An Open-Source Whole Slide Image Registration Workflow at Cellular Precision Using Fiji, QuPath and Elastix

Image analysis workflows for Histology increasingly require the correlation and combination of measurements across several whole slide images. Indeed, for multiplexing, as well as multimodal imaging, it is indispensable that the same sample is imaged multiple times, either through various systems for multimodal imaging, or using the same system but throughout rounds of sample manipulation (e.g. multiple staining sessions). In both cases slight deformations from one image to another are unavoidable, leading to an imperfect superimposition Redundant and thus a loss of accuracy making it difficult to link measurements, in particular at the cellular level. Using pre-existing software components and developing missing ones, we propose a user-friendly workflow which facilitates the nonlinear registration of whole slide images in order to reach sub-cellular resolution level. The set of whole slide images to register and analyze is at first defined as a QuPath project. Fiji is then used to open the QuPath project and perform the registrations. Each registration is automated by using an elastix backend, or semi-automated by using BigWarp in order to interactively correct the results of the automated registration. These transformations can then be retrieved in QuPath to transfer any regions of interest from an image to the corresponding registered images. In addition, the transformations can be applied in QuPath to produce on-the-fly transformed images that can be displayed on top of the reference image. Thus, relevant data can be combined and analyzed throughout all registered slides, facilitating the analysis of correlative results for multiplexed and multimodal imaging.

Requirements to Products and Processes for Software of Safety Important NPP I&C Systems

Features of software as a component of instrumentation and control (I&C) systems are analyzed. Attention is paid to the importance of functions performed by software and hazards of such software. Requirements for characteristics of software as a component of I&C systems are analyzed. Different regulatory documents are considered in order to disclose common approaches to the use of dedicated software and off-the-shelf software components. Classification of software, as well as classification of requirements, is described. Criteria of selection and structuring of requirements, as well as criteria for software verification, are defined. As long as the characteristics of software components directly depend on the quality of the processes of software development and verification, requirements for software life cycle processes are considered.

DIGITAL SAFETY MANAGER: IOT SERVICE TO ASSURE THE SAFE BEHAVIOUR OF MACHINES AND CONTROLS IN THE DIGITAL INDUSTRY

The digital industry requires increasingly complex and reliable software systems. They need to control and make critical decisions at runtime. As a consequence, the verification and validation of these systems has become a major research challenge. At design and development time, model testing techniques are used while run-time verification aims at verifying that a system satisfies a given property. The latter technique complements the former. The solution presented in this paper targets embedded systems whose software components are designed by state machines defined by Unified Modelling Language (UML). The CRESCO (C++ REflective State-Machines based observable software COmponents) platform generates software components that provide internal information at runtime and the verifier uses this information to check system-level reliability/safety contracts. The verifier detects when a system contract is violated and initiates a safeState process to prevent dangerous scenarios. These contracts are defined by internal information from the software components that make up the system. Thus, as demonstrated in the tested experiment, the robustness of the system is increased. All software components (controllers), such as the verifier, have been deployed as services (producers/consumers) of the Arrowhead IoT platform: the controllers are deployed on local Arrowhead platforms (Edge) and the verifier (Safety Manager) is deployed on an Arrowhead platform (Cloud) that will consume controllers on the Edge and ensure the proper functioning of the plant controllers. Keywords: run-time monitoring, robustness, software components, contracts, software models, state machines

Development of an Autonomous Quadrotor with a Robust Real-time Control: A Review on Modeling, Estimation, Control, and Hardware Aspects

The following report is a comprehensive discussion on the development of a resilient autonomous quadrotor equipped with a robust control mechanism for optimal performance. An introduction to quadrotor modeling and flight dynamics is provided first. The autopilot control and state estimation methods are then described from both software and hardware viewpoints. A review of PX4 autopilot control architecture is provided to comprehend a complete control system integration. It is followed by a survey of commonly used sensors, micro-controllers, actuators, and other hardware peripherals used in academic and commercial grade quadrotors, along with their architectural overview. Next, a brief discussion on the software components essential for a real-time implementation of the developed control system on the hardware is done. Finally, concluding remarks are made on each stage of quadcopter development, and potential research problems are forecasted.

Development of an Autonomous Quadrotor with a Robust Real-time Control: A Review on Modeling, Estimation, Control, and Hardware Aspects

The following report is a comprehensive discussion on the development of a resilient autonomous quadrotor equipped with a robust control mechanism for optimal performance. An introduction to quadrotor modeling and flight dynamics is provided first. The autopilot control and state estimation methods are then described from both software and hardware viewpoints. A review of PX4 autopilot control architecture is provided to comprehend a complete control system integration. It is followed by a survey of commonly used sensors, micro-controllers, actuators, and other hardware peripherals used in academic and commercial grade quadrotors, along with their architectural overview. Next, a brief discussion on the software components essential for a real-time implementation of the developed control system on the hardware is done. Finally, concluding remarks are made on each stage of quadcopter development, and potential research problems are forecasted.

TDCA: Improved Optimization Algorithm with Degree Distribution and Communication Traffic for the Deployment of Software Components Base on AUTOSAR Architecture

AUTOSAR (Automotive Open System Architecture), as an open, standardized framework for automotive electronic software development, has gradually become the standard followed by major automotive manufacturers and automotive electronic device suppliers. The electronic software system problem improves the development efficiency and portability of the system by reducing the development cost of automotive electronic software while ensuring the quality of products and services, which is beneficial for subsequent upgrades and updates of the system. In order to improve the reliability of the software component deployment algorithm based on AUTOSAR architecture, we proposed the TDCA algorithm. During the execution of the algorithm, communication volume and communication degree are introduced to improve the accuracy of the deployment plan by optimizing the bus load and ECU balancing. Algorithm comparison experiments show that comparing heuristic and linear optimization algorithms, the TDCA algorithm proposed in this paper has significant advantages in reducing bus load and balancing ECU utilization. The algorithm can reduce the communication between cores and balance ECU load according to the constraints of AUTOSAR architecture.

Using the Loginom analytical platform to process long-term field experience data

The article discusses the capabilities of the Loginom analytical platform for processing long-term field experience data; such software components are used as data transformation (row filter, sorting, grouping, cross-table, cross-diagram, sliding window); preprocessing (editing emissions, smoothing), research (correlation analysis, factor analysis), Data Mining (self-organizing network, clustering) to identify the effect of crop rotations, soil liming, application of various combinations of mineral and organic fertilizers, weather conditions on yield of oats and barley.

Using the Loginom analytical platform to process long-term field experience data

The article discusses the capabilities of the Loginom analytical platform for processing long-term field experience data; such software components are used as data transformation (row filter, sorting, grouping, cross-table, cross-diagram, sliding window); preprocessing (editing emissions, smoothing), research (correlation analysis, factor analysis), Data Mining (self-organizing network, clustering) to identify the effect of crop rotations, soil liming, application of various combinations of mineral and organic fertilizers, weather conditions on yield of oats and barley.