scholarly journals A data-driven based decomposition–integration method for remanufacturing cost prediction of end-of-life products

2020 ◽  
Vol 61 ◽  
pp. 101838 ◽  
Author(s):  
Zhigang Jiang ◽  
Zhouyang Ding ◽  
Ying Liu ◽  
Yan Wang ◽  
Xiaoli Hu ◽  
...  
Keyword(s):  
End Of Life ◽  
Integration Method ◽  
Data Driven ◽  
Cost Prediction

scholarly journals A Big Data based Cost Prediction Method for Remanufacturing End-of-Life Products

Procedia CIRP ◽  
2018 ◽  
Vol 72 ◽  
pp. 1362-1367 ◽  
Author(s):  
Zhouyang Ding ◽  
Zhigang Jiang ◽  
Ying Liu ◽  
Yan Wang ◽  
Congbo Li
Keyword(s):  
Big Data ◽  
End Of Life ◽  
Prediction Method ◽  
Cost Prediction

scholarly journals Neural Network-Based Model for Predicting Preliminary Construction Cost as Part of Cost Predicting System

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Diana Car-Pusic ◽  
Silvana Petruseva ◽  
Valentina Zileska Pancovska ◽  
Zlatko Zafirovski
Keyword(s):  
Neural Network ◽  
Prediction Models ◽  
Cost Model ◽  
Construction Project ◽  
Construction Cost ◽  
Data Driven ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Cost Prediction ◽  
Project Participants

A model for early construction cost prediction is useful for all construction project participants. This paper presents a combination of process-based and data-driven model for construction cost prediction in early project phases. Bromilow’s “time-cost” model is used as process-based model and general regression neural network (GRNN) as data-driven model. GRNN gave the most accurate prediction among three prediction models using neural networks which were applied, with the mean absolute percentage error (MAPE) of about 0.73% and the coefficient of determination R2 of 99.55%. The correlation coefficient between the predicted and the actual values is 0.998. The model is designed as an integral part of the cost predicting system (CPS), whose role is to estimate project costs in the early stages. The obtained results are used as Cost Model (CM) input being both part of the Decision Support System (DSS) and part of the wider Building Management Information System (BMIS). The model can be useful for all project participants to predict construction cost in early project stage, especially in the phases of bidding and contracting when many factors, which can determine the construction project implementation, are yet unknown.

scholarly journals Improving Semi-Supervised Learning for Remaining Useful Lifetime Estimation Through Self-Supervision

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Tilman Krokotsch ◽  
Mirko Knaak ◽  
Clemens G¨uhmann
Keyword(s):  
Supervised Learning ◽  
End Of Life ◽  
System Simulation ◽  
Vital Role ◽  
Data Driven ◽  
Lifetime Estimation ◽  
Realistic Evaluation ◽  
Data Imbalance ◽  
Using Data ◽  
Useful Lifetime

RUL estimation plays a vital role in effectively scheduling maintenance operations. Unfortunately, it suffers from a severe data imbalance where data from machines near their end of life is rare. Additionally, the data produced by a machine can only be labeled after the machine failed. Both of these points make using data-driven methods for RUL estimation difficult. Semi-Supervised Learning (SSL) can incorporate the unlabeled data produced by machines that did not yet fail into data-driven methods. Previous work on SSL evaluated approaches under unrealistic conditions where the data near failure was still available. Even so, only moderate improvements were made. This paper defines more realistic evaluation conditions and proposes a novel SSL approach based on self-supervised pre-training. The method can outperform two competing approaches from the literature and the supervised baseline on the NASA Commercial Modular Aero-Propulsion System Simulation dataset.

Much Ado About Fried Chicken: Abetting Aspiration or Respecting Autonomy?

2019 ◽  
Vol 28 (3) ◽  
pp. 1356-1362
Author(s):  
Laurence Tan Lean Chin ◽  
Yu Jun Lim ◽  
Wan Ling Choo
Keyword(s):  
Palliative Care ◽  
End Of Life ◽  
Multidisciplinary Team ◽  
Biopsychosocial Model ◽  
Family Members ◽  
Clinical Decisions ◽  
Goals Of Care ◽  
Complex Needs ◽  
Aspiration Risk ◽  
Patient Centric

Purpose Palliative care is a philosophy of care that encompasses holistic, patient-centric care involving patients and their family members and loved ones. Palliative care patients often have complex needs. A common challenge in managing patients near their end of life is the complexity of navigating clinical decisions and finding achievable and realistic goals of care that are in line with the values and wishes of patients. This often results in differing opinions and conflicts within the multidisciplinary team. Conclusion This article describes a tool derived from the biopsychosocial model and the 4-quadrant ethical model. The authors describe the use of this tool in managing a patient who wishes to have fried chicken despite aspiration risk and how this tool was used to encourage discussions and reduce conflict and distress within the multidisciplinary team.

End-of-Life Issues for People Who Use AAC

2005 ◽  
Vol 14 (3) ◽  
pp. 15-19 ◽  
Author(s):  
Melanie Fried-Oken ◽  
Lisa Bardach
Keyword(s):  
End Of Life ◽  
Life Issues ◽  
End Of Life Issues

Dysphagia in Hospice Care: The Roles of Social Work and Speech-Language Pathologists

2014 ◽  
Vol 23 (4) ◽  
pp. 173-186 ◽  
Author(s):  
Deborah Hinson ◽  
Aaron J. Goldsmith ◽  
Joseph Murray
Keyword(s):  
Social Work ◽  
End Of Life ◽  
Case Studies ◽  
End Of Life Care ◽  
Hospice Care ◽  
Patient Communication ◽  
Life Care ◽  
Speech Language Pathologists ◽  
Four Levels

This article addresses the unique roles of social work and speech-language pathologists (SLPs) in end-of-life and hospice care settings. The four levels of hospice care are explained. Suggested social work and SLP interventions for end-of-life nutrition and approaches to patient communication are offered. Case studies are used to illustrate the specialized roles that social work and SLP have in end-of-life care settings.

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