scholarly journals Symmetrical Model of Smart Healthcare Data Management: A Cybernetics Perspective

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2089
Author(s):  
Wajdi Alhakami ◽  
Abdullah Baz ◽  
Hosam Alhakami ◽  
Abhishek Pandey ◽  
Raees Khan
Keyword(s):  
Health Management ◽  
Performance Simulation ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Design Structure ◽  
Proposed Model ◽  
Critical Issues ◽  
Symmetrical Model ◽  
Industry Needs ◽  
Evaluation Techniques

Issues such as maintaining the security and integrity of data in digital healthcare are growing day-by-day in terms of size and cost. The healthcare industry needs to work on effective mechanisms to manage these concerns and prevent any debilitating crisis that might affect patients as well as the overall health management. To tackle such critical issues in a simple, feasible, and symmetrical manner, the authors considered the ideology of cybernetics. Working towards this intent, this paper proposes a symmetrical model that illustrates a compact version of the adopted ideology as a pathway for future researchers. Furthermore, the proposed ideology of cybernetics specifically focuses on how to plan the entire design concept more effectively. It is important for the designer to prepare for the future and manage the design structure from a product perspective. Therefore, the proposed ideology provides a symmetric mechanism that includes a variety of estimation and evaluation techniques as well as their management. The proposed model generates a symmetric, variety-issue, reduced infrastructure that can produce highly effective results due to an efficient usability, operatability, and symmetric operation execution which are the benefits of the proposed model. Furthermore, the study also performed a performance simulation assessment by adopting a multi-criteria decision-making approach that helped the authors compare the various existing and proposed models based on their levels of effectiveness.

scholarly journals Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Aisong Qin ◽  
Qinghua Zhang ◽  
Qin Hu ◽  
Guoxi Sun ◽  
Jun He ◽  
...  
Keyword(s):  
Health Management ◽  
Rotating Machinery ◽  
Remaining Useful Life ◽  
Programming Algorithm ◽  
Wiener Model ◽  
New Approach ◽  
Degradation Modeling ◽  
Proposed Model ◽  
Useful Life ◽  
Degradation Indicator

Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling. However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy. Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor. First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT. Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT. Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived. To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery. The experimental results indicate that the method can effectively improve the accuracy of RUL prediction.

scholarly journals eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning

2020 ◽  
Vol 4 (4) ◽  
pp. 37
Author(s):  
Khaled Fawagreh ◽  
Mohamed Medhat Gaber
Keyword(s):  
Random Forest ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Theoretic Approach ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Game Theoretic ◽  
Game Theoretic Approach

To make healthcare available and easily accessible, the Internet of Things (IoT), which paved the way to the construction of smart cities, marked the birth of many smart applications in numerous areas, including healthcare. As a result, smart healthcare applications have been and are being developed to provide, using mobile and electronic technology, higher diagnosis quality of the diseases, better treatment of the patients, and improved quality of lives. Since smart healthcare applications that are mainly concerned with the prediction of healthcare data (like diseases for example) rely on predictive healthcare data analytics, it is imperative for such predictive healthcare data analytics to be as accurate as possible. In this paper, we will exploit supervised machine learning methods in classification and regression to improve the performance of the traditional Random Forest on healthcare datasets, both in terms of accuracy and classification/regression speed, in order to produce an effective and efficient smart healthcare application, which we have termed eGAP. eGAP uses the evolutionary game theoretic approach replicator dynamics to evolve a Random Forest ensemble. Trees of high resemblance in an initial Random Forest are clustered, and then clusters grow and shrink by adding and removing trees using replicator dynamics, according to the predictive accuracy of each subforest represented by a cluster of trees. All clusters have an initial number of trees that is equal to the number of trees in the smallest cluster. Cluster growth is performed using trees that are not initially sampled. The speed and accuracy of the proposed method have been demonstrated by an experimental study on 10 classification and 10 regression medical datasets.

Construction Delay Analysis and early Warning Model Based on Design Structure Matrix

2013 ◽  
Vol 357-360 ◽  
pp. 2199-2206
Author(s):  
De Yin Liu ◽  
Jian Guo Chen
Keyword(s):  
Early Warning ◽  
Construction Projects ◽  
Design Structure Matrix ◽  
Delay Analysis ◽  
Model Case ◽  
Structure Matrix ◽  
Early Warning Model ◽  
Design Structure ◽  
Proposed Model ◽  
Warning Model

Schedule delays frequently occur in construction projects and bring unexpected consequence. Conducting an elaborate delay analysis and providing early warning are crucial for project performance. In this paper, factors are classified into internal risks and external risks based on the chain effect of schedule delays, and the design structure matrix (DSM) is employed to develop the delay analysis and early warning model. Case study has been performed to prove the effectiveness of the proposed model, finally, sensitivity analysis also draws conclusion the internal risks between tasks should be paid more attention than the external in environment.

scholarly journals Designing the Model of the Management of Mental Health Services

2020 ◽  
Vol 12 (4) ◽  
pp. 297-304
Author(s):  
Shahrooz Rahbari ◽  
Leila Riahi ◽  
Jamaleddin Tabibi
Keyword(s):  
Mental Health ◽  
Mental Health Services ◽  
Health Services ◽  
Health Management ◽  
Psychological Services ◽  
Monitoring And Control ◽  
Current State ◽  
Proposed Model ◽  
Control Community ◽  
And Control

Introduction: Having mental health is necessary for the growth and prosperity of humans and as a result of the growth of societies.Objectives: The purpose of this study was to design a mental health management model in Iran.Methods: In this exploratory study, a review study was first performed to analyze the current state of mental health services in Iran and the world. Countries were selected to compare mental health management with Iran in 6 domains. 311 faculty members with mental health were completed by completing a questionnaire with 50 items in the study. Using the factor analysis, the final model was explained. Results: The effective domains in Iranian mental health services management were named in 8 areas: Mental Health in Particular, Key Centers and Task-Shifting, Human Resources and Specialists Training, Psychological Services for Children and Adolescents, Financial Resources and Hospital Services, Mental Health in PHC and Primary medical services, Policy-Making and Human Rights, Monitoring and Control, Community-Based Services. Conclusions: The proposed model of mental health services management in Iran consists of 8 domains, which is a comprehensive and multidimensional concept. Paying attention to its factors can lead to the successful management of mental health services in Iran.

scholarly journals Additive manufacturing of a continuum topology-optimized palletizing manipulator arm

2021 ◽  
Vol 12 (1) ◽  
pp. 289-304
Author(s):  
Jiwen Chen ◽  
Qingpeng Chen ◽  
Hongjuan Yang
Keyword(s):  
Additive Manufacturing ◽  
Structural Design ◽  
Mechanical Performance ◽  
Lightweight Design ◽  
Optimization Methods ◽  
Performance Simulation ◽  
Design Structure ◽  
Manipulator Arm ◽  
Solid Works ◽  
Reconstruction Model

Abstract. In this article, the lightweight design of a palletizing manipulator arm structure is carried out. The optimization target is designed in 3D with Solid Works. To determine the optimization area and the secondary reconstruction model after the structure is optimized, the reliability and cost of the design structure are also considered. The meta-software performs mechanical performance simulation experiments under the corresponding working conditions for the lightweight structural design of the target structure via the topology optimization methods. Finally, with additive manufacturing technology, the design and printing of the filled skeletal Voronoi structure and the nested-external-removal Voronoi structure of the palletizing manipulator arm are performed.

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