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The main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).

A case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.

The maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.

Summary Reliability techniques in the widest sense may be applied to a diverse range of corporate activities, in order to predict the possibility of a successful outcome. The techniques could, for example, be applied to a series of commercial transactions, to a new marketing venture, or to research management. The outcome of any activity is sensitive to the configuration of the system producing it, and the probability of success may therefore be influenced by restructuring that system.

In the recent past, mobile technologies that track the movement of people, freight and vehicles have evolved rapidly. The major categories of such technologies are reviewed and a number of attributes for classification are proposed. The willingness of people to engage in such technologically based surveys and the reported biases in the make-up of the sample obtained are reviewed. Lessons are drawn about the nature of the samples that can be achieved and the representativeness of such samples is discussed. Data processing is addressed, particularly in terms of the processing requirements for logged data, where additional travel characteristics required for travel analysis may need to be imputed. Another issue explored is the reliability of data entered by respondents in interactive devices and concerns that may arise in processing data collected in real time for prompting or interrogating respondents. Differences, in relation to the data user, between data from mobile devices and data from conventional self-report surveys are discussed. Potentials that may exist for changes in modelling from using such data are explored. Conclusions are drawn about the usefulness and limitations of mobile technologies to collect and process data. The extent to which such mobile technologies may be used in future, either to supplement or replace conventional methods of data collection, is discussed along with the readiness of the technology for today and the advances that may be expected in the short and medium term from this form of technology.

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

The goals of this review are to identify key theories, constructs and themes in the international business travel (IBT) literature and to propose a model based on findings, theories and constructs drawn from adjacent research literature.

The authors reviewed the business travel (BT) literature to identify conceptual and empirical articles on IBT published from 1990 to 2022. Only 53 publications were suitable for review. The authors reviewed them using an open coding system.

The IBT literature is dispersed across several disciplines that use different methods, focus on different aspects of travel and emphasize different positive and negative outcomes that IBT engenders. The publications employed a diverse range of methods, including review and conceptual (11), quantitative (28) and qualitative methods (14). The samples were diverse in country, age, marital status and tenure. Many publications were descriptive and exploratory. The few that based their research on theory focused on two stress theories: Job Demands-Resources (JD-R) theory and conservation of resources (COR) theory.

Experimental and longitudinal designs are needed to reduce the causal ambiguity of this body of mostly correlational and cross-sectional research. The authors discuss the impact of emerging advances in virtual global communication technology on the future of IBT.

More research is needed on positive aspects of IBT. Human resource (HR) people should be aware of these issues and are encouraged to decrease the deleterious aspects of the international trips and increase the positive ones.

Increasing well-being of international business travelers is important for the travelers, their families and the organization.

This is the first IBT review focused on the theoretical underpinnings of research in the field. The authors offer a model for IBT and introduce adjustment and performance as important constructs in IBT research. The authors encompass crossover theory to add the reciprocal impact of travelers and spouses and label IBT a “double-edge sword” because it arouses both positive and negative outcomes.

Commonly studied hunter-gatherer traits, such as grouping and sharing, may require special attention when self-selection introduces bias into typical analyses. We therefore re-examine forager sociality by asking a series of nested questions: (1) To what extent are foraging groups random samples from the larger population? (2) What social and economic factors might explain the composition of foraging groups? (3) If certain groups of individuals preferentially forage together, do these same groups also preferentially share with each other when resident at their permanent settlement? (4) To what extent can we understand behavior in the foraging context without consideration of other contexts in which individuals live and work, and vice versa? Among the Ache of Paraguay, we show that foraging treks are not representative of the larger population, individuals vary in the kinds of treks in which they participate, and those who tend to share together at the reservation are more likely to forage together on trek.

Travel counseling and recommender systems on the Internet have not yet become smart enough to fulfill the elementary functions a fastidious consumer may expect. The EU‐funded project named DieToRecs (http://dietorecs.itc.it/) aims at improving recommender system functionality by incorporating relevant findings from tourist behavior research. The computational intelligence needed to optimize the user‐system encounter greatly depends on how far the user has advanced in his travel decision process. This report elaborates the levels of counseling intelligence, explores the basic marketing paradigm of matching the products/services desired and offered, and ponders on the consequences for devising a recommender or counseling system capable of learning.

This paper reports on an investigation of the integration of symbolic computation and reasoning into highly computerized numerically‐based realtime control systems for complex plant process management. This is the natural next step in an evolving maturation of the use of computers for automated monitoring and control of continuous processes. A particular implementation involving nuclear power plant intelligent monitoring is being developed from which overall principles and specifications can be distilled, ultimately leading to a general methodology that can be applied to other continuous plant processes.

Introduces the fourth and final chapter of the ISEF 1999 Proceedings by stating electric and magnetic fields are influenced, in a reciprocal way, by thermal and mechanical fields. Looks at the coupling of fields in a device or a system as a prescribed effect. Points out that there are 12 contributions included ‐ covering magnetic levitation or induction heating, superconducting devices and possible effects to the human body due to electric impressed fields.