Dynamic Decision-Making Method for Design Concept Evaluation Based on Sustainability Criteria

Previous studies of operating performance of listed companies usually adopt static comprehensive evaluation method but not dynamic evaluation method. Besides, the evaluation information is aggregated in a simple weighted method, without integration of management tool. Considering these two deficiencies, this paper puts forward a dynamic incentive evaluation model and applies it in the comprehensive evaluation of the operating performance of listed companies. The paper first introduces dynamic incentive evaluation model, and then carries out an empirical study, using the annual reports data (2005-2009) of 13 refrigeration and air-conditioning industry listed companies. The results indicate that, compared with the evaluation results of traditional static method and dynamic method, the evaluation results of dynamic incentive model can reflect the operating performance of listed companies more objectively and comprehensively. Thus this model achieves good evaluation effect and has practical value.

Dynamic evaluation method of water-sealed gas for ultra-deep buried fractured tight gas reservoir in Kuqa Depression, Tarim Basin, China

Low back pain of caregiver has serious problem in welfare field. Transfer motion is thought as a cause of the low back pain, and it is necessary to reduce the lumbar burden. Also practical quantification method of lumbar burden is required strongly. This study aims to develop a practical and dynamic evaluation method of lumber burden by measuring surface muscle potential of the Erector spine muscle. This study delas with transfer motion and divide it into three motions, "lifting motion", "rotation a motion" and "unloading motion". Experiments have been conducted to show that "lifting motion" and "rotation a motion" can be evaluated by the surface muscle potential of the erector spine muscle by previous studies. This paper focuses on the "unloading motion" and, the relationship between the load and the "surface muscle potential of the erector spine muscle" is confirmed by experiments. It is also shown that the lumbar burden during "unload motion" is possible to be evaluated by using the surface muscle potential. In addition, this study evaluates, whether dynamic evaluation by using the proposed evaluation method is possible. Because caregivers are required to slow down during the "unoad motion", inertial force increass the load during decelerated motion. For an example, a dynamic evaluation in the case of deceleration during the "unloading motion" were confirmed by experiments. Conducting experiments, we found that the value of the potential of the surface of the erector spine was increased during slow down motion. This result indicates that the lumbar burden can be increased by decelerated motion. This study showed the effectiveness of the dynamic evaluation method by surface muscle potential.

Photovoltaic-storage integrated systems, which combine distributed photovoltaics with energy storage, play a crucial role in distributed energy systems. Evaluating the health status of photovoltaic-storage integrated energy stations in a reasonable manner is essential for enhancing their safety and stability. To achieve an accurate and continuous assessment of the health status of photovoltaic-storage integrated energy stations, a dynamic evaluation method is proposed in this study. This method integrates both subjective and objective characteristics. Initially, considering the evaluation needs of low-carbon operation and health status for photovoltaic-storage integrated energy stations, a comprehensive health status evaluation system is developed. The significance of each indicator is subjectively analyzed, while also considering objective characteristics and sensitivity of indicators. The integration of subjective and objective characteristics is achieved using principles from game theory. Subsequently, through the establishment of the Grey-TOPSIS evaluation model, both positive and negative correlations of the health status of photovoltaic-storage integrated energy stations are determined, resulting in the derivation of a health status vector. Furthermore, the introduction of time-weight vectors and the incorporation of a time dimension enable dynamic evaluation and the comprehensive observation of health status. Finally, the scientific validity and effectiveness of the proposed evaluation method are demonstrated through practical examples, with comparisons made to traditional evaluation methods. The results clearly indicate that this method offers higher sensitivity when evaluating the health of photovoltaic-storage integrated energy stations.

Comparison of Two Different (Quasi-) Dynamic Testing Methods for the Performance Evaluation of a Linear Fresnel Process Heat Collector

In this study, we put forward multilayer behavior evaluation indicator system and dynamic multistage evaluation method based on individual advantage. From the perspective of best to each evaluated entrepreneur to determine each object's evaluation indicator weight vector that reflects advantages and disadvantages, one stage comprehensive evaluation method is put forward. Each stage weight is driven from individual comprehensive value with the thought of best to each entrepreneur, so to rank all the objects on multistage. It is helpful to encourage entrepreneur bearing environment society responsibility and sustainable development. Through calculation example, feasibility and effectiveness of the method is proved.

PurposeThis study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).Design/methodology/approachFirst, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).FindingsIn terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.Originality/valueThe analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

Experiment and optimization of a damping structure system with distributed multiple unidirectional single-particle dampers

Scientific dynamic evaluation of the power load supply capacity of thermal power units is crucial for the safe and economic dispatch of the power grid. This article constructs an evaluation index system for the power load supply capacity of thermal power units. A dynamic evaluation and correction method for the power load supply capacity of thermal power units is proposed based on entropy weight method, analytic hierarchy process, and differential theory, and case calculations are conducted using basic data from three thermal power units. Research has shown that for every 0.1 increase in equipment reliability indicators, the average power supply capacity increases by 1.2 - 3.5 percentage points. And optimizing coal quality indicators by 0.2 units can increase power supply capacity by 3.9 - 6.8 percentage points. The work done in this article has certain reference value for improving the power guarantee capability of thermal power units.

This paper presents simulation-based density forecast evaluation methods using particle filters. The simulation-based dynamic probability integral transformation or log-likelihood evaluation method is combined with the existing density forecast evaluation methods. This methodology is applicable to various density forecast models, such as log stochastic volatility models and affine jump diffusion (AJD) models, for which the probability integral transform or likelihood computation is difficult due to the presence of latent stochastic volatilities. This methodology is applied to the daily S&P 500 stock index. The empirical results show that the AJD models with jumps perform the best for out-of-sample evaluations.

Aiming at the fuzzy and random problems in the process of power quality evaluation, a multi-dimensional and multi rule dynamic weighted power quality cloud evaluation method is proposed on the basis of considering the dynamic characteristics of power quality evaluation indexes. Firstly, we construct a comprehensive evaluation system of power quality, and also establish a reverse cloud model of each qualitative evaluation index of power quality. Then, the multi-dimensional and multi rule dynamic cloud generator of power quality evaluation is constructed by combining different antecedent cloud and consequent cloud with dynamic weighting of evaluation index, and a reasoning framework and algorithm are designed to analyze the uncertain mapping relationship between each evaluation index and quality level in the value domain. The distribution of space and certainty space completes the mapping transformation from quantitative input to dynamic reasoning, and then to quantitative output. The feasibility and effectiveness of the new comprehensive evaluation method for power quality are proved by the comparative analysis of examples, which provide a new idea and method for the efficient evaluation of power quality.

Real-time electrocardiogram (ECG) and blood pressure signal analysis is crucial for cardiovascular health monitoring, particularly in critical care and unsupervised settings. However, challenges such as noise interference, limited user interaction, and difficulties in computing accurate physiological metrics persist. This study proposes a novel framework that integrates real-time signal detection with automatic signal quality evaluation, enabling researchers to manage noise through an interactive interface. By leveraging open-source software and introducing a dynamic statistical method for signal quality evaluation, the framework provides a more adaptable and dataset-independent solution. The study aims to enhance interaction between real-time signals and researchers, evaluate signal quality in real time, and analyze baroreceptor sensitivity. Ultimately, this framework improves the accuracy and reliability of cardiovascular signal analysis, leading to better clinical and research outcomes.

A dynamic testing method for effective bit number evaluation of digitizing signal analyzers is introduced. The technique is valid when, owing to particular working conditions, only a limited number of the sinewave test signal periods can be collected. In such a case other test methodologies can present problems for a correct application. The proposed method is based on a regression algorithm, and by virtue of using the acquisition of a sinewave test signal for a time interval enclosing only three zero crossings of the sinewave, requires a very short computational time. After a brief summary of existing test methodologies, the performances and limits of the proposed method are analyzed and highlighted. To illustrate the application field of the described methodology, preliminary simulated results arising from several devices and real data relative to one digitizer are reported. >

We investigated the feasibility and image quality of dynamic cine-mode imaging of the normal aortic valve using multidetector row computed tomography (MDCT). We acquired contrast-enhanced retrospectively echocardiography (ECG)-gated cardiac MDCT datasets of 35 patients (mean age, 62 years; range, 53-77) who received a transoesophageal echocardiography (TOE) precedent to cardiac bypass graft surgery. Twenty data sets in 5% steps of the R-R interval were reconstructed, and data analysis was performed using a 4D software. Read-out of the MDCT data was performed in parallel and perpendicular planes, similar to TOE standard planes, by 2 independent, blinded readers using a 4-point Likert scale (best score: 4) for the following parameters: image quality of the aortic valve components, contrast media enhancement, contrast media inflow related artifacts, and ECG gating-related artifacts. The aortic valve area (AVA) was measured planimetrically and was compared between TOE and MDCT. The best phase for assessing the open valve using MDCT was at 5% and the closed valve at 65% of the cardiac cycle. The mean image quality scores for cine-mode MDCT ranged between 3.26 and 3.75, with inter-reader agreements ranging between good (kappa = 0.723) and excellent (kappa = 1.00). They did not differ significantly from TOE scores for assessment of the closed and open valve. In transitional phases (close-to-open and open-to-close) TOE performed significantly better when compared with static MDCT images, whereas no significant difference was present between cine-mode presentation of MDCT and TOE. Planimetric AVA measurements correlated significantly between TOE and MDCT (Pearson correlation coefficient, r = 0.96; P < 0.0001). Contrast media inflow-related and ECG gating related artifacts were rated as slightly compromising (scores 3.24 and 3.21). Retrospectively ECG-gated MDCT offers a noninvasive, accurate, and dynamic imaging method for quantitative and qualitative evaluation of the normal aortic valve allowing determination of morphology and function throughout the cardiac cycle. Further studies regarding assessment of diseased valves are necessary.

Early estimation of performance has become necessary to facilitate design of complex multi-core architectures. Performance evaluation based on extensive simulations is time consuming and needs to be improved to allow exploration of different architectures in acceptable time. In this paper, we propose a method that improves the tradeoff between simulation speed and accuracy in performance models of architectures. This method computes during model execution some of the synchronization instants involved in architecture evolution. It allows grouping and abstracting architecture processes and this way significantly reduces the number of simulation events. Experiments show significant benefits from the computation method on the simulation time. Especially, a simulation speed-up by a factor of 4 is achieved in the considered case study, with no loss of accuracy about estimation of processing resource usage. The proposed method has potential to support automatic generation of efficient architecture models.