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Über dieses Buch

This two-volume set (CCIS 915 and CCIS 916) constitutes the refereed proceedings of the 5th Workshop on Engineering Applications, WEA 2018, held in Medellín, Colombia, in October 2018.

The 41 revised full papers presented in this volume were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections such as green logistics and optimization, Internet of Things (IoT), digital signal processing (DSP), network applications, miscellaneous applications.

Inhaltsverzeichnis

Frontmatter

Green Logistics and Optimization

Frontmatter

Optimal Location of Protective Devices Using Multi-objective Approach

In this paper a multi-objective model for the problem of optimal location of reclosers and fuses in power electric distribution systems is presented, considering the possibility of fuse rescue through the coordinated operation with reclosers and continuous operation with fuses of repetition. The problem is presented based on a mixed integer non-linear programming model with four objectives of minimization: Average System Interruption Frequency Index (ASIFI), System Average Interruption Frequency Index (SAIFI), Momentary Average Interruption Frequency Index (MAIFI) and the cost of the protective elements, and a set of non-linear technical and economic constraints. A Non-dominated Sorted Genetic Algorithm (NSGA II) is used as solution technique. In addition to this, the mathematical model presented for the MAIFI and SAIFI indices, is evaluated in the commercial optimization package of GAMS, in order to meet a global optimum from the one-objective point of view. The methodology proposed is assessed in two test systems from the literature highlight the efficiency of the presented model in improving system reliability while reducing associated costs.

Oscar D. Montoya, Ricardo A. Hincapie, Mauricio Granada

Adaptive Energy Management System for Self-consumption in Productive Processes

Productive processes are the largest consumers in power systems. The energy required by these processes is usually supplied by the power grid with its associated high operative costs. In this work, we propose a methodology to design energy management systems for self-consumption in productive processes with non-conventional local energy resources. Our goal is to maximize the use of the local energy resources to reduce the amount of energy contracted with the service supplier, and consequently to reduce production costs of the process. This methodology includes a robust-optimization-based energy management strategy to include power variability through the generation of a finite number of possible future scenarios of uncertain variables such as power demand and power from non-conventional energy sources. It allows improving the performance of the power supplies as our simulation results show.

Jorge Barrientos, José David López, Felipe Valencia

A Traffic Flows Scheme for User-BS Association in Green HetNets

Energy efficiency in the next-generation of cellular networks is an important topic due to the expected increase in the number of nodes. Previous research has shown the relationship between the number of users connected to a cellular network base station (BS) and its energy consumption. For this reason, the study of optimal mechanisms that balance the load of users over the available base stations is a key element in the field of energy efficiency in cellular networks. However, the user-BS association process is not trivial because the problem explodes combinatorially. For this reason, it is necessary to explore mechanisms able to be executed in the order of milliseconds. In this paper, we compare two different user - BS association policies and their impact on grid consumption in a heterogeneous cellular network (HetNet) powered by hybrid energy sources (grid and renewable energy). The first proposal is based on a discrete optimization problem and the second is a relaxation that uses traffic flows. These schemes are compared to the traditional best-signal-level mechanism and evaluated in a realistic simulation scenario to study the impact on grid consumption, number of users served, and computation time. The new proposed user allocation policies result in lower grid electricity consumption and lower average unserved users compared to the traditional association scheme.

Luis A. Fletscher, José M. Maestre, Catalina Valencia Peroni

Logistics IRP Model for the Supply Chain of Perishable Food

The joint management of routing and inventories has become a field of particular importance for the academic community in recent years. However, there were no models identified in the literature review that contemplate the characteristics of the supply chain of fresh food. The authors of this paper propose an IRP (Inventory Routing Problem), multi-objective, multi-product and multi-echelon model of mixed linear programming which considers the shelf life of the food. The model is applied to the supply chain of perishable fruits. The two scenarios evaluated constitute the base for a strategy proposal to reduce costs, maximize the contribution margin and diminish the losses of fruit.

Javier Arturo Orjuela-Castro, Diego Batero-Manso, Juan Pablo Orejuela-Cabrera

A Mathematical Model Under Uncertainty for Optimizing Medicine Logistics in Hospitals

Managing resources in hospitals is one of the most challenging duties in healthcare. The complexity of supply chain management in hospitals is high due to different factors such as life cycle of medicines, demand uncertainty, variation of prices, monetary resources, space constraints, among others. The main important factor of the supply chain in hospitals is the welfare of patients which depends of the correct management and administration of medicines, in this way backorders or stockouts are not allowed. In this paper we propose a mathematical model to make real planning over a health care supply chain considering real factors face by decision makers. For testing results we have used real data considering different sources of uncertainty. We have choose 5 different types of medicines and run the optimization model to determine the optimal solution over a set of scenarios generated for modeling uncertainty. For testing the results, we have compare over a year planning the results obtained by our policy and the results obtained by the hospital, improving the results in terms of costs.

Carlos Franco, Eduyn Ramiro López-Santana, Juan Carlos Figueroa-García

Hybrid PSO-TS-CHR Algorithm Applied to the Vehicle Routing Problem for Multiple Perishable Products Delivery

In this paper, we dealt with the routing of refrigerated and non-refrigerated vehicles for the delivery of multiple perishable products, with known demands, the capacity of vehicles in the heterogeneous fleet, and a number of available vehicles of both types. We propose a mathematical model that seeks to minimize the loss of freshness by perishable products, considering the time they remain in the vehicles and the vehicles’ storage door openings on the route, from the moment they leave the depot until they arrive at the final customer. The most important contribution of this work is the implementation of the hybrid PSO-TS-CHR algorithm to solve this problem, which is compared with a Genetic Algorithm (GA). The results showed that the metaheuristic that gives the greatest quality solutions for the stated problem of both is the hybrid algorithm.

Jesus David Galarcio Noguera, Helman Enrique Hernández Riaño, Jorge Mario López Pereira

Districting Decisions in Home Health Care Services: Modeling and Case Study

Home health care (HHC) services are a growing segment in the global health care industry in which patients receive coordinated medical care at their homes. When designing the service, HHC providers face a set of logistics decisions that include the districting configuration of the coverage area. In HHC, the districting problem seeks to group small geographic basic units-BUs (i.e., city quarters) into districts with balanced workloads. In this work, we present a modeling approach for the problem that includes a mixed integer linear programming (MILP) formulation and a greedy randomized adaptive search procedure (GRASP). The MILP formulation solves instances up to 44 BUs, while the GRASP allows to solve instances up to 484 BUs in less than 2.52 min. Computational experiments performed with a set of real instances from a Colombian HHC provider, show that the GRASP can reduce workload imbalances in a 57%.

Sebastian Cortés, Elena Valentina Gutiérrez, Juan D. Palacio, Juan G. Villegas

Modeling Strategy for Supply Chain Design Considering Multiple Periods and Backlogging

This paper presents a mathematical model to optimize the supply chain design considering a planning horizon with multiple periods and backlogging. The objective function aims to minimize the sum of transportation, inventory holding and backlogging costs. The model is represented in a graph, generalizing a minimum cost flow problem. A study case for a manufacturing company is presented and results are analyzed.

César Amilcar López Bello, William J. Guerrero, José Ignacio Rodríguez Molano

A Metaheuristic Approach for the Cumulative Capacitated Arc Routing Problem

In this paper we propose a new variant of the capacitated arc routing problem (CARP). In this new problem the objective function becomes a cumulative objective computed as the traveled distance multiplied by the vehicle load. A metaheuristic approach is proposed which is based on the hybridization of three known procedures: GRASP, VND and Set covering model. The metaheuristic is tested with some benchmark instances from CARP. The results allow to evaluate the performance with the different metaheuristic components and to compare the solutions with the classical objective function.

Sergio Andrés Lenis, Juan Carlos Rivera

A Mixed-Integer Linear Programming Model for a Selective Vehicle Routing Problem

In this paper, we propose a new vehicle routing problem variant. The new problem is a type of selective vehicle routing model in which it is not necessary to visit all nodes, but to visit enough nodes in such a way that all clusters are visited and from which it is possible to cover all nodes. Here, a mixed-integer linear programming formulation (MILP) is proposed in order to model the problem. The MILP is tested by using adapted instances from the generalized vehicle routing problem (GVRP). The model is also tested on small size GVRP instances as a special case of our proposed model. The results allow to evaluate the impact of clusters configuration in solver efficacy.

Andrea Posada, Juan Carlos Rivera, Juan D. Palacio

Internet of Things (IoT)

Frontmatter

Voltage Quality in Distribution Systems for Smart Cities Using Energy Internet

This paper shows the design of a prototype to measure voltage in a distribution system by means of the quality indicators established by energy regulation in Colombia. The design is proposed according to the new context where smart energy systems require energy internet, that is their real time manipulation with databases located in the cloud, in order to locate them in intelligent spaces such as the future cities. Therefore, the quality of the voltage in these environments is of vital importance to guarantee an adequate service in the different sectors in a city.

Alvaro Espinel, Adriana Marcela Vega

Failures Monitoring in Refrigeration Equipment

The refrigerators are the responsible to assure the temperature and humidity conditions for perishable products stored in it. In this sense, it is necessary to guarantee its good performance at all times in order to preserve the products. In this article We propose a failures monitoring system for refrigeration equipment using Internet of Things (IoT) technologies. The aim of the solution is to manage preventive and corrective maintenance programs and, in this way, We look for assuring the conditions of the consigned products that are distributed along an entire country. We present the conceptualization, the design of the system and the results of the proof of concept.

Oscar de Jesús Ballestas Ortega, José Luis Villa

From SDL Modeling to WSN Simulation for IoT Solutions

Both the Internet of Things (IoT) and Wireless Sensor Networks (WSN) are technologies characterized by integrating heterogeneous devices with low processing and storage capabilities and power consumption efficiency. The increasing number of operating systems and hardware platforms available for IoT applications suggests the need of developing a simple and agile approach which allows that specifications can be easily converted into executable code for simulation and implementation thus easing validation and verification of requirements. This involves the design, development, testing, and deployment phases. This paper proposes an integration scheme through which IoT solutions based on WSN can be designed using Specification and Description Language (SDL), and then translated directly into code for IoT-oriented operating systems like Contiki. The main goals are to quickly adjust the designs, and execute tests on different hardware-software configurations, thus reducing errors along the life cycle.

Andres Felipe Fuentes Vasquez, Eugenio Tamura

Design and Implementation of a Laboratory Sample Collection System Using an Unmanned Aerial Vehicle (UAV)

The use of innovative technology is available to apply in many ways and in different fields of knowledge, the Horus research group, has focused its efforts implementing solutions, integrating unmanned aerial vehicles known as drones in different areas. The use of drones to perform different tasks is not new, but from the point of view of the Horus research group, it was established that this technology can be applied to analyze different water systems with possible contamination quickly and efficiently, otherwise to collect samples in places where access is difficult it would take more time and money in the process. For that, a system was designed using a drone assembled by the research group with a pumping system, to collect samples for further analysis in laboratory in a way that they are not contaminated using technical standards according to the regulations of the area where they are collect.

Edgar Krejci Garzon, Yesid Diaz Gutiérrez, Manuel Alberto Salgado Alba, Fernando Agusto Celis Florez

Internet of Things Proposal for Measuring Wind Variables in a Smart Home Environment

This work presents a proposal to implement an appliance to get information from wind variables as renewable resource in electrical energy generation. The device is supported on an Arduino application and ThingSpeak tools to obtain important mount of data for future studies of the wind resource. The implemented device is presented from the smart home concepts explained as layers of an Internet of Things approach. Results show as easily this proposition can be developed as an alternative in a smart home environment, where each house can be employed to measure its own wind renewable resources.

Jairo Fernando Gutiérrez, Alvaro David Orjuela-Cañón, Juan Mauricio Garcia

Design of Urban Mobility Services for an Intermediate City in a Developing Country, Based on an Intelligent Transportation System Architecture

Problem: Services that use ICT (Information and Communications Technologies) have been developed to improve the mobility in cities; however, especially in developing countries, these services are not often based on adequate reference architectures, such as ITS (Intelligent Transport Systems) architectures, which prevent integration and interoperability. Objective: Propose a development process for the design of mobility services in an intermediate city of a developing country, based on an ITS architecture formulated particularly considering context. Methods: The reference ITS architectures and the particular context of a Colombian intermediate city are reviewed, in order to identify which is the best process to adapt an ITS architecture to these type of cities. With the process identified, the ITS architecture for Popayán (Colombian intermediate city) is designed and finally, the design of the services based on it, is carried out. Results: The methodology developed for the design of the ITS architecture and the architecture designed particularly for Popayán are summarized. Following, the design of two mobility services (“Public transport vehicle tracking” and “Traffic measurement”) for that city based on architecture is detailed. Conclusions: The particular environment of an intermediate city and its priorities allows to determine the services to select for its ITS architecture from a reference architecture. ITS architecture development of a city allows the incremental development of services that really improve their mobility in a sustainable manner.

Ricardo Salazar-Cabrera, Álvaro Pachón de la Cruz

Development of a WEB Prototype Based on JSON and REST Technology to Manage Progress in the Physical and Psychological Rehabilitation of People with Cognitive Disability

The vulnerable population with motor and cognitive disabilities in our country confronts daily to endless number of situations that transgress its rights and possibilities to carry on a dignified life. This way we implement a prototype of a web application using Ajax, JSON and REST technologies with the aim to avoid overloads and response times in the remote server and allow to improve the reliability, speed and veracity of the information, beside to can integrate and store the basic information of the patients, treatments performed and progresses in the rehabilitation of population with different kind of motor and cognitive disabilities.

William Ruiz Martínez, Roberto Ferro Escobar, Yesid Díaz

Automated Epileptic Seizure Detection System Based on a Wearable Prototype and Cloud Computing to Assist People with Epilepsy

Epilepsy is characterized by the recurrence of epileptic seizures that affect secondary physiological changes in the patient. This leads to a series of adverse events in the manifestation of convulsions in an uncontrolled environment and without medical help, resulting in risk to the patient, especially in people with refractory epilepsy where modern pharmacology is not able to control seizures. The traditional methods of detection based on wired hospital monitoring systems are not suitable for the detection of long-term monitoring in outdoors. For these reasons, this paper proposes a system that can detect generalized tonic-clonic seizures on patients to alert family members or medical personnel for prompt assistance, based on a wearable device (glove), a mobile application and a Support Vector Machine classifier deployed in a system based on cloud computing. In the proposed approach we use Accelerometry (ACC), Electromyography (ECG) as measurement signals for the development of the glove, a machine learning algorithm (SVM) is used to discriminate between simulated tonic-clonic seizures and non-seizure activities that may be confused with convulsions. In this paper, the high level architecture of the system and its implementation based on Cloud Computing are described. Considering the traditional methods of measurement, the detection system proposed in this paper could mean an alternative solution that allows a prompt response and assistance that could be lifesaving in many situations.

Nicolas Escobar Cruz, Jhon Solarte, Andres Gonzalez-Vargas

Modeling and Implementation Data Architecture for the Internet of Things and Industry 4.0

This paper analyzes Internet of Things (IoT), its use into manufacturing industry, its foundation principles, available elements and technologies for the man-things-software communication already developed in this area. And it proves how important its deployment is. Describes a proposal of data architecture of the Internet of things applied to the industry, a metamodel of integration (Internet of Things, Social Networks, Cloud and Industry 4.0) for generation of applications for the Industry 4.0, and the manufacturing monitoring prototype implemented with the Raspberry Pi microcomputer, a cloud storage server and a mobile device for controlling an online production.

José Ignacio Rodríguez-Molano, Cesar Amilcar López-Bello, Leonardo Emiro Contreras-Bravo

Automatic Intelligibility Assessment of Parkinson’s Disease with Diadochokinetic Exercises

This paper presents preliminary results for the analysis of intelligibility in the speech of Parkinson’s Disease (PD) patients. An automatic speech recognition system is used to compute the word error rate (WER), the Levenshtein distance, and the similitude based dynamic time warping. The corpus of the speech recognizer is formed with speech recordings of three Diadochokinetic speech tasks: /pa-ta-ka/, /pa-ka-ta/, and /pe-ta-ka/. The data consist of 50 PD patients and 50 Healthy Controls. According to the results, the recognition error is lower for the healthy speakers (WER = $$2.70\%$$ ) respect to the PD patients (WER = $$11.3\%$$ ).

L. Felipe Parra-Gallego, Tomás Arias-Vergara, Juan Camilo Vásquez-Correa, Nicanor Garcia-Ospina, Juan Rafael Orozco-Arroyave, Elmar Nöth

Modeling and Simulation of Integration of Internet of Things and Manufacturing Industry 4.0

Internet of Things (IoT) is changing the processes in the manufacturing industry. It is creating new opportunities for both economies and society. The deployment of Internet of Things for the development of Industry 4.0 improves processes and manufacturing systems. In this type of systems, the information is related to the manufacturing status, trends in energy consumption by machinery, material logistics, customer orders, supply data and all data related to smart devices implemented in the processes. This paper describes an Internet of Things architecture applied to industry, a metamodel of integration in its phase II (Internet of things, social networks, cloud and industry 4.0) for the generation of applications for Industry 4.0.

José Ignacio Rodríguez-Molano, Jenny Alexandra Triana-Casallas, Leonardo Emiro Contreras-Bravo

Digital Signal Processing (DSP)

Frontmatter

Continuous Wavelet Transform for Muscle Activity Detection in Surface EMG Signals During Swallowing

The surface electromyography (sEMG) has been used to characterize normal and abnormal behavior of the swallowing related muscles. One important activity in the analysis of the electromyographic recordings, is the detection of bursts, indicators of muscle activations but problematic in muscles with low signal-to-noise ratio (SNR). Most of methods for burst detection are based on amplitude measures which are signal-conditions dependent. We proposed a method to detect bursts based on the continuous wavelet transform and thresholding over the scalogram but not over amplitude. sEMG signals from 38 healthy subjects were recorded during swallowing tasks. We compared the proposed method to the visual method as a reference, and a previous method based on the Teager-Kaiser energy operator (TKEO). The proposed method avoids detection of false negatives better than TKEO, and it is suitable to apply in problems of burst detection in sEMG signals with low SNR.

Sebastian Roldan-Vasco, Estefania Perez-Giraldo, Andres Orozco-Duque

Hyperthermia Study in Breast Cancer Treatment

This paper assesses the initial collateral effects which result from the use of hyperthermia, a technique that elevates the temperature in specific areas of the body to tackle present malignant cells. In this particular case, the focus of study is breast cancer treatment by means of an electromagnetic simulation model. The breast model was created by using the electrical properties of tissues and was radiated by microwaves with a waveguide at 950 MHz, 2.45 GHz and 6 GHz to generate increased temperature and distribute power density inside the breast. In the model, two methods were used to obtain the power density in a tumor and other breast tissues (skin, fat, and muscle). One result shows the general distribution of power density throughout a map on color scale, and the second result shows the normalized power density in the local breast parts. In the same way, results show that the microwave applicator (waveguide) location is a determinant factor.

Hector Fabian Guarnizo Mendez, Mauricio Andrés Polochè Arango, John Jairo Pantoja Acosta

A Non-linear Dynamics Approach to Classify Gait Signals of Patients with Parkinson’s Disease

Parkinson’s disease is a neuro-degenerative disorder characterized by different motor symptoms, including several gait impairments. Gait analysis is a suitable tool to support the diagnosis and to monitor the state of the disease. This study proposes the use of non-linear dynamics features extracted from gait signals obtained from inertial sensors for the automatic detection of the disease. We classify two groups of healthy controls (Elderly and Young) and Parkinson’s patients with several classifiers. Accuracies ranging from 86% to 92% are obtained, depending on the age of the healthy control subjects.

Paula Andrea Pérez-Toro, Juan Camilo Vásquez-Correa, Tomas Arias-Vergara, Nicanor Garcia-Ospina, Juan Rafael Orozco-Arroyave, Elmar Nöth

Changes in Electrocardiographic Signals During Training in Laparoscopic Surgery Simulator: A Preliminary Report

The aim of this work is attempting to identify physiological characteristics of the learning process in surgery residents. As an exploratory approach, we are interested in determining statistically significant changes in electrocardiographic (ECG) signals recorded while a group of eleven first year general surgery residents were performing three basic skills tasks from the virtual reality (VR) laparoscopic simulator LapSim®. These signals were processed and heart rate (HR) was calculated to analyze it along with the overall score for each exercise. Statistical analysis was performed by means of analysis of variance showing the effects of training session, difficulty of the task and participants gender on heart rate and performance. Our preliminary experimental results show that the score obtained in the tasks improves with training session, being in the women where significant changes occur. HR analysis showed that it increases with the complexity of the task. Besides, the effect of gender on HR showed that in male group there were the significant changes with the difficulty of the task, and a decrease with the training session in the intermediate level of difficulty task.

Jazmín Ximena Suárez-Revelo, Any Ruiz-Duque, Juan Pablo Toro, Ana María Mejía-Bueno, Alher Mauricio Hernández-Valdivieso

Validation of EEG Pre-processing Pipeline by Test-Retest Reliability

Artifact removal and validation of pre-processing approaches remain as an open problem in EEG analysis. Cleaning data is a critical step in EEG analysis, per-formed to increase the signal-to-noise ratio and to eliminate unwanted artifacts. Methodologies commonly used for EEG pre-processing are: filtering, interpolation of bad channels, epoch segmentation, re-referencing, and elimination of physiological artifacts such as eye blinking or muscular activity. It is important to consider that the order and application of these steps affect signal quality for further analysis. In order to validate a pre-processing pipeline that can be considered in a clinical follow-up, this paper evaluated test-retest reliability of EEG recordings. EEG signals were acquired during eyes-closed resting state condition in two groups of healthy subjects with a follow-up of one and six months respectively. Signals were pre-processed with five different methodologies commonly used in literature. Test-retest reliability by intraclass correlation coefficient was calculated for power spectrum measures in each pre-processing approach and group. The results showed how test-retest reliability was significantly affected by pre-processing pipeline in both follow-ups. The pre-processing pipeline that com-bines robust reference to average and wavelet ICA improves the test-retest reliability.

Jazmín Ximena Suárez-Revelo, John Fredy Ochoa-Gómez, Carlos Andrés Tobón-Quintero

Bioacoustic Signals Denoising Using the Undecimated Discrete Wavelet Transform

Biological populations can be monitored through acoustic signal processing. This approach allows to sense biological populations without a direct interaction between humans and species required. In order to extract relevant acoustic features, signals must be processed through a noise reduction stage in which target data is enhanced for a better analysis. Due to the nature of the biological acoustic signals, the denoising strategy must consider the non-stationarity of the records and minimize the lost of significant information. In this work, a Last Approximation standard deviation algorithm (LAstd) for the processing of bioacoustic signals based on wavelet analysis is presented. The performance of the proposed algorithm is evaluated using a database of owls, which have been modified with different rates of coloured noise. Furthermore, the approach is compared to a standard denoising method from the Matlab Wavelet Toolbox. The results show that the proposed algorithm is able to improve the signal-to-noise ratio of the owl’s registers within a wide frequency range and different noise conditions. Furthermore, the algorithm can be adapted to process different biological species, thus it can be an useful tool for characterizing avian ecosystems.

Alejandro Gómez, Juan P. Ugarte, Diego Mauricio Murillo Gómez

Automatic Calculation of Body Mass Index Using Digital Image Processing

In this paper we present a vision system to detect BMI from images. The proposed system segments the image and extracts the most important features, from these features a classifier is trained. An analysis of the results with different classification techniques is presented in the experimental results. The results show that the system can obtain good classification accuracies using images under controlled conditions.

Juan D. J. Amador, Josué Espejel Cabrera, Jared Cervantes, Laura D. Jalili, José S. Ruiz Castilla

Network Applications

Frontmatter

Improving Early Attack Detection in Networks with sFlow and SDN

Network monitoring is a paramount aspect for the detection of abnormal and malicious activity. However, this feature must go hand by hand with mitigation techniques. On SDN environments, control techniques may be easily developed as a result of its ability for programming the network. In this work, we take advantage of this fact to improve the network security using the sFlow monitoring tool along with the SDN controller. We present an architecture where sFlow is in charge of detecting network anomalies defined by user rules, while the SDN technology is responsible to mitigate the intrusion. Our testbed has been implemented on Mininet and the SDN environment is governed by Opendaylight controller and the OpenFlow southbound protocol. Experimental validation demonstrate that our system can effectively report various types of intrusion associated with the reconnaissance phase of an attack.

Alexander Leal, Juan Felipe Botero, Eduardo Jacob

Design and Implementation of a Controlled and Monitored Multipurpose Exploratory Device Through a Wi-Fi Connection Using MatchPort

Currently, the use of remotely controlled and monitored devices that perform high-risk exploration activities is increasing. The design and implementation of a robot type device for exploration that allows real-time data capture of different conditions depending on the sensors that are configured, using one of the serial ports available in the MatchPort which in turn supports the connection using Wi-Fi technology the device has a camera that performs visual recognition of the environment.

Arnaldo Andres González, Luis Eduardo Pallares, Roberto Ferro Escobar, Jorge Enrique Portella

A Fast Reliability Analysis Approach for Colombian Natural Gas Subnetworks

The Colombian natural gas sector is going through a challenging stage concerning the management of available reserves. Recently, some weather conditions have shown drawbacks in security and reliability regarding supply and transportation. Regasification technology has been installed in the system as a solution for leading the unbalance between demand and supply. However, the inadequate pipeline infrastructure for transporting large natural gas flows in the short and long-term is demanding an expansion for enhancing the system reliability. Here, we develop a Markov chain-based isolation method for performing fast reliability analysis in subnetworks of the Colombian natural gas system, based on the optimal operational cost. We assess our methodology on a real data set concerning a simplified Colombian natural gas system. Obtained results show that our proposal remarkably improves the computation time employed for computing the reliability of subnetworks and preserves the accuracy in the calculation of the optimal operational cost.

Wilson González-Vanegas, Andrés Álvarez-Meza, Álvaro Orozco-Gutiérrez

Implementation of the AODV Routing Protocol for Message Notification in a Wireless Sensor Microgrid

This paper analyzes the behavior of the AODV routing protocol applied in a telecommunication network that transmits information for the management of the energy resources of an electric microgrid. Each node represents a sensor that captures primary data on voltage, current, phase, and frequency to be sent to a central node; in the opposite direction it receives instructions to activate or deactivate loads or sources. The implementation was performed with Raspberry Pi3 devices, encoding the routing protocol in Python 2.7. The network tests involve two topologies (trees and mesh). Through the tests, service quality metrics such as delay, throughput, and PDR were compared.

Elvis Gaona-García, Sergio Palechor-Mopán, Laura Murcia-Sierra, Paulo Gaona-García

SNMP Converter and the Forward Data Collection as Management Method in Dynamic Distributed Networks

A method of network management based on the protocol conversion SNMP to others, like serial or UDP, to manage small devices in a wireless sensor network is shown, whose reference framework combines the hierarchical network management with the dynamic, distributed and heterogeneous characteristics of an Ad Hoc network and how the SNMP protocol accomplish its habitual devices management functions, and at the same time, some of its messages are used to build a forward data collector that expands and contracts dynamically the storage capacity of the SNMP tables of the agent, adapting to the amount of devices in the network.

Mauricio Tamayo, Henry Zarate, Jorge Ortíz Triviño

Miscellaneous Applications

Frontmatter

How Does the Toolbox Choice Affect ERP Analysis?

Event-related potentials (ERP) help understanding neural activity related to both sensory and cognitive processes. But due to their low SNR, EEG signals must be processed to obtain the ERP waveform. Such a processing can be carried using a number of toolboxes that may provide different results on further analyses. Here, we present an experimental design that quantitatively evaluates the effect of choosing a particular toolbox in the further ERP analysis. We select three widely used toolboxes: EEGLAB, SPM12, and Fieldtrip to process EEG data acquired from a Flanker-like task with a Biosemi Active-Two device. Results show that although there is not a significant difference between ERP obtained from each toolbox, the choice of a specific toolbox may have subtle effects in the resulting ERP waveforms.

Andrés Quintero-Zea, Mónica Rodríguez, María Isabel Cano, Karen Melisa Pava, Manuela Suaza, Natalia Trujillo, José David López

A Test Bed to Measure Transverse Deflection of a Flexible Link Manipulator

In this paper, we present a test bed to measure transverse deflection in different parts of a link of a manipulator of flexible links. For the mathematical modeling of the link, the Euler-Bernoulli beam theory has been used as a simplification of the linear elasticity theory, which allows calculating the load and the deflection characteristics of a beam. In order to measure the transverse deflection of the beam, we have used strain gauge arrangements that have been placed at three points of the flexible link, the test bed, allowing to reconstruct the position of the beam taking into account the actual position of the end-effector, the motion controller, and real-time interface PC. In addition to knowing with certainty the position of the manipulator arm, it has also been considered in the calculation of the manipulator dynamics using Euler-Lagrange and assumed modes for modeling the transverse deflection and the vibrations of the beam. This information will be used in modern control schemes to perform transverse deflection compensation, vibration suppression and ensure that the end-effector, reaches the set point set in the control system in a finite time.

Cecilia Murrugarra, Osberth De Castro, Angel Terrones

Work of Breathing Dynamics Under Changes of PEEP and Pressure Support in Non-invasive Mechanical Ventilation

In spontaneous ventilation patient governs his breaths and the correct configuration of the mechanical ventilator is indispensable to avoid extra load in the ventilation process. Parameters like PEEP and pressure support (PS) affects directly the ventilatory comfort of the patient, therefore, they should be adjustable to improve oxygenation and reduce work of breathing (WOB). The objective of this study is to assess the WOB dynamics during incremental stimuli of PEEP and PS as additional information to the absolute WOB value. Variations of 2 cmH2O for 3 min up to 10 cmH2O for PEEP and PS separately were carried out in healthy subjects to analyze the changes in the WOB dynamics. 31 male adults were enrolled in this study, the absolute WOB, and three indexes of WOB dynamics (inspiratory slope, expiratory slope and ΔPeak) were calculated from ventilatory signals. Inspiratory slope shows a linear trend with the absolute WOB, nevertheless after the threshold of 0.8 J/L has a high dispersion, which suggests that high values of WOB could be obtained under different breathing pattern. In conclusion, the inspiratory slope like an index of WOB dynamics provides extra information that in future works could be compared with muscular and ventilator variables to identify positive or negative increases of WOB which clinicians could analyze to make decision about the optimum treatment of the patient.

Yessika María Ortega, Isabel Cristina Muñoz, Alher Mauricio Hernández

Design and Implementation of a Sliding Mode Observer-Based Controller for a Mass-Spring System

This work presents the implementation of a sliding mode observer-based controller on a mass-spring experimental platform. The controller is based on the super-twisting algorithm and the observer is based on a high order sliding mode algorithm, to obtain continuous control signal. The simulations and practical results show a good performance of the complete structure.

Carlos M. Florez R., Hector Botero Castro, Esteban Jiménez-Rodríguez

Design of a Device for Recording Bioelectric Signals with Surface Electrodes, in the Evaluation of the Effect of Ultraviolet Radiation on a Tissue

The accepted methodology by regulatory agencies to determine the efficacy of sunscreen products makes use of healthy human volunteers who are exposed to radiation. In order to find an alternative to these types of evaluations, the effect of exposure to UV radiation was investigated in an ex vivo pig skin model on the bioelectrical signals of the tissue in terms of energy and impedance. A system was implemented using the measurements configuration of 4 electrodes (Two electrostimulation electrodes and two electrodes for the signals acquisition all of them were silver cup electrodes) and a mathematical model was established in relation to electrical change as a function of exposure time. As a result, an attenuation of the energy response signal relative to the non-irradiated tissue was obtained, as well as impedance values after irradiation. This behavior is directly related to damage in the tissue structure. The results allow to conclude that the device can quantify the effect caused by radiation on the electrical properties of an ex vivo tissue and are promising in the understanding of the phenomena associated with the electrical response of a tissue to ultraviolet radiation.

Fabian Garay, Aura Hernández, Hans López, Helber Barbosa, Bibiana Vallejo

Bioinformatics Approach to Analyze Influenza Viruses

Influenza viruses are highly contagious respiratory illness and responsible for the severe annual morbidity and mortality worldwide. They are classified into types, influenza A, B and C. Influenza viruses accumulate point mutations during replication, especially in three proteins: matrix-membrane, hemagglutinin, and neuraminidase. Nucleotide and amino acid variations may produce selective advantages for viral strains, in the matrix-membrane and neuraminidase may be related to eluding host immunity, while variations in the hemagglutinin are responsible for the appearance of antigenic drift that evade preexisting host immunity and cause reinfections. In this paper, we present a bioinformatics study for detecting mutations implicated in variability in the hemagglutinin, neuraminidase and matrix-membrane of influenza strains using our bioinformatics tool BMA. In this study, we calculate, compare, and analyze genetic variations associated with antigenic drift in hemagglutinin protein from influenza A H1N1. BMA allows users to identify mutations in sequences quickly and efficiently for the detection of antigenic drift.

Karina Salvatierra, Hector Florez

3D Object Pose Estimation for Robotic Packing Applications

Given the growth of internet-based trading on a global level, there are several expected logistic challenges regarding the optimal transportation of large volumes of merchandise. With this in mind, the application of technologies such as computer vision and industrial robotics in facing these challenges presents significant advantages regarding the speed and reliability with which palletization tasks, a critical point in the merchandise transportation chain, can be performed. This paper presents a computer vision strategy for the localization and recognition of boxes in the context of a palletization process carried out by a robotic manipulator. The system operates using a Kinect 2.0 depth camera to capture a scene and processing the resulting point cloud. Obtained results permit the simultaneous recognition of up to 15 boxes, their position in space and their size characteristics within the workspace of the robot, with an average error of approximately 3 cm.

C. H. Rodriguez-Garavito, Guillermo Camacho-Munoz, David Álvarez-Martínez, Karol Viviana Cardenas, David Mateo Rojas, Andrés Grimaldos

Development of a Line-Follower Robot for Robotic Competition Purposes

A fast line follower is an intelligent robot that must detect and follow a line drawn on a surface with possible changes of inclination. The robotics competitions demand that the robot go over a racetrack in the shortest possible time. The purpose of this paper is to study the line follower robot from the Control Engineering point of view to optimize its performance in standard races. In this paper we propose a SISO angle control scheme based on the relation between estimated line position and yaw robot angle. A sensitive position estimation respect to the line was implemented to improve the provided information interpretation from infrared array sensors respect to the conventional robots. Finally a suction turbine engine and a guarantee action algorithm were added to improve the angle controller response at high speeds and loss of grip on the wheels.

Harold Murcia, Juan David Valenciano, Yeison Tapiero

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