Measures Of System Effectiveness Research Articles

Trends in In-Hospital Mortality in Patients Admitted With Cardiovascular Diseases in the United States With Demographics and Risk Factors of All Cardiovascular In-Hospital Mortality: Analysis of the 2021 National Inpatient Sample Database.

Introduction and background Cardiovascular diseases (CVDs) encompass a range of disorders involving coronary artery diseases, valvular heart diseases, myocardial diseases, pericardial diseases, hypertensive heart diseases, heart failure (HF), and pulmonary artery diseases. Given the high prevalence of CVDs, understanding both overall and in-hospital mortality rates from these diseases is crucial. Unsurprisingly, most research, procedures, and new pharmacological interventions aim to reduce these rates. No recent studies have comprehensively detailed in-hospital mortality rates, demographics, and risk factors for all CVDs combined. Yet, in-hospital mortality rates due to CVD significantly impact patients' families and healthcare teams and serve as a critical measure of healthcare system development and effectiveness. Therefore, analyzing in-hospital mortality rates is essential for filling the gap in the recent comprehensive analysis of in-hospital mortality rates, demographics, and risk factors of all CVDs. Method The study used data from the National Inpatient Sample and the Nationwide Inpatient Sample (NIS) Databases of 2021 and HCUP tools. The NIS database extrapolates national estimates based on a stratified sample of 20% of US hospital discharges. Results were expressed as probability and relative risk using the t-test, with a P-value <0.05 being statistically significant. Statistical analyses were done using Stata statistical software version 18 (StataCorp LLC, College Station, TX, US). Results This study included 6,666,752 hospital admissions in the United States. Of these, 2,337,589 patients were admitted with CVDs and related symptoms, with 70,552 deaths occurring during hospitalization, resulting in an in-hospital mortality rate of 3.01% due to CVDs. Our study showed all CVD-induced in-hospital mortality combined was found to have a higher association with diabetes but a lower association with hypertension, hyperlipidemia, alcohol, and smoking. Conclusion The highest rates of cardiovascular disease in-hospital mortality are cardiac arrest, rupture of the cardiac wall as a complication of acute myocardial infarction, cardiogenic shock, rupture of papillary muscle as a complication of acute myocardial infarction, and rupture of chorda tendinea as a complication of acute myocardial infarction. The most common causes of CVD in-hospital mortality are non-ST-elevation myocardial infarction (NSTEMI) (19.20%), ST-elevation myocardial infarction (STEMI) (17.80%), cardiac arrest (15.10%), hypertensive heart disease with heart failure (12.50%), ventricular fibrillation (4.70%), ventricular tachycardia (3.30%), and aortic stenosis (2.10%). The most common risk factors for CVD in-hospital mortality are age, male gender, and diabetes. Proper diabetes control and management might be the highest preventive measure for all CVD-induced in-hospital mortality.

Framework for Measuring Relevancy in Discovery Environments

Institutional discovery environments now serve as central resource databases for researchers in the academic environment. Over the last several decades, there have been numerous discovery layer research inquiries centering primarily on user satisfaction measures of discovery system effectiveness. This study focuses on the creation of a largely automated method for evaluating discovery layer quality, utilizing the bibliographic sources from student research projects. Building on past research, the current study replaces a semiautomated Excel Fuzzy Lookup Add-In process witha fully scripted R-based approach, which employs the stringdist R package and applies the Jaro-Winkler distance metric as the matching evaluator. The researchers consider the error rate incurred by relying solely on an automated matching metric. They also use Open Refine for normalization processes and package the tools together on an OSF site for other institutions to use. Since the R-based approach does not require special processing or time and can be reproduced with minimal effort, it will allow future studies and users of our method to capture larger sample sizes, boosting validity. While the assessment process has been streamlined and shows promise, there remain issues in establishing solid connections between research paper bibliographies and discovery layer use. Subsequent research will focus on creating alternatives to paper titles as search proxies that better resemble genuine information-seeking behavior and comparing undergraduate and graduate student interactions within discovery environments.

Novel Analysis between Two-Unit Hot and Cold Standby Redundant Systems with Varied Demand

Decisive applications, such as control systems and aerial navigation, require a standby system to meet stringent safety, availability, and reliability. The paper evaluates the availability, reliability, and other measures of system effectiveness for two stochastic models in a symmetrical way with varying demand: Model 1 (a two-unit cold standby system) and Model 2 (a two-unit hot standby system). In Model 1, the standby unit needs to be activated before it may begin to function; in Model 2, the standby unit is always operational unless it fails. The current study demonstrates that the hot standby system is more expensive than the cold standby system under two circumstances: a decrease in demand or the hot standby unit’s failure rate exceeding a predetermined threshold. The cold standby system’s activation time is at most a certain threshold, and turning both units on at once is necessary to handle the increasing demand. In that case, the hot standby will be more expensive than the cold standby system. The authors used semi-Markov and regenerative point techniques to analyze both models. They collected actual data from a cable manufacturing plant to illustrate the findings. Plotting several graphs and obtaining cut-off points make it easier to choose the standby to employ.

Efficient computational stochastic framework for performance optimization of E-waste management plant

PurposeReliability and maintainability are the key system effectiveness measures in process and manufacturing industries, and treatment plants, especially in E-waste management plants. The present work is proposed with a motto to develop a stochastic framework for the e-waste management plant to optimize its availability integrated with reliability, availability, maintainability, and dependability (RAMD) measures and Markovian analysis to estimate the steady-state availability of the E-waste management plant. In the analysis an effort is also made to identify the best performing algorithm for availability optimization of the e-waste plant. MethodologyA stochastic model for a particular plant is developed and its availability is optimized using various metaheuristic approaches like a genetic algorithm (GA), particle swarm optimization (PSO), and differential evolutions (DE). The most sensitive component is identified using RAMD methodology while the effect of deviation in various failure and repair rates are observed by the proposed model. The failure and repair rates follow an exponential distribution. All time-dependent random variables are statistically independent. Originality/NoveltiesA novel stochastic model is presented for an e-waste management plant and optimum availability is obtained using metaheuristic approaches. The proposed methodology is not so far discussed in the reliability analysis of process industries. FindingsThe numerical results of the proposed model compared to identify the most efficient algorithm. It is observed that genetic algorithm provides the maximum value (0.92330969) of availability at a population size 2500 after 500 iterations. PSO algorithm attained the maximum value (0.99996744) of availability just after 50 iterations and 100 population size. So, its rate of convergence is faster than GA. The optimum value of availability is 0.99997 using differential evolution after 500 iterations and population size of more than 1000. These findings are very beneficial for system designers. Practical ImplicationsThe proposed methodology can be utilized to find the reliability measures of other process industries.

Closed Loop Airline Rotable Component Float Availability and Control: A Case Study

The research presented in this paper tests various approaches for modeling a typical airline closed-loop rotable spare parts supply system and their usability for real-life spare parts availability prediction and control. Unlike previous work published dealing with economic models and finding optimal stock levels, we focus on actual airline workshop and analyze its throughput. The paper presents the queue model simulation with a limited population of customers, limited system capacity, and unknown queuing discipline. Simulations are conducted by generating interarrival time and system time data (due to unknown service time), taking a number of variations in the stock size and average system time. The purpose of the simulations and the experiment is to test the effect of stock size on different measures of system effectiveness. The results show how the total number of spare parts interplays with the service level and how the retention time of the spare part in the workshop affects the required number of spare parts.

Analysis of Two Non-Identical Unit Cold Standby System in Presence of Prior Information

Characteristics of a two non-identical unit system with a cold standby facility are studied from Bayesian point of view with different type of priors assumed for unknown parameters. Time to failure and time to repair of the operating units are assumed to follow Lindley distribution. Several measures of system effectiveness, such as reliability, MTSF, steady state availability, expected profit etc. are obtained by using regenerative point technique. At the end, a numerical illustration is also carried out, for validation of the proposed system model.

Quality control for a detected an appropriate queue from K‐independent M/M/C/N queueing models

AbstractIn this paper, we consider a system of K‐independent Markovian queues such that each one of them has a Poisson arrival process and exponential service time. We assume that every server has some characteristics such as the speed of the service performance or the service cost. To find an appropriate queue, which meets customer needs for the service performance, we present a new approach that gives a suitable decision to choose an appropriate queue from our system. This allows the customer to deal with minimum cost and faster server under steady state. We solve an interesting discrete stochastic optimization problem where the paid cost by the customer is bounded by a Gaussian distribution. Using these hypotheses, we perform a simulation study by generating the paid cost random values and choosing the minimum value between them. This minimum cost gives the highest service rate, which is used to obtain the optimum values of the system effectiveness measures.

Emergency Response after Disaster Strikes: Agent-Based Simulation of Ambulances in New Windsor, NY

AbstractEmergency medical services (EMS) rely on a robust road network to respond to patient demand as quickly as possible. An important measure of system effectiveness during adverse scenarios, su...

Operational availability analysis of generators in steam turbine power plants

The main aim of this study is to explore the availability and profitability of generators, which are key units of steam turbine power plants, considering exponential failure and arbitrary repair time distributions. A Markov birth–death process and supplementary variable technique are used to evaluate system effectiveness measures. Such a generator mainly consists of seven repairable components arranged in a series configuration. A stochastic model of the generator is developed, and the Chapman–Kolmogorov differential difference equation of the system derived. Finally, the results for the steady-state availability and profitability of the system are obtained for a particular case that will be helpful to system designers to enhance the performance of plants to some extent.

Reliability analysis of communication network system with redundant relay station under partial and complete failure

The purpose of this paper is to study the performance of a communication network system consisting of a transmitter, two relay stations and a receiver arranged in series parallel. Through the transition diagram, the partial differential equations are derived, and Laplace transforms are then taken on these equations to derive system reliability, availability, the mean time to system failure (MTTF) and cost function. It is assumed that failure rates are constant and follows exponential distribution, repair rates of partial failure state are assumed to follow general distribution and complete failure states are repaired through Gumbel-Hougaard family copula. The system is analyzed through supplementary variable technique and Laplace transform. Different measures of testing system effectiveness which include reliability, availability, mean time to failure (MTTF) and profit function have been calculated for particular values of time, failure and repair rates. From the study, it is clear that time and failure rates of both transmitter, relay stations and receiver influence the reliability, availability, MTTF and profit function. Mathematical models developed in this paper can aid plant management for proper maintenance and system safety, avoiding incorrect reliability, availability and profit assessment and leading to inadequate maintenance decision making, which may result in unnecessary expenditures and reduction of safety standards.

An adaptive probabilistic mapping matrix search algorithm for vulnerability analysis of PPS

The paper presents an adaptive probabilistic mapping matrix search algorithm for adversary path planning and vulnerability analysis of physical protection system. The algorithm represents the adversary transition process as stochastic risk-taking path choice behaviors under uncertainties. The interactions among the protective elements are characterized by a full probabilistic mapping scheme of discretized Cell-to-Cell transitions across the area of physical protection for path planning analysis. Practice of the proposed algorithm is demonstrated with a hypothetical case of nuclear facility for risk-significant adversary path identification. The analysis results show that the method is capable of path search analysis for determining the system effectiveness measures.

Performance analysis of evaporation system in sugar industry using RAMD analysis

The main aim of this study is to analyze the application of reliability, availability, maintainability and dependability in identification of most sensitive subsystem of evaporation system in sugar plant. For this analysis, transition diagram of all subsystems is drawn and respective Chapman–Kolmogorov differential equations are derived using Markov birth–death process. All failure and repair rates of each subsystem are exponentially distributed. Various measures of system effectiveness like mean time between failures, mean time to repair and dependability ratio for all the three subsystems are also computed. Sensitivity analysis of system reliability is also performed. The reliability and maintainability are estimated at various time instants. Analysis of all the subsystems shows that sulphited syrup is highly sensitive from reliability point of view. The derived measures are shared with system designers for their active deliberation.

Reliability analysis of a rodding anode plant in aluminum industry with multiple units failure and single repairman

The paper presents reliability analysis of a rodding anode plant in aluminum industry with multiple unit failure and single repairman. Manufacturing process of raw aluminum blocks in this plant passes through eight stations. Failure of any of the stations brings the plant to a complete halt, except the butt & thimble removal press stations because of the parallel standby arrangement, and does not affect the system operation completely unless both the units fail. Six years of real maintenance data on component failures, repairs and associated costs are used in this analysis. Measures of system effectiveness is gauged through reliability indices such as mean time to plant failure, availability of the plant, busy period of repairman and expected number of repairs. Effect of repair rate, failure rate and repair cost on system performance w.r.t. revenue is shown graphically. Theory of Semi-Markov and regenerative stochastic processes is used in the analysis.

The role of trust in e-Government effectiveness, operational effectiveness and user satisfaction: Lessons from Saudi Arabia in e-G2B

Electronic government (e-Government) systems are becoming an essential strategic tool in the delivery of e-Government-to-Business services (e-G2B). The purpose of this research is to explore direct and indirect effects of trust in online services on the satisfaction of the e-Government service users and other perceptions such as e-G2B system effectiveness and the operational effectiveness of organizations. Based on a sample of e-G2B service users from Saudi Arabia, our preliminary findings suggest that the effects of trust on user satisfaction are mediated by e-G2B system effectiveness measures (e.g., System Quality, Service Quality, and Information Quality) and by operational effectiveness. In addition, we find that operational effectiveness and information quality are the most important drivers of user satisfaction. In contrast to previous research, our results show a negative relationship between trust in online services and service quality and suggest that this finding may have important implications for theory and practice.

Reliability modelling and study of failure mechanism of distillery plant using supplementary variable technique

In this paper, an attempt has made to study the failure mechanism of distillery plant through reliability modelling. This plant consists of three processing parts, namely Liquefaction, Fermentation and Distillation. These parts connected in series configuration and each part consists of different subsystems according to their working. The distribution of failure times of subsystems of distillery plant is taken as exponential, while the distribution of repair times of subsystems is considered as arbitrary. The differential-difference equations associated with the state changeover model of the distillery plant are derived using supplementary variable technique and these equations are solved to get state probabilities of the system model. The results for some measures of system effectiveness are obtained in steady state. The performance analysis of availability and profit of the distillery plant have been studied numerically through tables for a particular case.

Profit analysis of a computer system with preventive maintenance and priority subject to maximum operation and repair times

The aim of the present study is to carry out the profit analysis of a computer system by considering the concept of priority to preventive maintenance over different hardware and software repair activities. For this purpose, three stochastic models have been developed under different priority policies. A single repair facility is available to perform all repair activities. The hardware unit undergoes replacement after a pre-specific maximum repair time. The repairman performs the preventive maintenance of the whole system after a pre-fixed maximum operation time. All time-dependent failure rates follow exponential distribution, while the repair rates follow arbitrary distribution. Switch devices, repairs and preventive maintenance are perfect. All random variables are statistically independent. Semi-Markov process and regenerative point technique were used to derive the necessary system effectiveness measure to evaluate the profit function of all the three models. To highlight the importance of the study, graphs for profit difference between models have been depicted for a particular set of values of various parameters with respect to preventive maintenance.

Analysis of some reliability measures of single-unit systems subject to abnormal environmental conditions and arbitrary distribution for failure and repair activities

This article analyzes the effect of abnormal environmental conditions on various reliability measures. After the continuous operation of single-unit systems for a long duration of time these systems cannot be restored again in a younger state after the failure of the system. The unit does not remain as new after repair. This phenomenon is known as degradation and the unit after repair is called degraded unit. Preventive maintenance is a proactive method to tackle and overcome from these types of problems. For this purpose, a stochastic model is developed for single-unit systems by using semi-Markov process. There is a single server who inspects the failed unit after failed to check the feasibility of repair and replacement. If repair is not feasible then unit is replaced with some replacement time. The failed unit after repair becomes degraded and degraded failed unit is replaced by new one. All time distributions are arbitrary distributed like Weibull distribution with common shape parameter and different scale parameters. The switching devices are instantaneous. The system is observed at suitable regenerative epochs to obtain various measures of system effectiveness of interest to system designers and operation managers.

Substantiation of Reliability Requirements for Mobility Means of Surface-to-Air Missile Systems

Common principles of substantiation of reliability requirements for vehicles (mobility means) of surface-to-air missile (SAM) systems are discussed. The principles mentioned include the impact of a hierarchically-branched structure of SAM system and reliability of their vehicles on system effectiveness under the real conditions. As the complex measure of SAM system effectiveness the coefficient of effectiveness sustainment of SAM system combat (technical) mobility means is used, which is the ratio of system output effect characteristic taking into account reliability measures of mobility means to its value in case, when mobility means do not have failures. The coefficient used here is considered to be the function of mean distance between failures (MDBF) of mobility means and their number.

Dynamic allocation of stochastically-arriving flexible resources to random streams of objects with application to kidney cross-transplantation

Two distinct random streams of discrete objects flow into a system and queue in two separate lines. Concurrently, two distinct types of resources arrive stochastically over time. Upon arrival, each resource unit is matched with a waiting object. One resource type is ʻflexible’ and can be allocated to either one of the object types. However, units of the other, non-flexible, resource type can be allocated only to units of one specific object type. The allocation probabilities are not fixed and may depend on both queue sizes of the two objects. If a resource unit is not allocated immediately, it is lost. The goal is to find an optimal state-dependent probabilistic dynamic allocation policy. We formulate the system as a two-dimensional Markov process, analyze its probabilistic behavior, and derive its performance measures. We then apply the model to the problem of kidney cross-transplantation and propose a new measure of system effectiveness, called Expected Value of Transplantation (EVT), based on the histocompatibility between kidneys and candidates. We further show that it is possible to balance the objectives of achieving equity in candidates’ expected waiting times (EW) and maximizing EVT by equating the value of EW/EVT between the two groups.

Stochastic Reliability Analysis of Two Identical Cold Standby Units with Geometric Failure &amp; Repair Rates

The present paper is based on the analysis of an two identical unit system wherein initially one unit is in operative state and other is in cold standby and total failure of the unit is via partial failure mode. Single repairman is always available with the system for any repair of failed unit (partially/ completely). Failure/repair time is considered to be a Geometric distribution. Measures of system effectiveness had also been calculated for the system.