Journal articles on the topic 'Model quality indices'
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Castillo Canalejo, Ana Ma, and Juan Antonio Jimber del Río. "Quality, satisfaction and loyalty indices." Journal of Place Management and Development 11, no. 4 (October 8, 2018): 428–46. http://dx.doi.org/10.1108/jpmd-05-2017-0040.
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Purpose The main purpose of this research was to develop a universal model to evaluate the perceived value of tourism services and satisfaction with, and loyalty to, destinations from the consumers’ perspective and demonstrated the model’s applicability in this context. Design/methodology/approach Using the structural equation model, cause and effect relationships were identified between the proposed model’s constructs, and indices of quality, satisfaction and loyalty among tourists were estimated. This system was applied to a large set of data collected with a structured questionnaire distributed to tourists visiting the city of Seville through a non-probabilistic sampling by intentional quotas method. In total, 922 valid surveys were obtained. Findings The indices show that tourists who visit Seville report a high level of loyalty to, and satisfaction with, this place because of the perceived quality of a variety of services. It is observed that the perceived quality index is much higher (17.95 per cent) than the expected quality index, so the quality of the service received by the tourist during his/her visit to Seville is described as excellent. Research limitations/implications Regarding this study’s limitations, other variables could have been included that influence tourist satisfaction, such as the climate, the effect of advertising medium, the prices and the emotional components. In addition, surveying tourists’ expectations before their visit is virtually impossible, as is surveying the same tourists again about their perceived value and satisfaction after their visit. Future lines of research could focus on the intersection of information between tourism offer and demand, providing information about an appropriate balance in specific markets. The proposed model can also be applied to other tourism places that are similar to Seville’s tourism offer, allowing useful comparisons and identification of critical points and ways to improve customer satisfaction continuously. Practical implications By establishing indices of expected and perceived quality and satisfaction and loyalty among tourists, tourism authorities and different economic agents involved in this sector can receive objective information about the results and quality of tourism services. Tourism managers, thus, can set objectives for improvements and competitiveness, as well as building and maintaining customer loyalty. At the same time, these indices allow comparisons with other organisations and places. By facilitating greater transparency in the measurement of quality and satisfaction, service providers connected to tourism can create a platform on which to articulate clearly their contributions to interested parties and local communities. Social implications These results constitute strategies and findings that any tourism place has to consider in the planning and development of its products. Therefore the model can help to encourage a long-term market perspective among tourism sector regulators, investors and agencies. With the information obtained with this model, areas needing improvement can be identified and the appropriate procedures can be put into practice to improve the tourism offer, adjusting it to meet travellers’ needs according to their motivations to travel to the destination. Residents also can benefit from these measures, as their quality of life will improve through upgrades of the city’s tourism facilities. Originality/value The unique contribution of the present study lies in how the indices or indicators of quality of, satisfaction with and loyalty to destinations among tourists are easily measured by applying structural equation modelling. A new approach to measure satisfaction, loyalty and quality is used based on a scale from 0 to 100, and the index results are very useful for comparing different tourist places.
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Dolgonosov, B. M., K. A. Korchagin, and E. M. Messineva. "Model of fluctuations in bacteriological indices of water quality." Water Resources 33, no. 6 (December 2006): 637–50. http://dx.doi.org/10.1134/s0097807806060054.
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Ayriev, R. S., and M. A. Kudryashov. "QUALITY INDICES OF PUBLIC TRANSPORTATION SERVICES." World of Transport and Transportation 16, no. 4 (August 28, 2018): 140–49. http://dx.doi.org/10.30932/1992-3252-2018-16-4-11.
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ABSTRACT The authors’ study was devoted to the methodology that could estimate quality and ranking of transport services provided to townspeople in urban passenger and baggage transit, particularly using road vehicles and land electric transport vehicles. The experience of the entities of the Russian Federation, of the United States and the European Union in relation to standardization of the quality of transport services is cited. A mathematical model of quality of transport services, and methods of its integral assessment are considered. Basing on the general analysis of the methodology for assessing transport services, the authors suggest conclusions on its adaptability regarding city of Moscow. A systematic approach to obtaining the initial data necessary for calculation of quality indicators is proposed. Keywords: quality of transport service, urban passenger transport, social standard of transport service, quality indicators.
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Aldrees, Ali, Mohsin Ali Khan, Muhammad Atiq Ur Rehman Tariq, Abdeliazim Mustafa Mohamed, Ane Wai Man Ng, and Abubakr Taha Bakheit Taha. "Multi-Expression Programming (MEP): Water Quality Assessment Using Water Quality Indices." Water 14, no. 6 (March 17, 2022): 947. http://dx.doi.org/10.3390/w14060947.
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Water contamination is indeed a worldwide problem that threatens public health, environmental protection, and agricultural productivity. The distinctive attributes of machine learning (ML)-based modelling can provide in-depth understanding into increasing water quality challenges. This study presents the development of a multi-expression programming (MEP) based predictive model for water quality parameters, i.e., electrical conductivity (EC) and total dissolved solids (TDS) in the upper Indus River at two different outlet locations using 360 readings collected on a monthly basis. The optimized MEP models were assessed using different statistical measurements i.e., coefficient-of-determination (R2), root-mean-square error (RMSE), mean-absolute error (MAE), root-mean-square-logarithmic error (RMSLE) and mean-absolute-percent error (MAPE). The results show that the R2 in the testing phase (subjected to unseen data) for EC-MEP and TDS-MEP models is above 0.90, i.e., 0.9674 and 0.9725, respectively, reflecting the higher accuracy and generalized performance. Also, the error measures are quite lower. In accordance with MAPE statistics, both the MEP models shows an “excellent” performance in all three stages. In comparison with traditional non-linear regression models (NLRMs), the developed machine learning models have good generalization capabilities. The sensitivity analysis of the developed MEP models with regard to the significance of each input on the forecasted water quality parameters suggests that Cl and HCO3 have substantial impacts on the predictions of MEP models (EC and TDS), with a sensitiveness index above 0.90, although the influence of the Na is the less prominent. The results of this research suggest that the development of intelligence models for EC and TDS are cost effective and viable for the evaluation and monitoring of the quality of river water.
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Rahmouni, Ali, Moufida Touhami, and Tahar Benaissa. "Fukui Indices as QSAR Model Descriptors." International Journal of Chemoinformatics and Chemical Engineering 6, no. 2 (July 2017): 31–44. http://dx.doi.org/10.4018/ijcce.2017070103.
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This article describes the Quantitative structure–activity relationship models of 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine inhibition of the human immunodeficiency virus (HIV-1) reverse transcriptase (RT) was developed using the multi linear regressions method. These studies were performed using 60 compounds with the help of quantum descriptors as Ionization Potential, Electron Affinity, Softness, global Electrophilicity index and Fukui functions. These indices are obtained at the DFT/B3LYP level of quantum calculation. The statistical quality of the QSAR models was assessed using statistical parameters R2. Good agreements between experimental and calculated log1/EC50 values of anti-HIV activity were obtained. Four QSAR models are presented and the best one use nine molecular quantum descriptors.
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Chen, You Wen, and Tian You Chai. "Optimal Control for Quality Indices of Heat Furnace." Advanced Materials Research 201-203 (February 2011): 1748–51. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.1748.
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Heat furnace is one of the most important parts in iron and steel industry which is one of the basic industries. The control of furnace quality indices has a direct impact on iron and steel qualities and energy consumptions in an iron and steel manufacturing process. Due to dramatic changes of exhaust gas in combustion, this multi-variable process becomes time-varying, and also has inherent nonlinearities, couplings among the variables, large inertias and time delays.Therefore, manual operations are still being widely used in quality indices control. In this paper, an optimization control method is proposed for the control of furnace quality indices. The optimization consists of a materials temperature calculation model, an optimization objective, an ideal materials heating model and a furnace heating model. Optimization algorithm consists of the maximum principle, the simulated annealing algorithm，the iterative algorithm and sensitive analysis.Finally, quality indices were controlled by lower layer loop control on-line.The proposed optimization control method has been successfully applied to some steel plants. The industrial applications show the effectiveness of the proposed method.
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Sen, Sedat, and Laine Bradshaw. "Comparison of Relative Fit Indices for Diagnostic Model Selection." Applied Psychological Measurement 41, no. 6 (March 8, 2017): 422–38. http://dx.doi.org/10.1177/0146621617695521.
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The purpose of this study was to thoroughly examine the performance of three information-based fit indices—Akaike’s Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size-adjusted BIC (SABIC)—using the log-linear cognitive diagnosis model and a set of well-known item response theory (IRT) models. Two simulation studies were conducted to examine the extent to which relative fit indices can identify the generating model under a variety of data conditions and model misspecifications. Generally, indices performed better when item quality was stronger. When the IRT was the generating model, all three indices correctly selected the IRT model for all replications. When the true model was a diagnostic classification model, for all three fit indices, the multidimensional IRT model was incorrectly selected as frequently as 70% of the replications. The results of this study identify situations for researchers where commonly used—and typically well-performing—fit indices may not be appropriate to compare models for selection.
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Aćimović, Milica, Lato Pezo, Tijana Zeremski, Biljana Lončar, Ana Marjanović Jeromela, Jovana Stanković Jeremic, Mirjana Cvetković, Vladimir Sikora, and Maja Ignjatov. "Weather Conditions Influence on Hyssop Essential Oil Quality." Processes 9, no. 7 (July 2, 2021): 1152. http://dx.doi.org/10.3390/pr9071152.
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This paper is a study of the chemical composition of Hyssopus officinalis ssp. officinalis grown during three years (2017–2019) at the Institute of Field and Vegetable Crops Novi Sad (Vojvodina Province, Serbia). Furthermore, comparisons with ISO standards during the years were also investigated, as well as a prediction model of retention indices of compounds from the essential oils. An essential oil obtained by hydrodistillation and analysed by GC-FID and GC-MS was isopinocamphone chemotype. The gathered information about the volatile compounds from H. officinalis was used to classify the samples using the unrooted cluster tree. The correlation analysis was applied to investigate the similarity of different samples, according to GC-MS data. The quantitative structure–retention relationship (QSRR) was also employed to predict the retention indices of the identified compounds. A total of 74 experimentally obtained retention indices were used to build a prediction model. The coefficient of determination for the training cycle was 0.910, indicating that this model could be used for the prediction of retention indices for H. officinalis essential oil compounds.
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Arfan, Yopy, and Dwita Sutjiningsih. "Development of correlation-regression model between land use change and water quality indices in Ciliwung watershed." MATEC Web of Conferences 192 (2018): 02047. http://dx.doi.org/10.1051/matecconf/201819202047.
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Urbanization and industrialization lead to the change of land cover from pervious into impervious. This can impact environmental problems such as water quality degradation that affects human health and water ecosystems. The study aimed to develop a regression-correlation model between impervious cover in Ciliwung watershed and water quality indices in Ciliwung river. The correlation-regression model can be used to predict changes in the status of Ciliwung river water quality due to impervious cover changes. Methods of assessing the indices of water quality are CCME-WQI, NSF-WQI, and STORET within the period of 2005-2016. Monitoring locations from the most upstream to downstream are Atta’awun, Katulampa, Kedung Halang, Pondok Rajeg, Panus Bridge, Kelapa Dua, Condet, Kalibata, MT Haryono and Manggarai. Impervious cover data for each water quality monitoring location is processed using ArcGIS Software. Test of correlation significance between percentage of impervious cover and water quality indices using Pearson Correlation test method. The result of correlation test is significantly a strong inverse relationship between impervious cover and water quality indices. The result of regression test is trend line between impervious cover change and water quality indices that can be used to predict the change of water quality status in Ciliwung River.
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Gossen, Tatiana, Michael Kotzyba, and Andreas Nürnberger. "Graph clusterings with overlaps: Adapted quality indices and a generation model." Neurocomputing 123 (January 2014): 13–22. http://dx.doi.org/10.1016/j.neucom.2012.09.046.
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Tian, Tao, Xiaoning Li, Qing Wang, and Dajian Tong. "Entropy Weight TOPSIS Evaluation of Corporate Internal Control Quality Based on Fuzzy Matter-Element Model." Discrete Dynamics in Nature and Society 2022 (June 15, 2022): 1–7. http://dx.doi.org/10.1155/2022/4891288.
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One of the core objectives of domestic and foreign regulation policies is to strengthen internal control and improve corporate risk management ability. To evaluate corporate internal control quality (CICQ), this paper constructs a composite fuzzy matter-element model based on the fuzzy matter-element theory and the data on 781 listed enterprises in China. By the entropy weight method, five evaluation indices of internal control were weighed and compared with the positive and negative ideal indices. Next, the internal control of the listed enterprises was measured by TOPSIS. The results show that the indices of laws and regulations (LR), financial statements (FS), assets safety (AS), operation (OP), and strategy (ST) are of different weights in terms of CICQ evaluation. The LR, OP, and ST indices are more important than the FS indices. Among the secondary indices, the most important indices, namely, major litigation and arbitration cases, turnover of total assets, and Tobin’s Q account for 66% of total weights. In addition, the CICQ varies with industries: the top-10 enterprises in terms of CICQ mostly belong to industries with strict requirements on work safety. The research findings lay a methodological and practical basis for the CICQ evaluation of Chinese enterprises.
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Chen, Yu, Hsu, Cai, and Chiou. "A Model for Evaluating the Performance of the Bearing Manufacturing Process." Applied Sciences 9, no. 15 (July 31, 2019): 3105. http://dx.doi.org/10.3390/app9153105.
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Reliability and product process quality are essential in meeting market demand and enhancing competitiveness in the machine tool industry. In addition, manufacturing time performance is also one of the important indices. Therefore, this paper focuses on process quality and manufacturing time and defines a manufacturing time performance index to feedback the acceptance rate of the manufacturing time. The process performance evaluation chart delineated the observations of variations in various workstations, and, hence, in controlling the stability of the work process. The Six Sigma quality indices are constructed by the process accuracy indices and precision indices are represented by X-axis and Y-axis respectively. The process quality evaluation chart evaluates the level of the process quality, as well as proposes the direction of improvement. The manufacturing time performance—Z-axis is used to assess whether the manufacturing time performance meets the requirements. The process performance evaluation chart constructed by this paper makes it easier for researchers to observe which workstations have a process variation in the process, to control the stability of the process effectively, to provide the improvement reference for staff on the scene and to enhance the competitiveness of the industry.
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Huang, Chiao-Tzu, and Kuei-Kuei Lai. "Process Quality Evaluation Model with Taguchi Cost Loss Index." Applied Sciences 11, no. 21 (October 30, 2021): 10182. http://dx.doi.org/10.3390/app112110182.
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Process Capability Indices (PCIs) are not only a good communication tools between sales departments and customers but also convenient tools for internal engineers to evaluate and analyze process capabilities of products. Many statisticians and process engineers are dedicated to research on process capability indices, among which the Taguchi cost loss index can reflect both the process yield and process cost loss at the same time. Therefore, in this study the Taguchi cost loss index was used to propose a novel process quality evaluation model. After the process was stabilized, a process capability evaluation was carried out. This study used Boole’s inequality and DeMorgan’s theorem to derive the (1−α)×100% confidence region of (δ,γ2) based on control chart data. The study adopted the mathematical programming method to find the (1−α)×100% confidence interval of the Taguchi cost loss index then employed a (1−α)×100% confidence interval to perform statistical testing and to determine whether the process needed improvement.
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Ke, Kun-Cheng, and Ming-Shyan Huang. "Quality Classification of Injection-Molded Components by Using Quality Indices, Grading, and Machine Learning." Polymers 13, no. 3 (January 22, 2021): 353. http://dx.doi.org/10.3390/polym13030353.
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Conventional methods for assessing the quality of components mass produced using injection molding are expensive and time-consuming or involve imprecise statistical process control parameters. A suitable alternative would be to employ machine learning to classify the quality of parts by using quality indices and quality grading. In this study, we used a multilayer perceptron (MLP) neural network along with a few quality indices to accurately predict the quality of “qualified” and “unqualified” geometric shapes of a finished product. These quality indices, which exhibited a strong correlation with part quality, were extracted from pressure curves and input into the MLP model for learning and prediction. By filtering outliers from the input data and converting the measured quality into quality grades used as output data, we increased the prediction accuracy of the MLP model and classified the quality of finished parts into various quality levels. The MLP model may misjudge datapoints in the “to-be-confirmed” area, which is located between the “qualified” and “unqualified” areas. We classified the “to-be-confirmed” area, and only the quality of products in this area were evaluated further, which reduced the cost of quality control considerably. An integrated circuit tray was manufactured to experimentally demonstrate the feasibility of the proposed method.
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Kolanović, Ines, Čedomir Dundović, and Alen Jugović. "Customer-based Port Service Quality Model." PROMET - Traffic&Transportation 23, no. 6 (February 21, 2012): 495–502. http://dx.doi.org/10.7307/ptt.v23i6.184.
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This port service quality study is an important precondition for an efficient development of port industry and traffic system as a whole. It is due to the complexity of any port, as a system consisting of a large number of stakeholders rendering services to customers with various requirements, that a unique set of port service quality indices has been still missing. For this reason, the paper explains the port service quality concept in compliance with stakeholders and their requirements within the context of port service quality. The aim of the paper is to present a proposal for a customer-based port service quality model based on empirical study and its reliability testing on a selected sample. The proposed model is defined by five factors and fits satisfactorily into the obtained poll questionnaire results. The statistical data processing package SPSS 16.0 and the LISREL 8.54 programme were used in the study. KEY WORDS: port service, customer, model, factor analysis
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Ellingsen, K., M. Gauss, R. Van Dingenen, F. J. Dentener, L. Emberson, A. M. Fiore, M. G. Schultz, et al. "Global ozone and air quality: a multi-model assessment of risks to human health and crops." Atmospheric Chemistry and Physics Discussions 8, no. 1 (February 6, 2008): 2163–223. http://dx.doi.org/10.5194/acpd-8-2163-2008.
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Abstract. Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5–10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15–20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2–4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to human health and vegetation from changing levels of surface ozone.
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Baksh, Hafiz M., Taofik O. Dauda, Shahrul Anuar M. S., and Karimullah K. "Statistical assessment of water quality of a Ramsar site wetland." Water Supply 17, no. 5 (March 24, 2017): 1400–1409. http://dx.doi.org/10.2166/ws.2017.041.
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This study was conducted to evaluate the wetland water quality (WWQ) over a period of 3 years and establish relationships between these qualities using Ramsar site Uchali Wetland, Pakistan (32 °33′N, 72 °01′E). WWQ data obtained were subjected to summary statistics, generalized linear model (glm), correlation, covariance and cluster analysis. The glm of the monthly mean water indices showed that the mean returned for pH (2.57) was not significant while means for others were significant (p < 0.05). The correlation analysis of the WWQ indices indicated that 56% of the pairing indices were inversely correlated while 44% were directly correlated and three piles of clusters of WWQ indices were distinct. The wetland water is not very safe for drinking but safe for other non-domestic uses since it contains fewer microbes and the water health model as arrived at in this study provides a management protocol for wetland water.
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Chen, Kuen-Suan, Ching-Hsin Wang, and Kim-Hua Tan. "Developing a fuzzy green supplier selection model using six sigma quality indices." International Journal of Production Economics 212 (June 2019): 1–7. http://dx.doi.org/10.1016/j.ijpe.2019.02.005.
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Hodgdon, Cameron T., Kisei R. Tanaka, Jocelyn Runnebaum, Jie Cao, and Yong Chen. "A framework to incorporate environmental effects into stock assessments informed by fishery-independent surveys: a case study with American lobster (Homarus americanus)." Canadian Journal of Fisheries and Aquatic Sciences 77, no. 10 (October 2020): 1700–1710. http://dx.doi.org/10.1139/cjfas-2020-0076.
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Stock assessments for a majority of the world’s fisheries often do not explicitly consider the effects of environmental conditions on target species, which can raise model uncertainty and potentially reduce forecasting quality. Model-based abundance indices were developed using a delta generalized linear mixed model that incorporates environmental variability for use in stock assessment to understand how the incorporation of environmental variability impacts our understanding of population dynamics. For this study, multiple model-based abundance indices were developed to test the incorporation of environmental covariates in a length-structured assessment of the American lobster (Homarus americanus) stock in the Gulf of Maine – Georges Bank on the possible improvement of stock assessment quality. Comparisons reveal that modelled indices with environmental covariates appear to be more precise than traditional indices, but model performance metrics and hindcasted fishery statuses revealed that these improvements to indices may not necessarily mean an improved assessment. Model-based abundance indices are not intrinsically better than design-based indices and should be tested for each species individually.
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Xu, Da, Xiaoyuan Hu, Wenhui Hong, Mengshi Li, and Ziming Chen. "Power Quality Indices Online Prediction Based on VMD-LSTM Residual Analysis." Journal of Physics: Conference Series 2290, no. 1 (June 1, 2022): 012009. http://dx.doi.org/10.1088/1742-6596/2290/1/012009.
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Abstract In order to ensure the provision of high-quality power quality and the smooth operation of the power system, aiming at the problem of low prediction accuracy of power quality indices, this paper proposes an online prediction method of power quality indices based on VMD-LSTM residual analysis. Firstly, the VMD-LSTM is used to simulate and predict the normal power quality signal; then the predicted signal data is different from the actual power quality signal data to obtain the residual signal, and the residual signal is input into the one-dimensional convolutional neural network for training, and finally the power quality indices prediction model is obtained. Finally, taking voltage flicker as an example, simulation experiments compared with other prediction models verify the better effectiveness and accuracy of the proposed method.
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Lo, Wei, Chun-Ming Yang, Kuei-Kuei Lai, Shao-Yu Li, and Chi-Han Chen. "Developing a Novel Fuzzy Evaluation Model by One-Sided Specification Capability Indices." Mathematics 9, no. 10 (May 11, 2021): 1076. http://dx.doi.org/10.3390/math9101076.
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When all of the one-sided specification indices of each quality characteristic reach the requirements of the process quality level, they can ensure that the process capability of the product meets the requirements of the process quality level. This study constructs a fuzzy membership function based on the upper confidence limit of the index, derives the fuzzy critical value, and then labels the fuzzy critical value on the axis of the visualized radar chart as well as connects adjacent critical points to shape a regular polygonal critical region. Next, this study calculates the observed value of the index to estimate and mark it on the axis for forming a visualized fuzzy radar evaluation chart. Obviously, this fuzzy evaluation model not only reduces the testing cost but also makes the quality level quickly meet the requirements of the specifications. Further, the radar chart can reduce the risk of misjudgment attributable to sampling errors and help improve the accuracy of evaluation by a confidence-upper-limit-based fuzzy evaluation model. Therefore, this easy-to-use visualized fuzzy radar evaluation chart is used as an evaluation interface, which has good and convenient management performance to identify and improve critical-to-quality quickly. Improving the quality of the process before the product is completed will also have the advantage of reducing social losses and environmental damage costs.
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Li, Nan. "A Fuzzy Evaluation Model of College English Teaching Quality Based on Analytic Hierarchy Process." International Journal of Emerging Technologies in Learning (iJET) 16, no. 02 (January 26, 2021): 17. http://dx.doi.org/10.3991/ijet.v16i02.19731.
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The evaluation of English teaching quality in colleges mainly faces two problems: the evaluation index system (EIS) is incomplete, and the evaluation model cannot easily handle complex fuzzy indices. To solve the problems, this paper explores deep into the fuzzy evaluation of college English teaching quality, and establishes a fuzzy evaluation model of college English teaching quality based on analytic hierarchy process (AHP). Firstly, theoretical analysis was combined with model calculation to create an improved multi-angle EIS for college English teaching quality. From both quantitative and qualitative analyses, a college English teaching quality evaluation model was constructed to handle fuzzy indices. Implementation results show that the proposed EIS and fuzzy evaluation model can effectively assess the quality of English teaching in colleges. The research results greatly promote the quality improvement of college English teaching.
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Tang, Xin, De Suo Cai, and Wen Ting Yao. "Grey Correlation Model Based on Diatom Indices Evaluating Water Quality of Longjiang River." Applied Mechanics and Materials 448-453 (October 2013): 43–47. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.43.
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In order to evaluate the water quality of Longjiang river comprehensively, diatoms of 15 sampling sites are collected to establish the Grey Relational Model based on three diatom indexesIPS, IBD and IDG. From the Cluster analysis of sampling sites and the box plot of diatom index, IBD is the best, then the IPS, the diatom index weights on water quality assessment are 0.637 for IBD, 0.2583 for IPS, 0.1074 for IDG respectively. Finally, by comparing the water quality standard level based on Grey Relational Model, it can be known that the water quality of most sampling sites is fine except that site No.1 and No.3 belong to III water quality standard. The result shows that it is more comprehensive and reasonable to use the Grey Relational Model based on diatom index rather than individual diatom index to assess water quality.
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Chen, Kuen-Suan, Tsun-Hung Huang, Ruey-Chyn Tsaur, and Wen-Yang Kao. "Fuzzy Evaluation Models for Accuracy and Precision Indices." Mathematics 10, no. 21 (October 25, 2022): 3961. http://dx.doi.org/10.3390/math10213961.
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The random variable X is used to represent the normal process containing two important parameters—the process average and the process standard deviation. The variable is transformed using Y = (X − T)/d, where T is the target value and d is the tolerance. The average of Y is then called the accuracy index, and the standard deviation is called the precision index. If only the values of the accuracy index and the process precision index are well controlled, the process quality level as well as the process yield are ensured. Based on this concept, this paper constructed a control chart for the accuracy index and the precision index and derived the confidence intervals of the accuracy index and the precision index using in-control data, as the process was stable. This paper aims to control process quality via monitoring the accuracy and precision of the process. At the same time, fuzzy tests are developed for the indicators of process accuracy and precision to evaluate whether the process quality can reach the k-sigma quality level, as well as offer suggestions about directions of improvement when it fails to reach the k-sigma quality level. Obviously, the model in this paper cannot only evaluate whether the process meets the requirements of the quality level; it can also provide a decision regarding whether the process should be improved. It is very helpful for the enhancement of enterprises’ process capabilities.
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Ait Lamqadem, Atman, Biswajeet Pradhan, Hafid Saber, and Abdelmejid Rahimi. "Desertification Sensitivity Analysis Using MEDALUS Model and GIS: A Case Study of the Oases of Middle Draa Valley, Morocco." Sensors 18, no. 7 (July 11, 2018): 2230. http://dx.doi.org/10.3390/s18072230.
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Oases can play a significant role in the sustainable economic development of arid and Saharan regions. The aim of this study was to map the desertification-sensitive areas in the Middle Draa Valley (MDV), which is in the southeast of Morocco. A total of 13 indices that affect desertification processes were identified and analyzed using a geographic information system. The Mediterranean desertification and land use approach; which has been widely used in the Mediterranean regions due to its simplicity; flexibility and rapid implementation strategy; was applied. All the indices were grouped into four main quality indices; i.e., soil quality; climate quality; vegetation quality and management quality indices. Each quality index was constructed by the combination of several sub-indicators. In turn; the geometric mean of the four quality index maps was used to construct a map of desertification-sensitive areas; which were classified into four classes (i.e., low; moderate; high and very high sensitivity). Results indicated that only 16.63% of the sites in the study were classified as least sensitive to desertification; and 50.34% were classified as highly and very highly sensitive areas. Findings also showed that climate and human pressure factors are the most important indicators affecting desertification sensitivity in the MDV. The framework used in this research provides suitable results and can be easily implemented in similar oasis arid areas.
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Laitinen, P. J., and H. Saxén. "A neural network based model of sinter quality and sinter plant performance indices." Ironmaking & Steelmaking 34, no. 2 (March 2007): 109–14. http://dx.doi.org/10.1179/174328107x155312.
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Hernández-Mira, Frank Aangel, José Luis Rosas-Acevedo, Maximino Reyes-Umaña, Juan Violante-González, José María Sigarreta-Almira, and Nodari Vakhania. "Multimetric Index to Evaluate Water Quality in Lagoons: A Biological and Geomorphological Approach." Sustainability 13, no. 9 (April 21, 2021): 4631. http://dx.doi.org/10.3390/su13094631.
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In recent years, Multimetric Indices (MMIs) have received a lot of attention thanks to their ability to develop integrative evaluations of water quality, particularly in lagoons. In this article, we propose a new MMI for determining the water quality in lagoons. The proposed index is composed of biotic and abiotic indicators, in particular macroinvertebrates, macrophytes and morphological indicators. The proposed index is based on a geometric representation of a phenomenon associated with an ecological system, the ecosystem elements are mapped as vertices of a network and the relationship between them is represented by the corresponding edges. We classify the status of water bodies, from very low to very high using the ecological quality ratio. We compare our index with different different indices that measure water quality, such as General Biotic Index (JP(G)), Macrophyte Index for River (MIR) and Shannon diversity index (H’) and validate our index with Pearson’s correlation coefficient. A strong correlation with the JP(G) and MIR indices (R2 = 0.8605 and R2=0.7661, respectively) is obtained. Although the proposed index is composed of other indices, the independence of the proposed index with respect to its component indices is proven and the structure of the geometric model associated to the proposed network is studied. A close relationship between the measure called medium articulation and the geometric model associated with the proposed index is highlighted, which allows to determine the missing relationships in the network using structural analysis. The proposed index presents a more comprehensive measure than most indices currently used and has the advantage in the scalability, since other existing indicators can be integrated into our model.
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Kang, Yan, Jinling Song, Zhuo Lin, Liming Huang, Xiaoang Zhai, and Haipeng Feng. "Water Quality Prediction Based on SSA-MIC-SMBO-ESN." Computational Intelligence and Neuroscience 2022 (August 3, 2022): 1–11. http://dx.doi.org/10.1155/2022/1264385.
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Water pollution threatens the safety of human production and life. To quickly respond to water pollution, it is important for water management staff to predict water quality changes in advance. Drawing on the temporality of water quality data, the leaky integrator echo state network (ESN) was introduced to construct the water quality prediction models for dissolved oxygen (DO), permanganate index (CODMn), and total phosphorus (TP), respectively. First, the missing values were filled by the linear trend method of adjacent points, and the outliers were detected and corrected by the Z-score method and the linear trend method. Second, the singular spectrum analysis (SSA) was performed to denoise the original monitoring data, such that the predicted data catch up with the real data, and the model accuracy is not affected by the hidden noise in the data. Third, the correlation between water quality indices was measured by the maximum information coefficient (MIC), and the strongly correlated indices were imported to the prediction model. Finally, according to these strong correlation indicators, the water quality prediction models based on multiple features were constructed, respectively, using the offline and online learning algorithms of the ESN. The hyperparameters of the models were optimized through the sequential model-based optimization (SMBO). Experimental results show that the proposed water quality prediction models, namely, SSA-MIC-SMBO-Offline ESN and SSA-MIC-SMBO-Online ESN, predicted DO, CODMn, and TP accurately, providing suitable tools for practical applications.
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Cai, Ming Shan, and Ling Shuang Kong. "An Interval-Index-Oriented Intelligent Optimization Method and its Industrial Application." Advanced Materials Research 219-220 (March 2011): 546–50. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.546.
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Based on the strong coupling and interval requirement of multiple quality indices, the interval-index-oriented optimization method is proposed to effectively realize the optimal control of alumina blending process. Firstly, the lexicographic interval goal programming model is built to describe the process requirements for quality indices. Then, based on the characteristics of the programming model, a kind of classificatory knowledge base is constructed by using the empirical knowledge accumulated in long-term production and the expert reasoning strategy is proposed to realize the optimal control of quality indexes with interval constraints. The results of industrial application shows that the proposed method can realize the optimal control of quality indices. It provides a good optimization mode for other blending processes of nonferrous metal production.
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Shah, Vishwa, Sarath Chandra K. Jagupilla, David A. Vaccari, and Daniel Gebler. "Non-Linear Visualization and Importance Ratio Analysis of Multivariate Polynomial Regression Ecological Models Based on River Hydromorphology and Water Quality." Water 13, no. 19 (September 30, 2021): 2708. http://dx.doi.org/10.3390/w13192708.
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Multivariate polynomial regression (MPR) models were developed for five macrophyte indices. MPR models are able to capture complex interactions in the data while being tractable and transparent for further analysis. The performance of the MPR modeling approach was compared to previous work using artificial neural networks. The data were obtained from hydromorphologically modified Polish rivers with a widely varying water quality. The modeled indices were the Macrophyte Index for Rivers (MIR), the Macrophyte Biological Index for Rivers (IBMR), and the River Macrophyte Nutrient Index (RMNI). These indices measure the trophic and ecological status of the rivers. Additionally, two biological diversity indices, species richness (N) and the Simpson index (D), were modeled. The explanatory variables were physico-chemical properties depicting water quality and river hydromorphological status indices. In comparison to artificial neural networks, the MPR models performed similarly in terms of goodness of fit. However, the MPR models had advantages such as model simplicity and ability to be subject to effective visualization of complex nonlinear input–output relationships, as well as facilitating sensitivity analysis using importance ratios to identify effects of individual input variables.
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Kim, Ki-Hoon, Wona Choi, Soo-Jeong Ko, Dong-Jin Chang, Yeon-Woog Chung, Se-Hyun Chang, Jae-Kwon Kim, Dai-Jin Kim, and In-Young Choi. "Multi-Center Healthcare Data Quality Measurement Model and Assessment Using OMOP CDM." Applied Sciences 11, no. 19 (October 2, 2021): 9188. http://dx.doi.org/10.3390/app11199188.
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Healthcare data has economic value and is evaluated as such. Therefore, it attracted global attention from observational and clinical studies alike. Recently, the importance of data quality research emerged in healthcare data research. Various studies are being conducted on this topic. In this study, we propose a DQ4HEALTH model that can be applied to healthcare when reviewing existing data quality literature. The model includes 5 dimensions and 415 validation rules. The four evaluation indicators include the net pass rate (NPR), weighted pass rate (WPR), net dimensional pass rate (NDPR), and weighted dimensional pass rate (WDPR). They were used to evaluate the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) at three medical institutions. These indicators identify differences in data quality between the institutions. The NPRs of the three institutions (A, B, and C) were 96.58%, 90.08%, and 90.87%, respectively, and the WPR was 98.52%, 94.26%, and 94.81%, respectively. In the quality evaluation of the dimensions, the consistency was 70.06% of the total error data. The WDPRs were 98.22%, 94.74%, and 95.05% for institutions A, B, and C, respectively. This study presented indices for comparing quality evaluation models and quality in the healthcare field. Using these indices, medical institutions can evaluate the quality of their data and suggest practical directions for decreasing errors.
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Vadiati, Meysam, Deasy Nalley, Jan Adamowski, Mohammad Nakhaei, and Asghar Asghari-Moghaddam. "A comparative study of fuzzy logic-based models for groundwater quality evaluation based on irrigation indices." Journal of Water and Land Development 43, no. 1 (December 1, 2019): 158–70. http://dx.doi.org/10.2478/jwld-2019-0074.
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AbstractGroundwater quality modelling plays an important role in water resources management decision making processes. Accordingly, models must be developed to account for the uncertainty inherent in the modelling process, from the sample measurement stage through to the data interpretation stages. Artificial intelligence models, particularly fuzzy inference systems (FIS), have been shown to be effective in groundwater quality evaluation for complex aquifers. In the current study, fuzzy set theory is applied to groundwater-quality related decision-making in an agricultural production context; the Mamdani, Sugeno, and Larsen fuzzy logic-based models (MFL, SFL, and LFL, respectively) are used to develop a series of new, generalized, rule-based fuzzy models for water quality evaluation using widely accepted irrigation indices and hydrological data from the Sarab Plain, Iran. Rather than drawing upon physiochemical groundwater quality parameters, the present research employs widely accepted agricultural indices (e.g., irrigation criteria) when developing the MFL, SFL and LFL groundwater quality models. These newly-developed models, generated significantly more consistent results than the United States Soil Laboratory (USSL) diagram, addressed the inherent uncertainty in threshold data, and were effective in assessing groundwater quality for agricultural uses. The SFL model is recommended as it outperforms both MFL and LFL in terms of accuracy when assessing groundwater quality using irrigation indices.
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Galal, Hoda, Salah Elsayed, Osama Elsherbiny, Aida Allam, and Mohamed Farouk. "Using RGB Imaging, Optimized Three-Band Spectral Indices, and a Decision Tree Model to Assess Orange Fruit Quality." Agriculture 12, no. 10 (September 27, 2022): 1558. http://dx.doi.org/10.3390/agriculture12101558.
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Point samples and laboratory testing have historically been used to evaluate fruit quality criteria. Although this method is precise, it is slow, expensive, and destructive, making it unsuitable for large-scale monitoring of these parameters. The main objective of this research was to develop a non-invasive protocol by combining color RGB indices (CIs) and previously published and newly developed three-band spectral reflectance indices (SRIs) with a decision tree (DT) model to evaluate the fruit quality parameters of navel orange. These parameters were brightness (L*), red–green (a*), blue–yellow (b*), chlorophyll meter (Chlm), total soluble solids (TSS), and TSS/acid ratio. The characteristics of fruit quality of navel orange samples were measured at various stages of ripening. The outcomes demonstrated that at various levels of ripening, the fruit quality parameters, RGB imaging indices, and published and newly developed three-band SRIs differed. The newly developed three-band SRIs based on the wavelengths of blue, green, red, red-edge, and NIR are most effective for estimating the six measured parameters in this study. For example, NDI574,592,724, NDI572,584,724, and NDI574,722,590 had the largest R2 value (0.90) with L*, whereas NDI526,664,700 and NDI524,700,664 exhibited the highest R2 value (0.97) with a*. Moreover, integrating CIs and SRIs with the DT model has provided a potentially useful tool for the accurate measurement of the six studied parameters. For instance, the DT-SRIs-CIs-30 model performed better in terms of measuring a* using 30 various indices. The R2 value was 0.98 and RMSE = 1.121 in the cross-validation, while R2 value was 0.964 and RMSE = 2.604 in the test set. Otherwise, based on the fusion of five various indices, the DT-SRIs-CIs-5 model was the most precise for recognizing b* (R2 = 0.957 and 0.929, with RMSE = 1.713 and 3.309 for cross-validation and test set, respectively). Overall, this work proves that integrating the different characteristics of proximal reflectance sensing systems such as color RGB indices and SRIs via the DT model may be considered a reliable instrument for evaluating the quality of different fruits.
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Mendes, Tânia, Ana Raquel Calapez, Carmen L. Elias, Salomé F. P. Almeida, and Maria João Feio. "Comparing alternatives for combining invertebrate and diatom assessment in stream quality classification." Marine and Freshwater Research 65, no. 7 (2014): 612. http://dx.doi.org/10.1071/mf13135.
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The present study aimed to determine if a predictive model integrating freshwater assemblages from different trophic levels (macroinvertebrates and diatoms) produces a more sensitive assessment of stream health than single-assemblage assessments combined a posteriori. For this purpose, individual and combined models based on two approaches (BEAST and RIVPACS) were developed for Portuguese streams: two for diatoms; two for macroinvertebrates; and two combining diatoms and macroinvertebrates as a single community. Twenty-three sites affected by organic contamination, industrial effluents and mine drainage were evaluated with the predictive models and also by the official biotic indices used in Portugal. The sensitivity of the RIVPACS assessment to disturbance was improved by the a priori combination of diatoms and macroinvertebrates, whereas for BEAST the a posteriori approaches were slightly more sensitive. Diatom and invertebrate indices combined a posteriori performed better than single-assemblage indices but with lower sensitivity than combined models. We conclude that the a priori combination of the two biological assemblages is valuable (more sensitive to disturbance) for the RIVPACS approach and that the a posteriori combination of assessments for individual biological elements may not always provide the most realistic indication of stream health.
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Yen, Ching-Ho, Heng Ma, Chi-Huang Yeh, and Chia-Hao Chang. "The economic design of variable acceptance sampling plan with rectifying inspection." Kybernetes 44, no. 3 (March 2, 2015): 440–50. http://dx.doi.org/10.1108/k-05-2013-0091.
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Purpose – The purpose of this paper is to develop an economic model, which could determine the acceptance sampling plan that minimizes the quality cost for batch manufacturing. Design/methodology/approach – The authors propose a variable sampling plan based on one-sided capability indices for dealing with the quality cost requirement. Findings – The total quality cost is much more sensitive to process capability indices and inspected cost than internal and external failure costs. Research limitations/implications – The experimental data were randomly generated instead of real world ones. Practical implications – The proposed model is specifically designed for manufacturing industries with high sampling cost. Originality/value – The one-sided capability indices were utilized for the first time to be suitable for the purpose.
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Xu, S., and M. Ehlers. "CRITICAL REFLECTION ON QUANTITATIVE ASSESSMENT OF IMAGE FUSION QUALITY." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (May 30, 2022): 551–57. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-551-2022.
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Abstract. Image fusion technique has been extended its development from multi-sensor fusion, multi-model fusion to multi-focus fusion. More and more advanced techniques such as deep learning have been integrated into the development of image fusion algorithms. However, as an important aspect, fusion quality assessment has been received less attention. This paper intends to reflect on the commonly used indices for quantitative assessment and investigate how they can represent the fusion quality regarding spectral preservation and spatial improvement. We found that image dissimilarities are unavoidable due to the spectral coverage of different image sensors. Image fusion should integrate these dissimilarities when they are representing spatial improvement. Such integration will naturally change the pixel values. However, as the quality indices for the assessment of spectral preservation are measuring image dissimilarities, the integration of spatial information will lead to a low fusion quality assessment. For the evaluation of spatial improvement, the quality indices only work if the spatial details have been lost; however, in the case of spatial details gain, these indices do not reflect them as spatial improvements. Moreover, this paper raises attention to image processing procedures involved in image fusion, including image geo-registration, image clipping and image resampling, which will change image statistics and thereby influence the quality assessment when statistical indices are used.
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Wei, Pengfei, Chenghu Tang, and Yuting Yang. "Structural reliability and reliability sensitivity analysis of extremely rare failure events by combining sampling and surrogate model methods." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 6 (May 17, 2019): 943–57. http://dx.doi.org/10.1177/1748006x19844666.
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The aim of this article is to study the reliability analysis, parametric reliability sensitivity analysis and global reliability sensitivity analysis of structures with extremely rare failure events. First, the global reliability sensitivity indices are restudied, and we show that the total effect index can also be interpreted as the effect of randomly copying each individual input variable on the failure surface. Second, a new method, denoted as Active learning Kriging Markov Chain Monte Carlo (AK-MCMC), is developed for adaptively approximating the failure surface with active learning Kriging surrogate model as well as dynamically updated Monte Carlo or Markov chain Monte Carlo populations. Third, the AK-MCMC procedure combined with the quasi-optimal importance sampling procedure is extended for estimating the failure probability and the parametric reliability sensitivity and global reliability sensitivity indices. For estimating the global reliability sensitivity indices, two new importance sampling estimators are derived. The AK-MCMC procedure can be regarded as a combination of the classical Monte Carlo Simulation (AK-MCS) and subset simulation procedures, but it is much more effective when applied to extremely rare failure events. Results of test examples show that the proposed method can accurately and robustly estimate the extremely small failure probability (e.g. 1e–9) as well as the related parametric reliability sensitivity and global reliability sensitivity indices with several dozens of function calls.
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Yan, Shengyuan, Cong Chi Tran, Yingying Wei, and Jean Luc Habiyaremye. "Driver’s mental workload prediction model based on physiological indices." International Journal of Occupational Safety and Ergonomics 25, no. 3 (September 15, 2017): 476–84. http://dx.doi.org/10.1080/10803548.2017.1368951.
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Li, Ye. "Employment Quality Difference and Employment Quality Evaluation of English Majors in Colleges." International Journal of Emerging Technologies in Learning (iJET) 16, no. 15 (August 11, 2021): 194. http://dx.doi.org/10.3991/ijet.v16i15.24891.
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Our society needs talents that excel in English-Chinese translation and English education. However, there is not yet a unified and scientific evaluation index system (EIS) for the employment quality of graduates from English department of colleges. Very few scholars have analyzed the difference between English majors in employment ability. Therefore, this paper decides to analyze the difference between English majors in employment ability, and evaluate their employment quality. Firstly, an EIS was constructed to evaluate and predict the employment quality of English majors in colleges. Secondly, the relevant indices were selected and analyzed in turn. Thirdly, an employment quality prediction model was constructed for English majors in colleges. The proposed EIS and model were proved effective through experiments.
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Shubin, I. G., and M. V. Shubina. "Study of a forecasting possibility of high carbon wire rods quality at production of them at a wire rod mill." Ferrous Metallurgy. Bulletin of Scientific , Technical and Economic Information, no. 12 (December 19, 2018): 60–67. http://dx.doi.org/10.32339/0135-5910-2018-12-60-67.
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The choice of technological parameters of high carbon wire rods production process determines the values of mechanical properties and quality indices. Variations of technological parameters of rolling process and steel chemical composition predetermine considerable dispersion of mechanical characteristics values and quality indices of high carbon wire rods: tensile strength, percent elongation, reduction of area and microstructure. Stabilization of obtained mechanical characteristics values and quality indices during wire rods production was the main task of the study. During the work execution statistical methods of experiment data processing with application of regression analysis methods. Equations for carbon equivalent value determining were elaborated and applied. Regression dependences of quality indices change on the steel chemical composition and the rolling process technological factors plotted, which allow to forecast their values and effective correct the wire rods rolling regimes. General tendencies of the quality indices change, simulated by the obtained regression equations, correlate with industrial data. At the confidence probability of 95%, all the obtained equations of wire rods quality indices interrelation with technological factors of their production are statistically significant. Error of the obtained regression dependences is in the range of 4–11%. Results of the study allow recommending application of those mathematical dependences for a model elaboration, capable of finished products required properties forecasting. When it is necessary to change the regulation level of quality indices, application of obtained mathematical dependences will allow to make corrections on the value range of the wire rods rolling process technological parameters. Forecasting of quality indices values and effective correction of wire rods rolling regimes increase reproducibility stability of mechanical characteristics and wire rods quality indices.
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Морозова, Анна, Anna Morozova, Владимир Мельников, Vladimir Melnikov, Игорь Дроздов, Igor Drozdov, Владислав Смоленцев, and Vladislav Smolentsev. "TYPOLOGICAL APPROACH TO QUALITY LEVEL DEFINITION OF OBJECTS AND PROCESSES IN ORGANIZATION SYSTEM CONTROL." Bulletin of Bryansk state technical university 2017, no. 1 (March 31, 2017): 162–70. http://dx.doi.org/10.12737/24907.
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The purpose of this work consists in the presentation of the results of the theoretical generalization of the problem in the quality level definition in processes and objects of arbitrary origin with the use of a typological approach as a basis of control in organization systems.
In the investigation there were used methods of a system analysis, a mathematical modeling of multi-parametric social objects, methods of a structural anal-ysis and also a methodology of a universal quality management (UQM).
Investigation results. A multidimensional information object space of matrices of groups of quality indices is considered, a generalized model of a twodimensional matrix of relations of quality indices parameters in Cartesian coordinates is presented, quality indices are shown and their application for adaptive marketing control is shown, a procedure for the quality assessment of objects with the aid of models of a neuro-network typification is offered, and the expediency of basic directions realization in strategy of quality control regarding the set of objects and processes of an organization system under analysis is also substantiated. As an example there is considered a neuro-network approach at the typification of engineering positions in modern mechanical engineering and procedures on the basis of a competence approach of the identification process of young specialists with available vacant seats.
Conclusions. The quality parameters are a com-plex category in control of objects/processes and can be considered as a general methodological approach to the control of different organization systems. At the same time there can be used simulators of quality me-tering and typification, and also clusterization and grouping quality indices with the aid of which it is possible to ensure efficiently enough the realization of the identification procedure of objects/processes on quality indices with the application of neuro-network models.
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Toby, Brian H. "R factors in Rietveld analysis: How good is good enough?" Powder Diffraction 21, no. 1 (March 2006): 67–70. http://dx.doi.org/10.1154/1.2179804.
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The definitions for important Rietveld error indices are defined and discussed. It is shown that while smaller error index values indicate a better fit of a model to the data, wrong models with poor quality data may exhibit smaller values error index values than some superb models with very high quality data.
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Chen, Kuen-Suan, Der-Fa Chen, Ming-Chieh Huang, and Tsang-Chuan Chang. "Analyzing processing quality of machine tools via processed product: Example of ball valve processing machine." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 234, no. 4 (May 14, 2020): 331–41. http://dx.doi.org/10.1177/0954408920925028.
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Machine tools are fundamental equipment in industrial production, and their processing quality exerts a direct impact on the quality of the component product that they process. Thus, machine tool manufacturers develop various machine tools depending on market needs and processing functions, and the processed component products generally possess multiple smaller-the-better, larger-the-better, and nominal-the-best quality characteristics at the same time. For this reason, this study employed the widely used process capability indices, [Formula: see text], [Formula: see text], and [Formula: see text] to develop a model that can evaluate the process quality of component products and analyze the processing quality of various machine tools. We first converted the process capability indices into functions of the accuracy and precision indices and constructed a multi-characteristic quality analysis chart that can identify the reason for poor process quality in a quality characteristic. Furthermore, considering the fact that the process capability indices can only be estimated, which may lead to misjudgment in the evaluation of process quality, we derived the [Formula: see text] upper confidence limits of indices and the coordinates formed by the corresponding accuracy and precision indices. Manufacturers can then evaluate the process quality levels of the quality characteristics based on where the coordinates falls in the multi-characteristic quality analysis chart. This can more reliably assist manufacturers in monitoring the processing quality of their machine tools and providing feedback to the machine tool manufacturers for machine improvement.
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Gálvez, Jorge, Miriam Parreño, Jordi Pla, Jaime Sanchez, María Gálvez-Llompart, Sergio Navarro, and Ramón García-Domenech. "Application of Molecular Topology to the Prediction of Water Quality Indices of Alkylphenol Pollutants." International Journal of Chemoinformatics and Chemical Engineering 1, no. 1 (January 2011): 1–11. http://dx.doi.org/10.4018/ijcce.2011010101.
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In this paper, topological-mathematical models based on multilineal regression analysis have been built as a model of the degradability of 26 alkylphenols through the Chemical Oxygen Demand (COD) and Biochemical Oxigen Demand (BOD5). Two models with three-variable were selected (r2= 0.8793 and q2=0.8075 for log(1/COD) and r2= 0.8928 and q2=0.8327 for log(1/BOD5). The models were validated by cross-validation, internal validation and randomization tests. The results, which stand in good accordance with the obtained results, confirm the robustness of the method.
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Кузнецова, Екатерина, Ekaterina Kuznetsova, Любовь Морозова, Lyubov Morozova, Ирина Трусевич, and Iryna Trusevich. "On research into the interdependence between service quality indices and a hotel’s business processes." Services in Russia and abroad 8, no. 3 (May 28, 2014): 80–95. http://dx.doi.org/10.12737/4101.
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The article covers the major technical and human factors (indices) determining hotel guest satisfaction, and proposes a questionnaire model. An analysis of the models of service quality and guest satisfaction assessment, a number of service quality assessment models employed by international hotel networks, and the Cause and Effect diagram developed by Ishikawa lead the authors to relate guest-satisfaction-determining factors to the hotel’s individual business processes. The authors have developed a Guest Questionnaire designed to reveal a guest’s evaluation of the “significance” and “perceived quality” of service provision for each of the factors identified. The authors also rely on Noriaki Kano’s model, which is widely used in managerial decision-making on issues concerning business-process improvement, to develop a methodology for hotel service factor significance evaluation. The hotel service factors most affecting guest satisfaction are grouped by the authors into (1) quantitative, (2), compulsory, (3) surprise, (4) neutral, and (5) reverse. According to the authors, when making decisions on business-process improvement, managers should take into account the processes related to qualitative and compulsory hotel service factors.
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Li, Juan, Wenjing Yang, and Yin Xuan. "Influence of Quality Development Over College Students’ Entrepreneurial Competency." International Journal of Emerging Technologies in Learning (iJET) 17, no. 11 (June 7, 2022): 297–311. http://dx.doi.org/10.3991/ijet.v17i11.32035.
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At present, the entrepreneurship of college students is rarely successfully. It is of great significance to reasonably evaluate college students’ entrepreneurial competency, and discuss how to improve their entrepreneurial performance. The existing studies only focus on specific jobs, and emphasize on theoretical research. There is little report on the empirical quantification and effective promotion of the evaluation model, or on the effects of quality development training. Therefore, this paper explores the influence of quality development over college students’ entrepreneurial competency. Firstly, the indices of college students’ entrepreneurial competency were examined under the effect of quality development. The research contents were combined with the features of the entrepreneurship of college students, the training requirements of quality development, and the current background of society, politics, and economics, producing a reasonable composite evaluation index system. Next, the composite weights of the evaluation indices were solved by the hierarchical structure model and dominant feature recognition model of college students’ entrepreneurial competency. On this basis, the dominant feature recognition model was established for college students’ entrepreneurial competency under quality development planning. Through experiments, the proposed evaluation index system was proved scientific, and the entrepreneurial competency was evaluated for an entrepreneurial team of college students.
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Ferrando, Pere J., and Urbano Lorenzo-Seva. "Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis." Educational and Psychological Measurement 78, no. 5 (July 7, 2017): 762–80. http://dx.doi.org/10.1177/0013164417719308.
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This article proposes a comprehensive approach for assessing the quality and appropriateness of exploratory factor analysis solutions intended for item calibration and individual scoring. Three groups of properties are assessed: (a) strength and replicability of the factorial solution, (b) determinacy and accuracy of the individual score estimates, and (c) closeness to unidimensionality in the case of multidimensional solutions. Within each group, indices are considered for two types of factor-analytic models: the linear model for continuous responses and the categorical-variable-methodology model that treats the item scores as ordered-categorical. All the indices proposed have been implemented in a noncommercial and widely known program for exploratory factor analysis. The usefulness of the proposal is illustrated with a real data example in the personality domain.
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Мирошников, Вячеслав, Vyacheslav Miroshnikov, Виктор Круглов, Viktor Kruglov, Олег Горленко, Oleg Gorlenko, Татьяна Можаева, and Tatyana Mozhaeva. "Model for higher education quality assessment." Bulletin of Bryansk state technical university 2015, no. 4 (December 30, 2015): 73–80. http://dx.doi.org/10.12737/17094.
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Quality ensuring in training students and educational institutions graduates is one of the state directions in the sphere of education. In view of this the significance consists in the development, introduction and improvement of the assessment model for the quality of training students on the baccalaureate’s , specialist’s and master’s curricula. This paper reports the model considered for the correspondence assessment of curricula to the requirements of the Federal State All-Russian Standard for Higher Vocational Education (FSARS HVE) on basis of four indices and thirtytwo criteria according to the recommendations of the Russian Accreditation Agency of the Russian federation. For each of the criteria there are shown documents and materials confirming its fulfillment. Failure to execute at least one of the criteria means lack of correspondence of the curriculum to the requirements of the FSARS HVE. A not less significant procedure of curricula quality assessment – a confirmation, by means of the presentation of documents and materials on the successful application of knowledge, abilities and skills obtained in the course of mastering a compulsory cur-riculum by students and graduates under real or simu-lated working conditions.
One of the conditions for the increase of curricula effectiveness – the availability in an educational institution (EI) of the incollege system for education quality assessment which would allow planned carrying out organizational measures on a fundamental analysis and objective self-appraisal of educational activities of all departments of the EI and obtaining complete information on the curricula realization, and also correcting a training procedure with the aim of quality increase in college graduate students training. The main purpose of such incollege system consists in the definition of areas for education quality increase in all kinds of activities of the university and its departments.
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Ghorbani, M. Jawad, and Hossein Mokhtari. "Impact of Harmonics on Power Quality and Losses in Power Distribution Systems." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 1 (February 1, 2015): 166. http://dx.doi.org/10.11591/ijece.v5i1.pp166-174.
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This paper investigates the harmonic distortion and losses in power distribution systems due to the dramatic increase of nonlinear loads. This paper tries to determine the amount of the harmonics generated by nonlinear loads in residential, commercial and office loads in distribution feeders and estimates the energy losses due to these harmonics. Norton equivalent modeling technique has been used to model the nonlinear loads. The presented harmonic Norton equivalent models of the end user appliances are accurately obtained based on the experimental data taken from the laboratory measurements. A 20 kV/400V distribution feeder is simulated to analyze the impact of nonlinear loads on feeder harmonic distortion level and losses. The model follows a “bottom-up” approach, starting from end users appliances Norton equivalent model and then modeling residential, commercial and office loads. Two new indices are introduced by the authors to quantize the effect of each nonlinear appliance on the power quality of a distribution feeder and loads are ranked based on these new defined indices. The simulation results show that harmonic distortion in distribution systems can increase power losses up to 20%.
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Prevc, Tjaša, Blaž Cigić, Rajko Vidrih, Nataša Poklar Ulrih, and Nataša Šegatin. "Correlation of Basic Oil Quality Indices and Electrical Properties of Model Vegetable Oil Systems." Journal of Agricultural and Food Chemistry 61, no. 47 (November 15, 2013): 11355–62. http://dx.doi.org/10.1021/jf402943b.
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