Conceptual and formal models of the monitoring of laboratory analytical techniques

Este trabajo presenta la conceptualización y la representación formal de los conocimientos que utiliza un técnico experto en la monitorización del desarrollo de un protocolo químico experimental. Se obtuvieron los modelos conceptuales de los conocimientos que emplea el experto, se documentaron en forma gráfica y se obtuvo el Mapa de Conocimientos de la tarea que realiza el experto. La formalización del modelo conceptual de cono - cimientos se realizó mediante un modelo híbrido de marcos con sistemas de producción. En conclusión, la conceptualización de los conocimientos y la formalización logradas son bastante completas y profundas.This paper presents the conceptualization and the formal representation of the knowledge applied by a technical expert when monitoring the development of a chemical experimental protocol. The conceptual knowledge models applied by the expert were obtained and graphically documented. In addition, the Knowledge Map of the task performed by the expert was obtained. The formalization of the conceptual knowledge model was carried out by means of a hybrid model of frames and production-systems. In conclusion, the knowledge conceptualization and formalization achieved are quite detailed and thorough.Fil: Lima, Julio. Universidad Nacional de Luján; Argentina. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Angiorama, Marina. Universidad del Centro Educativo Latinoamericano; Argentina. Universidad Tecnologica Nacional; ArgentinaFil: Roda, Fernando. Universidad del Centro Educativo Latinoamericano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ybalo, Carolina. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Patti, Miguel. Universidad del Centro Educativo Latinoamericano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Salvia, Romina. Universidad del Centro Educativo Latinoamericano; Argentin

A Design Science Research Methodology for Expert Systems Development

The knowledge of design science research (DSR) can have applications for improving expert systems (ES) development research. Although significant progress of utilising DSR has been observed in particular information systems design – such as decision support systems (DSS) studies – only rare attempts can be found in the ES design literature. Therefore, the aim of this study is to investigate the use of DSR for ES design. First, we explore the ES development literature to reveal the presence of DSR as a research methodology. For this, we select relevant literature criteria and apply a qualitative content analysis in order to generate themes inductively to match the DSR components. Second, utilising the findings of the comparison, we determine a new DSR approach for designing a specific ES that is guided by another result – the findings of a content analysis of examination scripts in Mathematics. The specific ES artefact for a case demonstration is designed for addressing the requirement of a ‘wicked’ problem in that the key purpose is to assist human assessors when evaluating multi-step question (MSQ) solutions. It is anticipated that the proposed design knowledge, in terms of both problem class and functions of ES artefacts, will help ES designers and researchers to address similar issues for designing information system solutions

Data-driven offline learning approach for excavating control of cutter suction dredgers

Cutter suction dredgers (CSDs) play a very important role in the construction of ports, waterways and navigational channels. Currently, most of CSDs are mainly manipulated by human operators, and a large amount of instrument data needs to be monitored in real time in case of unforeseen accidents. In order to reduce the heavy workload of the operators, we propose a data-driven offline learning approach, named Preprocessing-Prediction-Learning Control (PPLC), for obtaining the optimal control policy of the excavating operation of CSDs. The proposed framework consists of three modules, i.e., a data preprocessing module, a dynamics prediction module realized by a Convolutional Neural Network (CNN), and a deep reinforcement learning based control module. The first module is responsible for filtering out irrelevant variables through correlation analysis and dimensionality reduction of raw data. The second module works as a state transition function that provides the dynamics prediction of the excavating operation of a CSD. To realize the learning control, the third module employs the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm to control the swing speed during the excavating operation. The simulation results show that the proposed framework can provide an effective and reliable solution to the automated excavating control of a CSD

A review of the Digital Twin technology for fault detection in buildings

publishedVersio

Data-driven Bayesian network for risk analysis of global maritime accidents

Maritime risk research often suffers from insufficient data for accurate prediction and analysis. This paper aims to conduct a new risk analysis by incorporating the latest maritime accident data into a Bayesian network (BN) model to analyze the key risk influential factors (RIFs) in the maritime sector. It makes important contributions in terms of a novel maritime accident database, new RIFs, findings, and implications. More specifically, the latest maritime accident data from 2017 to 2021 is collected from both the Global Integrated Shipping Information System (GISIS) and Lloyd’s Register Fairplay (LRF) databases. Based on the new dataset, 23 RIFs are identified, involving both dynamic and static risk factors. With these developments, new findings and implications are revealed beyond the state-of-the-art of maritime risk analysis. For instance, the research results show ship type, ship operation, voyage segment, deadweight, length, and power are among the most influencing factors. The new BN-based risk model offers reliable and accurate risk prediction results, evident by its prediction performance and scenario analysis. It provides valuable insights into the development of rational accident prevention measures that could well fit the increasing demands of maritime safety in today’s complex shipping environment

Projektovanje, razvoj i implementacija ekspertskog sistema za brzu detekciju i izolaciju neželjenih stanja dinamičkih sistema

Rad je posvećen problemu rane i brze detekcije i izolacije neželjenih stanja dinamičkih sistema, sa posebnim naglaskom na rano otkrivanje različitih nepravilnosti u radu i kvarova industrijskih procesa.The thesys is dedicated to the problem of early and swift detection and isolation of unwanted working regimes of dynamical systems, with particular emphasis on the early detection of various irregularities and failures of industrial processes

Exploring the role of system operation modes in failure analysis in the context of first generation cyber-physical systems

Typically, emerging system failures have a strong impact on the performance of industrial systems as well as on the efficiency of their operational and servicing processes. Being aware of these, maintenance and repair researchers have developed multiple failure detection and diagnosis techniques that allow early recognition of system or component failures and maintaining continuous system operation in a cost-effective way. However, these techniques have many deficiencies in the case of self-tuning first generation cyber-physical systems (1G-CPSs). The reason is that these systems compensate for the effects of emerging system failures until their resources are exhausted, and the compensatory actions not only mask the failures, but also make their recognition difficult. Late recognition of failures is however in contrast with the principles of preventive maintenance. Therefore, the promotion research concentrated on the issue of recognizing and forecasting failures under dynamic and adaptive behavior of 1G-CPSs. CPSs are enabled to compensate for failure symptoms by changing their system operation modes (SOMs). It was also observed that transitions of SOMs reduce the reliability of a signal-based failure diagnosis. It was hypothesized that the frequency and the duration of the changes of the operational states of the 1G-CPS may be strong indicators of the failure emergence phenomenon and that investigation of SOMs facilitates early detection of failures. Therefore, the completed exploratory studies were aimed at exploring how the frequency and duration of transitions of SOMs can be brought into correlation with specific types of failures, and how they can be computed as measures of failure occurrence. The obtained results revealed that system failures tend to induce unusual system operation modes that can be used as basis for failure characterization, and even for failure forecasting. The empirical research made use of a cyber-physical greenhouse testbed to get experimental data and was completed by the development of computational model. A failure injection strategy was implemented in order to induce failure occurrence in a controlled manner. The proposed approach can be applied as a basis of forecasting system failures of 1G-CPSs, but additional research seems to be necessary

An ethnographic exploration of ship - shore communication

Shore based monitoring, communication, coordination and management of vessel traffic in ports worldwide is a real world problem. Informed by ethnomethodological studies of work, this thesis explores the ordered in situ work of Vessel Traffic Service Operators (VTSOs); the coordination of vessel traffic; the fine grained artful performance and achievement of safe fairway navigation and the challenges faced by the VTS operators in the daily accomplishment of their institutional role. An important source of data in this ethnographic study is the naturally occurring interaction on the main working Very High Frequency (VHF) radio channel of the port, which helps explore institutional talk at work deployed to facilitate interaction, negotiation and the accomplishment of safe navigation. Three additional research techniques are utilised for data generation – observations, semi structured interviews and unstructured interviews. The case of a major Indian world port is utilised to explore the daily work of marine traffic coordination and the (pro)active interactional accomplishment of channel navigation. Research takes place against the dynamic backdrop of the harbour – a complex space with a myriad of social actors populating the scene – the VTS operators atop their tower; shipboard seafarers negotiating restricted waters; pilots rendering pilotage services; Dock Master commanding the station; seafarers aboard small local craft and lively fishermen who at times pepper the marine radio with colourful language. Two categories of findings emerge – port interaction order, institutional talk and the contingent practices that accomplish the safety/time critical work and the technological, organisational and social constraints that shape, affect and inform the work of the VTS operators. This study fills a gap in ethnomethodological studies of work with its focus on the VTS work site – a centre of coordination; it explores social order and contributes to the understanding of the local practical achievement of traffic coordination and channel navigation in restricted waters. It also contributes to our understanding of the constraints faced by the workers in the safety critical VTS work setting. Also discussed are the status of VTS operators and occupational hierarchy in the world port. The thick description of in situ VTS’ work informs maritime safety, particularly relevant in safety critical, congested and restricted sea areas