Risk Analysis Of Systems Research Articles

Signalling and responding to zoonotic threats using a One Health approach: a decade of the Zoonoses Structure in the Netherlands, 2011 to 2021.

In the Netherlands, the avian influenza outbreak in poultry in 2003 and the Q fever outbreak in dairy goats between 2007 and 2010 had severe consequences for public health. These outbreaks led to the establishment of an integrated human-veterinary risk analysis system for zoonoses, the Zoonoses Structure. The aim of the Zoonoses Structure is to signal, assess and control emerging zoonoses that may pose a risk to animal and/or human health in an integrated One Health approach. The Signalling Forum Zoonoses (SO-Z), the first step of the Zoonoses Structure, is a multidisciplinary committee composed of experts from the medical, veterinary, entomology and wildlife domains. The SO-Z shares relevant signals with professionals and has monthly meetings. Over the past 10 years (June 2011 to December 2021), 390 different signals of various zoonotic pathogens in animal reservoirs and humans have been assessed. Here, we describe the Zoonoses Structure with examples from signals and responses for four zoonotic events in the Netherlands (tularaemia, Brucella canis, West Nile virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)). This may serve as an example for other countries on how to collaborate in a One Health approach to signal and control emerging zoonoses.

Systemic risk and real economic activity: A South African insurance stress index of systemic risk

This study investigates the link between systemic risk in the South African insurance sector real economic activity in South Africa. To this end, we use six systemic risk measures, the Conditional Value at Risk (CoVaR), the Marginal Conditional Value at Risk (ΔCoVaR), the Comovement and Interconnectedness of the South African insurance sector (Eigen), the Dynamic Mixture Copula Marginal Expected Shortfall (DMC-MES), the Average Conditional Volatility (Ave-vol), and the South African Volatility Index (SAVI). We first evaluate the significance of each measure by assessing its ability to forecast future economic downturns in South Africa. We find that only two systemic risk measures possess the ability to predict future economic downturns in South Africa. We then use principal component quantile regression analysis to aggregate these measures into a composite stress index of systemic risk for the South African insurance sector and assess the ability of the proposed index to predict future economic downturns in South Africa. Our results reveal that the proposed index is a good predictor of future economic downturns in South Africa. Thus, our results suggest that regulators and risk managers must develop an analysis of systemic risk in the insurance sector with particular attention to its effects on real economic activity. In addition, our index can potentially be used as an instrument to monitor and mitigate systemic risk in the insurance sector in order to ensure the stability of the financial system and the economy in South Africa.

Optimization of Drought Limited Water Level and Operation Benefit Analysis of Large Reservoir

As an important water conservancy engineering project, reservoir regulation plays a crucial role in the insurance of water resources supply and demand balance and sustainable development and utilization, especially during drought seasons. The drought limited water level (DLWL) is the characteristic controlling water level of reservoir regulation operation during dry seasons, and the construction of reliable controlling schemes of DLWL is of great significance for the improvement of regional water resources utilization efficiency. Therefore, basing on the variation analysis of water inflowing series and water resources utilization characteristics among different sectors of Meishan Reservoir in Shihe Irrigation Area of China, firstly, the Hausdorff Dimensional Fractal (HDF) method was applied to divide drought early-warning periods of Meishan reservoir. Then, the initial scheme of DLWL of reservoir was determined through reservoir water inflow and water supply processes analysis during each drought warning periods of different typical hydrological years. And finally, the optimal dynamic controlling scheme of DLWL, described by drought warning water level (DWWL) and drought depleted water level (DDWL) respectively, was eventually proposed in this study based on the establishment of simulation and regulation model of reservoir and irrigation areas system. Moreover, the reliability and effectiveness of the proposed optimal controlling scheme of DLWL was further testified in terms of drought risk analysis of reservoir and irrigation area system under typical consecutive and annual drought scenarios, and meanwhile, the agricultural crop yield loss risk due to drought events corresponding to different controlling schemes of DLWL was also determined. The related research findings of this study could be favorable and beneficial for guiding drought-resistance regulation of reservoir and irrigation area system during drought seasons and providing reasonable decision-making basis of water resources utilization schemes as well.

Evaluation of effectiveness of the STAMP / STPA in risk analysis of autonomous ship systems

To ensure safety of Maritime Autonomous Surface Ships (MASS), the importance of risk assessment is emphasized in classification societies, but the assessment method is not specified, and standardization of the method is expected. In the risk analysis of conventional ship, we focus on equipment failure mainly on hardware, but in MASS, it is necessary to analyze not only hardware but also large-scale and complicated systems including software and human beings. STAMP / STPA is an analysis method for large-scale and complicated systems, and it may be applicable to MASS risk analysis. In this paper, we will verify the effectiveness of STAMP / STPA in the initial stage of MASS design and consider it from a certification point of view.

Advanced Risk Analysis for Biological Hazards in Greek PDO Food Products

The present research received fund from the Single State Action Aid for Research, Technological Development & Innovation «INVESTIGATE - CREATE – INNOVATE" project "Trust Trace" T1EDK-04028. Abstract Food safety is increasingly concern both consumers and public health authorities. Food safety management systems have been implemented in food industry in order to protect consumer’s health. Moreover, risk analysis strategies are usually included in food safety management plans. The aim of this study was to present and suggest an integrated system for risk analysis in food industry. Risk assessment combined with Next Generation Sequencing technology were performed. Greek food products which hold a PDO or PGI quality scheme (Avgotaracho Mesolonghiou and Vostizza currant) were selected as case studies because of their uniqueness and economic impact. From the results obtained, existing strategies were adequate in terms of Greek regulation for pathogens in foodstuff. However, NGS technique opens up possibilities to detect total microbiota of food products and minimize possible foodborne incidents. NGS analysis of Greek PDO products identified bacterial species ( Bacillus cereus and Acitenobacter Venetianus) that can provide managers extra information about potential consumers’ exposure to biological hazards. In conclusion, by advanced risk analysis, existing limitations regarding foodborne pathogens could be addressed. Therefore, this integrated risk analysis plan should be implemented in food industry in terms of food safety. Keywords: biological hazards, food industry, NGS, risk assessment, risk factors DOI: 10.7176/FSQM/117-05 Publication date: July 31 st 2022

Vyznachennia ta upravlinnia zahrozamy u strukturi derzhavnoi polityky zakhystu krytychnoi infrastruktury

The article analyses the theoretical approaches to the content of the concept of «critical infrastructure protection». It is determined that the key emphasis in most approaches is on the problems of threats and risks of their occurrence for critical objects. It is noted that the foundation of the scientific substantiation of the state policy of critical infrastructure protection should be formed on the basis of theoretical and methodological approaches to the detection and management of these categories. The greatest danger to the functioning of critical infrastructure in Ukraine is recognized as military threats and risks of emergencies at critical facilities. The analysis of scientific developments on identification of the definition of «critical infrastructure security risk» in the state protection policy is carried out. It is disclosed as the probability of an accident, danger, accident or catastrophe in the operation of critical infrastructure. Management takes place in conditions of uncertainty and the need to predict many alternative situations. It is emphasized that the variety of problems of critical infrastructure protection determines the need for systematic risk analysis in security management (risk analysis). Features of critical risk analysis are the analysis of potentially negative consequences arising from the failure of technical systems, failures or errors by personnel of the facility. Emphasis is placed on the component of «critical risk management» as the main component of the state policy of critical infrastructure security. This category is analysed from the standpoint of administration and management. The conclusion is made that it is necessary to supplement the state policy of critical infrastructure protection with «critical risk management». The result will be a stronger component of the protection of public and private critical facilities. It is determined that making managerial decisions within the proposed critical risk management is carried out in conditions of uncertainty. To solve such problems, it is proposed to use the theory of fuzzy logic as a means of modelling.

System and Risk Analysis of Cloud-Manufacturing System

The Cloud manufacturing(C-Mfg) system involves remote distributed manufacturing resources and capabilities collaborating as a single virtual entity. The system receives orders for custom products and provides manufacturing as a service to the end customers. The primary activities of the system, among others, are transaction control, resource allocation and monitoring, distributed manufacturing, quality control, and delivery of consignments to the customers. The actual manufacturing is done by a network of third-party partner manufacturers providing the services to end customers, helping them with cost reduction, shorter time-to-market, and enabling efficient collaboration between manufacturers in the CMfg network. This paper aims to deep dive into C-Mfg as a system and perform a risk analysis to assess and mitigate the risks associated with the system. While cybersecurity and data security-related concerns are deemed the most serious and need immediate management for the system to succeed, the control of data, compliance with manufacturing standards and guidelines, and lack of accountability and ownership are other serious risks that need significant attention. Identifying these factors will help channel the focus on the management and resolution of these risks to establish digital trust in the C-Mfg system leading to the system’s success.

Risk characterisation and methods of improving practice for municipal waste management in disaster situations: A case study in Qom Province, Iran.

Developing strategies to control environmental challenges and various aspects of health consequences of waste management is one of the major programs in metropolitan management. The main purpose of this study is to examine the level of preparedness, having a contingency plan and the emergency response ability to waste management in disaster situations. A descriptive study was designed in two phases: in the first phase of the study, composition, quantity and characteristics of municipal solid waste in the disaster were estimated, and by using DotMapper software, temporary waste sites for disaster situations (map waste) were determined. In the second phase of the study, the preliminary hazard analysis (PHA) to identify the initial events and risk analysis in the municipal waste management system was considered. Results show that more than 50% of the generated waste in the disaster is allocated to construction waste resulting from the destruction and more than 30% to recyclable items (metals, glass, plastic), and a very small part of about 1% of biodegradable waste was determined. Twenty points were designated as temporary sites for municipal waste in a disaster situation. Results of risk analysis in the disaster were described that for three events containing lack of temporary waste storage sites, lack of identification and determination of hazardous waste production centres and lack of waste management training programme in emergency situations were in the red range. Developing the necessary strategies to control environmental challenges and various aspects of health outcomes in waste management is one of the basic programmes in metropolitan management.

Probabilistic Risk Assessment in Space Launches Using Bayesian Network with Fuzzy Method

Space launch projects are extremely risky, and any equipment failure or human error may lead to disastrous consequences. Probabilistic risk assessment (PRA) is beneficial to qualitative analysis of risk, but it has not been paid enough attention in risk analysis for space launch systems (SLSs). Compared with most qualitative risk analysis in this field, this paper proposes a risk analysis framework based on Bayesian network (BN) with fuzzy method, which is suitable for probabilistic risk analysis of SLS. This method establishes a risk analysis model of SLS based on statistics and expert experience and reduces the uncertainty of the model by using fuzzy theory. By predicting the system risk probabilities, diagnosing the key risk causes, determining the risk conduction path, and performing a sensitivity analysis, the proposed risk analysis framework is aimed at alleviating this drawback to deal more effectively with the uncertainties in the field of space launches. A case study of space launches demonstrates and verifies the proposed method, and it also provides guidance for similar engineering projects.

An Internet of Things Sensor Array for Spatially and Temporally Resolved Indoor Climate Measurements.

The COVID-19 pandemic has emphasized the need for infection risk analysis and assessment of ventilation systems in indoor environments based on air quality criteria. In this context, simulations and direct measurements of CO2 concentrations as a proxy for exhaled air can help to shed light on potential aerosol pathways. While the former typically lack accurate boundary conditions as well as spatially and temporally resolved validation data, currently existing measurement systems often probe rooms in non-ideal, single locations. Addressing both of these issues, a large and flexible wireless array of 50 embedded sensor units is presented that provides indoor climate metrics with configurable spatial and temporal resolutions at a sensor response time of 20 s. Augmented by an anchorless self-localization capability, three-dimensional air quality maps are reconstructed up to a mean 3D Euclidean error of 0.21 m. Driven by resolution, ease of use, and fault tolerance requirements, the system has proven itself in day-to-day use at ETH Zurich, where topologically differing auditoria (at-grade, sloped) were investigated under real occupancy conditions. The corresponding results indicate significant spatial and temporal variations in the indoor climate rendering large sensor arrays essential for accurate room assessments. Even in well-ventilated auditoria, cleanout time constants exceeded 30 min.

Особливості управління ризиками у митній сфері

The article is devoted to the study of theoretical principles of risk management in customs sphere. In the customs sphere, the most common risks arise when declaring goods in the appropriate regimes - this allows to reduce duty rates or provide exemptions from taxation; when declaring an unreliable product code according to the UKG FEA, which is also an attempt to evade taxation. In addition, the source of risk may be the vehicle carrying the goods and the carrier who is responsible for transporting the goods from seller to buyer. The stages of occurrence of risks in the process of customs activity are determined, in particular risks during control of delivery of goods, risks arising during customs control and customs clearance of delivery, risks identified after customs clearance, risks during customs audit. The main tasks of the risk analysis and management system are to create a single information space that ensures the functioning of the risk analysis and management system, identifying the causes and conditions contributing to customs offenses, assessing the possibility of damage in case of potential risks and risks or minimizing them, as well as identifying the necessary resources and developing proposals for their optimal allocation, development and application of methods for assessing the effectiveness of measures taken, assessing the effectiveness of measures to analyze and manage risks and adjust management decisions. The main reasons that indicate the need to improve the customs clearance of goods belonging to risk groups for enterprises can be considered frequent delays in customs clearance of goods at customs due to the introduction of goods in the ASAUR system, unreasonable assignment of a code with a higher duty rate. goods and disregard for the basic rules of interpretation of UKG FEA, increase the efficiency of foreign economic activity of the enterprise. For subjects of foreign economic activity unified technology of customs clearance of goods at risk should include the following stages: formation of goals and objectives of technology of customs clearance of goods at risk, as well as appointment of persons responsible for its implementation, development, documentation of customs clearance of goods at risk risks, development of neutralization measures for risk groups, selection of the optimal technology of customs clearance of goods at risk and control of the main stages of the process.

Measuring systemic risk for bank credit networks: A multilayer approach

Systemic risk analysis has become a very important undertaking in most central banks after the Global Financial Crisis (GFC). This paper describes the Colombian credit system of banks and firms as a bipartite network of lenders and borrowers. To such network, we apply a spectral method to identify the most central actors, and a variant of the DebtRank algorithm to identify the banks and firms that would be the most vulnerable to shocks in the system, and the most impactful in propagating them. We perform our analysis with a multi-layer approach, analysing networks of loans in the Commercial, Housing, and Microcredit domain. Our analyses reveal a rich and heterogeneous systemic risk profile across the Colombian credit system, and highlight the presence of considerable network effects that would contribute to shape the propagation of shocks from the real economy to the banking system.

Systemic risk analysis and SIFI detection: Mechanisms and measurement

This paper introduces the relevance of systemic risk measurement in the financial system, and the related issue of identifying systemically important financial institutions (SIFIs), in an evolving regulatory framework. It goes on to perform a detailed review of systemic risk mechanisms (both in the short and medium run), highlighting the interaction between solvency and liquidity problems. The paper also discusses how systemic risk should be measured. Finally, the paper puts forward some high-level suggestions on the use of multi-layer network simulation to measure systemic risk.

A Novel Dynamic Approach for Risk Analysis and Simulation Using Multi-Agents Model

Static risk analysis techniques (SRATs) use event graphs and risk analysis assessment models. Those techniques are not time-based techniques and hence are inadequate to model dynamic stochastic systems. This paper proposes a novel dynamic approach to model such stochastic systems using Dynamic Fault Trees (DFT). The proposed model is called Generic Dynamic Agent-Based Model (GDABM) for risk analysis. GDABM is built on top of the well-known Agent-Based Modeling and Simulation (ABMS) technique. GDABM can model the dynamic system agents in both nominal (failure-free) and degraded (failure) modes. GDABM shows the propagation of failure between system elements and provides complete information about the system’s configurations. In this paper, a complete detailed case study is provided to show the GDABM capabilities to model and study the risk analysis for such dynamic systems. In the case study, the GDABM models the risk analysis for a chemical reactor/operator and performs a complete risk analysis for the entire system. The GDABM managed to simulate the dynamic behavior of the system’s components successfully using Repast Simphony 2.0. Detailed agent behavioral modes and failure modes are provided with various scenarios, including different time stamps. The proposed GDABM is compared to a reference model. The reference model is referred to as the ABM model. GDABM has given very promising results. A comparison study was performed on three performance measures. The performance measures used are (1) Accuracy, (2) response time, and (3) execution time. GDABM has outperformed the reference model by 15% in terms of accuracy and by 27% in terms of response time. GDABM incurs a slightly higher execution time (13%) when compared to the ABM reference model. It can be concluded that GDABM can deliver accepted performance in terms of accuracy and response time without incurring much processing overhead.

Marketing System Construction and Risk Analysis Based on Random Forest of Machine Learning

This paper analyses the innovative marketing model of enterprises in the new era from the perspective of the characteristics of enterprises and the problems of innovative marketing strategies and puts forward solution strategies and suggestions to provide reference for enterprises to get faster and better development in the new era. Based on the connotation of credit in the random forest, this paper follows the principles of science, standardization, fairness, and objectivity, draws on various credit factor analysis methods and famous credit scoring systems (such as FICO and Sesame Credit), closely links with relevant government and enterprise policy documents, combines with the actual situation of enterprise market, and finally builds a credit factor from three aspects of enterprise market: foundation, marketing, and monopoly. The credit index system consists of 3 primary indicators, 10 secondary indicators, and 22 tertiary indicators.

Financial Resilience and Financial Reliability for Systemic Risk Assessment of Electricity Markets With High-Penetration Renewables

Over the past 20 years, the rapid integration of renewable energy has resulted in electricity markets that are increasingly complex, interconnected, and uncertain. Similar to the banking system's financial crisis in 2008 due to chained reactions, severe financial losses due to uncertainty at a large renewable farm could induce significant financial losses at other market participants. The spread of such financial shocks can be worsened by centralized market clearing, and systemic risks consequently germinate in electricity market operations. Therefore, our previous work has compared <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">systemic</i> risk with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">systematic</i> risk in the electricity market with uncertainties. However, the scope of our previous work has been limited to risk indices. This paper aims to broaden the study by proposing the theoretical foundation of systemic risk analysis in electricity markets with uncertainties. First, an electricity market financial network is defined to describe the cash inflow/outflow of all participants, and the financial contagion is employed to model the interlinks between different entities. Then, two financial properties, financial resilience and financial reliability, are proposed to evaluate the systemic risk in market settlements with uncertainties. Finally, the proposed theoretical foundation of systemic risk is demonstrated on the Texas synthetic 2000-bus system with 70% renewable penetration.

Data-Driven Intelligent Risk System in the Process of Financial Audit

Financial auditing is an important part of government control, and monitoring the risks of the financial system helps maintain the stability of a country’s financial system. This paper aims to study the operation of data-driven intelligent risk analysis system in the process of financial auditing. When the risk level of the financial system reaches a certain warning point, it needs to be adjusted, conduct strict audits on high-risk institutions, strengthen cooperation with financial audit institutions, and make them more systematic. Risk control within a reasonable range will neither have a significant impact on the financial system nor increase the impact on the industry. This paper proposes to integrate the internal and establish an internal control system for the financial system.. If the internal control of the financial system cannot be sustained, financial innovation will cause great damage to financial institutions if the compensation is not good. Especially in terms of access strategy, it has made a strong contribution to economic innovation. The experimental data in this paper show that more than 25% of data-driven intelligent risk analysis systems have begun to be used in the process of financial auditing. At the same time, its utilization rate is significantly increasing with the development of technology. This paper introduces the relevant content of financial auditing, analyzes the auditing systems in different fields, integrates resources, taps on multisectoral needs, establishes a cross-departmental governance system, and improves financial stability and the efficiency of a wide range of social services.

A Risk Curtailment Strategy for Solar PV-Battery Integrated Competitive Power System

Power system networks are becoming more complex and decentralized with the foreword of deregulation in the global power sector. In this scenario, an independent system operator (ISO) is responsible for determining the appropriate actions to deliver stable and quality power to the customers connected to the network at the lowest cost without violating the system security limits. Violations of any security limit may result in system risk. The unstable and non-reliable system always has some drawbacks and is not desirable from the consumer’s point of view. A deregulated power market always keeps the consumer on the advantage side by giving stable, reliable, and less costly power. By using risk assessment tools, we identify the fault conditions and we try to minimize the risk by various uses of sequential programming methods. In this paper, a novel power system risk analysis and congestion management approach are introduced with considering meta-heuristic algorithms i.e., Slime Mould Algorithm (SMA) and Artificial Bee Colony Algorithm (ABC) in renewable energy integrated electricity market. The proposed power system risk analysis is constructed with the help of two risk valuation tools named Conditional-Value-at-risk (CVaR) and Value-at-risk (VaR). The higher negative value of VaR and CVaR represents the higher risk system and lower negative value or towards a positive value of VaR and CVaR denotes the less risk or stable system. The projected method has been experienced on the IEEE 14-bus test system and IEEE 30-bus test system to examine the usefulness of the meta-heuristic algorithm in system risk analysis under the deregulated environment. The importance of renewable energy integration in system risk curtailment has also been depicted in this work: basically, to measure the system’s risk, hence enhancing the system’s reliability and societal welfare. As a result, it will benefit both supply and demand-side participants.

Dynamic Control of Water Level in Flood Limited Reservoir Based on Intelligent Calculation

Determining the flood-limited water level is the focus of the contradiction between flood control and profit-making. The dynamic control of the flood-limited water level of the reservoir is an effective way to ensure flood control safety and realize flood resource utilization. Based on the analysis of the availability of forecast information, this paper conducts a study on the dynamic control of the flood-limited water level in Panjiakou Reservoir. The dynamic control area of Panjiakou Reservoir is determined by the “predischarge capacity constraint method.” On the premise of satisfying the flood control safety of the reservoir, the “prestorage and predischarge method” is adopted according to the real-time forecast information, the water conditions, work conditions, disaster conditions, etc. to develop a dynamic control plan for the flood-limited water level in the main flood season of the reservoir. Finally, based on the improved first-order second moment method (AFOSM), the dispatch risk model of the dynamic control of the flood-limited water level of the reservoir is constructed, and the risk analysis of the flood forecasting system is carried out. The results show that (1) the flood forecast accuracy of Panjiakou Reservoir conforms to the standard of the B-level forecasting scheme, and the results can be applied under the condition of considering the forecast error; (2) it is suggested that the maximum water level of the Panjiakou Reservoir in the main flood season is dynamically controlled to be 218 m. In the case of water supply guarantee rate P = 75 % , compared with the current situation of the flood-limited water level of 216 m, the water supply is increased by 40 million m3, and the flow of electricity is increased by 30 million. The flood control risk rate under the rain leakage error is lower than 0.1, which is the minimum risk level, which is acceptable. However, when the net rain leakage error is greater than 25 mm, there may be insufficient leakage or excessive leakage, which will cause inconvenience to downstream flood control.

Application of FRAM to perform Risk Analysis of the Introduction of a Data Glove to Assembly Tasks

• Introducing data glove to assembly system in realistic case studies • Analyzing the occupational health and safety (OHS) and operational risks of the use of data gloves in assembly through the application of FRAM • Categorizing risks from the perspective of FRAM • Discussing results of the application of FRAM in manufacturing in the context of industry 4.0 The manufacturing sector is an increasingly complex operational structure. This complexity is compounded when a new technology is introduced. In the context of industry 4.0, the development of new technologies and their introduction into assembly lines will lead to emerging and new occupational health and safety (OHS) and operational risks. In this study, these risks will be assessed using the Functional Resonance Analysis Method (FRAM) on realistic case studies to provide insight into OHS and the operational risks posed by the introduction of a data glove to an assembly system. FRAM presents components of the system as human, organizational and technological functions whose interactions might lead to a risk for the system. Findings show that FRAM is an appropriate method for risk analysis of such complex systems and provides a prospective approach to design an assembly 4.0 system that interacts with a data glove. However, FRAM provides less precise and detailed results in a proactive analysis than in a reactive analysis.