The effect of nonconformities encountered in the use of technology on the occurrence of collision, contact and grounding accidents

Technology and its innovative applications make life easier and reduce the workload on seafarers. Today's ship bridges have much more modern and integrated navigation systems than before, and the ship's handling and management have become much easier. However, nonconformities encountered in the use of technological devices may cause accidents. In this study, the effect of human factor related errors associated with the use of the bridge's electronic navigational devices on grounding and collision-contact accidents was investigated. Non-conformities obtained from 175 collision-contact and 115 grounding accident reports were qualitatively analysed by means of human factor analysis and a classification system. Afterwards, relationships between nonconformities and their probabilities were evaluated quantitatively via a Bayesian network method. As a result of the study, the accident network was revealed. This accident network summarizes how operating errors in the use of technological equipment cause accidents. Recommendations on the prevention of accidents caused by operating errors associated with the use of new technologies are finally given

HACCP plan fresh fish processing Marituna

In the past regulatory authorities for food products had a duty to ensure that foods offered tothe consumer are at least safe to eat. The authorities required a positive approach of using Good Manufacturing Practices (GMP), producing food in a hygienic manner, and by inspection of finished product. It is now realised that inspection of finished product gives a poor control over the safety of foods. Therefore, since 1 January 1993, regulatory authorities in Europe required that companies take a preventative approach to safety based on the principles of Hazard Analysis and Critical Control Points (HACCP). Anyone exporting fish products to Europe or North America will have to implement a programme based on HACCP. If a company cannot demonstrate to the satisfaction of regulating agencies in importing countries that it has an effective programme operating in their processing plant, importers will not be permitted to accept the products. The United Nations food standard group Codex Alimentarius Commission has recommended HACCP's adoption as a system for ensuring the safety of foods (including finfish and shellfish) and the prevention of foodborne diseases

The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey

Driver models play a vital role in developing and verifying autonomous vehicles (AVs). Previously, they are mainly applied in traffic flow simulation to model realistic driver behavior. With the development of AVs, driver models attract much attention again due to their potential contributions to AV certification. The simulation-based testing method is considered an effective measure to accelerate AV testing due to its safe and efficient characteristics. Nonetheless, realistic driver models are prerequisites for valid simulation results. Additionally, an AV is assumed to be at least as safe as a careful and competent driver. Therefore, driver models are inevitable for AV safety assessment. However, no comparison or discussion of driver models is available regarding their utility to AVs in the last five years despite their necessities in the release of AVs. This motivates us to present a comprehensive survey of driver models in the paper and compare their applicability. Requirements for driver models in terms of their application to AV safety assessment are discussed. A summary of driver models for simulation-based testing and AV certification is provided. Evaluation metrics are defined to compare their strength and weakness. Finally, an architecture for a careful and competent driver model is proposed. Challenges and future work are elaborated. This study gives related researchers especially regulators an overview and helps them to define appropriate driver models for AVs

Cybersecurity of Agricultural Machinery: Exploring Cybersecurity Risks and Solutions for Secure Agricultural Machines

Modern agriculture is reliant on agricultural machinery for the production of food, fuel, and other agricultural products. The need for producing large quantities of quality agricultural products while sustainably stewarding environmental resources has led to the integration of numerous digital technologies into modern agricultural machinery, such as the CAN bus and telematic control units (Liu et al., 2021). An unintended drawback of these integrated digital technologies is the opportunity for these components to become cyberattack vectors. Cyberattack instances have increasingly targeted critical infrastructures, with numerous reports from agencies such as the Federal Bureau of Investigation (FBI) and Department of Homeland Security (DHS) warning of the significance of cyberattacks targeting the agricultural infrastructure specifically (Boghossian et al., 2018; Federal Bureau of Investigation, 2021; Federal Bureau of Investigation, 2022). Agricultural machinery, which is included in the agricultural infrastructure, has the potential to be targeted by cyberattacks, although the impacts are not well quantified or understood. This project demonstrates a hypothetical case study, where cyberattacks targeting in-season side-dress nitrogen application to corn could cause as much as $100 or more in profit loss per acre. Literature discussing practical cybersecurity solutions for agricultural machinery from both industry and academic institutions is absent, therefore two possible solutions were demonstrated in this project: modeling and the use of security testbeds. A four-step modeling methodology was developed and investigated as a solution in identifying the most security-critical areas of a machine. Two specific cyberattack scenarios were modeled to demonstrate the potential of the modeling methodology. A Security Testbed for Agricultural Vehicles and Environments (STAVE) was also developed as a useful solution for the identification of cybersecurity vulnerabilities to agricultural machinery (Freyhof et al., 2022). A replay attack and wireless signal recordings were performed to evaluate various components on STAVE. Advisor: Santosh K. Pitl