Manuel Vargas

Intelligent Packaging Systems: Sensors and Nanosensors to Monitor Food Quality and Safety

The application of nanotechnology in different areas of food packaging is an emerging field that will grow rapidly in the coming years. Advances in food safety have yielded promising results leading to the development of intelligent packaging (IP). By these containers, it is possible to monitor and provide information of the condition of food, packaging, or the environment. This article describes the role of the different concepts of intelligent packaging. It is possible that this new technology could reach enhancing food safety, improving pathogen detection time, and controlling the quality of food and packaging throughout the supply chain.

Copper Metal Price Using Chaotic Time Series Forecating

The present research focuses on the ability to generate a predictive model of the future value of the price of copper using time series of the international price of copper from the last 30 years and the study of chaotic systems. The interest of this study lies in the economic, political and social impacts on a large number of countries with economies based on non-renewable mineral resources. Our approach uses the theoretical foundation of nonlinear dynamic systems for the characterization and analysis of the time series with chaotic component, by using nonlinear tools and methods. Recurrence visual analysis, the Fourier spectrum, the autocorrelation function, mutual information and the Lyapunov exponents are the methods used in the analysis phase of the series, and then a predictive model was generated using nonlinear system techniques. The results identify two cycles of copper prices and price forecasts in the short term. These cycles are connected by a transient and provide further evidence of the effect of investment cycles and infrastructure industries to the value of commodities.

Proposal of Two Measures of Complexity Based on Lempel-Ziv for Dynamic Systems: An Application for Manufacturing Systems

The measure of complexity of Lempel-Ziv (LZC) is used for the analysis of time series generated by dynamic systems with the objective of determining its complexity. This work measures LZC of different series coming from periodic functions, probabilistic functions, and chaotic systems. Later, these metrics of complexity are applied to the average of the number of parts in the waiting line in a manufacturing workshop. The results demonstrate the efficiency of the LZC to establish the level of the dynamic behavior of the manufacturing systems, through the time series.

The Effect of Entropy on the Performance of Modified Genetic Algorithm Using Earthquake and Wind Time Series

The dynamic complexity of time series of natural phenomena allowed to improve the performance of the genetic algorithm to optimize the test mathematical functions. The initial populations of stochastic origin of the genetic algorithm were replaced using the series of time of winds and earthquakes. The determinism of the time series brings in more information in the search of the global optimum of the functions, achieving reductions of time and an improvement of the results. The information of the initial populations was measured using the entropy of Shannon and allowed to establish the importance of the entropy in the initial populations and its relation with getting better results. This research establishes a new methodology for using determinism time series to search the best performance of the models of optimization of genetic algorithms (GA).

Nanosensors for a Monitoring System in Intelligent and Active Packaging

A theoretical wireless nanosensor network (WNSN) system that gives information about the food packaging condition is proposed. The protection effectiveness is estimated by measuring many factors, such as the existence of microorganisms, bacteria, gases, and contaminants. This study is focused on the detection of an antimicrobial agent (AA) attached on a polymer forming an active integrated package. All monitoring technologies for food conservation are analyzed. Nanobiosensor nanomachine (NM), which converts biological or chemical signals into electrical signals, is used. A mathematical model, which describes the constituent’s emigration from the package to food, is programmed in MatLab software. The results show three nanobiosensors forming a WNSN. The nanobiosensors are able to carry out the average concentration for different spots in the package. This monitoring system shows reading percentages in three degrees and different colors: excellent (green), good (cyan), and lacking (red). To confirm the utility of the model, different simulations are performed. Using the WNSNs, results of AA existing in food package (FP) through time were successfully obtained.

Forecast of Chaotic Series in a Horizon Superior to the Inverse of the Maximum Lyapunov Exponent

In this article, two models of the forecast of time series obtained from the chaotic dynamic systems are presented: the Lorenz system, the manufacture system, and the volume of the Great Salt Lake of Utah. The theory of the nonlinear dynamic systems indicates the capacity of making good-quality predictions of series coming from dynamic systems with chaotic behavior up to a temporal horizon determined by the inverse of the major Lyapunov exponent. The analysis of the Fourier power spectrum and the calculation of the maximum Lyapunov exponent allow confirming the origin of the series from a chaotic dynamic system. The delay time and the global dimension are employed as parameters in the models of forecast of artificial neuronal networks (ANN) and support vector machine (SVM). This research demonstrates how forecast models built with ANN and SVM have the capacity of making forecasts of good quality, in a superior temporal horizon at the determined interval by the inverse of the maximum Lyapunov exponent or theoretical forecast frontier before deteriorating exponentially.

REVERSE AND INVERSE LOGISTIC MODELS FOR SOLID WASTE MANAGEMENT

This paper presents a literature review of different models of reverse and inverse logistics for solid waste management by using the content analysis method. The article has two parts. In the first part, the studies of diverse authors are discussed to define the activities or steps to be followed for a general model of reverse and inverse logistics. These authors establish four basic steps for managing solid waste (gatekeeping, collection, sorting, and disposal). The second part deals with exploratory studies, designs, methodologies, and proposed mathematical models to solve problems in inverse logistics, based on articles published between 2010 and 2016.

Facing the data analysis complexity for the energetic efficiency management at great copper mining, in Codelco Chuquicamata, Chile

This study is centered in the complexity of the data analysis for the management of the energetic efficiency in the productive processes of copper. For that the study is divided in two stages, in the first one, through a process of hierarchical analysis (AHP), it is stablished the importance of the characteristics to be considered for the gathering of information related to the energetic efficiency. In the second stage, it is analyzed how the energetic consumption results a critical variable in copper production, being the unitarian operation of the concentrator, the one of the most energetic consumption, together with its most important actives, the SAG and Ball mills. Consequently, the study standardized a model to obtain data in the concentrator, thus evaluate the different areas of the organization, according to the characteristics or qualities of the information.