Co-evolution of Information Systems in Fast-Growing Small Firms

The paper examines the co-evolution of different dimensions of information systems for a sample of fast-growing small firms. The investigation uses primary source longitudinal empirical evidence. The data are taken from a large database on the lifecycle experience of one-hundred-and-fifty new business starts over a four-year period. They were collected by face to face interviews with owner-managers of small entrepreneurial firms. Interviews were conducted using an administered questionnaire that covered the agenda of markets, finance, costs, business strategy, the development of a management information system, human capital, organisation and technical change. This work uses primarily the data on management information systems. The basic approach used is to compare the attributes of the fastest and slowest paced firms, as identified by their growth rates. We then examine the evolution of these firms' management information systems. The measures used to identify changes in systems include: capital investment techniques, such as return on investment, residual income, net present value, internal rate of return and payback period; methods for managing costs, like just-in-time management, activity-based costing, quantitative risk analysis, value analysis, strategic pricing and transfer pricing; and using computer applications for storing information, project appraisal, financial modelling, forecasting and sensitivity analysis. 'Time lines' are graphed to show the points at which various features of information systems are introduced (e.g. data storage, forecasting, sensitivity analysis), and derived techniques (e.g. ROI, ABC) implemented. Firms are dichotomised into highgrowth and low-growth groups. Comparisons are made within firms and across firms in terms of the co-evolution of different aspects of their accounting information systems

Data Requirements to Enable PHM for Liquid Hydrogen Storage Systems from a Risk Assessment Perspective

Quantitative Risk Assessment (QRA) aids the development of risk-informed safety codes and standards which are employed to reduce risk in a variety of complex technologies, such as hydrogen systems. Currently, the lack of reliability data limits the use of QRAs for fueling stations equipped with bulk liquid hydrogen storage systems. In turn, this hinders the ability to develop the necessary rigorous safety codes and standards to allow worldwide deployment of these stations. Prognostics and Health Management (PHM) and the analysis of condition-monitoring data emerge as an alternative to support risk assessment methods. Through the QRA-based analysis of a liquid hydrogen storage system, the core elements for the design of a data-driven PHM framework are addressed from a risk perspective. This work focuses on identifying the data collection requirements to strengthen current risk analyses and enable data-driven approaches to improve the safety and risk assessment of a liquid hydrogen fueling infrastructure

Reliability Analysis Approach For Operations Planning Of Hydropower Systems

Many existing hydropower storage facilities were built decades ago and components of these aging infrastructure facilities have higher risk of failure. Insufficient capacity or forced outages of the spillway and other waterway passage facilities during flooding incident could potentially increase the probability of dam safety incidents leading to public safety concerns. Currently approaches used to assess the risk and uncertainty in operational decision making are mainly based on qualitative assessment and expert judgment and can be significantly improved by the development of a framework that formally incorporates both qualitative and quantitative reliability analysis methods. Event tree analysis and fault tree analysis have traditionally been used in dam safety risk analysis, with results subject to data adequacy and availability. Our research shows that other methods, such as nonparametric analysis and Monte Carlo simulation techniques can yield good results as well. This study investigated the application of reliability analysis methods to existing hydropower storage facilities, with the objective of developing a new systems engineering based approach for risk and uncertainty analysis to assess and manage the risks of hydropower system operations. Our approach integrates reliability-based methods with hydro system optimization modeling to develop an operational reliability-based modeling framework and to formally treat risk and uncertainty in operations planning. This approach incorporates different sources of uncertainty that are typically encountered in operations planning of these systems, including failure probability of hydro system components such as non-power release structures and turbine facilities. This paper presents the framework we have developed and illustrates the application of our investigation for a hydropower system facility in British Columbia, Canada

Quantitative risk assessment on a hydrogen refuelling station

The Directive 2014/94/UE (DAFI, Alternative Fuel Initiative Directive) on the deployment of alternative fuels (i.e. hydrogen) infrastructures has been recently transposed into national law in Italy. Consequently, the technical regulation on fire prevention for H2fuelling stations has been updated, in order to consider the current maximum delivery pressure (700 bar) of gaseous hydrogen for road vehicles. This technical regulation establishes the prescriptive safety distance from a piece of equipment. In the case of a new station, an assessment of the frequency of the event and its potential consequences is necessary. This is to understand which risk can reasonably be mitigated by a safety distance or whether additional mitigation or prevention measures should be taken. This paper presents the quantitative risk assessment (QRA) study on a hydrogen station planned to be installed, study which aims at determining the safety distances. Such study utilizes the Sandia-developed QRA tool, Hydrogen Risk Analysis Model (HyRAM), to calculate risk values when developing risk-equivalent plans. HyRAM combines reduced order deterministic models that characterize hydrogen release and flame behavior with probabilistic risk models to quantify risk values. Thanks to HyRAM tool it is possible to estimate physical effects and consequences on people and structures and plants, related to risk scenarios, by means of a damage model library. Use of risk assessment may allow station owners and designers to flexibly define station-specific mitigations, with the purpose of achieving equal or better levels of safety with respect to prescriptive recommendation levels, as suggested by ISO19880-1 (2018)

A Dynamic Quantitative Microbial Risk Assessment for Norovirus in Potable Reuse System

This study describes the results of a dynamic quantitative microbial risk assessment (QMRA) for norovirus (NoV) that was used to evaluate the relative significance of foodborne, person-to-person, and person-to-sewage-to-person transmission pathways. This last pathway was incorporated into simulated potable reuse systems to evaluate the adequacy of typical treatment trains, operational conditions, and regulatory frameworks. The results confirm that secondary and foodborne transmission dominate the overall risk calculation and that waterborne NoV likely contributes no appreciable public health risk, at least in the scenarios modeled in this study. De facto reuse with an environmental buffer storage time of at least 30 days was comparable or even superior to direct potable reuse (DPR) when compound failures during advanced treatment were considered in the model. Except during these low-probability failure events, DPR generally remained below the 10−4 annual risk benchmark for drinking water. Based on system feedback and the time-dependent pathogen load to the community\u27s raw sewage, this model estimated median raw wastewater NoV concentrations of 107–108 genome copies per liter (gc/L), which is consistent with high-end estimates in recent literature

Expert-based development of a standard in CO2 sequestration monitoring technology

Bureau of Economic Geolog

Functional foods : a conceptual model for assessing their safety and effectiveness

This report shows that the product-diet dilemma can be solved by developing a predictive model. The model integrates food intake data, dynamic consumption patterns and the production chain model and combines them with a risk-benefit approach

The public health risk posed by Listeria monocytogenes in frozen fruit and vegetables including herbs, blanched during processing

A multi-country outbreak ofListeria monocytogenesST6 linked to blanched frozen vegetables (bfV)took place in the EU (2015–2018). Evidence of food-borne outbreaks shows thatL. monocytogenesisthe most relevant pathogen associated with bfV. The probability of illness per serving of uncooked bfV,for the elderly (65–74 years old) population, is up to 3,600 times greater than cooked bfV and verylikely lower than any of the evaluated ready-to-eat food categories. The main factors affectingcontamination and growth ofL. monocytogenesin bfV during processing are the hygiene of the rawmaterials and process water; the hygienic conditions of the food processing environment (FPE); andthe time/Temperature (t/T) combinations used for storage and processing (e.g. blanching, cooling).Relevant factors after processing are the intrinsic characteristics of the bfV, the t/T combinations usedfor thawing and storage and subsequent cooking conditions, unless eaten uncooked. Analysis of thepossible control options suggests that application of a complete HACCP plan is either not possible orwould not further enhance food safety. Instead, specific prerequisite programmes (PRP) andoperational PRP activities should be applied such as cleaning and disinfection of the FPE, water control,t/T control and product information and consumer awareness. The occurrence of low levels ofL. monocytogenesat the end of the production process (e.g.<10 CFU/g) would be compatible with thelimit of 100 CFU/g at the moment of consumption if any labelling recommendations are strictly followed(i.e. 24 h at 5°C). Under reasonably foreseeable conditions of use (i.e. 48 h at 12°C),L. monocytogeneslevels need to be considerably lower (not detected in 25 g). Routine monitoring programmes forL. monocytogenesshould be designed following a risk-based approach and regularly revised based ontrend analysis, being FPE monitoring a key activity in the frozen vegetable industry