Search

Numerous countries are implementing building-integrated photovoltaic (BIPV) technology to enhance the energy performance of buildings, as new energy sources have attracted global interest. BIPV residential programs are an essential method to alleviate energy stress and promote energy transition in buildings; however, the high level of technology and capital investment required have hampered their marketization. Although certain obstacles have been examined by researchers, there remains a lack of studies concerning risk assessment in the context of the development of BIPV residential projects. Therefore, this study strives to develop a risk assessment model for the development of these projects. First, a risk evaluation index system is proposed by identifying and analyzing the risks associated with the development of BIPV residential projects, following the lines of risk identification–risk analysis–risk evaluation–risk management. Second, the DEMATEL-ANP-gray cluster analysis was utilized to construct the development risk assessment model. Finally, a case study demonstrates that the methodology proposed in this study can effectively solve the issues associated with correlating risk factors and the quantification of the magnitude of risks in the development of BIPV residential projects. This study will serve as a valuable reference for architect-urban developers and engineer contractors to formulate risk governance countermeasures for BIPV residential projects as it provides a framework for assessing the risk associated with their development. [ABSTRACT FROM AUTHOR]

Copyright of Food Research & Development is the property of Food Research & Development Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Numerous countries are implementing building-integrated photovoltaic (BIPV) technology to enhance the energy performance of buildings, as new energy sources have attracted global interest. BIPV residential programs are an essential method to alleviate energy stress and promote energy transition in buildings; however, the high level of technology and capital investment required have hampered their marketization. Although certain obstacles have been examined by researchers, there remains a lack of studies concerning risk assessment in the context of the development of BIPV residential projects. Therefore, this study strives to develop a risk assessment model for the development of these projects. First, a risk evaluation index system is proposed by identifying and analyzing the risks associated with the development of BIPV residential projects, following the lines of risk identification–risk analysis–risk evaluation–risk management. Second, the DEMATEL-ANP-gray cluster analysis was utilized to construct the development risk assessment model. Finally, a case study demonstrates that the methodology proposed in this study can effectively solve the issues associated with correlating risk factors and the quantification of the magnitude of risks in the development of BIPV residential projects. This study will serve as a valuable reference for architect-urban developers and engineer contractors to formulate risk governance countermeasures for BIPV residential projects as it provides a framework for assessing the risk associated with their development.

As a new kind of functional fiber, hollow coffee carbon polyester (HCCP) has the advantages of antibacterial and warmth retention properties. HCCP's wear-ability performances in knitted textiles were studied by changing the specifications of the raw materials, blending ratios and knitted structures. Plain knit, interlock knit and Ponte knit fabrics were prepared with compact siro-spun HCCP/cotton yarns in five different blended ratios. Eight groups of experiments were conducted to test the performances of the mechanical properties, comfortable capability and antibacterial behavior. Then a comprehensive wear-ability evaluation was made based on the grey clustering analysis method. Results revealed that fabrics with a higher blended ratio of HCCP showed more preferred performance in terms of bursting strength, air permeability, moisture absorption, warmth preservation and antibacterial property, but the anti-pilling performance showed a downward trend. Compared to plain stitch, the interlock knit and Ponte knit fabrics showed a visibly better result. [ABSTRACT FROM AUTHOR]

The leather production from paiche skins (Arapaima gigas) has recently grown in Peru, as this allows adding value and earnings from this Amazonian aquaculture waste. The development of this process requires that the tanning techniques could preserve environment as these are meant to take place in Amazonian zones. The present study evaluated the environmental performance of two chrome-free tanning techniques of paiche skins compared with traditional chrome tanning technique, developed at pilot scale by CITEccal Lima. The evaluation was carried out using environmental performance indicators (EPI), analyzed and compared using the grey clustering method, identifying coefficients (σ) respecting to the stablished classes in the study (λ1 - good, λ2 - regular, λ3 - deficient). As result, the two chrome-free tanning techniques showed a better environmental performance than the traditional chrome tanning technique (σ - 0.54, class λ2). The optimized tanning technique applying phenolic compounds had the best environmental performance (σ - 0.98, class λ1), and its values for each environmental performance indicator per 1000 kg of initial processed paiche skin were: 30.0 m3 for water consumption, 815.0 kg of chemical products applied, 2022.7 kWh for energy consumption, 105.5 kg of solid wastes; and from wastewater characterization: 2780.9 mg/L for BOD, 11682.9 mg/L for COD and non-detectable chromium. On the basis of these results, its transfer is recommended, including a wastewater treatment system and environmental management measures implementation. [ABSTRACT FROM AUTHOR]

The intelligent development of smart industrial parks (SIPs) can not only promote the development of smart cities, but also promote the development of intelligent large-scale buildings. China is strengthening the construction of SIPs; however, the development of SIPs is limited. Due to different understandings of SIPs, the intelligence level of each SIP varies greatly. It is necessary to develop a SIP intelligence level assessment model to check these limitations. Most of the existing evaluations focus on the qualitative evaluation of the overall intelligence level of SIPs, ignoring the influence of each individual dimension. Therefore, this study used quantitative methods to measure the intelligence level of SIPs from the overall and dimensional levels. The evaluation method included five processes: (1) Classifying the intelligence level of SIPs through expert interviews; (2) Using the literature analysis method to identify various dimensions of the intelligence level; (3) Using literature analysis and expert interviews to determine the evaluation indicators (4) Weighting indicators based on correlation and induced ordered weighted average (IOWA) operator; (5) Using grey clustering analysis to calculate the overall intelligence performance of SIPs and each dimension. Finally, the developed model was verified by Z SIP. The analysis results show that the developed model can measure both overall and dimensional performance of SIPs, and demonstrated that enterprise information services, public information services, SIP security, and energy consumption monitoring platform construction make the greatest contributions to the improvement of the intelligence level. Our research results will help to improve the intelligence level of SIPs, and lay the foundation for the determination of the operating costs of SIPs and the formulation of national standards related to SIPs in the future. [ABSTRACT FROM AUTHOR]

With the deepening of exploration and development, the lithology of the drilling strata becomes more complex. Using the digital technology for processing the data obtained by the cuttings logging helps to provide accurate lithological data and evaluate clamping of the formation interface. However, the existing logging digitization technology relies on element logging and is restricted by the large error of the cuttings logging instrument, the disunity of multi-source data, and the poor pertinence of data. In this paper, we propose an intelligent identification model of the cuttings logging based on grey clustering analysis. First, the grey prediction method is used for processing the in-depth instrument data, and then the extended Kalman filter is used to standardize and unify the multi-instrument data. Finally, the identification model based on the grey clustering method is applied to identify the cuttings. The results of the simulation analysis and field application show that the identification model proposed in this paper can accurately identify the rock strata. Compared with the traditional methods, the accuracy of the proposed has been greatly improved. The field applications show that the model provides important theoretical support for the development of rock-cutting digital technology. [ABSTRACT FROM AUTHOR]

The intelligent development of smart industrial parks (SIPs) can not only promote the development of smart cities, but also promote the development of intelligent large-scale buildings. China is strengthening the construction of SIPs; however, the development of SIPs is limited. Due to different understandings of SIPs, the intelligence level of each SIP varies greatly. It is necessary to develop a SIP intelligence level assessment model to check these limitations. Most of the existing evaluations focus on the qualitative evaluation of the overall intelligence level of SIPs, ignoring the influence of each individual dimension. Therefore, this study used quantitative methods to measure the intelligence level of SIPs from the overall and dimensional levels. The evaluation method included five processes: (1) Classifying the intelligence level of SIPs through expert interviews; (2) Using the literature analysis method to identify various dimensions of the intelligence level; (3) Using literature analysis and expert interviews to determine the evaluation indicators (4) Weighting indicators based on correlation and induced ordered weighted average (IOWA) operator; (5) Using grey clustering analysis to calculate the overall intelligence performance of SIPs and each dimension. Finally, the developed model was verified by Z SIP. The analysis results show that the developed model can measure both overall and dimensional performance of SIPs, and demonstrated that enterprise information services, public information services, SIP security, and energy consumption monitoring platform construction make the greatest contributions to the improvement of the intelligence level. Our research results will help to improve the intelligence level of SIPs, and lay the foundation for the determination of the operating costs of SIPs and the formulation of national standards related to SIPs in the future.

Currently, there are two main problems with the evaluation of college English teaching quality: the lack of a complete evaluation system, and the limited quantification of evaluation indices. To solve the problems, this paper sums up the evaluation contents of college English teaching quality, and identifies the factors affecting the teaching quality of college English. On this basis, an improved evaluation system was established for the assessment of college English teaching quality, which is theoretically innovative. Next, grey clustering analysis and entropy weight method were combined into a robust evaluation model for college English teaching quality. This research provides a new and applicable solution to quantification of college English teaching quality. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the lack of reliability data and the uncertain factors in the product development stage,a reliability allocation model based on grey system theory was proposed. Considering 6 effecting factors such as the importance,complexity, technology development level, manufacturing level, working time and environmental conditions,combining with the expert experience and known reliability data,the relative failure relationship among fuel cell vehicle subsystems was elevated using improved method of solving index weight based on grey correlation. The reliability of each subsystem was allocated according to the comprehensive grey evaluation value. Compared with the actual failure data,the validity of this model was verified.

The Haier's environmental invest have a positive impact on Economic and environmental performance. The pollution and waste created by enterprises has increasingly become a serious problem as it leads to deterioration of ecological environment and climate change. The enterprises are tend to ignore the impact of toxic waste on the environment, and the lack of initiative from governing bodies to fulfill the environmental responsibility of enterprises will inevitably lead to serious damage to the natural environment. To perform their environmental responsibility, calculating the costs and benefits of environmental protection invest is an important content of enterprises' performance assessment. In the present paper, Haier enterprises' environmental responsibility was analyzed by calculating their environmental protection invest, reduction of environmental pollutants emission, and optimization of energy from 2007 to 2011. Grey clustering evaluation model was constructed using selected environmental cost and benefit indices, the evaluation results were analyzed, and the effects of environmental invest on environmental benefit in enterprises' energy-saving emission and low carbon development were discussed. The study results showed that the enterprises' environmental invest have a long-term impact on business performance. Because of increasing investments in environmental cost, Haier's environmental performance has improved significantly, and the impacts of environmental investment are perennial. The enterprises' environmental awareness and contribution on prevention of toxic waste resulted in increased economy, and improvement in energy consumption indicators, pollutant emission indicators, and greenhouse gases emission indicators. [ABSTRACT FROM AUTHOR]

Today's leading businesses have understood the role of 'social' in their everyday activity. Online social networks (OSN) and social media have melt and become an essential part of every firm's concern. Brand advocates are the new leading triggers for company's success in online social networks and are responsible for the long-term engagement between a firm and its customers. But what can it be said about this impressive crowd of customers that are gravitating around a certain brand advocacy or a certain community? Are they as responsive to a certain message as one might think? Are they really impressed by the advertising campaigns? Are they equally reacting to a certain comment or news? How they process the everyday grey knowledge that is circulating in OSN? In fact, how impressionable they are and which are the best ways a company can get to them? To give an answer to these questions, the present paper uses grey systems theory for spreading the customer's crowd into groups based on how impressionable they are by commercials, ads, videos and comments in OSN. [ABSTRACT FROM AUTHOR]

Precision in flow cytometry depends on many factors, the first of which is accurate and stable positioning of the hydrodynamically focused cells. However, no method exists to evaluate the stability of laminar flow and single-cell flow in the flow chamber of the flow cytometer directly because of the small size of the rectangular channel of the flow chamber. In this paper, a method of high-speed particle image velocimetry is proposed to solve this problem. The velocity stability of the particles in the flow chamber is used to evaluate the flow stability of the fluid path of the flow cytometer. The side scattering images of particles are obtained by a high-speed camera. Upon exposure, cells were imaged at random positions in the flow cell, resulting in four different types of the images: blank, inadequate, normal, or overlapped. Normal images were identified utilizing a grey cluster analysis algorithm based on trapezoid whitenization weight functions. A mid-point method is applied to determine the length of the particle track at a fixed exposure time. The variation of the trajectory lengths of the normal images are used to evaluate the stability of the liquid path. Experiments are carried out to verify the feasibility of our method in which different diameter microspheres at different flow rates. The results indicate that the standard deviation and relative standard deviation of the trajectory lengths can be used as the evaluation indices of the liquid path stability of the flow cytometer. © 2016 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

The article presents the model of successors' competencies in family firms. The model was created on the basis of empirical data collected in Poland and analysed with the use of Grey Clustering Analysis. At the first i.e. an empirical stage of the studies, a list of competences was identified which are estimated as significant for the successors. At the second stage, on the basis of significance assessment of the competences distinguished by the successors, a list of distinguished competences according to their significance level in a succession process was sorted out. At the third stage, using the basis of grey systems theory, the competences were classified according to their relation of similarities. As the result the successors' competency model was proposed. [ABSTRACT FROM AUTHOR]

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios.

This study aims to evaluate and select the optimum comprehensive performances of metal wire composite fabrics (composite fabrics) made from stainless steel filaments and staple fibres yarns. Grey clustering analysis (GCA) was used to investigate and evaluate the electromagnetic shielding effectiveness (EMSE) and wearability of 11 different composite fabrics. Six effect factors on the performances of the fabrics, namely EMSE, breathability, moisture permeability, water-washing durability, and warp-way and weft-way shrinkages, were tested and analysed. Research shows that the metal content and metal mesh grid size of fabrics mostly affect their comprehensive performances. GCA suggests that composite fabrics with 14–19% metal content and 0.4–0.9 mm2 metal mesh are the best design qualities for both EMSE and wearability. [ABSTRACT FROM AUTHOR]

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities. [ABSTRACT FROM AUTHOR]

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios. [ABSTRACT FROM PUBLISHER]

This paper takes 30 provinces in China as the research objects, and by using the data of CDM projects from 2005 to 2012, the characteristics of regional differences have been analyzed. According to the Q-Q-S evaluation principles, the measure index system is firstly proposed from the dimensions of quantity, quality and reduction scale. Then grey incidence and grey clustering analysis methods are used to do the further research; at last the regional differences and characteristics have been discussed. The conclusions are as follows: (1) the comprehensive development levels of CDM projects -in different provinces in China are relatively weak; (2) the development level in quantity, quality and reduction scale dimensions of CDM projects varies with the provinces obviously; (3) the development of CDM projects in eastern, central and western regions presents a strong disequilibrium. The eastern and western regions have the advantages in quality, reduction scale and the comprehensive development of CDM projects. However, the level of the central region is relatively low. [ABSTRACT FROM AUTHOR]

Abstract: Deng proposed grey clustering analysis (GCA) in 1987. Later, Jin presented a new method in 1993, called grey relational clustering (GRC) method that combined grey relational analysis with clustering. However, the GRC method cannot use a tree diagram to make appropriate classification decisions without re-computation. This study thus attempts to combine GRC and hierarchical clustering analysis. Given the existence of an excess of medical resources in the Taipei area, this study attempts to understand the degree of concentration of medical resources in this area. Specifically, this study applies a geographical information system (GIS) to present the geographical distribution of hospitals in Taipei. Additionally, a new-type of cluster analysis, known as hierarchical grey relation clustering analysis, is used to analyze the distribution of hospitals and understand how they compete with one another. The analytical results demonstrate that hierarchical grey relation clustering analysis is a suitable method of analyzing geographical position. Tree diagrams can help policymakers make appropriate classification decisions without re-computation. The study results can inform hospitals of their competitors and help them to develop appropriate responses. Additionally, the analytical results can also provide a reference to government or hospital policymakers to help them position hospitals in areas, thus achieving a better distribution of medical resources in Taipei. [Copyright &y& Elsevier]

With respect to increasing the evaluated sensitivity, this study employs the Grey Clustering Analysis (GCA) to refine the Grey Relational Analysis (GRA) not only to detect the slight fluctuation in the ten economies through evaluating the 7-year major ten nation-performance competitive indicators in the ten economies comprised of two developed economies (USA and Japan), four booming economies (Four Asia Tigers) and four emerging economies (BRIC) but also, further, to create the innovative Grey-Clustering Macroeconomic Assessment Model (GCMAM). According to the measured results of the Grey Clustering Analysis (GCA), the comprehensive 7-year nation-performance of top 5 ranking originally are Singapore, USA, Japan, Hong Kong and Taiwan. However, through cross-employ comparison of the Grey Clustering Analysis (GCA) and Grey Relational Analysis (GILA), Singapore, USA, China, Brazil and Korea have been the new top 5 economies through the evaluation of the innovative Grey-Clustering Macroeconomic Assessment Model (GCMAM). [ABSTRACT FROM AUTHOR]

Abstract: An intelligent decision-making method has been put forward to deal with overseas project loans decision-making, which is based on grey clustering analysis method. The grey clustering analysis is an algorithm based on the risk classification causes risk index system which clusters risk of harm degree into grey clustering risk index system, and realizes the decision overseas project loans to measure the risk accurately, and also can measure the results as a sample data set clustering analysis to get to the loan plan for clustering center decision model to complete the project implementation plan outside loans. The effectiveness of the method through the contrast experiment has been validated. [Copyright &y& Elsevier]

A method is proposed for dissolved gases forecast and fault diagnosis in oil-immersed transformers using grey prediction-clustering analysis. Incipient faults can produce hydrocarbon molecules and carbon oxides due to the thermal decomposition of mineral oil, cellulose and other solid insulation. Dissolved gas analysis is employed to detect and monitor abnormal conditions in oil-immersed power transformers. However, the procedure takes a long time to decompose overall key gases and monitor conditions. The grey prediction GM(1, 2) model uses the variant information of hydrogen to forecast the further trends of both combustible and non-combustible gases. Grey clustering analysis is applied to diagnose internal faults including thermal faults, electrical faults and faults involving cellulose degradation. Numerical tests with field gas records were conducted to show the effectiveness of the proposed model, and are easy to implement with the help of portable devices. [ABSTRACT FROM AUTHOR]

The forest ecological security of the Yangtze River Economic Belt has an important influence on improving the regional environment and promoting the sustainable development of the social economy. Therefore, the aim of this paper is to provide countermeasures and suggestions for improving the level of regional ecological security by quantitatively analyzing the forest ecological security status of the Yangtze River Economic Belt and the tributaries of the Yangtze River. Using three main aspects, i.e., resources, socio-economic pressure and maintenance response, the study established 26 indicators that affect the forest ecological security of 11 provinces (cities) in the Yangtze River Economic Belt. The index weights were determined by principal component analysis, and the forest ecological security levels of 11 provinces (cities) in the Yangtze River Economic Belt were classified and evaluated by the grey clustering method. The results show the following: (1) the principal component analysis determined the weight of the three aspect indicators. The order is as follows: resource index > socio-economic pressure index > maintenance response index. This means that the basic environmental condition which the forest growth depends on and quality and quantity of forest is most important, and the maintenance activities performed by human beings in forest resources need to be strengthened. (2) The level of the forest ecological security in all the provinces (cities) of the Yangtze River Economic Belt is relatively good, with an upward trend. The level of forest ecological security in each province (city) decreases from the upper reaches of the Yangtze River basin to the lower reaches, and the level of forest ecological security in the central cities is lower. (3) The resource index, socio-economic pressure index and maintenance response index of all the provinces and cities showed an upward trend in these four years. The provinces with a significantly higher forest resource index include Yunnan and Guizhou. Shanghai, Chongqing, Sichuan, Hunan and Jiangxi were the provinces with significantly higher socio-economic pressure values; Yunnan province, Shanghai, Jiangxi Province and Hubei province were the provinces with higher forest maintenance response values. [ABSTRACT FROM AUTHOR]

Most concrete dams have seepage problems to some degree, so it is a common strategy to maintain ongoing monitoring and take timely repair measures. In order to grasp the real operation state of dam seepage, it is vital to analyze the measured data of each monitoring indicator and establish an appropriate prediction equation. However, dam seepage states under the load and environmental influences are very complicated, involving various monitoring indicators and multiple monitoring points of each indicator. For the purpose of maintaining the temporal continuity and spatial correlation of monitoring objects, this paper used a multi-indicator grey clustering analysis model to explore the grey correlation among various indicators, and realized a comprehensive evaluation of a dam seepage state by computation of the clustering coefficient. The case study shows that the proposed method can be successfully applied to the health monitoring of concrete dam seepage. [ABSTRACT FROM AUTHOR]