Emilio L. Cano

Emilio L. Cano
King Juan Carlos University | URJC · Computer Science and Statistics

PhD

About

91
Publications
29,046
Reads
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210
Citations
Introduction
Data Scientist. Associate professor at the University of Castilla-La Mancha. R enthusiast and activist.
Additional affiliations
September 2020 - present
King Juan Carlos University
Position
  • Professor
Description
  • Research group: Data Science Laboratory
September 2017 - September 2020
University of Castilla-La Mancha
Position
  • Professor
September 2016 - August 2017
University of Castilla-La Mancha
Position
  • Professor
Education
September 2011 - June 2014
King Juan Carlos University
Field of study
  • Information Systems
September 2010 - June 2011
King Juan Carlos University
Field of study
  • Decision Science
October 2009 - September 2010
Complutense University of Madrid
Field of study
  • Statistics

Publications

Publications (91)
Article
Full-text available
Sensors have become a key element for the development of the Information Society [...].
Article
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In this paper, a method to classify behavioural patterns of cattle on farms is presented. Animals were equipped with low-cost 3-D accelerometers and GPS sensors, embedded in a commercial device attached to the neck. Accelerometer signals were sampled at 10 Hz, and data from each axis was independently processed to extract 108 features in the time a...
Article
Scrum is an iterative and incremental development framework that, nowadays, is mainly used for software development. In this work, a Scrum-Based New Product Development (SBNPD) approach is introduced. This new framework stems from the basis of Scrum and incorporates tools suitable for being applied to the design and development of physical products...
Article
Full-text available
The success on the design of new oral nanocarriers greatly depends on the identification of the best physicochemical properties that would allow their diffusion across the mucus layer that protects the intestinal epithelium. In this context, particle tracking (PT) has arisen in the pharmaceutical field as an excellent tool to evaluate the diffusion...
Article
Some of the most overlooked valuation systems in current literature are those based on expert algorithms. Yet these algorithms can form the basis of a good estimation of the value of real estate since they allow simple computational methods that use big data to be integrated with the appraiser’ own knowledge of the situation. The main usefulness of...
Article
Full-text available
The close relationship between collateral value and bank stability has led to a considerable need to a rapid and economical appraisal of real estate. The greater availability of information related to housing stock has prompted to the use of so-called big data and machine learning in the estimation of property prices. Although this methodology has...
Article
We studied changes in chemical composition, somatic cell count, and immunoglobulin G (IgG) and M (IgM) content in red deer (Cervus elaphus) colostrum during the transition to milk at different times after parturition (<5 h, 24 h, 48 h, 2 wk, and 4 wk). The production level was higher at 2 and 4 wk of lactation than during the first day after partur...
Article
This study evaluated the viability of using oil extracted from Salvia hispanica L. seeds as a source of omega-3 for sheep's cheese enrichment. Two concentrations (3 and 5 g/L) of chia oil prepared as emulsions stabilized with calcium caseinate were assayed in pressed sheep's milk cheese, and their physicochemical, microbiological and organoleptic p...
Article
During the last decade, there has been growing interest to grant nanoparticles with diffusion properties across mucosae. In this sense, the non-ionic block copolymer Pluronic F127 (PF127) has arisen as a promising coating agent to formulate mucus penetrating particles (MPP). In the journey to find efficient coating agents, most of the studies have...
Article
Full-text available
Energy systems optimization under uncertainty is increasing in its importance due to on-going global de-regulation of the energy sector and the setting of environmental and efficiency targets which generate new multi-agent risks requiring a model-based stakeholders dialogue and new systemic regulations. This paper develops an integrated framework f...
Conference Paper
In this work we develop an integrated framework for energy-efficient technology investments based on a Deci- sion Support System (DSS). The framework provides an environment that promotes the necessary stakeholders dialog, been this the main contribution of this research. The proposed scheme allows the represenation of the optimization model, inclu...
Chapter
In order to assess quality, specification limits are to be established. In this chapter a method to set specification limits taking into account customers’ and producer’s loss is presented. Furthermore, the specification limits are the voice of the customer, and quality can be assessed by comparing it with the voice of the process, that is, its nat...
Chapter
Control charts constitute a basic tool in statistical process control. This chapter develops the fundamentals of the most commonly applied control charts. Although the general basic ideas of control charts are common, two main different classes are to be considered: control charts for variables, where continuous characteristics are monitored; and c...
Chapter
In many situations, processes are often represented by a function that involves a response variable and a number of predictive variables. In this chapter, we show how to treat data whose relation between the predictive and response variables is nonlinear and, as a consequence, cannot be adequately represented by a linear model. This kind of data ar...
Chapter
The aim of this chapter is to smoothly introduce the reader to Quality Control techniques from the so-called Seven Basic Quality Control tools: Cause-and-effect-diagram, check sheet, control chart, histogram, Pareto chart, scatter diagram, and stratification. These are basic but powerful tools when used wisely.
Chapter
This chapter introduces Quality Control by means of an intuitive example. Furthermore, that example is used to illustrate how to use the R statistical software and programming language for Quality Control. A description of R outlining its advantages is also included in this chapter, all in all paving the way to further investigation throughout the...
Chapter
This chapter introduces R as statistical software and programming language for quality control. The chapter is organized as a kind of tutorial with lots of examples ready to be run by the reader. Moreover, the code is available at the book’s companion website. Even though the RStudio interface is also introduced in the chapter, any other user inter...
Chapter
This chapter provides the necessary background to understand the fundamental ideas of descriptive and inferential statistics. In particular, the basic ideas and tools used in the description both graphical and numerical, of the inherent variability always present in real world are described. Additionally, some of the most usual statistical distribu...
Chapter
Undoubtedly, an effective but expensive way of providing conforming items to a customer is making a complete inspection of all items before shipping. In an ideal situation, a process designed to assure zero defects would not need inspection at all. In practice, a compromise between these two extremes is attained, and acceptance sampling is the qual...
Chapter
This chapter details the way ISO international standards for quality control are developed. Quality Control starts with Quality, and standardization is crucial to deliver products and services where quality satisfies final users, whatever they are customers, organizations, or public bodies. The development process, carried out by Technical Committe...
Chapter
Statistical Quality Control tries to predict the behavior of a given process through the collection of a subset of data coming from the performance of the process. This chapter showcases the importance of sampling and describes the most important techniques used to draw representative samples. An example using R on how to plot Operating Characteris...
Article
Strategic decision making at the building level is gaining importance in the context of a more and more deregulated energy market. The increase of the set of available options regarding distributed and renewable energy technologies leads to a complex decision process. Importantly, such decision making process is affected by uncertainties and theref...
Article
Full-text available
Optimization instances relate to the input and output data stemming from optimization problems in general. Typically, an optimization problem consists of an objective function to be optimized (either minimized or maximized) and a set of constraints. Thus, objective and constraints are jointly a set of equations in the optimization model. Such equat...
Conference Paper
Full-text available
Una norma ISO está reconocida y aceptada internacionalmente. Son desarrolladas por expertos de todo el mundo a través de comités técnicos a los que pertenecen entidades de normalización nacionales como AENOR, que canaliza la participación española en la elaboración de normas. El subcomité AENOR de métodos estadísticos CTN66/SC3 participa en el comi...
Article
Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control prof...
Article
Strategic decisions regarding energy systems deployment at the building level are becoming a great challenge in the global market. On the one hand, competition policies are allowing the arriving of new actors to the market, resulting in sophisticated pricing options. On the other hand, efficiency and sustainability policies and regulations aim at e...
Article
Due to deregulations of the energy sector and the setting of targets such as the 20/20/20 in the EU, operators of public buildings are now more exposed to instantaneous (short-term) market conditions. On the other hand, they have gained the opportunity to play a more active role in securing long-term supply, managing demand, and hedging against ris...
Conference Paper
Full-text available
The process of developing and implementing technical standards, or standardisation, is usually unknown, and often even disregarded. Nontheless, in specific areas of activity, such as Electrical Engineering or Aeronautics, practitioners are more concerned as technical standars are mandatory in many cases. However, in crossing disciplines as Statisti...
Conference Paper
Full-text available
Within the EnRiMa project (Energy Efficiency and Risk Management in Public Buildings) a Decision Support System (DSS) is being developed aiming at supporting building operators on both operational and strategic decisions. Such DSS is composed by several integrated modules, which are in charge of specific tasks as a distributed system. Even though S...
Article
La liberalización del sector energético ha promovido la aparición de oportunidades y retos para los responsables de las facturas energéticas y operadores del sistema energético de los edificios. La Directiva de Eficiencia Energética en edificios también va encaminada en esa dirección [1]. La volatilidad de los precios de energía y las restricciones...
Conference Paper
Building managers and operators as at Campus Pinkafeld are interested in a cost optimal fulfilment of their energy needs. From a strategic point of view they are interested in optimal investments and upgrades. From an operative point of view they are interested in an optimal use of all available resources. This paper shows how the decision support...
Conference Paper
Full-text available
Within the frame of a Decision Support System for decision making concerning energy-efficient buildings, a flexible framework for dynamic generation of optimization models is advisable in order to allow reproducibility and scalability and avoid limited solutions. In this work, a new framework for model representation and integration is presented. F...
Conference Paper
Full-text available
Industries and companies recognize that increasing efficiency of energy use and/or implementing alternative methods of production and operation with energy conservation/saving technologies may increase profit. Due to deregulation of the energy sector and the setting of targets such as the 20/20/20 in the EU, operators are now more exposed to short-...
Book
Full-text available
Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. With Six Sigma, we are solving problems and improving processes using as a basis one of the most powerful tools of human development: the scientific method. For the analysis of data, Six Sigma requires the use of statistical software, being R an Open Sour...
Chapter
Pareto analysis is a technique that can be used in several stages of a Six Sigma project. In the Measure phase of the design, measure, analyze, improve, and control cycle, we use it to prioritize the possible causes of defects and then focus on the important ones. The basis of Pareto analysis is the Pareto principle, which applies to many processes...
Chapter
Capability analysis is a very important part of the Measure phase in a Six Sigma project. It is also part of classical statistical process control. Through capability analysis we can measure how the process performance fits the customer/client requirements. These requirements must be translated into the specification limits for the characteristic o...
Chapter
Charts are particularly important in Six Sigma projects. The aim of a chart is usually to support the interpretation of data. Hence, providing an adequate explanation of data through charts is crucial. Two-dimensional charts can be used as the basis for more complex representations, and multidimensional data can be shown through extensions of these...
Chapter
Most features defining a product are not usually important to the customer. Only a few of them are critical to quality, in particular, those defining what the customer expects. To meet these expectations, the processes involved in the development of the final product should be correct. This is the Six Sigma way: high-quality processes lead automati...
Chapter
R is a system for statistical computing and graphing. It consists of a language and a software environment. R has been widely used for academic and research purposes and is increasingly being deployed in corporate environments. R is a freely available software, under a GNU license, and is supported by the R Development Core Team. The strength of R...
Chapter
Engineers usually associate statistical process control (SPC) with a set of charts to monitor whether the outputs of a process are in or out of control. This is the classic approach to quality control (QC) and consists of adjusting processes only when their outputs are out of control. Under this approach, inspection is a standard way to proceed. On...
Chapter
Statistics can be defined as the collection, classification, analysis, and interpretation of data. It is a mathematical discipline traditionally divided into two fields: descriptive statistics and inferential statistics. It makes use of the tools and methods of probability theory. Nowadays, statistics is an interdisciplinary knowledge area, used in...
Chapter
Full-text available
Process mapping is a tool to retrieve information about a process. This information will be used in the phases of the Six Sigma project to be discussed later, and many of the measurements, analyses, and conclusions will be based on this information. The result of process mapping is a map of a process. This map stems from the Project Charter and sho...
Chapter
In this chapter, we describe other tools and methodologies related to the topic of the book. In this way, we provide for the reader a global view of the advanced possibilities of Six Sigma and R. These tools include failure mode, effects, and criticality analysis (FMECA), design for Six Sigma (DFSS), lean, Gantt charts, and some advanced R reportin...
Chapter
Full-text available
Statistical inference is the branch of statistics whereby we arrive at conclusions about a population through a sample of the population. We can make inferences concerning several issues related to the data, for example, the parameters of the probability distribution, the parameters of a given model that explains the relationship among variables, g...
Chapter
Design of experiments (DoE) is one of the most important tools in the Six Sigma methodology. It is the essence of the Improve phase and the basis for the design of robust processes. An adequate use of DoE will lead to the improvement of a process, but a bad design can result in wrong conclusions and engender the opposite of the desired effect: inef...
Chapter
Full-text available
Measurement system analysis (also known as gage R&R study) identifies and quantifies the sources of variation that influence the measurement system. R&R stands for repeatability and reproducibility. It is a very important matter in Six Sigma, because if the variability of the measurement system is not controlled, then the process cannot be improved...
Chapter
Full-text available
Many total quality management methodologies have been introduced in recent decades. Six Sigma has emerged as a breakthrough methodology. With Six Sigma, we are solving problems and improving processes using as our basis one of the most powerful tools of human development: the scientific method. The basis of the Six Sigma methodology is the DMAIC cy...
Conference Paper
Full-text available
In this work we describe the strategic planning module of a decision-support system (DSS) for operators of energy-efficient buildings and spaces of public use. This DSS is been developed within the EU Energy Efficiency and Risk Management in Public Buildings (EnRiMa) project. In particular, we focus on Symbolic Model Specification (SMS) by defining...
Book