The paper proposes an innovative approach in solving the fault detection problem of sewerage treatment plant machinery. The proposed approach treats the fault detection data with the class decomposition problem, ensuring that a classification algorithm overlooks no disjunct instances. As the class decomposition technique requires heavy customization to each class of instances in every data set, Grey Wolf Optimizer is used to determine the appropriate clustering method with the appropriate setting for each class of instances. The proposed approach is tested on real-life sensor data from a sewerage treatment plant, and the results show that here proposed approach overshadows several manually proposed class decomposition methods.
ECG graphs show the electrical activity of the heart in function of time. It helps doctors to better understand the actual heart activity of the patient. Before the use of computers in the medical field, the ECG was printed and analyzed on a paper format. Nowadays medical data is archived in digital format and many data formats for ECG data storage are available. The many formats present an important problem of interoperability and compatibility between different data representations. A new technique to solve the interoperability issue and furthermore to store even stream-like ECG data became a necessity to assure better service quality of hospitals and to ensure smooth transition between different formats. This paper proposes a new (working and tested) solution for ECG data conversion, using an intermediate JSON format designed especially for ECG data, from/to SCP-ECG, DICOM-ECG, and HL7 aECG.
Contact tasks represent the most challenging elements of robotic operations. Simulation of such operations is a key element in space robotic applications and also sim-to-real transfer in reinforcement learning. Complex unilateral contact interfaces, friction, diversity of material properties are among the many contributors that make such robotic tasks extremely difficult to realistically reproduce in simulation and in virtual environments in general. In this presentation, we describe and demonstrate simulation methods for such complex robotic systems and tasks in the context of space robotic operations. The techniques rely on the concept of system decomposition and real-time interfacing using co-simulation. We will introduce the concept of model-based coupling that can significantly enhance the performance and accuracy of real-time simulation. Challenging space robotic contact tasks, such as grasping and insertion with jamming, will be used to illustrate the methods and their performance.
Work for this paper was motivated by the recognition that cooperation between engineering model system (EMS) representing cyber physical system (CPS) and cyber units of represented CPS is essential for both sides mainly to assist critical decisions. While EMS provides sophisticated model representations, procedures and much more for CPS, CPS acts as verified source of experience information to enhance models in EMS. This cooperation results theoretically grounded and, at the same time, experience proven representation fulfilling one of the essential current requirements against EMS. This paper contributes to methodology for the above connection mainly to enhance autonomous cooperation between EMS and the related cyber units of CPS. Cooperation between virtual and physical CPS configurations are analyzed using new organized scenario. Results of this analysis are applied at development concept and process to provide autonomous EMS (AEM) support for engineering in autonomous CPS. Following this, concept of model mediated research (MMR) is introduced to support research in engineering for AEM and CPS. Finally, experimental implementation of MMR concept in activity of the Virtual Research Laboratory (VRL) at the Doctoral School of Applied Informatics and Applied Mathematics (AIAMDI), Obuda University is discussed.
This paper provides a brief overview of the novel Meat Factory Cell and discusses its concept in the context of increasing sustainability in the meat sector. Job quality, environment, health risks, industrial development and education are discussed as sustainability goals that can be mapped against some of the United Nations Sustainable Development Goals (SDG). Technology can arguably help to improve related processes on a societal level, and to achieve the SDGs.
