Tópicos Sugeridos dentro de su búsqueda.
Tópicos Sugeridos dentro de su búsqueda.
Buscar alternativas:
predicting process » writing process (Expander búsqueda), picking process (Expander búsqueda), pressing process (Expander búsqueda)
para predicting » para prediccion (Expander búsqueda), padua prediction (Expander búsqueda)
predicting process » writing process (Expander búsqueda), picking process (Expander búsqueda), pressing process (Expander búsqueda)
para predicting » para prediccion (Expander búsqueda), padua prediction (Expander búsqueda)
1
artículo
Publicado 2017
Enlace
Enlace
Peruvian retail market today, more than ever, has turned the phrase “everything goes through the eyes” into a competitive tool. The design and optimization of space, as well as visual merchandising, are techniques that impact the sale new concepts such as omnicanality and buying experience are fed by data analytics in order to describe the commercial mode; and new qualitative sources of information, among them color theory, specially help to understand and predict the impact of future decisions on the point of sale. This paper describes the utility of image processing techniques to innovate the retail market in the effort to extract useful information from advertising pieces frequently used in this sector.
2
artículo
Publicado 2017
Enlace
Enlace
Peruvian retail market today, more than ever, has turned the phrase “everything goes through the eyes” into a competitive tool. The design and optimization of space, as well as visual merchandising, are techniques that impact the sale new concepts such as omnicanality and buying experience are fed by data analytics in order to describe the commercial mode; and new qualitative sources of information, among them color theory, specially help to understand and predict the impact of future decisions on the point of sale. This paper describes the utility of image processing techniques to innovate the retail market in the effort to extract useful information from advertising pieces frequently used in this sector.
3
artículo
Publicado 2016
Enlace
Enlace
Teachers´ engagement in change processes is closely related to their attitudes and views on education. Therefore, any successful educational change demands that teachers reevaluate their profession, as personal and professional factors are clearly relevant. The goal of this study is to test a predictive statistical model of teacher´s engagement in educational change considering personality factors and self-evaluation. The random and representative sample of Peruvian teachers comprised of 888 subjects. Results show good model fit and a strong predictive power on educational changes. The study confirms that personality and selfconcept are strong predictors on teacher´s engagement with educational change.
4
artículo
Publicado 2016
Enlace
Enlace
Teachers´ engagement in change processes is closely related to their attitudes and views on education. Therefore, any successful educational change demands that teachers reevaluate their profession, as personal and professional factors are clearly relevant. The goal of this study is to test a predictive statistical model of teacher´s engagement in educational change considering personality factors and self-evaluation. The random and representative sample of Peruvian teachers comprised of 888 subjects. Results show good model fit and a strong predictive power on educational changes. The study confirms that personality and selfconcept are strong predictors on teacher´s engagement with educational change.
5
artículo
Publicado 2008
Enlace
Enlace
The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.
6
artículo
Publicado 2008
Enlace
Enlace
The predictive control (MPC) is an advanced control strategy widely used in industrial processes. MPC is also one of the most active areas of research in the theory of control. Subjects such as optimality, stability and robustness are well known, especially for linear systems. However, despite this large adoption, both in the media industry and academics, little has been written about how these drivers are implemented in practice. This article tries to fill this gap, introducing the development of systems optimization and MPC, and discussing their integration into a hierarchical control structure. The proposed integrated control scheme is applied to the Tennessee Eastman plant, and the results show the effectiveness of the proposed strategy for optimal control of processes.
7
artículo
Publicado 2021
Enlace
Enlace
In the present study, the control of the pyrolysis temperature was carried out in a gasification process of eucalyptus wood, its prediction is made based on the operating parameters of the reactor to ensure the obtaining of a synthesis gas with the required quality. The results obtained from the mathematical modeling for the prediction of the pyrolysis temperature with the use of artificial intelligence techniques and the development of artificial neural networks are shown, with experimental data of the process. For this reason, an experimental statistical design of type 3n was implemented, with two additional replications, by means of which the training of an artificial neural network capable of predicting the pyrolysis temperature in a downdraft type gasifier with cogeneration was carried out. The prediction of the pyrolysis temperature has an error of 4.6 oC and an adjustment of 93.71...
8
objeto de conferencia
Publicado 2021
Enlace
Enlace
The main objective of this research was to show the predictive model implementation effects adjusted to grinding process on the economic profitability of a rice milling company. In first instance, quality and production area database was used to model a multiple regression equation, using the “Step by Step” technique in Minitab 19, resulting in: Actual Performance = 0.001 + 0.9317Hest Analysis - 0.000339 Processed Sacks; Predictive R2 = 95.81% and PRESS = 47.5168; concluding that the model fits the process, it is significant and has good predictive capacity. The regression equation was then simulated with Monte Carlo by analyzing probabilities and ranges in MS-Excel, earning operational revenue amounting to S/. 3,263,787.74 corresponding to an improvement of 3.94% compared to 2019, thus improving the company's economic profitability to 9.34% in Net Profit Margin and 15.92% in the ROA...
9
artículo
Publicado 2015
Enlace
Enlace
Strategic consensus in work teams is a group process related to the shared comprehension among team members of the strategies defined to attain work goals. This study aimedto verify the predictive power of strategic consensus in relation to team performance. The prediction model was constructed based on data collected from teachers and coordi-nators of 70 educational institutions in Ecuador. The individual data were aggregated per institution to obtain group level scores. The results indicate that strategic consensus predicts about 6% of the team performance as rated by the coordinator. We concluded that more studies are required to gain a better understanding of the role of strategic consensus in workteams.
10
artículo
Publicado 2025
Enlace
Enlace
Predicting the onset of psychosis is crucial for early intervention and improved outcomes. This review examines the current state of prediction models based on clinical, neurocognitive, and linguistic factors. Clinical predictors, including sociodemographic characteristics, family history, and subthreshold psychotic symptoms, have shown promise in identifying people at risk, and some models achieve concordance indices of 0.79-0.80 in external validation. Neurocognitive evaluation, particularly of verbal learning, processing speed, and attention/vigilance, has emerged as a cost-effective predictor, although the effect sizes remain modest. Recent advances in natural language processing have enabled automated analysis of speech patterns, with reduced semantic coherence and specific linguistic features predicting the transition to psychosis with precisions of up to 83%. Although these approa...
11
artículo
The objective of this research work is to provide a new predictive approach to fragmentation in the rock blasting processes, developed based on the Kuz-Ram model, Multivariate Analysis techniques (MVA) and Artificial Neural Network techniques (ANN).The objective of the new approach predictive approach to (X50), fragmentation is based on the fact that this research, would provide us with an optimization in the metallurgical mining operations, because delivering an optimal fragmentation requerid for the grinding processes, it could minimize their times and maximize their productivity.
12
objeto de conferencia
Prediction of the river flow, irradiance and wind velocity is a challenge for all the countries to improve the natural resources, the uses of the satellite and meteorological data allow to improve the statistical processing, in this research article a new methodology is proposed for the river flow forecasting in Lima, it is associated to the Transandean tunnel with the watershed of the Atlantic and Pacific ocean. with the basins of Tamboraque, Sheque and Tulumayo. Our findings are the implementation of river flow prediction with the data from 2016 to 2022 with an hourly data, the forecasting allows to obtain information from the satellite data of ambient temperature, rainfall precipitation, wind velocity and atmospheric pressure and evaluated river flows in three basins, with the MAE and RMSE metrics evaluation, it is Tamboraque (3.63 m/s and 5.55), Sheque (0.92 m/s and 1.29 m/s) and Tul...
13
artículo
Desertion is a problem that affects public and private universities, and leads to a series of negative consequences for both institutions and students. Therefore, the objective of this study was to determine how the use of predictive models in low pass-rate courses helps to identify students at risk of desertion. Seven predictive models were designed using CRISP (Cross- Industry Standard Process for Data Mining) methodology and students’ academic records to be applied in seven low pass-rate courses. Among the main results, it can be noted that predictive models contributed to the reduction of fail rates by 25% and 40%, and that the variables that best forecast desertion were career choice (vocation), number of times students enrolled in the course, and grades obtained in mathematics or language arts when students attended the fifth year of high school.
14
artículo
Publicado 2023
Enlace
Enlace
Early mathematical competencies have a great impact on academic performance and on the development of more complex mathematical skills, especially in early education. Several authors have highlighted the importance of working memory and inhibition in the development of these mathematical skills; however, there is no agreement regarding the explanatory capacity of these executive domains with respect to differentiated performance in mathematics. The aim of this research was to evaluate the predictive capacity of verbal and visuospatial working memory and of behavioral and cognitive inhibition in mathematical competencies of relational logic and numerical type in 106 Chilean children of early education between 4 and 6 years old, who were evaluated with four executive tasks and an early mathematical assessment test. For data analysis, correlations and multiple linear regressions were perfor...
15
artículo
Publicado 2019
Enlace
Enlace
Cervical cancer is currently the fourth most frequent type of cancer in women. A large number of techniques from the Artificial Intelligence (AI) such as Neuronal Networks, Support Vector Machines (SVM), Decision Trees and others; have been used to deal with the problem of predicting this disease. The following paper shows the cervical cancer risk prediction, by implementing a probabilistic model based on Bayesian Networks and using 322 instances where we could retrieve 15 different features that are known information from each patient. The tests were made using the 40% of the whole dataset, confusion matrix and AUC indicator. The results show that this work has raised a 96% of success rate as well as 0.9864 in terms of the AUC indicator, in addition to this, the results suggest that Bayesian Networks are able to reach a high performance and provide transparency during the inference proc...
16
tesis doctoral
Publicado 2023
Enlace
Enlace
State-of-the-art control and robotics challenges have long been tackled using model-based control methods like model predictive control (MPC) and reinforcement learning (RL). These methods excel in complex dynamic domains, such as manipulation tasks, but struggle with real-world issues like wear-and-tear, uncalibrated sensors, and misspecifications. These factors often perturb system dynamics, leading to the 'reality gap' problem when robots transition from simulations to real-world environments. This work aims to bridge this gap by combining RL and control in a learning framework that adapts MPC to robot decisions, optimizing performance despite uncertainties in dynamics model parameters. This thesis presents three key contributions to robotics control. The first is a novel reward-based framework for refining stochastic Model Predictive Control (MPC). It utilizes Bayesian Optimization (...
17
artículo
Publicado 2021
Enlace
Enlace
The results of 4 predictive models, logistic regression, decision trees, KNN and a neural network are compared to predict the academic dropout of students at the National Intercultural University of the Amazon, applied to a dataset extracted from the system's database. of academic management of the university, which contains socioeconomic and academic performance data which were processed and formatted using onehotencoding techniques in order to apply the predictive models already mentioned. For data processing and formatting, Transac Sql queries were used and the application of predictive models was done through Knime Software and using Python through Google Colab. The results obtained by applying 4 predictive models are very good since they all exceeded 80% of Accuracy, which guarantees that they can be put into production for the benefit of the university and thus can make better deci...
18
artículo
Publicado 2024
Enlace
Enlace
Gentrification is an urban phenomenon that displaces the original inhabitants of a neighborhood due to regeneration processes. In this analysis carried out in the historic center of the heritage city of Cuenca, the beginning of the process does not necessarily respond to a significant transformation of the architecture. It has been proven that the phenomenon arises invisibly due to changes in the demographic composition of the neighborhood. The methodology of this research requires the correlation of census data for each minimum applicable unit known as a block. This information is contrasted with historical photographs available on the Google platform. The significant contribution to the concept of gentrification results in a method that allows identifying and predicting the phenomenon, more important than its visual-late diagnosis.
19
artículo
Publicado 2022
Enlace
Enlace
Solid waste management is one of the main environmental challenges in cities around the world due to factors such as population growth and consumption habits. One of the main tools for the design of waste management projects is the estimation of per capita generation, however, the traditional method to obtain this information demands a lot of effort and time, therefore this research proposes an alternative approach to estimate per capita generation based on socioeconomic factors. For this purpose, socioeconomic demographic information and information on the per capita generation of solid waste of 50 families was collected, subsequently the variables that have significant influence were determined from the correlation coefficient ρ of Spearman for numerical variables and an ANOVA for categorical variables with an acceptance threshold of 0.4 and 0.05 respectively. The selected variables w...
20
tesis doctoral
Publicado 2020
Enlace
Enlace
Descargue el texto completo en el repositorio institucional de la Universidade Estadual de Campinas: https://hdl.handle.net/20.500.12733/1641647
