Program

ETCM 2016 Program Layout

programa

ETCM 2016 Accepted Papers with Abstracts

Communications Integration using a CPPS Architecture

Abstract: Low Cost Automation promotes cost effective reference architectures and development approaches to increase flexibility and efficiency of production operations. This has led to the adoption of open networking standards for plant floor communications. . OPC-UA may help industrial companies to become industry 4.0 as it enables remote access to plant information, achieving thus vertical integration. The main goal of this work is to make vertical integration a reality by means of a low-cost CPPS architecture that provide access to process data. The use of this architecture along the whole production automation system may certainly reduce the Total Cost of Ownership (TCO). The paper describes both the hardware platform as well as the software including the proposed configuration file of the OPC-UA server

Optimal Geographic Placement of PMU for Wide Area Measurement System

Abstract: This paper presents a methodology to solve the problem of optimal placement of WAMS in an electric power transmission system. In this paper two approaches are introduced aiming at reducing the computational burden in Optimal Placement problems. The goal is to make a preliminary analysis of optimal placement of PMU (OPP) and subsequently to optimize the costs of the communication network (CN) through the minimization of distances of connection between each node. For this purpose, an Integer Linear Programming (ILP) based on algorithm for the PMU placement has been modified and expanded to determine optimal PMU locations by incorporating the effect of zero-injection buses and conventional measurements. In addition, Kruskal’s Minimum Spanning Tree algorithm is used to obtain the optimal communication networks with minimum investment. The effectiveness of the proposed method is verified in a real large size transmission system, where geo-referenced data (coordinates) of the buses (nodes) and transmission lines that make up the entire network are obtained. The main objective focuses on minimizing the cost associated with PMU placement and communication network, while ensuring the full observability of the system.

Entropy as an Event Detector in a Class of Hybrid Dynamic Systems. Study Case: A Steam Boiler

Abstract: In a Hybrid Dynamical System (HyDS) event occurrences can be generated by many causes. Also, these events may be controlled or uncontrolled (wanted or unwanted) which in turn might generate imbalances and/or disorder in the system, with the potential of causing catastrophic faults. In order to be able to deal with controllable events regulation it is important solving an early detection
problem, whenever there is no 100% reliable method for detecting them. The main objective of this work is to study and implement an innovative method to detect certain events in a HyDS, such as faults, starts and/or plant shutdowns, setpoint changes, among others. The proposed method is based on the estimation of entropy balance in the system and its efficiency as an event detector is illustrated using Matlab computer simulations on a steam boiler case of study. It is also showed how the entropy balance may be used as an event detector in different operation regions of the process.

Fast Computation of Cramer-Rao Bounds for TOA

Abstract: As part of a larger scope work that studies network-based positioning, this article proposes a methodology that enables a very quick computation of Cramer-Rao Bounds for timing, avoiding the growing computational effort resulting from Fisher’s matrix formulation and its inversion for each required position at the simulation stage, assuring at the same time the reliability of required data in the study of positioning using space-time diversity. This methodology considers the variability of the propagation conditions in terms of delay spread (DS) and Signal-to-Noise ratio (SNR) in a realistic scenario; it also coordinates the operation of concurrent models within simulation, and finally performs bi-exponential regression and interpolation procedures on pertinent operational regions for CRBs. Models properly validated were integrated to the positioning simulation platform.

Machine Learning Approach to Forecasting Urban Pollution: A case study of Quito, Ecuador

Abstract: This work addresses the question of how to predict fine particulate matter given a combination of weather conditions. A compilation of several years of meteorological data in the city of Quito, Ecuador, are used to build models using a machine learning approach. The study presents a decision tree algorithm that learns to classify the concentrations of fine aerosols, into two categories (>15µg/m3 vs. <15µg/m3), from a limited number of parameters such as the level of precipitation and the wind speed and direction. Requiring few rules, the resulting models are able to infer the concentration outcome with significant accuracy. This fundamental research intends to be a preliminary step in the development of a web-based platform and smartphone app to alert the inhabitants of Ecuador’s capital about the risk to human health, with potential future application in other urban areas.

Analysis and Determination of Minimum Requirements for a Data Link Communication System for Unmanned Aerial Vehicles- UAV’s

Abstract: Abstract— In recent years, UAVs (Unmanned Aerial Vehicles) they have shown enormous potential in civilian and military applications. They have become an essential tool in the field of defense, security and scientific development of a nation. Technological advancement has allowed these aircrafts to fly autonomously. That is why the different systems containing a UAV have to be monitored and controlled at all times from the Command and Control Station. The accuracy with which this information is sent will give confidence and autonomy to run the mission and perform flight tests autonomously and safely. It guarantees safe navigation of the aircraft. The analysis presented in this document sets out the necessary calculations to determine the link budget to ensure the permanent availability of information. It will determine the best band frequency, propagation loss, antenna gain, sensitivity of communication equipment, among others. These requirements are the basis for selecting the right equipment for the implementation of the communications system for a UAV. The results of performed tests are shown. They will consider multiple distances that the data link must reach, the field conditions in which the operations are to be carried out, the parameters affecting communications, field tests in real missions and the analysis of the obtained results.

A Fixed-Frequency Sliding-mode Control in a Cascade Scheme for the Half-bridge Bidirectional DC-DC Converter

Abstract: For the Half-bridge Bidirectional DC-DC power converter focused on electric traction applications, this paper develops a fixed-frequency Sliding-mode control (SMC) based on a cascade structure. First, the use of cascade control is justified by means of the state space small-signal averaged equations. Then, the design of the proposed cascade SMC scheme is detailed. Lastly, the simulation results showed that the developed control strategy outperforms the sole use of SMC for different comparison scenarios.

Towards a fast multi-tier storage system simulator

Abstract: —This paper presents StorageSim, a multi-tier storage system simulator. StorageSim is a process-based discrete-event simulator developed using the SimPy simulation framework. It simulates the operation of a multi-tiered storage system; for example, a system that stores super “hot” files in non-volatile RAM, less “hot” files in solid state drives (SSDs) and “warm” and “cold” files in hard disk drives (HDDs). StorageSim comes with three data-placement policies, and can be extended to support other policies. It can replay publicly available storage
traces from the Storage Networking Industry Association (SNIA) and other public sources, and can be used to evaluate dataplacement policies prior to implementing them on a real system. By abstracting away many complex details, StorageSim provides a fast simulation framework that can be used to simulate large scale storage systems. Experimental results show that StorageSim is useful, can reproduce prior results from real deployments (error < 6 percentage points), and is fast enough to handle Big Data workloads in a timely manner (up to 8 000 operations per
second).

Experimental transmission of a wireless radio-frequency signal by using a microwave photonic filter over an optical link

Abstract: This work describes an electro-optical system capable to transmit a wireless reference signal of 0.915 GHz utilizing the Radio-over-Fiber technique. The reference signal is supplied by a RF multiband transceiver, sensed by an antenna, and coded on a series of microwave band-pass windows located at 2.31 GHz, 4.62 GHz, and 6.86 GHz. Mixing the reference signal with an analog microwave signal, the resulting electrical signal is transmitted by using an electro-optical system communication at external modulation over 25.25 km of optical fiber and radiated at the end of the link. The electro-optical system here described exhibits a SNR of 31.93 dB, which is an acceptable value in a Radio-over-Fiber system.

Trajectory Tracking for Quadcopter’s Formation with two Control Strategies

Abstract: The aim of this paper is to model, simulate and control the trajectory tracking for the formation of three quadcopters based on their kinematic model, then implements the model in Matlab-Simulink software and the respective controllers are made.  The controllers designed for the quadcopters formation are a classic PD controller and a robust SMC controller. To evaluate the performance of each one, they were tested in one trajectory and error behavior was analyzed through the performance indexes IAE and ISE.

Two-wheeled Inverted Pendulum Path Planning: An Experimental Validation

Abstract: This paper presents experimental results of a two wheeled inverted pendulum path planning. The model of the robot is linearised by least squares estimation. The two-wheeled inverted pendulum is stabilized using the Linear-quadratic Regulator. An integral part is added to the controller which results in an optimal PI. The path planning is designed using a Rapidly Exploring Random Tree Connect method. Two algorithms are presented in order to improve the quality of the path . The first algorithm reduces the redundant paths and the second algorithm
uses the Bezier curves to smooth the path.

Large-Scale Network Connectivity of Synechococcus elongatus PCC7942 Metabolism

Abstract: The prediction of the metabolic network connectivity allows to determine the underlying functioning principles of certain cellular process. This analysis is an inherent part of Systems Biology that paved the way for metabolic engineering. From the topological perspective, the availability of genome-scale metabolic models assists the large-scale analysis of the metabolites connections, and thus, the evaluation of the cell metabolic capabilities to produce high added-value molecules. In this study, a comprehensive connectivity analysis of the published genome-scale metabolic model of Synechococcus elongatus PCC7942 (iSyf715) is presented, highlighting the most connected metabolites of this biological system. Additionally, through the comparison of the connectivity distributions in different microbial metabolic network models, the scale-free behavior of these metabolic network is verified.

Predictive and adaptive nonlinear controller applied to a drying process of cocoa beans.

Abstract: This paper describes the study for the design of a predictive controller based on the parametric model obtained for a dryer cocoa plant. The drying system is a nonlinear process, the parametric model obtained is nonlinear, these conditions allowed test the performance of algorithm NEPSAC (extended, predictive and self-adaptive nonlinear controller). It shows characteristics of the plant and a brief description of nonlinear model of the plant is made. The controller design details are shown and furthermore NEPSAC results are compared with Generalized Model Predictive Control (GPC) and PID control results. The implementation of the controllers was done using MATLAB® Software and an embedded system for the collect of the data.

Linear Effects present in a system of radio over optical fiber using wavelength division multiplexing.

Abstract: Because of the large bandwidth that the optical fiber offers as transmission medium of information and the flexibility of communication of the wireless systems, a new mixed infrastructure called radio over fiber system (Radio over Fiber, RoF) have been developed, these have been characterized for implementing division multiplexing wavelength (WDM) and these work with radio carrier signals in the band of extremely high frequencies (extremely high frequency, EHF). Nevertheless, this type of communication systems presents linear errors as the dispersion. This article describes the research done and the results obtained from the simulation of a RoF system using multiplexing WDM through the Matlab software, the which it has as main objective to model and simulate an RoF system for to assess the degradations produced by the dispersion that affect the signal in the transmission of information.

Human activity recognition from object interaction in domestic scenarios

Abstract: This paper presents a real time approach to the recognition of human activity based on the interaction between people and objects in domestic settings, specifically in a kitchen. Regarding the procedure, it is based on capturing partial images where the activity takes place using a colour camera, and processing the images to recognize the present objects and its location. For object description and recognition, a histogram on rg chromaticity space has been selected. The interaction with the objects is classified into four types of possible actions; (unchanged, add, remove or move). Activities are defined as receipts, where objects plays the role of ingredients, tools or substitutes. Sensed objects and actions are then used to analyze in real time the probability of the human activity performed at
particular moment in a continuous activity sequence.

Ergonomic analysis for people with physical disabilities when the wheelchair is considered as their workstation

Abstract: An ergonomic study was performed using the RULA and MAPFRE methods, the assessment is centered on the relationship between the user and his wheelchair analyzed as their inevitable workstation rather than on the performed tasks. The sample is conformed of 22 people who: are wheelchairs users, are capable of performing professional activities with their upper limbs, have acquired the disability after reaching their physical maturity, are in working-age and that lives in the city of Ambato, Ecuador. Since there are few studies that approach the assessment of the wheelchair as a workstation; this is emphasized in this research where the evaluations are made during the performance of job and/or home tasks since not all the wheelchair users evaluated have a remunerated job but all perform a variety of tasks during the day. The results show the urgent need of the user to be able to change the sitting position during the working hours and the postural risk associated to reach objects from that position. Other interesting finding is the high percentage of users that made rudimentary changes in order to adjust the wheelchair to their body size or to facilitate the accomplishment of some tasks, evidencing the need of these types of studies and the development of technical solutions that prioritize the health preservation and the promotion of their capabilities.

Phenomenological Modeling and Computer Simulation of a Clinker Kiln

Abstract: This article uses a two-dimensional phenomenological model representing the dynamic behaviour of a clinker kiln, and includes another model to estimate the height of the solid material (crude) inside the kiln. These models are parameterized according to design specifications and operating conditions of a real industrial kiln, which belongs to a cement production plant. The whole model consists of 16 partial differential equations, one ordinary nonlinear differential equation and a set of algebraic equations, and is computationally simulated using the finite elements method. The model allows analyzing temperature profiles in the kiln, as well as qualitative characteristics associated with fractions of final components in the clinker production.

Control Performance Monitoring of Nonlinear Processes

Abstract: This paper presents a novel approach to monitor control performance of nonlinear processes that can be modelled as state-dependent models. A discrete Kalman filter is used to estimate the state-dependent model parameters. A covariance control formulation is used to split the system closed-loop variance/covariance into two terms, one term to account for minimum expected quadratic loss bound (equivalent to the minimum variance performance bound but in state space formulation) and one to account performance deviations from the minimum variance bound. The proposed algorithm is computationally efficient and can be implemented in real time monitoring and control. Simulation results show that the approach can be used for a wide variety of nonlinear processes such as steel processes with fast, highly nonlinear and time-varying dynamics.

Compress sensing for wireless sensor networks using gossip pairwise algorithm and optimization algorithms

Abstract: For retrieving information in a wireless sensor network (WSN) from any node, each node must know the status of the entire network, leading to a high cost of energy in communication and information storage. In this paper, we evaluated a recovery method, to request information from any node of a WSN with the use of compress sensing to compact the data to be stored and transmitted, and the use of a gossip pairwise to obtain the network status. To recover the compressed information, two optimization algorithms are proposed and tested for convergence errors.

A spatial perspective of the domestic energy consumption intensity patterns in sub-city areas. A case study from the United Kingdom

Abstract: This paper explore the benefits of an bottom-up spatially-enable building-based energy framework in identifying districts, neighbourhoods, and community’s building aggregated areas that have spatial expressions patters most similar to a given parameter within the energy profile. In districts, we argue that the hot spot cluster technique simplify the complexity of the urban extent of the energy consumption intensity which potentially signpost ad-hoc energy retrofit planning scenarios and flexible local micro-generation strategies. In neighbourhoods and communities, our results suggest that the number of heated rooms rather than the simple count of the number of rooms, as a proxy for the usable floor area, leads to a better density metric indicator, the space per person, which is more appealing to energy studies despite not being available in UK statistics as it should be. Additionally, certain geometry on the local construction of the UK’s city settlements lead to original building types, like the Tyneside Flats, that are both difficult to harmonize with existing national data sets, and to model; and, more importantly, to effectively assess the estimated energy savings that will result from potential measures. This represent a challenge not only to the government energy-efficiency national financing mechanism like the Green Deal but also for manufactures and suppliers, which have to provide specifications for a large number of architectural details. Finally, the extent of heating controls, which are not recorded in the Homes Energy Efficiency Database (HEED) database, but we believe would be considered good practice to maintain balanced temperatures around the house, reduce the complexity in modelling the thermal zones, and seen as compulsory in new building regulations, an eligible measure in Green Deal and Energy Company Obligations, and in the Department of Energy and Climate Change DECC heat strategy. This modelling exercise is undertaken within the city limits and are set in the context of an unique identification of Local Land and Property Gazetteer (LLPG) in a Geographical Information System (GIS).

Different perspectives for kernel spectral clustering: A theoretical study

Abstract: Spectral clustering is a suitable technique to deal with problems involving unlabeled clusters and having a complex structure, being kernel-based approaches the most recommended ones. This work aims at demonstrating the relationship between a widely-recommended method, so-named kernel spectral clustering (KSC) and other well-known approaches, namely normalized cut clustering and kernel k-means. Such demonstrations are done by following a primal-dual scheme. Also, we mathematically and experimentally prove the usability of using LS-SVM formulations with a model. Experiments are conducted to assess the clustering performance of KSC and the other considered methods on image segmentation taks.

Active Power Control of a Virtual Power Plant

Abstract: The present work develops the entire control system to achieve the active power regulation in a detailed model of a small-scale Virtual Power Plant (VPP). Firstly, the proposed VPP topology is exposed. A DC bus has been used for the integration of the different distributed generators and the storage system. Different DC-DC power converters schemes have been employed to fulfill this goal. Later, by means of an Energy Management System strategy who commands a three-leg three-phase inverter having a suitable modulation technique, the control of the demanded active power is performed. The results exhibit successful responses of the system for both, dynamic and steady state.

A Control Engineering Approach for Optimizing Physical Activity Behavioral Interventions

Abstract: This paper presents the use of control engineering principles to optimize mobile and wireless health (mHealth) adaptive behavioral interventions for physical activity based on Social Cognitive Theory (SCT). SCT is a conceptual framework that describes human behavior and has been used in many behavioral interventions. The physical activity intervention is formulated as a control systems problem relying on a dynamical model of SCT that is developed utilizing fluid analogies. To obtain values for model parameters, system identification experiments are designed including two phases: an initial informative stage followed by an optimized stage that includes “patient-friendly” conditions. With the obtained model, a closed-loop intervention is formulated relying on Hybrid Model Predictive Control (HMPC). The HMPC algorithm includes the representation of categorical and discrete constraints that are natural for behavioral interventions, and the definition of behavioral initiation and maintenance phases. A simulation study is performed illustrating representative scenarios of the system.

Design of an electronic device for turbidity detection in blood serum in newborns

Abstract: This work introduces the engineering design of a device capable to detect serum turbidity. We hypothesized that an electronic, portable, and low cost device that can provide objective, quantitative measurements of serum turbidity might have the potential to improve the early detection of neonatal sepsis. The design features, testing methodologies, and the obtained results are described. The final electronic device was evaluated in two experiments. The first one consisted in recording the turbidity value measured by the device for different solutions with known concentrations and different degrees of turbidity. The second analysis demonstrates positive correlation between visual turbidity estimation an electronic turbidity measurement. Furthermore, our device correlated high turbidity in serum with sepsis in one neonate. We conclude that our electronic device may effectively measure serum turbidity at the bedside. Future studies will widen the possibility of additional clinical implications.

Use of Experimental Material Management Tools in Experimental Replication: A Systematic Mapping Study

Abstract: In experimental software engineering (ESE), experimental replication is applied to validate results of an experiment. Much information and one version of the experimental materials are required for replication. Prior to the replication execution, all or part of the materials may require changes, producing new or modified versions of these, which should be incorporated into the material of the original experiment. There is a direct relationship between the increase in the number of replications with the increase of versions of the experimental material, which commonly causes confusion and disorder for administrators experiments. Objective: The aim of this paper is to conduct a mapping study to locate articles about the use of experimental material management tools in experimental replication in ESE. Method: We applied the mapping study to search, analyse and select published papers from reported replications. Results: We analyzed a total of 592 articles published between 1998-2014, 24 of them have been preselected and 4 have finally been selected. Conclusion: The results show the limited existence of articles on this subject. In addition, the analysis of the articles allowed us to identify that most suffer from problems in versions management for both replication and experimental material. These data provide information of interest to begin an investigation about adoption of the paradigm of software configuration management inside the management of the experimental material in ESE.

LQI controllers for a Ladder Converter modeled by Generalized Equivalent Continuous Model

Abstract: This article presents a study of four controllers designed for a ladder converter with the generalized equivalent continuous model. Two controllers are designed minimizing the input, and the other two controllers are designed minimizing the changes in the input. The article compares the designed controllers. Also, the article shows a Kalman filter with shaping noise filter to estimate the states of the system. The use of a Kalman filter with shaping noise filter is necessary because the output voltage presents a high ripple. The shaping noise filter is designed with the three highest harmonics components of the output voltage. The article shows simulation results of the controllers with changes in the voltage reference, disturbance in the input voltage, and changes in the load.

Analytical strategy to achieve optimized grating couplers with high precision for both TE and TM polarizations on SOI platform

Abstract: Diffraction elements are periodic structures that whose performance is based on the light diffraction principle. One application of this structure the are grating couplers which consist in coupling light on or off plane between two propagation means, in our case between a subwavelength waveguide and a single mode fiber optic. Optimized gratings are required to ensure a maximum coupling efficiency. Gratings on silicon on insulator (SOI) platform can be optimized in a few steps analyzing its behavior and linking some structure parameters. But advanced computational calculations and algorithms are used to optimize its design. Period and fill-factor are essential parameters in the optimization. In this paper, several analytical expressions based on the fundamental grating equation are proposed to accurately obtain the optimal period and fill-factor, and moreover how to get analytically the optimal parameters for polarization transversal-magnetic through the optimal parameters of polarization transversal-electric, avoiding simulation time.

Fault Location in Distribution Systems with Distributed Generation Using Support Vector Machines and Smart Meters

Abstract: In this paper the fault location is presented in distribution systems with distributed generation using Support Vector Machines and information provided by smart meters located on the system. Different types of faults that can occur in a distribution system are simulated for fault resistances 5 to 30 Ohms in steps of 5 Ohms. Support Vector Machines were trained with effective voltage values measured at the substation in distributed generation and smart meters. The results show that the accuracy in locating all types of failure is higher than 87%, demonstrating a fortress in this tool.

Implementing a Gamified application for a Risk Management Course

Abstract: Gamification is a technique that, through the use of game elements, encourages users to learn and create opportunities to explore issues that necessarily must be approached from a theoretical perspective. For example, theories related to risk management. This work implements a proposal of a Gamified Web Application to strengthen the teaching of risk management. The building of the application focuses particularly on the stages of identification, analysis and mitigation of risks in technological projects. The findings of this study shows, through the use of decision tree, why Gamification is a suitable framework for the issues raised in comparison with other game based learning techniques. In addition, to the implementation of a web application, built according to Gamification Framework 6D which can be used both to teach risk management, and for future experimentation to prove the effectiveness of Gamification.

ECG signal feature extraction

Abstract: The electrocardiogram (ECG) signal is used to assess electrical abnormalities and provides vital information about of heart health. One of the most important problem is the feature extraction such as the morphology analysis, the fiducial point localization, and the time intervals measurements, due to the intrinsic noise. This paper presents a feature extraction method using continuous and discrete wavelet transforms over real ECG signals, obtained from a CardioExpress SL3 medical device. The results obtained are under the International Committees the Common Standards for quantitative Electrocardiography (CSE), with a Sensitivity (Se) of 96% and with standard deviation (std) less than 8%.

Prospects of Model Predictive Control of the Drum Level at a 225 MW Combined Cycle Power Plant

Abstract: We report the application of the Model-based Predictive Control (MPC) to improve the performance of the startup of a 15075 MW combined cycle power plant whose gas turbine is fueled by natural gas. In concrete the simulations have shown that an efficient drum level control is reflected on the improvement of power efficiency in the sense of reaching the 225 MWset point in around 45 minutes faster than the case when PID is used. Experimental data taken from ordinary runs from power plant was used for ends of system identification which is based on convolution integrals resulting well adjustable to the acquired data. Simulations have demonstrated that the performance of the MPC surpasses to the one of classic PID essentially in two aspects: (i) reducing the time for reaching set point and (ii) avoiding unexpected critical situations during the plant start-up. Results have indicated that MPC might reduce in up to 455 minutes, the time of reaching the set point established to be 255 MW within a computational error of 5%, that is translated in the MPC error of order of 2.5% working as software in plant.
All these results might sustain the fact that the MPC based on convolution models appears to be interesting scheme to optimize the full functionality in power plants whose expected power is ranging between 200 and 250 MW.

An ontology-based expert system to generate therapy plans for children with disabilities and communication disorders

Abstract: Nowadays there are no precise estimates about the number of persons (especially children) living with disabilities and communication disorders in the world. This situation becomes more complex in developing countries, where the World Health Organization (WHO) claims that only between 5 and 15\% of children and adults with disabilities have the opportunity to access to assistive technologies. In the same way, a Speech-Language Pathologist (SLP) has a work overload, and must carry out several activities related with monitoring patients, designing therapy plans, preparing reports, providing couseling services, among others. On those grounds, in this paper we present an expert system able to automatically infer general intervention guidelines for children with disabilities and communication disorders. The system relies on ontologies and implements a semantic web environment to provide several services related with information querying, reports generation, inference of intervention strategies, etc. In order to populate the ontology and validate the system, we have used the clinical information of 152 real cases of patients of Cuenca, Ecuador and 1,005 speech-language therapy information elements.

Load Flow for Radial Distribution Systems with Distributed Generation using a Dynamic Data Matrix

Abstract: This paper proposes an algorithm to build a dynamic data matrix (DDM) that allows to organize the topology information of a radial distribution system (RDS). The DDM is then used in load flow analysis of RDSs with and without distributed generation (DG). The deterministic equations of the load flow method and the iterative loop to find the bus voltage magnitude and phase angle solutions of an RDS are presented. The load flow method is valid for RDSs with or without DGs, and it is flexible for RDS reconfiguration. A computational program was developed to build the DDM and run the load flow for RDSs of n buses. Finally, the load flow program performance is analyzed with a 33-bus radial distribution system. The results show that the DDM’s algorithm and the load flow method are computationally efficient and that the load flow program converges in a short number of iterations.

Embedded mini-Heater Design for Power Loss Remote Measurement and Thermal Runaway Control on Power Devices for Accelerated Life Testing

Abstract: Accelerated Life Tests (ALTs) are performed to determine semiconductor devices reliability. During ALTs, devices under test (DUTs) can be strongly affected by thermal runaway phenomenon because of the DUTs degradation and an uncontrolled single device temperature. Under these scenarios, the leakage current generates self-heating, especially in large area devices, which elevates even more the device temperature forming a positive feedback until a failure happens. In this work, a single Embedded mini-Heater (EmH) design is presented. EmH can detect and control the thermal runaway on a power DUT while thermal and electrical stress test is applied. Even more, due to the small size and low heating power consumption of the EmH, loss power dissipation from a single DUT can be measured remotely without any electrical interface connection in order to detect its degradation.

EMR system synchronization in Venezuela

Abstract: In Venezuela and other countries where it coexists public health system and a private one, we find a variety of organizations that present health services. Even when we have a strong public system, often we find that each health center uses different Electronic Medical Record systems, hindering data sharing for improved patient care. One of the strongest challenges for the integration of all stakeholders in the health system is to have a system for synchronizing heterogeneous databases. In this article synchronization and data sharing mechanisms are proposed to achieve an integrated health system.

Tremors Quantification in Parkinson Patients Using Smartwatches

Abstract: Parkinson’s disease is a neurological disorder that affects about 1% of people over 60 years. The complexity of the disease difficult to carry out objective medical assessments of the level of tremors. This article presents a system which uses the accelerometer and gyroscope sensors in smart watches to quantify the tremors in patients with Parkinson’s disease. The system is based on a Wireless Body Area Network composed by multiple sensor nodes (Android Wears) and one sink node (Android Smartphone). The system integrates four processes: user authentication, placement of sensors on the body, movement sensing and data uploading. The system was evaluated in 12 patients with PD (five males and seven female) while they were doing several activities, but in this article we only analyses when the patients were seated at rest. The patients had an average disease duration of 6.25 years, an average age of 66.33 years and a range of 5186 years. The tremor magnitudes were presented in the form of linear acceleration and angular velocity in the time domain. The results indicates that these features can determined Parkinson’s disease evolution in a patient diagnosed in stage 3 and 4.

How Easy is to Break Password Protection: A Preliminary Empirical Study

Abstract: Background: These days, users are given access to information system functionalities through several security mechanisms, passwords being the most common form of access. There are many policies and rules, some stricter than others, to create passwords; however, they still remain vulnerable to attacks. Goal: In order to find out: the vulnerabilities of different passwords complexity levels created for this study, types of passwords used in attacks, and types of attackers and their origins; we conducted an empirical study. Method: This research was conducted using an empirical study based on a controlled experiment. The study was based on honeypots in order to emulate a SSH server, which was exposed to attacks for approximately 30 days on the Internet. Results: A large number of attacks were recorded, which were not capable of breaching any passwords complexity level. Conclusion: Although some attacks were carried out by means of sophisticated tools, none password complexity level was breached. We believe that it could be due to the experiment’s duration was too short, or that the attackers simply did not have enough motivation to persist in the attempt to breach the access password to a site possibly listed as unattractive.

Control of an island Micro-hydropower Plant with Self-excited AVR and combined ballast load frequency regulator

Abstract: This project describes the design and construction of an Automatic Voltage Regulator (AVR) and an Electronic Load Controller (ELC) for the voltage and the frequency regulation in an island Micro-Hydropower Plant (MHP). For the frequency control, the speed regulation by ballast load method has been used. To this approach, a combined binary-continuous load regulation was employed. The implemented AVR is totally self-excited by means of an energy transfer system which allows an isolated operation of the MHP. The entire system has been designed considering the current standard regulations of the Ecuadorian Electricity Regulator (CONELEC). The frequency and the voltage regulation were properly achieved through the implementation of digital PI controllers tuned based on mathematic models obtained from experimental data of frequency and voltage. The control of the system was validated by both, software simulations and field tests performed.

Robust Multivariable PID Control for Quadruple-Tank Process Using an ILMI Approach

Abstract: This paper shows a robust multivariable PID controller design for a nonlinear quadruple tank process. The controller synthesis is reduced to an equivalent static output feedback control problem. The closed loop -stabilizable performance is guarantee for the linearized system with convex polytopic uncertainty. The algorithm is based on an iterative linear matrix inequality approach. Parameter-dependent Lyapunov matrix functions is used in robust stabilizability conditions; this approach provides better results than the classical quadratic stabilizability. Also, decoupling between the Lyapunov matrix and the system dynamic matrix is used. The design technique is illustrated with a numerical example.

Model Predictive Current Control with Neutral Current Elimination for H-Bridge Two-Level Active Power Filters

Abstract: In this paper, a scheme for reactive power compensation and neutral current elimination based on model predictive control strategy is proposed. In this context, a H-bridge four-wire two-level active power filter is presented. The main feature of the proposed method focuses on the compensation of reactive power and neutral current elimination for unbalanced load in order to improve the power factor. This approach predicts the future
behavior of the control actions considering all possible switching states. The proposed method selects the optimal switching vector by using an optimization process considering a defined cost function. The effectiveness of the proposed control approach is evaluated through simulations.

Linguistic profiles on microblogging platforms to characterize political leaders: the Ecuadorian case on Twitter

Abstract: Social interaction on microblogging platforms are becoming a valid aspect for studying political communication characteristics. Microblogging platforms, such as Twitter, let political leaders and citizens interact more closely and frequently than before. This make possible to build a linguistic profile for leaders and average citizens. We have conducted a linguistic analysis of 330,000 tweets collected from 221 Ecuadorian tweeters classified into three different groups of user profiles: political leaders, leaders’ followers, and average local users. We built a feature vector for the tweets of each user using 12 psychological dimensions included in the LIWC (Linguistic Inquiry Word Count) text analysis software and compared users in each group using those vectors. Our findings show that the leaders group exhibits a different linguistic profile from the others two groups: around 30% of leader followers are similar to at least one leader while just 19% of average local users are similar to at least one leader. Furthermore, the results of our analysis allows to determine whether local users have some similar characteristics on language uses on social networks of political leaders’ followers without relying on critical discourse analysis.

Determination of converge parameters for Monte Carlo experiments in the simulation of the failure of bone tissue

Abstract: The Monte Carlo method is widely used in the field of biomechanics to study the variability of diverse parameters, like tissues properties, magnitude and direction of loads, kinematic of joints, among others. In particular, the failure of bone tissue, which is the target of this investigation, has been extensively studied; however, it is common to find in the literature realizations of Monte Carlo experiments with arbitrary sample size, or with a convergence criterion for which a statistically valid confidence level, or interval, is not defined. These strategies lead to results with presumed low, but unknown uncertainty. One option to address this problem is the acceptable shifting convergence band rule which, if appropriately configured and applied, serves as a convergence criterion with an implicit confidence level. However, in order to ensure a desired confidence level, it is necessary to determine the correct parameters for the method. As the typical biomechanical simulation is very time consuming, it is not advisable to calculate these parameters with the full model. Therefore, it is recommended to run a Monte Carlo experiment with a simpler, faster to simulate, model that is probabilistically similar to the full model. In this work, a pilot experiment is developed in order to compute the parameters required to stop the Monte Carlo simulation of the failure of bone tissue, with a desired confidence level. Two different failure criteria are applied, one with two and the other with three input probabilistic variables. Also, the variation of the convergence parameter with the desired precision of the mean is explored. Results led to determine suitable parameters for the different combinations of desired confidence level, precision of the mean and failure criterion. It was also found that when three input variables were involved, or when a three significant digits precision of the mean was required, the number of trials needed to attain convergence was greater than when two inputs variables were involved or when two significant digits precision was required.

An Upper-limbs Activities Analysis of PD Patients in OFF and ON State of Medication

Abstract: In this paper the analysis of the movement of the upper-limbs of patients with Parkinson’s disease (PD) in four activities is presented. An accelerometer-based sensor was used to acquire and store the acceleration data of the upper-limbs of the patiens while they were doing the activities. The data was processed in MatLab; specifically the data was filtered and an estimation of Power Spectral Density (PSD) was done with Burg’s Periodogram. The PSD analysis of PD patients activities were performed on patients medicated (ON) and no medicated (OFF). Additionally, the PSD analysis of one healthy patient was useful to compare his signal with the PD patient’s signal.

Equipment for Monitoring the Electrodermal Skin Response Using an Embedded System Based on Soft Processor NIOS II

Abstract: This work presents the results of construction of an equipment for to measure the resistance of the skin along of a period of time based on Electrodermal Skin Effect or Galvanic Skin Response (GSR). The GSR phenomenon allow supervise the variation of the resistance of the human skin, because the resistance of human skin, change in function of amount of sweat produced by it. This amount of sweat varies depending on the emotion a person feels in a specific moment. This does that the resistance in the skin also change, so can evaluate the emotional condition of a person in a determined moment, measuring its resistance and correlating both. Between applications for GSR monitor can found machines for aids to psychological treatments and as a part of machine called polygraph or lies detector. The work includes the design and construction for a data acquisition system and digital processing of the data acquired using an embedded reconfigurable system based on NIOS II microprocessor of Altera Corporation. The results of variation for skin resistance for some persons placed under several test cases, and the results correlated with the intensity of their emotions are shown.

EEG Occipital Signals clusterization using K-means algorithm

Abstract: Recent Works show that is feasible the use of electric signals from electroencephalography (EEG) for controling devices or prothesis, these signals are provided by the body and can be measured through the scalp to determine volunteer’s intentionality when observing visual stimulus in a range frequency detectable for the human eye. This group of signals are very susceptible to the noise due to acquisition voltage levels, therefore this work proposes a statistical analysis of normality distribution in bruto-aquired EEG signals to determine the need of pre-processing to remove noise components coming from electric networks or any other source. This pre-processing includes the design and use of a filter that allows remove any signal component that is not in the frequency range in which the EEG operate in occipital area of the brain. Finally, the k-means algorithm will be used to cluster the signals based on temporal and frequency characteristics.

Evaluation of type-2 Diabetes Progress in Adult Patients by Using Predictive Algorithms

Abstract: A prediction-based algorithm has been tested inside a teleconsult scheme aimed to improve the quality of life of type-2 diabetes patients belonging to vulnerable zones of Lima city. Concretely, the predictive algorithm performs estimations of the future situation of patients by using history and previous information about the process of individual recovery. The obtained information from the results of the prediction is used to anticipate risk situations especially in those patients already in advanced levels of disease. According to the results of this paper, two thirds of sample of diabetes patients might reconfigure their treatment with a success probability above 80%. These results might be translated as the improving of the stability of diabetes patients against the progress of disease in their forms of necrosis and diabetic nephropathy.

An Architecture For Emotional Smartphones in Internet of Things

Abstract: In the past few years, the idea of the “Internet of Things” (IoT) has been developing rapidly, with sensors and machines communicating with each other through the Internet. These new technologies can be used to support new types of Cyber-Physical Systems (CPS). Even though CPS consider humans as a part of themselves, they still treat humans as external elements, with unpredictable behavior. In fact, in order to the new IoT serves human needs better, it has to take into account all sorts of psychological and emotional states.
Smartphones present an excellent opportunity to do so as they are a key element in IoT and they contain several sensors that allow us to collect information about user movement, location, environment, and interactions with other people. This type of mobile device usually accompanies the user anywhere he goes throughout the day.
This paper presents a work about a new paradigm that integrates human in the IoT. This paradigm is validated by the implementation of 3 applications that are detailed in this paper – HappyWalk, WeDocare and HappySpeak.

Selection of the reference anchor node by using SNR in TDOA-based positioning

Abstract: This article studies the positioning problem for wireless networks when TDOA measures are used and the reference anchor node is not previously known. We carried out various experiments to show the impact on accuracy when a poor selection of this reference is achieved. Furthermore, we study the use of SNR at receivers as a mean to proper select the closest node as the reference anchor, previously to perform mobile positioning. An appropriate mechanism to perform this selection is provided within a simulation platform built to study network-based positioning using space-time diversity in realistic conditions.

Algorithm and Rapid Intervention to Attenuate Zika Virus Outbreak in Large Cities

Abstract: A rapid-decision algorithm aimed to tackle the increase of cases by infection due to Zika virus in Lima city assuming a rapid outbreak, was developed and tested computationally. This approach targets to provide rapid assistance to possible cases caused by the Aedes mosquitoes minimizing the time of processes of identification, evaluation and intervention. Basically, the algorithm focuses on the rapid decision for a better localization of pregnant women away from infected areas or individuals already carrying Zika symptoms. The algorithm
assumes that the people already have become infected by Zika virus would have to phone to health specialists, fact which would serve to design an optimized route for a rapid attention and improvement of attention. Also, Geographic localization of possible infected might be also crucial to accelerate a rapid attention and focus efforts to identify vulnerable ones living around. The simulations have shown that the scenario where 1000 people were infected, algorithm applied systematically might avoid complications in a 90% of pregnant women.

Development of a Smart Glove as a Communication Tool for People with Hearing Impairment and Speech Disorders

Abstract: This paper describes a project to create a novel design of a communication tool for individuals with hearing disabilities and speech disorders. It provides a detailed analysis of the engineering and scientific aspects of the system, and the fundamentals taken into account for social inclusion of such individuals. It also describes an exhaustive study of present and future applications of this technology to provide an enhanced tool to individuals to further improve their communication skills. Morse code is the base over which this new technology is proposed, which has gathered feedback from specialists and individuals with disabilities, to patent in a short future as a newer communication tool solution, with a robust functionality
and an ergonomic design.

Internal Mode Control for power system load frequency regulation assessment and analysis with Real Time Simulator

Abstract: Electrical power systems must balance demand and generation almost instantly to maintain frequency. This task is performed at each power station with the load frequency controller. On wider areas, the energy management systems supervise generation control automatically to preserve stability and reliability. Due to the unpredictability of the demand, the control response must be as fast as possible to prevent larger deviations that could lead to cascading failures and outages. In order to understand the dynamic behavior and capabilities of the controllers, real time simulation offers a great advantage over its offline predecessors, not only for operational training but also for prototyping. This paper studies the effectiveness of the real time simulator in the assessment and analysis of a power system load frequency control.

Demand response systems for integrating energy storage batteries for residential users

Abstract: This paper develops the optimization of the response to the demand for electricity in the residential sector, where the energy required to supply demand is supplied by the electrical system, which may have distributed generation, optimization of demand is to target flatten the curve of peak demand, and thus promotes energy conservation by users without affecting the comfort of the same, for which a system of energy storage is used by batteries allowing decreased energy delivery system to the user. The system power management allow respond relieving the burden on the electrical system, especially when peak demand occurs and when the cost of energy is higher, delivering energy from the battery bank, as well as this research can route to use of the excess energy of electric vehicles.

Design of Telemedicine management system in Ecuador

Abstract: In Ecuador, the ambulatory emergency system has a numbered paper handwriting information registry procedure, which means that the medical staff knows about the patient condition after his arrival to the health facility, in certain cases this means the loss of a human life. This article details the proposal of a system which transmit detailed patient health status information and also his vital signs during the ambulance transfer, developing simultaneously a hardware and software adjusted to the requirements of the paramedics. The system is divided in three parts, firstly a prototype that consist in a touchscreen computer for data input, connected to a pulse oximeter sensor for live broadcast of pulse rate and oxygen saturation. In second place a management and database server software for emergency events registry. And finally an easy integration system monitoring app for mobile devices. The link of the ambulance to main server and medical entities is achieved through LTE network, with the appropriate data security measures. The project have the goal to actively support the emergency personal for the opportune attention of any trauma or pathology that a patient present.

Reconfiguration Strategy for Fault Tolerance of Power Distribution Systems Using Petri Net

Abstract: This article presents a new heuristic strategy for the elaboration of a reconfiguration model for Fault Tolerant System Distribution (DSFT) using Petri nets (PN). It is intended to model, analyze and optimize the program for the management of Smart Reclosers and Sectionalizers in a Smart Grid Distribution System, which together with the detection of faults, manage its isolation and the reconnection of a new system that maintains working capacity. In addition, according to the condition of protective equipment, thereby guarantees supply continuity. The restoration of the distribution system with the support of the block diagram of the Study Guide Modes Start and Stop (GEMMA) arises. The objective is to design with PN a decision sequence for the programming design of intelligent electronic devices (RTU-IED-PLC) that allows the operation of the distribution network in fault status in branch form or in combination. This keeps quality levels of energy delivery to a vast majority of users, and is able to perform autonomously with the rapid restoration of customers for a Smart Distribution System. It also provides greater flexibility for the following: control design for validation states (State feedback control), the Event Feedback control, and simplification and plans for the restoration of the smart restoration plans system intelligent distribution.

A Methodological Proposal Concerning to the Management of Information Security in Industrial Control Systems

Abstract: The most recent international reports of security issues documented a growing number of cybernetic attacks to Industrial Control Systems. Therefore, an increase of information technology implementations in manufacturing processes arose offering solutions in Information Security of the involved manufacturers and professionals. In this respect, a notable tendency emerges in which information security has been particularly intended to be used in businesses’ administrative areas, where ISO-27000 is the most favored standard. Nonetheless, it has been determined that ISO is not yet an ideal standard for an industrial approach, due to the fact that it has not been created for these systems. We designed and implemented a methodology for the management of information security of the Industrial Control Systems of industrial businesses, based on standards issued by NIST. Such methodology presents the development of a series of phases, which provide two main contributions: firstly a group of strategies to reduce risks and secondly a Guide for standards-based instructions as well as security policies for the effective management of information security

Sitting-Pose Detection Using Data Classification and Dimensionality Reduction

Abstract: The research area of sitting-pose analysis allows for preventing a range of physical health problems mainly physical. Despite that different systems have been proposed for sitting-pose detection, some open issues are still to be dealt with, such as: Cost, computational load, accuracy, portability, and among others. In this work, we present an alternative approach based on a sensor network to acquire the position-related variables and machine learning techniques, namely dimensionality reduction (DR) and classification. Since the information acquired by sensors is high-dimensional and therefore it might not be saved into embedded system memory, a DR stage based on principal component analysis (PCA) is performed. Subsequently, the automatic posed detection is carried out by the k-nearest neighbors (KNN) classifier. As a result, regarding using the whole data set, the computational cost is decreased by 33 % as well as the data reading is reduced by 10 ms. Then, sitting-pose detection task takes 26 ms, and reaches 75% of accuracy in a 4-trial experiment.

Performance Evaluation of Radar Systems in Noise Jamming Environments

Abstract: Radar systems are widely used for military, transportation and scientific purposes. For radars, the ability of the device to mitigate the effects of noise and interference is of great importance because it will determine its performance. Radars may suffer from attacks aimed to hinder their performance, known as jamming attacks. In this context, noise jamming attacks are a very common type of attack, thus reducing their effect is fundamental. Due to this fact, simulation and analysis of radar performance in different scenarios could help decrease possible threats. For this reason, in this paper the performance of radars in noise jamming environments is evaluated. To achieve this, a radar system, jammer attacks and anti-jamming algorithm are modelled and evaluated through simulations. The models and algorithms developed in this work could aid in the process of performance test and analysis of radars and could be used as a design platform of radars and jammers to reduce developing and implementation time.

Evaluating Channel Capacity oportunities for potential use by Short Range Devices based on OSA

Abstract: Dense urban zones with high concentration of Wireless networks can degenerate in problems such as spectrum scarcity for devices in licensed bands or in high interference levels for unlicensed band devices, which can produce QoS problems. In this context, a possible solution to deal with this issue is using wireless devices which can access a licensed band opportunistically. For this reason, in this paper is proposed the evaluation of a channel probabilistic modelling in urban zones, with the purpose of allowing unlicensed band devices the access to licensed bands (e.g. TV Band) in an opportunistic way. As result of this study, the channel capacity of the band is compared with different technologies.

Comparison of the Performance and Energy Consumption Index for Model Based Controllers

Abstract: This paper presents a comparison of the performance of different control algorithms in two types of systems; one with fast dynamics and the other with slow dynamics. The first control system regulates the speed of a dc motor, while the second control system regulates the temperature of an electric niquelina. The comparison in the systems’ performance pretend to evaluate the energy consumption, as well as the transient response of the controllers, in order to identify the best method of control for each system. The models of the systems are obtained through responses to a pseudorandom binary signal (PRBS) and the method of least squares fit using an auto-regressive model with exogenous variable (ARX). The control algorithms implemented for this study are: pole placement regulator (state-space controller) with integral error processing, auto-tunable proportional-integral-derivative (PID) controller, neural PID controller, unconstrained model predictive control (MPC), fuzzy PID controller, neuro-fuzzy controller, bayesian controller and an optimal quadratic regulator (LQR) with integrated processing error. The results show the analysis of the performance and energy consumption index, which allow the categorization of the control strategies in accordance with their performance.

Performance Evaluation of Channel Capacity in Wireless Sensor Networks using ISM band in Dense Urban Scenarios

Abstract: Nowadays the deployment of Wireless sensor networks (WSN) is rapidly increasing specially in dense urban scenarios, due to upcoming new technologies based on Internet of things. In this context, the presence of WSN, Wi-Fi and Bluetooth sharing the ISM band, could cause unsuspected interference levels that could deteriorate channel capacity in WSN and consequently deteriorate the performance of WSN and other wireless systems. Viewing this future perspective, this paper sees the importance of evaluating the performance of wireless sensor networks under dense urban scenarios considering chaotic interference conditions.

Fingertip Detection Approach on Depth Image Sequences for Interactive Projection System

Abstract: This study presents a vision-based approach for fingertip tracking on tabletop solutions which combines infrared and depth image processing. This approach intends to tackle three main issues on tabletop interaction: improve the performance for real-time applications, increase fingertip detection accuracy and enhance interaction through more flexible gestures. A prototype using this fingertip tracking method was implemented with a depth camera. This novel approach processes the user’s arm, hands and fingertips images using depth-space constraints, as well as clustering. Fingertip positions are accurately corrected using additional infrared information. Quantitative results show high accuracy of fingertip detection, with lower error rates compared to previous studies. Also, increased capabilities for real-time multi-user interaction are further demonstrated through a set of response time tests.

Modeling and Monte Carlo Simulation of Call Completion Success Probabilities Under the Input-Output Scheme

Abstract: We present a model of Probability of Success Call Completion (PSCC) from a typical I/O procedure and computationally tested through Monte Carlo simulation with Gaussian profiles. Under the I/O view the input and transfer functions are prepared without to abandon the randomness nature of the phenomenology. We assumed that the kernel are represented by the Dirac-Delta functions represent the kernels as required by the I/O formulation. The results would indicate that under certain circumstances the formulation I/O is valid by a 10% of error
respect to the Meo-Ajmone model. However, the weakness of the I/O approach would be in the extraction of a large number of free parameters, which do not necessarily encompasses the dynamic of phenomenon.

AliciaVR: Exploration of Scientific Articles in an Immersive Virtual Environment with Natural User Interfaces

Abstract: Researchers share their research results through articles that are published and indexed in scientific databases, which serve as consultation for further research. Generally, the user interface of these systems are traditional, restrict user interaction and limit their field of view. In this paper a new interface model is proposed, based on virtual reality and natural language processing , which together provide a excellent user experience and better use of human capabilities, such as intuition and spatial cognition. Furthermore, in the research design is used the devices Oculus Rif and Leap Motion. The case study is the exploration of scientific articles using Alicia, which is the scientific database of Peru. The motivation for this research is to contribute with better tools to optimize the tasks of literature review and facilitate the work of researchers.

Evaluation of performance and scalability of Mininet in scenarios with large data centers

Abstract: Due to the increased demand for internet services, the challenges that large data centers must handle are bigger. Therefor in recent years the development of networks defined by software (SDN) has caught the attention of the scientific community, mainly because of the flexibility it presents in its model of centralized management, which facilitates the development of solutions according to demand of the network and / or users. Mininet is one of the most commonly tools used for the study of the SDN, as it allows to recreate data networks that can support various topologies and protocols; nevertheless, like any other emulation software can present failures due to hardware limitations or depending on what you want to emulate, which prevents it to be be scaleable. The present work pretends to establish minimum tests that will validate the performance and scalability of Mininet in a typical topology of a large data center. The results of these tests conclude that in one case the values approximate the expected ones, while for the success of the other, there is a strong dependence on the SDN controller chosen as it intervenes in this situation.

LQR Control of a Quad-Active-Bridge Converter for Renewable Integration

Abstract: In this paper, the design of a linear quadratic regulator (LQR) controller for the DC-DC stage of a Solid State Transformer (SST) based on a quad-active-bridge (QAB) to integrate both photovoltaic (PV) power generation and battery energy storage is presented. The gyrator-based average model is used for deriving the state-space representation of the plant. The dynamic performance of the designed controller is verified through extensive simulation of the switching model and validated with experimental results.

Enhancing Quality of Argumentation in a Co-located Collaborative Environment through a Tabletop System

Abstract: This study validates the potential of a tabletop system to enhance students’ quality and intensity of argumentation when engaging in co-located collaborative design activities. Twenty-four undergraduate students participated in a two-group experimental study where one group used the proposed system and the other group used a paper-based approach. Overall students using the Tabletop system over exceeded their peers in relation to their quality and intensity of argumentation. Further studies should increase the number of students to be able to generalize our findings.

Comparison of CPG topologies for bipedal gait

Abstract: A central pattern generator (CPG) is a network of neurons, capable of producing oscillatory signals without oscillatory inputs. In this paper has been working in a proposal of gait generator for lower lumbar exoskeleton, based on neurophysiological principles. In this manner, it is proposed the use of the ACPO model for CPG as trajectory generator in normal gait for hip and knee joints of a lower lumbar exoskeleton. Three
types of topologies are evaluated to determine the most suitable for this system. The results indicated that the ”A” topology reacts more smoothly to perturbations, which is desirable for a safe and comfortable human-machine interaction. It is proposed as future work to evaluate the trajectories generator in the exoskeleton model and control.

Energy Wideband Spectrum Sensing Based On SubNyquist Sampling And Second Order Statistics

Abstract: In this paper, a novel wideband spectrum sensing algorithm based on Compressive Sensing (CS) and reconstruction of second order signal statistics from covariance matrix of the acquired samples for Cognitive Radio (CR) systems is presented. This allows cognitive users to sense the spectrum without apriori knowledge of signal characteristics in the radio environment by minimizing the amount of samples to be processed. Simulation
results show that the proposed algorithm allows to sense the spectrum efficiently, improving the performance in terms of detection probability, false alarm probability and miss detection probability regarding previously proposed algorithms.