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Construction of the scale of quality perceived by electric power services offered by Brazilian companies

Quality and Quantity 2025年 1-22页

作者： de Souza Mendonça, Anny Key Schmitt, Jeovani da Silva, Silvio Aparecido de Andrade Conradi Barni, Gabriel Bornia, Antonio Cezar de Andrade, Dalton Francisco Federal University of Santa Catarina: Graduate Program in Production Engineering Santa Catarina Florianópolis Brazil

The global demand for electricity and the assessment of service quality provided by electricity utility companies requires robust methodological approaches to ensure accurate and reliable measurements. Traditional methods, such as Classical Test Theory (CTT), have been applied to the evaluation of latent traits, but they present limitations concerning reliability. Alternative methods derived from Psychometrics, such as Confirmatory Factor Analysis (CFA) and more recently, Item Response Theory (IRT), overcome these limitations. IRT offers advantages over CTT as it takes into account the difficulty and discrimination of each item, allowing for a more accurate estimation of the latent trait. In contrast, CTT uses only the total score, which can lead to inaccurate assessments. This paper applies Item Response Theory (IRT) to develop and validate a perceived quality of services scale. Using data from the Consumer Satisfaction Questionnaire of the Brazilian Electricity Regulatory Agency (ANEEL), Confirmatory Factor Analysis (CFA) and IRT validated the scale’s unidimensional structure, demonstrating high reliability, as well as the difficulty and discrimination of the items. The results identified four levels of perceived quality, with most consumers classified as satisfied or very satisfied, although regional disparities were observed—satisfaction was highest in the South and lowest in the North. These findings reinforce the advantages of IRT in service quality assessment, enabling detailed response pattern modeling and the development of standardized, interpretable scales. The validated instrument provides regulators and utility companies with a valuable tool for monitoring service quality and optimizing policies to enhance consumer satisfaction. Future research may refine benchmarking methodologies for cross-market comparisons. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

关键词： ANEEL consumer satisfaction index Consumer satisfaction Graded response model Item response theory Perceived quality Reliability Service quality metrics

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An Expert System for Decision Making in the Face of Imprecise, Inconsistent and Paracomplete Data – Metaverse Security Application Using DLP 14th

An Expert System for Decision Making in the Face of Imprecis...

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14th International Conference on Information, Intelligence, Systems, and Applications, IISA 2023

作者： Sakamoto, Liliam Sayuri Abe, Jair Minoro Graduate Program in Production Engineering Paulista University SP São Paulo Brazil

ISBN: (纸本)9783031674259

With the advancement of numerous applications of AI techniques, in situations involving imprecision or uncertainty, experts may issue inaccurate, conflicting opinions or omit information. The usual systems based on classical reasoning to manipulate such data show us difficulty in implementation or their logical analysis. Even decision-makers are not comfortable with the presence of inaccurate information. This work presents an expert system that allows manipulating data from databases with imprecise, inconsistent, or incomplete information. Such a system is based on a new class of non-classical logic, the paraconsistent annotated evidential logic Eτ, which allows working with the concepts mentioned earlier to provide a more reliable decision to the decision maker. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Expert systems

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The main contributions of digitalisation to servitisation

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International Journal of Manufacturing Technology and Management 2025年第3-5期39卷 358-389页

作者： Fronteli, Márcio Henrique Paladini, Edson Pacheco Gaspar Santa Catarina89111-009 Brazil Postgraduate Program in Production Engineering Federal University of Santa Catarina Carvoeira Florianópolis Santa Catarina88040-535 Brazil

Digital servitisation has aroused the interest of many researchers and managers. IoT, big data, and cloud computing are the most prominent technologies. This study sought to investigate the impact of other digital technologies (DTechs) on servitisation. This research is based on an exploratory-qualitative approach covering 146 published articles selected from the Scopus and Web of Science databases. We grouped the digital technologies that impacted servitisation positively. Our results were synthesised into four categories. These procedures allowed for building a framework that shows the contribution potential of digitisation as a success factor of servitisation, as well as competitive opportunities based on the combination of DTs. Digitisation is confirmed as the main driver for the development of digital-servitisation based business models. Our results aim to contribute to the industry in terms of establishing innovation strategies for business models. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Dynamic random access storage

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A Proposal for Markerless Gait Analysis Based on 3D Points Cloud 14th

A Proposal for Markerless Gait Analysis Based on 3D Points C...

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14th International Conference on Information Society and Technology, ICIST 2024

作者： da Rocha, Luiz Gustavo Schitz Rudek, Marcelo Pontifical Catholic University of Parana PUCPR Production and System Engineering Graduate Program – PPGEPS Curitiba Brazil

ISBN: (纸本)9783031714184

This paper proposes a solution for markerless gait analysis based on point cloud data, which are three-dimensional data obtained by sensors such as LiDAR, that can capture body movements in real-time and in various environments. Gait analysis aims to evaluate the differences in symmetry between the left and right sides of the body, which can indicate diseases such as Parkinson’s and Alzheimer’s. The point cloud is a sparse matrix with N points in 3D space and the intensity of reflected light, which does not have an ordering between the points and the minimum distance between them is responsible for the density of the cloud. In the proposed method the point cloud is transformed into voxels, which are cubic units that facilitate data processing, and each set of points in the voxel is used for person detection. The points of the person are used to segment the body parts, and each part is used to estimate the joint position. The joint position is used to construct a rigid body model, where a person is represented by their segments. The rotations and translations of the segment over time are used to build the gait analysis graph. By comparing the rotation of each segment over time, it is possible to calculate the difference between the left and right sides and detect at what moment of the movement the difference is large enough to indicate the onset of pathology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Neurodegenerative diseases

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Physics-Constrained Data-Driven Dynamic Modeling of Underactuated Robotic Systems 6

Physics-Constrained Data-Driven Dynamic Modeling of Underact...

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6th IEEE Novel Intelligent and Leading Emerging Sciences Conference, NILES 2024

作者： Asker, Ahmed Nile University Meng Program Giza Egypt Mansoura University Faculty of Engineering Production Engineering and Mechanical Design Dept. Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378511

Underactuated robots are intriguing systems that have found numerous applications across various fields. These systems are characterized by having fewer actuators than degrees of freedom, resulting in complex behaviors that challenge traditional modeling and control techniques. Despite the prevalent use of data-driven modeling, extracting the dynamic model of underactuated systems is particularly challenging. This paper focuses on deriving from data the dynamic model of the Double Inverted Pendulum on a Cart (DIPC). The Euler-Lagrange equations are employed to derive the model's terms from the symbolic form of the DH parameters of the system. The coefficients of the model terms are obtained by formulating a constrained least-squares (LS) problem. The constraints leverage the properties of the robot's dynamic equations to limit the solution space to the physically possible ones. The conventional LS method failed to calculate the coefficients of the underactuated DIPC and got only the trivial solution. The proposed method accurately identifies the dynamic model of the underactuated DIPC, overcoming issues related to finding a solution by searching the null space of the regressor matrix and dealing with ill-conditioned regressor matrices. The proposed method provides a systematic approach for determining the dynamic model of actuated or underactuated robotic systems. Additionally, it can extend the capabilities of dynamic simulation software by extracting the nonlinear dynamic model of the robot from simulation data. © 2024 IEEE.

关键词： Inverted pendulum

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Analysis of the ANEEL Consumer Satisfaction Index Through the Application of Item Response Theory 29th

Analysis of the ANEEL Consumer Satisfaction Index Through th...

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29th International Joint Conference on Industrial engineering and Operations Management, IJCIEOM 2023

作者： de Souza Mendonça, Anny Key da Silva, Silvio Aparecido Bornia, Antonio Cezar de Andrade, Dalton Francisco Graduate Program in Production Engineering Federal University of Santa Catarina SC Florianópolis Brazil

ISBN: (纸本)9783031470578

This research aims to measure the ANEEL Consumer Satisfaction Index (IASC) of CELESC electricity distributor through the application of the Item Response Theory. The IASC is an indicator that allows evaluates the satisfaction of the residential consumer with the services provided by the electricity distributor with the intention of stimulating continuous improvement. The data set of the satisfaction survey fulfilled out by ANEEL in 2020 is quantitative and was obtained through secondary sources. It was possible to test the validity and internal consistency of the items and through the Item Response Theory (IRT) an interpretable scale was built to measure the level of consumer satisfaction. It was possible to calculate and explain the information curves of the items and the test, as well as demonstrate the gain that can be obtained with its application to measure the level of consumer satisfaction. The satisfaction level scale was created in five categories: "very dissatisfied, dissatisfied, neither dissatisfied/nor satisfied, satisfied and very satisfied. The results showed that 1.05% of consumers are very dissatisfied, 15.85% are dissatisfied, 55.75% are neither dissatisfied/nor satisfied with the company;26.31% are satisfied, and 1.05% are very satisfied with the energy distributor. The created scale allows the energy distributor to monitor the measured indicators and evaluate the evolution of consumer satisfaction. In addition, managers to develop strategies to improve the level of consumer satisfaction can use the model created, to achieve continual improvement in service delivery of the Electricity Distributor. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： ANEEL consumer satisfaction index Consumer satisfaction Item response theory

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Empirical mode decomposition of near-infrared spectroscopy signals for predicting oil content in palm fruits

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Information Processing in Agriculture 2023年第3期10卷 289-300页

作者： Inna Novianty Ringga Gilang Baskoro Muhammad Iqbal Nurulhaq Muhammad Achirul Nanda Computer Engineering Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Informatics Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Technology and Plantation Production Management Study Program College of Vocational StudiesIPB UniversityBogor 16680Indonesia Department of Agricultural and Biosystem Engineering Faculty of Agro-Industrial TechnologyUniversitas PadjadjaranJatinangor 45363Indonesia

Oil content estimation in palm fruits is a precious property that significantly impacts oil palm production,starting from the upstream and *** content can be used to monitor the progress of the oil palm fresh fruit bunch(FFB)and be applied to identify product *** on the near-infrared(NIR)signals,this study proposes an empirical mode decomposition(EMD)technique to decompose signals and predict the oil content of palm ***,350 palm fruits with Tenera varieties(Elaeis guineensis ***),at various ages of maturity,were harvested from the Cikabayan Oil Palm Plantation(IPB University,Indonesia).Second,each sample was sent directly to the laboratory for NIR signal measurements and oil content ***,the EMD analysis and arti-ficial neural network(ANN)were employed to correlate the NIR signals and oil ***,a robust EMD-ANN model is generated by optimizing the lowest possible *** on performance evaluation,the proposed technique can predict oil content with a coefficient of determination(R2)of 0.933±0.015 and a root mean squared error(RMSE)of 1.446±*** results demonstrate that the model has a good predictive capacity and has the potential to predict the oil content of palm fruits directly,without neither solvents nor reagents,which makes it environmentally ***,the proposed technique has a promising potential to be applied in the oil palm *** like this will lead to the effective and efficient management of oil palm production.

关键词： Artificial neural network Empirical mode decomposition Oil palm Oil content prediction

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Circular Economy of Water: A Review of Scientific production 2nd

Circular Economy of Water: A Review of Scientific Production

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2nd International Conference on Water Energy Food and Sustainability, ICoWEFS 2022

作者： Endo, Gustavo Yuho Lenzi, Giane Gonçalves Postgraduate Program in Production Engineering Federal University of Technology – Paraná Ponta Grossa84017-220 Brazil

ISBN: (纸本)9783031268489

The general aim of the research was to analyse the scientific production on the circular economy of water in the Web of Science database. The systematic and integrative review used the Methodi Ordinatio, which made it possible to identify the most relevant articles on the circular economy of water. The main findings were the identification of 38 articles on the circular economy of water, in which the years 2018 and 2020 were the years with the most publications. The contexts already studied demonstrated that the circular economy is related to assessing the life cycle, the techniques related to the reuse and recovery of water, education models and strategic issues. The areas surveyed were mainly associated with the public area, tourism, entrepreneurship and manufacturing. It is essential to emphasise the importance of research related to water since the concern with this resource has been observed. The discussions are far from being exhausted;therefore, a proposal for a future agenda has been presented, indicating the direction for future research about the theme. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Water conservation

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A methodology for coffee price forecasting based on extreme learning machines

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Information Processing in Agriculture 2022年第4期9卷 556-565页

作者： Carolina Deina Matheus Henrique do Amaral Prates Carlos Henrique Rodrigues Alves Marcella Scoczynski Ribeiro Martins Flavio Trojan Sergio Luiz Stevan Jr Hugo Valadares Siqueira Department of Production Engineering Federal University of Rio Grande do Sul90.035-190Brazil Department of Electronics Federal University of TechnologyParana 84017-220Brazil Graduate Program in Production Engineering Federal University of TechnologyParana 84017-220Brazil

This work introduces a methodology to estimate coffee prices based on the use of Extreme Learning *** process is initiated by identifying the presence of nonstationary components,like seasonality and *** components are withdrawn if they are ***,the temporal lags are selected based on the response of the Partial Autocorre-lation Function *** predictors,we address the following models:Exponential Smooth-ing(ES),Autoregressive(AR)and Autoregressive Integrated and Moving Average(ARIMA)models,Multilayer Perceptron(MLP)and Extreme Learning Machines(ELMs)neural *** computational results based on three error metrics and two coffee types(Ara-bica and Robusta)showed that the neural networks,especially the ELM,can reach higher performance levels than the other *** methodology,which presents preprocess-ing stages,lag selection,and use of ELM,is a novelty that contributes to the coffee prices forecasting field.

关键词： Coffee price forecasting Linear models Artificial neural networks Computational intelligence

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Truck Scheduling: A Case Study in the Automotive Sector

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International Journal of Applied and Computational Mathematics 2024年第2期10卷 1-24页

作者： de Oliveira, Caroline Maruchi Kleina, Mariana da Silva, Arinei Carlos Lindbeck Postgraduate Program in Production Engineering Federal University of Parana Av. Cel. Francisco Heráclito dos Santos 210 Paraná Curitiba 19011 Brazil

Logistic companies face several problems in their services, leading to increased time and costs in their operations. These issues could be mitigated if decision-making were based on models that consider resource optimization and respect process constraints. An example of this problem is the queues generated by trucks at docks for loading and unloading materials in the automotive sector. Therefore, this work studies truck scheduling with the inclusion of forbidden time windows for breaks. The aim is to propose a mathematical model in order to minimize the time spent by drivers within companies and to present exact and approximate solutions with the use of Operational Research techniques and algorithms. Methods and algorithms that adapt to this type of problem were identified. Then, the mathematical model was developed, computationally implemented in the LINGO and Gurobi software, and validated according to the case study conditions. A metaheuristic based on the Simulated Annealing algorithm was implemented in Visual Basic for Applications language, and used as a form of approximate resolution for problems larger than the ones solved optimally. Computational experiments were conducted to evaluate the performance of the model and metaheuristic proposed. The GAP between the metaheuristic solution and the optimal solution is less than 4% for all problems tested. For larger problems, with more than 10 trucks and 5 docks, Gurobi optimization software is not able to find the optimal solution in a feasible time. However, the metaheuristic is able to find good solutions for bigger problems in a reasonable time. Therefore, results proved the performance of the mathematical model, indicating that truck scheduling is an important tool for automotive companies, as it can help to improve efficiency and productivity. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Forbidden time window Open Shop Simulated Annealing Truck scheduling

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