Design Expert System to Simulate Control System of Gas Generating Stations

The use of computer technology to support technical decisions and training is now widespread and pervasive across a broad range of technical areas. Accordingly, computer-aided diagnosis has become an increasingly important area for intelligent computational systems. The objective of project research is to design an expert system able to  provide the way to simulate the technical crew training , technical crew evaluating, testing of station parts, fault diagnosing of gas turbine power plant which uses natural gas to help the technical  maintenance crew and others trainees to reduce the error of the technical crew as minimum as possible and significantly reduce the cost of the training technical crew ,and  in same time can be applied this proposed system in all generating stations which work in ministry of electricity and private sector stations. The proposed system contains two main modules first one is the System Information and the second model is Expert system. Those two models creates our system simulators. The Information System of proposed system contains the static information about different malfunctions of the gas turbine power plant field which is used for training crews by showing pictures and videos about affected part of the station and giving the correct action,  and containing exam question for evaluating technical crew level to give the correct decision about them such as an increase training period of the crew,  and containing testing procedure steps of the station parts with given correct action to start  up  the station or wait according  to test result ,and containing fault diagnosing of the station with advice and required solution, and containing information related to monitoring and remote control the station with given correct action using visual Basic 6.0, and can make the prediction and warning  according to environment information and received parameters from station compared with the standard level which is stored in system and giving the required advice to protect the system from damage .The second model of proposed system is Expert system of which performs the program, so this system represents a computer program design to simulate human ability to solve the problem, and it consists of knowledge base which contain all knowledge and information which are collected from experts (engineers) about specific problems in specific domain and inference machine to search for knowledge base to find the solution of the problem in this restricted domain, this research clearly also  describes  how the  neural computing system designed to support the technical decision process to save the station from damage and continuously prepare good technical crew and develop their capability . The most prominent feature of our proposed system is simplicity, flexibility and friendly user interface with high speed of the execution. Keywords: Gas Turbine, Expert system, Simulation, power Generation, control Syste

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background: Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods: This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was coprioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low-middle-income countries. Results: In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of 'single-use' consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low-middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion: This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high- and low-middle-income countries