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The purpose of this study is to advance a novel evaluation index system and evaluation approach for ability of older adults in China.

This study constructed a comprehensive older adult ability evaluation index system with 4 primary indicators and 17 secondary indicators. Grey clustering analysis and entropy weight method are combined into a robust evaluation model for the ability of older adults.

The result demonstrates that the proposed grey clustering model is readily available to calculate the disability level of elderly individuals. The constructed index system more comprehensively considers all aspects of the disability of the elderly.

This study provides a quantitative method and a more reasonable index system for the determination of the disability level of the elderly.

The purpose of this paper is to present the terms of grey clustering evaluation models.

The definitions of basic terms about grey clustering evaluation models are presented one by one.

The reader could know the basic explanation about the important terms about various grey clustering evaluation models from this paper.

Many of the authors’ colleagues thought that unified definitions of key terms would be beneficial for both the readers and the authors.

It is a fundamental work to standardise all the definitions of terms for a new discipline. It is also propitious to spread and universal of grey system theory.

This paper aims to implement quality of service(QoS) dynamic optimization for the integrated satellite-terrestrial network(STN) of the fifth-generation Inmarsat system(Inmarsat-5).

The structure and operational logic of Inmarsat-5 STN are introduced to build the graphic evaluation and review technique(GERT) model. Thus, the equivalent network QoS metrics can be derived from the analytical algorithm of GERT. The center–point mixed possibility functions of average delay and delay variation are constructed considering users' experiences. Then, the grey clustering evaluation of link QoS is obtained combined with the two-stage decision model to give suitable rewards for the agent of GERT-Q-learning, which realizes the intelligent optimization mechanism under real-time monitoring data.

A case study based on five time periods of monitoring data verifies the adaptability of the proposed method. On the one hand, grey clustering based on possibility function enables a more effective measurement of link QoS from the users' perspective. On the other hand, the method comparison intuitively shows that the proposed method performs better.

With the development trend of integrated communication, STN has become an important research object in satellite communications. This paper establishes a modular and extensible optimization framework whose loose coupling structure and flexibility facilitate management and development. The grey-clustering-based GERT-Q-Learning model has the potential to maximize design and application benefits of STN throughout its life cycle.

The purpose of this paper is to solve the dilemma in the process of major selection decision-making.

Firstly, the group of weight vector with kernel has been defined. Then, the weighted comprehensive clustering coefficient vector was calculated based on the group of weight vector with kernel. Under the action of weighted comprehensive clustering coefficient vector, the information including in other components around component k and supporting object i to be classified into the k-th category has been gathered to component k. At last, a novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector is put forward to solve the dilemma in grey clustering evaluation. Then the overall evaluation conclusion can be consistent with the clustering result according to the rule of maximum value.

A new way to solve the dilemma in the process of major selection decision-making has been found. People can obtain a consistent result with two-stage decision model at the case of dilemma. That is, the conclusion of the overall evaluation is consistent with the clustering result according to the rule of maximum value.

Several functional groups of weight vector with kernel have been put forward. The proposed model can solve the clustering dilemma effectively and produce consistent results. A practical application of decision problem to solve the dilemma in supplier evaluation and selection of a key component of large commercial aircraft C919 have been completed by the novel two-stage decision model.

The two-stage decision model, the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector were presented in this paper firstly. People can solve the dilemma in grey clustering evaluation effectively by the novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector.

The purpose of this research is to provide a theoretical framework for complex equipment quality risk evaluation. The primary aim of the framework is to enhance the ability to identify risks and improve risk control efficiency during the development phase.

A novel framework for quality risk evaluation in complex equipment is proposed, which integrates probabilistic hesitant fuzzy set-quality function deployment (PHFS-QFD) and grey clustering. PHFS-QFD is applied to identify the quality risk factors, and grey clustering is used to evaluate quality risks in cases of poor quality information during the development stage. The unfolding function of QFD is applied to simplify complex evaluation problems.

The methodology presents an innovative approach to quality risk evaluation for complex equipment development. The case analysis demonstrates that this method can efficiently evaluate the quality risks for aircraft development and systematically trace back the risk factors through hierarchical relationships. In comparison to traditional failure mode and effects analysis methods for quality risk assessment, this approach exhibits superior effectiveness and reliability in managing quality risks for complex equipment development.

This study contributes to the field by introducing a novel theoretical framework that combines PHFS-QFD and grey clustering. The integration of these approaches significantly improves the quality risk evaluation process for complex equipment development, overcoming challenges related to data scarcity and simplifying the assessment of intricate systems.

The purpose of this paper is to present a novel synthetic index of two counts and mathematical model for researcher evaluation.

A synthetic index L for researcher evaluation considering both the total number of other citations (C) and nonacademic impact (I) and a synthetic evaluation model are proposed in this paper. C and I are verified impact indexes. According to investigation by Delphi method, researchers are divided into five different classes of “below average,” “average,” “good,” “excellent” and “stellar.” The threshold values for counts C of grey class “stellar” are determined by deep investigation. The possibility functions of the two counts C and I on four grey classes of “below average,” “average,” “good” and “excellent” are built.

The novel synthetic index of two counts and mathematical model for researcher evaluation provide a better way to conduct researcher assessment.

The synthetic index L presented in this paper can be used to evaluate a researcher. It's more reasonable than the current research assessment indexes such as the number of publications and the numbers of so-called high-quality journal publications and the amount of granted funds and so on. The synthetic index L reflects the actual value created by a researcher. No artificial maneuver can change them significantly.

A synthetic index L for researcher evaluation considering both the total number of other citations (C) and nonacademic impact (I) and a synthetic evaluation model are proposed in this paper.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

Treatment delays must be avoided, especially in oncology, to assure sustainable high-quality health care and increase the odds of survival. The purpose of this paper is to hypothesize that waiting times would decrease and patients and employees would benefit, when specific lean interventions are incorporated in an organizational improvement approach.

In 2013, 15 lean interventions were initiated to improve flow in a single radiotherapy institute. Process/waiting times, patient satisfaction, safety, employee satisfaction, and absenteeism were evaluated using a mixed methods methodology (2010-2014). Data from databases, surveys, and interviews were analyzed by time series analysis, χ², multi-level regression, and t-tests.

Median waiting/process times improved from 20.2 days in 2012 to 16.3 days in 2014 (p<0.001). The percentage of palliative patients for which waiting times had exceeded Dutch national norms (ten days) improved from 35 (six months in 2012: pre-intervention) to 16 percent (six months in 2013-2014: post-intervention; p<0.01), and the percentage exceeding national objectives (seven days) from 22 to 17 percent (p=0.44). For curative patients, exceeding of norms (28 days) improved from 17 (2012) to 8 percent (2013-2014: p=0.05), and for the objectives (21 days) from 18 to 10 percent (p<0.01). Reported safety incidents decreased 47 percent from 2009 to 2014, whereas safety culture, awareness, and intention to solve problems improved. Employee satisfaction improved slightly, and absenteeism decreased from 4.6 (2010) to 2.7 percent (2014; p<0.001).

Combining specific lean interventions with an organizational improvement approach improved waiting times, patient safety, employee satisfaction, and absenteeism on the short term. Continuing evaluation of effects should study the improvements sustainability.

The empirical properties of benchmark revisions to key US macroeconomic aggregates are examined. News versus noise impact of revisions is interpreted via the cointegration property of successive benchmark revisions. Cointegration breaks down in the last two years before a benchmark revision. Hence, we conclude that there is some information content in benchmark revisions. This last point is illustrated by reporting that inflation forecasts could be improved by the addition of a time series that reflects benchmark revisions to real GDP. Standard backward- and forward-looking Phillips curves are used to explore the statistical significance of benchmark revisions.