Abstract: The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.
Abstract: Robotic rovers which are designed to work in
extra-terrestrial environments present a unique challenge in terms
of the reliability and availability of systems throughout the mission.
Should some fault occur, with the nearest human potentially millions
of kilometres away, detection and identification of the fault must
be performed solely by the robot and its subsystems. Faults in
the system sensors are relatively straightforward to detect, through
the residuals produced by comparison of the system output with
that of a simple model. However, faults in the input, that is, the
actuators of the system, are harder to detect. A step change in
the input signal, caused potentially by the loss of an actuator,
can propagate through the system, resulting in complex residuals
in multiple outputs. These residuals can be difficult to isolate or
distinguish from residuals caused by environmental disturbances.
While a more complex fault detection method or additional sensors
could be used to solve these issues, an alternative is presented here.
Using inverse simulation (InvSim), the inputs and outputs of the
mathematical model of the rover system are reversed. Thus, for a
desired trajectory, the corresponding actuator inputs are obtained.
A step fault near the input then manifests itself as a step change
in the residual between the system inputs and the input trajectory
obtained through inverse simulation. This approach avoids the need
for additional hardware on a mass- and power-critical system such
as the rover. The InvSim fault detection method is applied to a
simple four-wheeled rover in simulation. Additive system faults and
an external disturbance force and are applied to the vehicle in turn,
such that the dynamic response and sensor output of the rover
are impacted. Basic model-based fault detection is then employed
to provide output residuals which may be analysed to provide
information on the fault/disturbance. InvSim-based fault detection
is then employed, similarly providing input residuals which provide
further information on the fault/disturbance. The input residuals are
shown to provide clearer information on the location and magnitude
of an input fault than the output residuals. Additionally, they can
allow faults to be more clearly discriminated from environmental
disturbances.
Abstract: Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.
Abstract: This paper presents modeling and control of a highly nonlinear system including, non-interacting two spherical tanks using iterative learning control (ILC). Consequently, the objective of the paper is to control the liquid levels in the nonlinear tanks. First, a proportional-integral-derivative (PID) controller is applied to the plant model as a suitable benchmark for comparison. Then, dynamic responses of the control system corresponding to different step inputs are investigated. It is found that the conventional PID control is not able to fulfill the design criteria such as desired time constant. Consequently, an iterative learning controller is proposed to accurately control the coupled nonlinear tanks system. The simulation results clearly demonstrate the superiority of the presented ILC approach over the conventional PID controller to cope with the nonlinearities presented in the dynamic system.
Abstract: The growing popularity of solid state thermoelectric
devices in cooling applications has sparked an increasing diversity of
thermoelectric coolers (TECs) on the market, commonly known as
“Peltier modules”. They can also be used as generators, converting
a temperature difference into electric power, and opportunities are
plentiful to make use of these devices as thermoelectric generators
(TEGs) to supply energy to low power, autonomous embedded
electronic applications. Their adoption as energy harvesters in this
new domain of usage is obstructed by the complex thermoelectric
models commonly associated with TEGs. Low cost TECs for the
consumer market lack the required parameters to use the models
because they are not intended for this mode of operation, thereby
urging an alternative method to obtain electric power estimations
in specific operating conditions. The design of the test setup
implemented in this paper is specifically targeted at benchmarking
commercial, off-the-shelf TECs for use as energy harvesters in
domestic environments: applications with limited temperature
differences and space available. The usefulness is demonstrated by
testing and comparing single and multi stage TECs with different
sizes. The effect of a boost converter stage on the thermoelectric
end-to-end efficiency is also discussed.
Abstract: Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.
Abstract: Genetic algorithms (GA) are applied to the solution
of high-dimensional optimization problems. Additionally, sensitivity
analysis (SA) is usually carried out to determine the effect on optimal
solutions of changes in parameter values of the objective function.
These two analyses (i.e., optimization and sensitivity analysis)
are computationally intensive when applied to high-dimensional
functions. The approach presented in this paper consists in performing
the SA during the GA execution, by statistically analyzing the data
obtained of running the GA. The advantage is that in this case
SA does not involve making additional evaluations of the objective
function and, consequently, this proposed approach requires less
computational effort than conducting optimization and SA in two
consecutive steps.
Abstract: Nitrogen implantation in aluminum and its alloys is acquainted for the difficulties in obtaining modified layers deeper than 200 nm. The present work addresses a new method to overcome such a problem; although, the coating with nitrogen and oxygen obtained by plasma immersion ion implantation (PIII) into a 7075 aluminum alloy surface was too shallow. This alloy is commonly used for structural parts in aerospace applications. Such a layer was characterized by secondary ion mass spectroscopy, electron microscopy, and nanoindentation experiments reciprocating wear tests. From the results, one can assume that the wear of this aluminum alloy starts presenting severe abrasive wear followed by an additional adhesive mechanism. PIII produced a slight difference, as shown in all characterizations carried out in this work. The results shown here can be used as the scientific basis for further nitrogen PIII experiments in aluminum alloys which have the goal to produce thicker modified layers or to improve their surface properties.
Abstract: One of the biggest challenges in nonparametric
regression is the curse of dimensionality. Additive models are known
to overcome this problem by estimating only the individual additive
effects of each covariate. However, if the model is misspecified, the
accuracy of the estimator compared to the fully nonparametric one
is unknown. In this work the efficiency of completely nonparametric
regression estimators such as the Loess is compared to the estimators
that assume additivity in several situations, including additive and
non-additive regression scenarios. The comparison is done by
computing the oracle mean square error of the estimators with regards
to the true nonparametric regression function. Then, a backward
elimination selection procedure based on the Akaike Information
Criteria is proposed, which is computed from either the additive or
the nonparametric model. Simulations show that if the additive model
is misspecified, the percentage of time it fails to select important
variables can be higher than that of the fully nonparametric approach.
A dimension reduction step is included when nonparametric estimator
cannot be computed due to the curse of dimensionality. Finally, the
Boston housing dataset is analyzed using the proposed backward
elimination procedure and the selected variables are identified.
Abstract: The segregation of waste of electrical and electronic equipment (WEEE) in the generating source, its characterization (quali-quantitative) and identification of origin, besides being integral parts of classification reports, are crucial steps to the success of its integrated management. The aim of this paper was to count WEEE generation at the Federal University of Espírito Santo (UFES), Brazil, as well as to define sources, temporary storage sites, main transportations routes and destinations, the most generated WEEE and its recycling potential. Quantification of WEEE generated at the University in the years between 2010 and 2015 was performed using data analysis provided by UFES’s sector of assets management. EEE and WEEE flow in the campuses information were obtained through questionnaires applied to the University workers. It was recorded 6028 WEEEs units of data processing equipment disposed by the university between 2010 and 2015. Among these waste, the most generated were CRT screens, desktops, keyboards and printers. Furthermore, it was observed that these WEEEs are temporarily stored in inappropriate places at the University campuses. In general, these WEEE units are donated to NGOs of the city, or sold through auctions (2010 and 2013). As for recycling potential, from the primary processing and further sale of printed circuit boards (PCB) from the computers, the amount collected could reach U$ 27,839.23. The results highlight the importance of a WEEE management policy at the University.
Abstract: In the construction of a building, it is necessary to minimize construction period and secure enough work space for stacking of materials during the construction especially in city area. In this manner, various top-down construction methods have been developed and widely used in Korea. This paper investigates the stress variation of underground structure of a building constructed by using SPS (Strut as Permanent System) known as a top-down method in Korea through an analytical approach. Various types of earth pressure distribution related to ground condition were considered in the structural analysis of an example structure at each step of the excavation. From the analysis, the most high member force acting on beams was found when the ground type was medium sandy soil and a stress concentration was found in corner area.
Abstract: Social networks play an important role in the lives of children and young people. Along with the high penetration of mobile technologies such as smartphones and tablets among the younger generation, there is an increasing use of social networks already in elementary school. The paper presents the results of research, which was realized at schools in the Hradec Králové region. In this research, the authors focused on issues related to communications on social networks for children, teenagers and young people in the Czech Republic. This research was conducted at selected elementary, secondary and high schools using anonymous questionnaires. The results are evaluated and compared with the results of the research, which has been realized in 2008. The authors focused on the possibilities of using social networks in education. The paper presents the possibility of using the most popular social networks in education, with emphasis on increasing motivation for learning. The paper presents comparative analysis of social networks, with regard to the possibility of using in education as well.
Abstract: The aim of this paper is to investigate the effect of the building fundamental period of reinforced concrete buildings of (6, 9, and 12-storey), with different floor plans: Symmetric, mono-symmetric, and unsymmetric. These structures are erected at different epicentral distances. Using the Boumerdes, Algeria (2003) earthquake data, we focused primarily on the establishment of the deterministic formulation linking the base shear force to two parameters: The first one is the fundamental period that represents the numerical fingerprint of the structure, and the second one is the epicentral distance used to represent the impact of the earthquake on this force. In a second step, with a view to highlight the effect of uncertainty in these parameters on the analyzed response, these parameters are modeled as random variables with a log-normal distribution. The variability of the coefficients of variation of the chosen uncertain parameters, on the statistics on the seismic base shear force, showed that the effect of uncertainty on fundamental period on this force statistics is low compared to the epicentral distance uncertainty influence.
Abstract: Linear actuators are deployed in a wide range of applications. This paper presents the modeling and system identification of a variable excited linear direct drive (LDD). The LDD is designed based on linear hybrid stepper technology exhibiting the characteristic tooth structure of mover and stator. A three-phase topology provides the thrust force caused by alternating strengthening and weakening of the flux of the legs. To achieve best possible synchronous operation, the phases are commutated sinusoidal. Despite the fact that these LDDs provide high dynamics and drive forces, noise emission limits their operation in calm workspaces. To overcome this drawback an additional excitation of the magnetic circuit is introduced to LDD using additional enabling coils instead of permanent magnets. The new degree of freedom can be used to reduce force variations and related noise by varying the excitation flux that is usually generated by permanent magnets. Hence, an identified simulation model is necessary to analyze the effects of this modification. Especially the force variations must be modeled well in order to reduce them sufficiently. The model can be divided into three parts: the current dynamics, the mechanics and the force functions. These subsystems are described with differential equations or nonlinear analytic functions, respectively. Ordinary nonlinear differential equations are derived and transformed into state space representation. Experiments have been carried out on a test rig to identify the system parameters of the complete model. Static and dynamic simulation based optimizations are utilized for identification. The results are verified in time and frequency domain. Finally, the identified model provides a basis for later design of control strategies to reduce existing force variations.
Abstract: The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.
Abstract: In this work, efficient directional coupler composed of
dielectric waveguides and metallic film has been analyzed in details
by simulations using finite element method (FEM). The structure
consists of a step-index fiber with dielectric core, silica cladding, and
a metal nanowire parallel to the core. The results show that an
efficient conversion of optical dielectric modes to long range
plasmonic is possible. Low insertion losses in conjunction with short
coupling length and a broadband operation can be achieved under
certain conditions. This kind of couplers has potential applications for
the design of photonic integrated circuits for signal routing between
dielectric/plasmonic waveguides, sensing, lithography, and optical
storage systems. A high efficient focusing of light in a very small
region can be obtained.
Abstract: In order to reduce numerical computations in the
nonlinear dynamic analysis of seismically base-isolated structures, a
Mixed Explicit-Implicit time integration Method (MEIM) has been
proposed. Adopting the explicit conditionally stable central
difference method to compute the nonlinear response of the base
isolation system, and the implicit unconditionally stable Newmark’s
constant average acceleration method to determine the superstructure
linear response, the proposed MEIM, which is conditionally stable
due to the use of the central difference method, allows to avoid the
iterative procedure generally required by conventional monolithic
solution approaches within each time step of the analysis. The main
aim of this paper is to investigate the stability and computational
efficiency of the MEIM when employed to perform the nonlinear
time history analysis of base-isolated structures with sliding bearings.
Indeed, in this case, the critical time step could become smaller than
the one used to define accurately the earthquake excitation due to the
very high initial stiffness values of such devices. The numerical
results obtained from nonlinear dynamic analyses of a base-isolated
structure with a friction pendulum bearing system, performed by
using the proposed MEIM, are compared to those obtained adopting a
conventional monolithic solution approach, i.e. the implicit
unconditionally stable Newmark’s constant acceleration method
employed in conjunction with the iterative pseudo-force procedure.
According to the numerical results, in the presented numerical
application, the MEIM does not have stability problems being the
critical time step larger than the ground acceleration one despite of
the high initial stiffness of the friction pendulum bearings. In
addition, compared to the conventional monolithic solution approach,
the proposed algorithm preserves its computational efficiency even
when it is adopted to perform the nonlinear dynamic analysis using a
smaller time step.
Abstract: In this paper, an advanced Nonlinear Exponential
Model (NEM), able to simulate the uniaxial dynamic behavior of
seismic isolators having a continuously decreasing tangent stiffness
with increasing displacement in the relatively large displacements
range and a hardening or softening behavior at large displacements, is
presented. The mathematical model is validated by comparing the
experimental force-displacement hysteresis loops obtained during
cyclic tests, conducted on a helical wire rope isolator and a recycled
rubber-fiber reinforced bearing, with those predicted analytically.
Good agreement between the experimental and simulated results
shows that the proposed model can be an effective numerical tool to
predict the force-displacement relationship of seismic isolation
devices within the large displacements range. Compared to the
widely used Bouc-Wen model, unable to simulate the response of
seismic isolators at large displacements, the proposed one allows to
avoid the numerical solution of a first order nonlinear ordinary
differential equation for each time step of a nonlinear time history
analysis, thus reducing the computation effort. Furthermore, the
proposed model can simulate the smooth transition of the hysteresis
loops from small to large displacements by adopting only one set of
five parameters determined from the experimental hysteresis loops
having the largest amplitude.
Abstract: In this paper, a one-dimensional (1d) Parallel Elasto-
Plastic Model (PEPM), able to simulate the uniaxial dynamic
behavior of seismic isolators having a continuously decreasing
tangent stiffness with increasing displacement, is presented. The
parallel modeling concept is applied to discretize the continuously
decreasing tangent stiffness function, thus allowing to simulate the
dynamic behavior of seismic isolation bearings by putting linear
elastic and nonlinear elastic-perfectly plastic elements in parallel. The
mathematical model has been validated by comparing the
experimental force-displacement hysteresis loops, obtained testing a
helical wire rope isolator and a recycled rubber-fiber reinforced
bearing, with those predicted numerically. Good agreement between
the simulated and experimental results shows that the proposed
model can be an effective numerical tool to predict the forcedisplacement
relationship of seismic isolators within relatively large
displacements. Compared to the widely used Bouc-Wen model, the
proposed one allows to avoid the numerical solution of a first order
ordinary nonlinear differential equation for each time step of a
nonlinear time history analysis, thus reducing the computation effort,
and requires the evaluation of only three model parameters from
experimental tests, namely the initial tangent stiffness, the asymptotic
tangent stiffness, and a parameter defining the transition from the
initial to the asymptotic tangent stiffness.
Abstract: The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.