Immunity-based aircraft actuator failure evaluation

2016 ◽  
Vol 88 (6) ◽  
pp. 729-739
Author(s):  
Mario Perhinschi ◽  
Dia Al Azzawi ◽  
Hever Moncayo ◽  
Andres Perez ◽  
Adil Togayev
Keyword(s):  
Prediction Models ◽  
Health Management ◽  
Actuator Failure ◽  
Content Type ◽  
Flight Envelope ◽  
Comprehensive Health ◽  
Relevant Variables ◽  
Process System ◽  
Failure Conditions ◽  
Low Dimensional

Purpose This paper aims to present the development of prediction models for aircraft actuator failure impact on flight envelope within the artificial immune system (AIS) paradigm. Design/methodology/approach Simplified algorithms are developed for estimating ranges of flight envelope-relevant variables using an AIS in conjunction with the hierarchical multi-self strategy. The AIS is a new computational paradigm mimicking mechanisms of its biological counterpart for health management of complex systems. The hierarchical multi-self strategy consists of building the AIS as a collection of low-dimensional projections replacing the hyperspace of the self to avoid numerical and conceptual issues related to the high dimensionality of the problem. Findings The proposed methodology demonstrates the capability of the AIS to not only detect and identify abnormal conditions (ACs) of the aircraft subsystem but also evaluate their impact and consequences. Research limitations/implications The prediction of altered ranges of relevant variables at post-failure conditions requires failure-specific algorithms to correlate with the characteristics and dimensionality of self-projections. Future investigations are expected to expand the types of subsystems that are affected and the nature of the ACs targeted. Practical implications It is expected that the proposed methodology will facilitate the design of on-board augmentation systems to increase aircraft survivability and improve operation safety. Originality/value The AIS paradigm is extended to AC evaluation as part of an integrated and comprehensive health management process system, also including AC detection, identification and accommodation.

An analysis of Industry 4.0 implementation-variables by using SAP-LAP and e-IRP approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Veepan Kumar ◽  
Ravi Shankar ◽  
Prem Vrat
Keyword(s):  
Industry 4.0 ◽  
Business Environment ◽  
Content Type ◽  
Qualitative And Quantitative ◽  
Wide Range ◽  
Interpretive Ranking Process ◽  
Relevant Variables ◽  
Manufacturing Organization ◽  
Industry Associations ◽  
Practical Implications

PurposeIn today’s uncertain business environment, Industry 4.0 is regarded as a viable strategic plan for addressing a wide range of manufacturing-related challenges. However, it appears that its level of adoption varies across many countries. In the case of a developing economy like India, practitioners are still in the early stages of implementation. The implementation of Industry 4.0 appears to be complex, and it must be investigated holistically in order to gain a better understanding of it. Therefore, an attempt has been made to examine the Industry 4.0 implementation for the Indian manufacturing organization in a detailed way by analyzing the complexities of relevant variables.Design/methodology/approachSAP-LAP (situation-actor-process and learning-action-performance) and an efficient interpretive ranking process (e-IRP) were used to analyze the various variables influencing Industry 4.0 implementation. The variables were identified, as per SAP-LAP, through a thorough review of the literature and based on the perspectives of various experts. The e-IRP has been used to prioritize the selected elements (i.e. actors with respect to processes and actions with respect to performance) of SAP-LAP.FindingsThis study ranked five stakeholders according to their priority in Industry 4.0 implementation: government policymakers, industry associations, research and academic institutions, manufacturers and customers. In addition, the study also prioritized important actions that need to be taken by these stakeholders.Practical implicationsThe results of this study would be useful in identifying and managing the various actors and actions related to Industry 4.0 implementation. Accordingly, their prioritized sequence would be useful to the practitioners in preparing the well-defined and comprehensive strategic roadmap for Industry 4.0.Originality/valueThis study has adopted qualitative and quantitative approaches for identifying and prioritizing different variables of Industry 4.0 implementation. This, in turn, helps the stakeholder to comprehend the concept of Industry 4.0 in a much simpler way.

A review of literature on risk prediction tools for hospital readmissions in older adults

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michelle Louise Gatt ◽  
Maria Cassar ◽  
Sandra C. Buttigieg
Keyword(s):  
Risk Prediction ◽  
Prediction Models ◽  
Hospital Readmissions ◽  
Predictive Ability ◽  
Chronic Obstructive ◽  
Risk Category ◽  
Extensive Literature ◽  
Content Type ◽  
Prediction Tools ◽  
Readmission Risk

Purpose The purpose of this paper is to identify and analyse the readmission risk prediction tools reported in the literature and their benefits when it comes to healthcare organisations and management.Design/methodology/approach Readmission risk prediction is a growing topic of interest with the aim of identifying patients in particular those suffering from chronic diseases such as congestive heart failure, chronic obstructive pulmonary disease and diabetes, who are at risk of readmission. Several models have been developed with different levels of predictive ability. A structured and extensive literature search of several databases was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis strategy, and this yielded a total of 48,984 records.Findings Forty-three articles were selected for full-text and extensive review after following the screening process and according to the eligibility criteria. About 34 unique readmission risk prediction models were identified, in which their predictive ability ranged from poor to good (c statistic 0.5–0.86). Readmission rates ranged between 3.1 and 74.1% depending on the risk category. This review shows that readmission risk prediction is a complex process and is still relatively new as a concept and poorly understood. It confirms that readmission prediction models hold significant accuracy at identifying patients at higher risk for such an event within specific context.Research limitations/implications Since most prediction models were developed for specific populations, conditions or hospital settings, the generalisability and transferability of the predictions across wider or other contexts may be difficult to achieve. Therefore, the value of prediction models remains limited to hospital management. Future research is indicated in this regard.Originality/value This review is the first to cover readmission risk prediction tools that have been published in the literature since 2011, thereby providing an assessment of the relevance of this crucial KPI to health organisations and managers.

Forecasting the risk at infractions: an ensemble comparison of machine learning approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lei Li ◽  
Desheng Wu
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Short Term Memory ◽  
Model Performance ◽  
Large Data ◽  
Support Vector ◽  
Learning Approaches ◽  
Content Type ◽  
Day To Day Operations ◽  
Prediction Approach

PurposeThe infraction of securities regulations (ISRs) of listed firms in their day-to-day operations and management has become one of common problems. This paper proposed several machine learning approaches to forecast the risk at infractions of listed corporates to solve financial problems that are not effective and precise in supervision.Design/methodology/approachThe overall proposed research framework designed for forecasting the infractions (ISRs) include data collection and cleaning, feature engineering, data split, prediction approach application and model performance evaluation. We select Logistic Regression, Naïve Bayes, Random Forest, Support Vector Machines, Artificial Neural Network and Long Short-Term Memory Networks (LSTMs) as ISRs prediction models.FindingsThe research results show that prediction performance of proposed models with the prior infractions provides a significant improvement of the ISRs than those without prior, especially for large sample set. The results also indicate when judging whether a company has infractions, we should pay attention to novel artificial intelligence methods, previous infractions of the company, and large data sets.Originality/valueThe findings could be utilized to address the problems of identifying listed corporates' ISRs at hand to a certain degree. Overall, results elucidate the value of the prior infraction of securities regulations (ISRs). This shows the importance of including more data sources when constructing distress models and not only focus on building increasingly more complex models on the same data. This is also beneficial to the regulatory authorities.

Enhanced prediction of vulnerable Web components using Stochastic Gradient Boosting Trees

2019 ◽  
Vol 15 (2) ◽  
pp. 201-214 ◽  
Author(s):  
Mahmoud Elish
Keyword(s):  
Web Applications ◽  
Prediction Models ◽  
Stochastic Gradient ◽  
Gradient Boosting ◽  
Data Sets ◽  
Content Type ◽  
Stochastic Gradient Boosting ◽  
Security Inspection ◽  
Novel Model ◽  
Efficient Software

Purpose Effective and efficient software security inspection is crucial as the existence of vulnerabilities represents severe risks to software users. The purpose of this paper is to empirically evaluate the potential application of Stochastic Gradient Boosting Trees (SGBT) as a novel model for enhanced prediction of vulnerable Web components compared to common, popular and recent machine learning models. Design/methodology/approach An empirical study was conducted where the SGBT and 16 other prediction models have been trained, optimized and cross validated using vulnerability data sets from multiple versions of two open-source Web applications written in PHP. The prediction performance of these models have been evaluated and compared based on accuracy, precision, recall and F-measure. Findings The results indicate that the SGBT models offer improved prediction over the other 16 models and thus are more effective and reliable in predicting vulnerable Web components. Originality/value This paper proposed a novel application of SGBT for enhanced prediction of vulnerable Web components and showed its effectiveness.

scholarly journals Using Action Research and Action Learning (ARAL) to develop a response to the abuse of older people in a healthcare context

2015 ◽  
Vol 7 (1) ◽  
pp. 38-51 ◽  
Author(s):  
Fiona McAlinden
Keyword(s):  
Action Research ◽  
Older People ◽  
Hospital Admissions ◽  
Elder Abuse ◽  
Health Management ◽  
Action Learning ◽  
Public Hospitals ◽  
Public Healthcare ◽  
Content Type ◽  
Policy And Procedure

Purpose The purpose of this paper is to describe Monash Health’s development of a Policy and Procedure on the abuse of older people in metropolitan Australia. Monash Health is a public healthcare network that consists of six public hospitals and over 40 community health care sites throughout the South East of Melbourne. Design/methodology/approach An Action Research Action Learning approach was employed to develop a comprehensive set of policy and procedure documents to ensure that Monash Health became compliant with the State Government’s expectations around responding to the abuse of older people in a consistent manner. Findings Almost 90,000 Monash Health hospital admissions per year are older people aged over 65 years. Senior Monash Health management recognized that staff did not have adequate information, education and resources to consistently identify and respond to situations of elder abuse. What is more, the existing internal Monash Health document Supporting Older People at Risk did not meet obligations stated in the Victorian Government’s Elder Abuse Strategy (2009). Originality/value The project’s emphasis upon participatory action research, cooperative inquiry and action learning further resulted in the identification of an opportunity to develop a strategic response to violence and abuse for all patients of Monash Health, not just older people.

Online argumentation-based learning aided by digital concept mapping during COVID-19: implications for health management teaching and learning

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dorit Alt ◽  
Lior Naamati-Schneider
Keyword(s):  
Concept Mapping ◽  
Undergraduate Students ◽  
Online Teaching ◽  
Teaching And Learning ◽  
Health Management ◽  
Phase 1 ◽  
Advanced Technology ◽  
Learning Activity ◽  
Constructivist Teaching ◽  
Content Type

PurposeThe COVID-19 pandemic has affected educational systems worldwide, forcing them to abruptly shift from face-to-face to online teaching and learning. This case study illustrates how a traditional lecture-based activity for undergraduate students in a Management of Health Service Organizations program was transformed into an argumentation-based learning activity using the technique of digital concept mapping and was deployed in an online format during the COVID-19 lockdown.Design/methodology/approachThe students were tasked with solving an ill-structured problem bearing significance for their future professional lives and connected to the contents of their course (entitled “Assimilation of service quality in health systems”). The activity was composed of two phases. In Phase 1, participants were asked to provide five arguments to establish their proposed solution to the problem by using a concept map on a digital platform (Mindomo). In Phase 2, they were asked to substantiate their arguments. Reflective journals were used to ascertain how the participants viewed the activity. Thematic analysis was used to analyze the qualitative data by searching for themes demonstrating different epistemological positions.FindingsSix themes were inductively derived from the students' reflections: (1) transitioning from passive to active learning; (2) generating epistemic change; (3) social perspective-taking; (4) domain-based knowledge; (5) prior knowledge and experience; and (6) online collaboration with other students. Episodes, thoughts and feelings expressed by the students were reported so as to increase the reliability of the recurrent and common themes.Originality/valueThis study mainly shows that combining constructivist teaching and learning tools with advanced technology in an online course enables the development of lifelong learning capabilities among students in the health management professions.

Impact of training and professional development on health management and leadership competence

2019 ◽  
Vol 33 (4) ◽  
pp. 354-379 ◽  
Author(s):  
Reuben Olugbenga Ayeleke ◽  
Nicola Henri North ◽  
Annette Dunham ◽  
Katharine Ann Wallis
Keyword(s):  
Professional Development ◽  
Systematic Review ◽  
Mixed Methods ◽  
Health Management ◽  
Mixed Methods Design ◽  
Content Type ◽  
Development Interventions ◽  
Leadership Competence ◽  
The Impact ◽  
Management And Leadership

Purpose Training to improve health management and leadership competence is recommended. However, there is limited evidence showing the impact of training on competence. The purpose of this paper is to evaluate the evidence for the impact of training and professional development on health management and leadership competence. Design/methodology/approach A systematic review was conducted using a mixed-methods design. Studies using qualitative, quantitative or mixed-methods design were included. The following electronic databases were searched to October 2018: CENTRAL, CINAHL, EMBASE, ERIC, NEDLINE and PsycINFO. Study eligibility and methodological quality were assessed independently by two review authors. Data from qualitative studies were synthesised using thematic analysis. For quantitative studies, odds ratio (OR) or mean difference (MD) and 95% confidence interval (CI) were calculated for each intervention. Where appropriate, qualitative and quantitative data were integrated into a single synthesis using Bayesian methods. Findings In total, 19 studies were identified for inclusion in the review. Training and professional development interventions using flexible, multiple training techniques tailored to organisational contexts can improve individual competence and performance. Such training is typified by a leadership development programme. There was insufficient evidence to determine the effects of interventions on organisational performance. Originality/value This is the first systematic review evaluating the impact of training and professional development interventions on health management and leadership competence.

The impact of working conditions on the health of taxi drivers in an urban metropolis

2020 ◽  
Vol 13 (6) ◽  
pp. 671-686
Author(s):  
Husayn Marani ◽  
Brenda Roche ◽  
Laura Anderson ◽  
Minnie Rai ◽  
Payal Agarwal ◽  
...  
Keyword(s):  
Mental Health ◽  
Working Conditions ◽  
Health Management ◽  
Primary Care Providers ◽  
Care Providers ◽  
Convenience Sample ◽  
Content Type ◽  
Taxi Drivers ◽  
Targeted Interventions ◽  
The Impact

PurposeThis descriptive qualitative study explores how working conditions impact the health of taxi drivers in Toronto, Canada.Design/methodology/approachDrivers were recruited between September 2016 and March 2017. A total of 14 semi-structured qualitative interviews and one focus group (n = 11) were conducted. Transcripts were analyzed inductively through a socioecological lens.FindingsThe findings of this study are as follows: drivers acknowledged that job precariousness (represented by unstable employment, long hours and low wages) and challenging workplace conditions (sitting all day and limited breaks) contribute to poor physical/mental health. Also, these conditions undermine opportunities to engage in health-protective behaviors (healthy eating, regularly exercising and taking breaks). Drivers do not receive health-enabling reinforcements from religious/cultural networks, colleagues or their taxi brokerage. Drivers do seek support from their primary care providers and family for their physical health but remain discreet about their mental health.Research limitations/implicationsAs this study relied on a convenience sample, the sample did not represent all Toronto taxi drivers. All interviews were completed in English and all drivers were male, thus limiting commentary on other experiences and any gender differences in health management approaches among drivers.Practical implicationsGiven the global ubiquity of taxi driving and an evolving workplace environment characterized by growing competition, findings are generalizable across settings and may resonate with other precarious professions, including long-haul truck operators and Uber/Lyft drivers. Findings also expose areas for targeted intervention outside the workplace setting.Originality/valueHealth management among taxi drivers is understudied. A fulsome, socioecological understanding of how working conditions (both within and outside the workplace) impact their health is essential in developing targeted interventions to improve health outcomes.

Psychological well-being of people living near landfills: preliminary case study in Indonesia

2020 ◽  
Vol 13 (4) ◽  
pp. 365-379
Author(s):  
Hamka Hamka ◽  
Ni'matuzahroh Ni'matuzahroh ◽  
Tri Astuti ◽  
Mein-Woei Suen ◽  
Fu-An Shieh
Keyword(s):  
Personal Growth ◽  
Health Management ◽  
Well Being ◽  
Psychological Well Being ◽  
Content Type ◽  
Positive Attitudes ◽  
The People ◽  
The Government ◽  
Voice Recorder

Purpose The purpose of this study is to explore the psychological well-being of people living around landfills, which constitutes a preliminary case study localized in Samarinda city, Indonesia. Design/methodology/approach This current study used a descriptive, participatory case study design. For data collection, interviews and participatory observation were used. Specifically, this case study took place in Samarinda City, Indonesia. Findings The psychological well-being of the people living around landfills was indicated very low in the light of psychological well-being such as personal growth, life’s goals and self-acceptance dimensions. Research limitations/implications Psychological well-being is part of an attitude of gratitude, thus making individuals happy and satisfied in life. The results of this study point to the fact that people who live around landfills have low psychological well-being due to lack of support from the community and government. In addition, with this research, people who live near landfills are very happy because they feel cared for and care about their condition. People who live near landfills expect the government and surrounding communities to know about their situation so that they become prosperous and well-being. In addition, providing medical team services, sending clean water and providing good solutions can help people who live near landfills. The limitation of this preliminary study was that researchers could deeply explore the lives of people in the next research. Besides, the next research can provide a camera or voice recorder in the state of only observation. In addition, the researcher can analyze more deeply in the next research. The final limitation was that participants could not have enough time to interact with, thus, the researcher could not collect the data to explore further. Practical implications Base on the result in this study, the government needs to have the policy to take care of those people who stay near landfills, for example, improving drinking water, establish the health management and giving a right to people to stay near landfills. Social implications By improving the growing environment, the people live near landfills can have some changes in their life. In addition, the negative stereotype and prejudice can be decreased and establish a more friendly society and increasing their well-being. Originality/value The participants were found to be problematic, primarily in managing their environment and influencing their personal growth. On top of that, the participants appeared to possess a lack exposure of to social interaction with other communities, which might cause them social gap and lack of caring perceived toward the surrounding environment, lack of better life’s goals, the disappointment of current conditions due to low educational and skill backgrounds. Nonetheless, the participants were still of gratefulness upon the situation for they were still granted health for studies to support their families. Besides, the participants did not show any positive attitudes toward themselves because of the disappointment of their condition and personal qualities.

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