day exploitation of localization systems in mines, the technical staff tends to incorrectly rearrange radio equipment: positions of devices may not be accurately marked on a map or their positions may not correspond to the truth. This situation may lead to positioning inaccuracies and errors in the operation of the localization system.This paper presents two Bayesian algorithms for the automatic corrections of positions of the equipment on the map using trajectories restored by the inertial measurement units mounted to mobile objects, like pedestrians and vehicles. As a basis, a predefined map of the mine represented as undirected weighted graph was used as input. The algorithms were implemented using the Simultaneous Localization and Mapping (SLAM) approach.The results prove that both methods are capable to detect misplacement of access points and to provide corresponding corrections. The discrete Bayesian filter outperforms the unscented Kalman filter, which, however, requires more computational power

Correction of Uncertain Access Points Positions in Underground Mines Using SLAM Approach

This paper presents an extended version of a previously published Bayesian algorithm for the automatic correction of the positions of the equipment on the map with simultaneous mobile object trajectory localization (SLAM) in underground mine environment represented by undirected graph. The proposed extended SLAM algorithm requires much less preliminary data on possible equipment positions and uses an additional resample move algorithm to significantly improve the overall performance

MEMS Sensors Bias Thermal Profiles Classification Using Machine Learning

The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach. A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm. The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained

IL-1alpha and IL-1beta recruit different myeloid cells and promote different stages of sterile inflammation.

Item does not contain fulltextThe immune system has evolved to protect the host from invading pathogens and to maintain tissue homeostasis. Although the inflammatory process involving pathogens is well documented, the intrinsic compounds that initiate sterile inflammation and how its progression is mediated are still not clear. Because tissue injury is usually associated with ischemia and the accompanied hypoxia, the microenvironment of various pathologies involves anaerobic metabolites and products of necrotic cells. In the current study, we assessed in a comparative manner the role of IL-1alpha and IL-1beta in the initiation and propagation of sterile inflammation induced by products of hypoxic cells. We found that following hypoxia, the precursor form of IL-1alpha, and not IL-1beta, is upregulated and subsequently released from dying cells. Using an inflammation-monitoring system consisting of Matrigel mixed with supernatants of hypoxic cells, we noted accumulation of IL-1alpha in the initial phase, which correlated with the infiltration of neutrophils, and the expression of IL-1beta correlated with later migration of macrophages. In addition, we were able to show that IL-1 molecules from cells transfected with either precursor IL-1alpha or mature IL-1beta can recruit neutrophils or macrophages, respectively. Taken together, these data suggest that IL-1alpha, released from dying cells, initiates sterile inflammation by inducing recruitment of neutrophils, whereas IL-1beta promotes the recruitment and retention of macrophages. Overall, our data provide new insight into the biology of IL-1 molecules as well as on the regulation of sterile inflammation