scholarly journals Multidimensional Connection Cloud Model Coupled with Improved CRITIC Method for Evaluation of Eutrophic Water

2022 ◽  
Vol 2022 ◽  
pp. 1-12
Author(s):  
Daguo Wu ◽  
Jiahui Yan ◽  
Mingwu Wang ◽  
Guangyao Chen ◽  
Juliang Jin ◽  
...  
Keyword(s):  
Cloud Model ◽  
Water Environment ◽  
Correlation Method ◽  
Evaluation Standard ◽  
Connection Degree ◽  
Appropriate Treatment ◽  
Proposed Model ◽  
Eutrophic Water ◽  
Classification Boundary ◽  
Criteria Importance

The degree of eutrophication in the water environment is deepening. For the appropriate treatment of eutrophication, it is essential to evaluate it accurately. However, the evaluation of eutrophication has not been well solved because it is full of uncertainty. Herein, a multidimensional connection cloud model, combined with the improved CRITIC (Criteria Importance Through Inter-criteria Correlation) method, was put forward here to assess water eutrophication and depict the randomness, ambiguity, and interaction of evaluation factors. First, an improved CRITIC was adopted to determine indicator weight so that the correlation among different indicators and more information were depicted. Secondly, a multidimensional connection cloud was simulated to characterize fuzzy indicators and ambiguous classification boundary values according to classification criteria. Next, the connection degree was calculated relative to the evaluation standard. The eutrophication grade was specified under the “maximum connection degree” principle. At last, the effectiveness and practicality of the model proposed here were affirmed by two cases and comparisons with supplementary methods. The results suggest that the proposed model can avoid shortcomings of the original CRITIC method and cloud model, and make the assessment result more realistic.

scholarly journals Risk Evaluation of Debris Flow Hazard Based on Asymmetric Connection Cloud Model

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xinyu Xu ◽  
Mingwu Wang ◽  
Yafeng Li ◽  
Libiao Zhang
Keyword(s):  
Risk Assessment ◽  
Debris Flow ◽  
Cloud Model ◽  
Reliability And Validity ◽  
Complex Problem ◽  
Evaluation Standard ◽  
Classification Boundary ◽  
Asymmetric Connection ◽  
Interval Lengths ◽  
Debris Flow Hazard

Risk assessment of debris flow is a complex problem involving various uncertainty factors. Herein, a novel asymmetric cloud model coupled with connection number was described here to take into account the fuzziness and conversion situation of classification boundary and interval nature of evaluation indicators for risk assessment of debris flow hazard. In the model, according to the classification standard, the interval lengths of each indicator were first specified to determine the digital characteristic of connection cloud at different levels. Then the asymmetric connection clouds in finite intervals were simulated to analyze the certainty degree of measured indicator to each evaluation standard. Next, the integrated certainty degree to each grade was calculated with corresponding indicator weight, and the risk grade of debris flow was determined by the maximum integrated certainty degree. Finally, a case study and comparison with other methods were conducted to confirm the reliability and validity of the proposed model. The result shows that this model overcomes the defect of the conventional cloud model and also converts the infinite interval of indicators distribution into finite interval, which makes the evaluation result more reasonable.

scholarly journals Ensemble of Deep Capsule Neural Networks: An Application to Pneumonia Prediction

2022 ◽  
Author(s):  
Jyostna Bodapati ◽  
Rohith V N ◽  
Venkatesulu Dondeti
Keyword(s):  
Performance Measures ◽  
Laboratory Testing ◽  
Deep Neural Network ◽  
Routing Algorithm ◽  
Experimental Studies ◽  
Single Model ◽  
Appropriate Treatment ◽  
Pediatric Pneumonia ◽  
Proposed Model ◽  
Pneumonia Diagnosis

Abstract Pneumonia is the primary cause of death in children under the age of 5 years. Faster and more accurate laboratory testing aids in the prescription of appropriate treatment for children suspected of having pneumonia, lowering mortality. In this work, we implement a deep neural network model to efficiently evaluate pediatric pneumonia from chest radio graph images. Our network uses a combination of convolutional and capsule layers to capture abstract details as well as low level hidden features from the the radio graphic images, allowing the model to generate more generic predictions. Furthermore, we combine several capsule networks by stacking them together and connected them with dense layers. The joint model is trained as a single model using joint loss and the weights of the capsule layers are updated using the dynamic routing algorithm. The proposed model is evaluated using benchmark pneumonia dataset\cite{kermany2018identifying}, and the outcomes of our experimental studies indicate that the capsules employed in the network enhance the learning of disease level features that are essential in diagnosing pneumonia. According to our comparison studies, the proposed model with Convolution base from InceptionV3 attached with Capsule layers at the end surpasses several existing models by achieving an accuracy of 94.84\%. The proposed model is superior in terms of various performance measures such as accuracy and recall, and is well suited to real-time pediatric pneumonia diagnosis, substituting manual chest radiography examination.

scholarly journals Sustainable procurement practices in the supplier selection process: an exploratory study in the context of Brazilian manufacturing companies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alex Moysés Barbanti ◽  
Rosley Anholon ◽  
Izabela Simon Rampasso ◽  
Vitor William Batista Martins ◽  
Osvaldo Luiz Gonçalves Quelhas ◽  
...  
Keyword(s):  
Supplier Selection ◽  
Local Community ◽  
Manufacturing Sector ◽  
Selection Process ◽  
Correlation Method ◽  
Manufacturing Companies ◽  
Content Type ◽  
Sustainable Procurement ◽  
Starting Point ◽  
Criteria Importance

Purpose This paper aims to evaluate the adoption of sustainable procurement practices adopted by Brazilian manufacturing companies in supplier selection; additionally, it is aimed to understand which of these practices enable a better differentiation of the analysed companies. Design/methodology/approach A systematic literature review was performed to compose the theoretical base of this research. In addition, a detailed study of ISO 20400 standard was conducted. The guidelines of ISO 20400 were used as a base to structure a questionnaire used in a survey with professionals working in procurement sphere of manufacturing companies in Brazil. The data were analysed via frequency and CRITIC (Criteria Importance Through Intercriteria Correlation) method. Findings A moderate dispersion in the adoption level of sustainable procurement practices in supplier selection process of the manufacturing companies was observed; in practices associated with social aspects, the dispersion is greater. A negative issue to be highlighted is that almost 20% of analysed companies did not even considered in their supplier selection process if their candidates accomplish philanthropic activities, generate jobs in local community and fulfill the Universal Declaration of Human Rights of United Nations (UN). Those two last practices are the ones with the best capacity to differ the companies in the sample. Originality/value There are few studies that focuses on understanding the adoption of sustainable procurement practices in manufacturing companies' supplier selection process. The main contribution of this study to the literature is to evidence that social requirements in supplier selection process are considered in a clear and well-structured form only by few Brazilian manufacturing companies. Despite the sample size, companies analysed in this research are prominent organisations in manufacturing sector. Thus, if this situation occurs in these companies, a more critical scenario will be evidenced in other organisations. This study has implication for practice and academy. For companies' managers, information present here can be used to debate the theme in the organisational context and the nine practices and scale can be used to perform a critical analysis of company's practices. For researchers, the information present here can be used as starting point for futures studies.

scholarly journals QUANTUM FOG CLOUD MODEL IN INTERNET OF THINGS WITH ANALYSIS OF GREEN COMPUTING

2017 ◽  
Vol 5 (1) ◽  
pp. 230-238
Author(s):  
Sayantan Gupta
Keyword(s):  
Internet Of Things ◽  
Cloud Model ◽  
Modern Society ◽  
Green Computing ◽  
Modern World ◽  
Security Issues ◽  
Proposed Model ◽  
Implementation Techniques ◽  
The Many ◽  
The Internet Of Things

The technology of Quantum Green Computing has been discussed in this paper. It also discusses the need of the many implementation techniques and approaches in relation with Fog-Cloud Computing. Moreover, we would like to introduce the latest algorithms like Stack Algorithm, Address Algorithm and many others which will help in the analysis of Green-Quantum Computing Technology in the modern society and would create a technological revolution. With the Internet of Things rising in the modern world time, new security issues have also been developed. So, our proposed Model the Fog-Things Model will help us to determine the security issues and indeed secure the entire IoT network.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

scholarly journals Biobjective Emergency Logistics Scheduling Model Based on Uncertain Traffic Conditions

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Youqiang Sun ◽  
Yeqing Ren ◽  
Xingjuan Cai
Keyword(s):  
Cloud Model ◽  
Traffic Volume ◽  
One Dimension ◽  
Trajectory Data ◽  
Inference Procedure ◽  
Traffic Conditions ◽  
Mutation Operators ◽  
Scheduling Model ◽  
Emergency Logistics ◽  
Proposed Model

Emergency logistics scheduling appears more and more important in modern society because of frequent occurrence of unpredictable disasters. Most of the existing studies consider a certain emergency logistics scheduling model, and most of them are based on an ideal scenario. Considering the uncertain traffic condition and the real road condition, a biobjective emergency logistics scheduling model is proposed, which includes two objectives: transportation time and transportation cost. The uncertainty of the proposed model is reflected in two aspects: the occurrence time of emergencies and the traffic volume predicted by the cloud model. The numerical characteristics of traffic information are abstracted from the spatial-temporal trajectory data by the reverse cloud model, and the inference procedure of the one-dimension cloud model further predicts the uncertain traffic volume using the numerical characteristics. In addition, the crossover and mutation operators of multiobjective evolutionary algorithms are modified to solve the model. The experimental results show that the inference procedure of one-dimension cloud model can accurately predict the traffic volume at the departure time; and the proposed model is more reasonable than the existing scheduling models; at the same time, the improved NSGA-II can also provide superior schemes in different departure times and traffic conditions for decision makers.

scholarly journals Application of a Cloud Model-Set Pair Analysis in Efficacy Assessment for Diabetic Ulcers

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Le Kuai ◽  
Jia-qi Xing ◽  
Jing-ting Zhang ◽  
Xun-zhe Xu ◽  
Min-feng Wu ◽  
...  
Keyword(s):  
Cloud Model ◽  
Assessment Method ◽  
Set Pair Analysis ◽  
Connection Degree ◽  
Diabetic Ulcers ◽  
Efficacy Assessment ◽  
Model Set ◽  
Importance Assessment ◽  
Pair Analysis ◽  
Assessment Results

Because treatment of diabetic ulcers includes various uncertainties, efficacy assessments are needed and significant. In previous studies, set pair analysis (SPA) has been applied to the efficacy assessments of traditional Chinese medicine (TCM) that pick out uncertainties related to the development and prognosis of disease. Optimized clinical protocols of SPA improve clinical efficacy. In the article, cloud model (CM) is employed to improve SPA, and a novel efficacy assessment method for a treatment of diabetic ulcers is proposed based on the cloud model-set pair analysis (CM-SPA). It is recommended to replace connection degree (CD) with cloud connection degree (CCD) that the efficacy assessment results are shown as normal clouds. Then, three diabetic ulcers patients treated with TCM made importance assessment by both CM-SPA and AHP based SPA. The comparison of assessment results shows that the CM-SPA is efficacious for the efficacy assessment of a treatment for diabetic ulcers and the results will be more scientific and accurate via CM-SPA.

scholarly journals A Hybrid MCDM Model to Evaluate and Classify Outsourcing Providers in Manufacturing

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1962
Author(s):  
Ching-Fang Liaw ◽  
Wan-Chi Jackie Hsu ◽  
Huai-Wei Lo
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Operating Costs ◽  
Visual Rating ◽  
Proposed Model ◽  
Ideal Solutions ◽  
Four Levels ◽  
Criteria Importance ◽  
Outsourcing Strategies

It is a common practice for enterprises to use outsourcing strategies to reduce operating costs and improve product competitiveness. Outsourcing providers or operators need to be aware of environmental protection and make products comply with the restrictions of international environmental regulations. Therefore, this study proposes a set of multiple criteria decision-making (MCDM) approaches for systematic green outsourcing evaluation. First, a team of experts is established to discuss mutually dependent relationships among criteria, and the decision-making trial and evaluation laboratory (DEMATEL) technique is applied to generate subjective influential weights. Then, a large amount of data from outsourcing providers is collected, and the criteria importance through the intercriteria correlation (CRITIC) method is used to obtain the objective influential weights. Finally, a novel classifiable technique for ordering preference based on similarity to ideal solutions (classifiable TOPSIS) is proposed to integrate the performance of green outsourcing providers and classify them into four levels. The classifiable TOPSIS improves the shortcomings of conventional TOPSIS and establishes a visual rating diagram to help decision-makers to distinguish the performance of outsourcing providers more clearly. Taking a Taiwanese multinational machine tool manufacturer as an example, the performance of outsourcing providers related to manufacturing activities was investigated to demonstrate the effectiveness and applicability of this proposed model.

scholarly journals Ecological Environment Evaluation of Forest Ecosystem Nature Reserves Using an Unweighted Cloud Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1905
Author(s):  
Mengshi Xiang ◽  
Xiaonan Lin ◽  
Xiyan Yang ◽  
Shanghong Zhang
Keyword(s):  
Quantitative Evaluation ◽  
Forest Ecosystem ◽  
Nature Reserve ◽  
Cloud Model ◽  
Water Environment ◽  
Past Research ◽  
Research Area ◽  
Indicator System ◽  
Nature Reserves ◽  
Ecological Environment

The ecological environment is the foundation of human survival and development, and forest ecosystem nature reserves play an important role in the protection of the ecological environment. The evaluation of forest ecosystem nature reserves facilitates the formulation of relevant management policies. At present, the evaluation of the ecological environment of forest ecosystem nature reserves is mainly based on detailed evaluation of some elements of the ecological environment, rather than on a comprehensive quantitative evaluation that reflects the ecological environment in many aspects. To address this shortcoming, the quantitative evaluation indicator system of comprehensive ecological environment for forest ecosystem nature reserves was established based on the water, air, soil, and biological environments, according to the consensus on ecological environment in the past research and characteristics of the research area. The weight is still a necessary and important link in the evaluation of forest ecosystem nature reserves, but the accuracy of the weight results is difficult to get a scientific judgment. To prevent the evaluation results being influenced by weighting uncertainty, an unweighted cloud model was constructed to provide an evaluation mechanism without weight. The ecological environment evaluation was then carried out using the unweighted cloud model, taking Songshan Nature Reserve as a research area. The results show that the grades of the ecological environment of Songshan Nature Reserve are 21% excellent, 67% good, and 12% qualified, and that the state of the ecological environment is stable and performing well. The evaluation results for the grades of the environmental dimension layers are water environment > soil environment > biological environment > air environment. The study’s research results can provide theoretical support for the evaluation of forest ecosystem nature reserves, and for evaluation work in general when weights are difficult to determine or uncertain.

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