Abstract: Privacy of RFID systems is receiving increasing attention in the RFID community. RFID privacy is important as the RFID tags will be attached to all kinds of products and physical objects including people. The possible abuse or excessive use of RFID tracking capability by malicious users can lead to potential privacy violations. In this paper, we will discuss how the different industries use RFID and the potential privacy and security issues while RFID is implemented in these industries. Although RFID technology offers interesting services to customer and retailers, it could also endanger the privacy of end-users. Personal data can be leaked if a protection mechanism is not deployed in the RFID systems. The paper summarizes many different solutions for implementing privacy and security while deploying RFID systems.
Abstract: This paper presents a nonlinear differential model,
for a three-bladed horizontal axis wind turbine (HAWT) suited
for control applications. It is based on a 8-dofs, lumped
parameters structural dynamics coupled with a quasi-steady sectional
aerodynamics. In particular, using the Euler-Lagrange Equation
(Energetic Variation approach), the authors derive, and successively
validate, such model. For the derivation of the aerodynamic model,
the Greenbergs theory, an extension of the theory proposed by
Theodorsen to the case of thin airfoils undergoing pulsating flows,
is used. Specifically, in this work, the authors restricted that theory
under the hypothesis of low perturbation reduced frequency k,
which causes the lift deficiency function C(k) to be real and equal
to 1. Furthermore, the expressions of the aerodynamic loads are
obtained using the quasi-steady strip theory (Hodges and Ormiston),
as a function of the chordwise and normal components of relative
velocity between flow and airfoil Ut, Up, their derivatives, and
section angular velocity ε˙. For the validation of the proposed model,
the authors carried out open and closed-loop simulations of a 5
MW HAWT, characterized by radius R =61.5 m and by mean chord
c = 3 m, with a nominal angular velocity Ωn = 1.266rad/sec.
The first analysis performed is the steady state solution, where
a uniform wind Vw = 11.4 m/s is considered and a collective
pitch angle θ = 0.88◦ is imposed. During this step, the authors
noticed that the proposed model is intrinsically periodic due to
the effect of the wind and of the gravitational force. In order
to reject this periodic trend in the model dynamics, the authors
propose a collective repetitive control algorithm coupled with a PD
controller. In particular, when the reference command to be tracked
and/or the disturbance to be rejected are periodic signals with a
fixed period, the repetitive control strategies can be applied due to
their high precision, simple implementation and little performance
dependency on system parameters. The functional scheme of a
repetitive controller is quite simple and, given a periodic reference
command, is composed of a control block Crc(s) usually added
to an existing feedback control system. The control block contains
and a free time-delay system eτs in a positive feedback loop, and a
low-pass filter q(s). It should be noticed that, while the time delay
term reduces the stability margin, on the other hand the low pass
filter is added to ensure stability. It is worth noting that, in this
work, the authors propose a phase shifting for the controller and
the delay system has been modified as e^(−(T−γk)), where T is the
period of the signal and γk is a phase shifting of k samples of the
same periodic signal. It should be noticed that, the phase shifting
technique is particularly useful in non-minimum phase systems, such
as flexible structures. In fact, using the phase shifting, the iterative
algorithm could reach the convergence also at high frequencies.
Notice that, in our case study, the shifting of k samples depends
both on the rotor angular velocity Ω and on the rotor azimuth
angle Ψ: we refer to this controller as a spatial repetitive controller.
The collective repetitive controller has also been coupled with a C(s) = PD(s), in order to dampen oscillations of the blades.
The performance of the spatial repetitive controller is compared
with an industrial PI controller. In particular, starting from wind
speed velocity Vw = 11.4 m/s the controller is asked to maintain the
nominal angular velocity Ωn = 1.266rad/s after an instantaneous
increase of wind speed (Vw = 15 m/s). Then, a purely periodic
external disturbance is introduced in order to stress the capabilities
of the repetitive controller. The results of the simulations show that,
contrary to a simple PI controller, the spatial repetitive-PD controller
has the capability to reject both external disturbances and periodic
trend in the model dynamics. Finally, the nominal value of the
angular velocity is reached, in accordance with results obtained with
commercial software for a turbine of the same type.
Abstract: Manufacturing technologies are becoming continuously
more diversified over the years. The increasing use of robots for
various applications such as assembling, painting, welding has also
affected the field of machining. Machining robots can deal with
larger workspaces than conventional machine-tools at a lower cost
and thus represent a very promising alternative for machining
applications. Furthermore, their inherent structure ensures them a
great flexibility of motion to reach any location on the workpiece with
the desired orientation. Nevertheless, machining robots suffer from
a lack of stiffness at their joints restricting their use to applications
involving low cutting forces especially finishing operations. Vibratory
instabilities may also happen while machining and deteriorate the
precision leading to scrap parts. Some researchers are therefore
concerned with the identification of optimal parameters in robotic
machining. This paper continues the development of a virtual robotic
machining simulator in order to find optimized cutting parameters in
terms of depth of cut or feed per tooth for example. The simulation
environment combines an in-house milling routine (DyStaMill)
achieving the computation of cutting forces and material removal
with an in-house multibody library (EasyDyn) which is used to
build a dynamic model of a 3-DOF planar robot with flexible links.
The position of the robot end-effector submitted to milling forces is
controlled through an inverse kinematics scheme while controlling
the position of its joints separately. Each joint is actuated through
a servomotor for which the transfer function has been computed
in order to tune the corresponding controller. The output results
feature the evolution of the cutting forces when the robot structure
is deformable or not and the tracking errors of the end-effector.
Illustrations of the resulting machined surfaces are also presented.
The consideration of the links flexibility has highlighted an increase
of the cutting forces magnitude. This proof of concept will aim
to enrich the database of results in robotic machining for potential
improvements in production.
Abstract: Mobile augmented reality (MAR) tracking targets from the surroundings and aids operators for interactive data and procedures visualization, potential equipment and system understandably. Operators remotely communicate and coordinate with each other for the continuous tasks, information and data exchange between control room and work-site. In the routine work, distributed control system (DCS) monitoring and work-site manipulation require operators interact in real-time manners. The critical question is the improvement of user experience in cooperative works through applying Augmented Reality in the traditional industrial field. The purpose of this exploratory study is to find the cognitive model for the multiple task performance by MAR. In particular, the focus will be on the comparison between different tasks and environment factors which influence information processing. Three experiments use interface and interaction design, the content of start-up, maintenance and stop embedded in the mobile application. With the evaluation criteria of time demands and human errors, and analysis of the mental process and the behavior action during the multiple tasks, heuristic evaluation was used to find the operators performance with different situation factors, and record the information processing in recognition, interpretation, judgment and reasoning. The research will find the functional properties of MAR and constrain the development of the cognitive model. Conclusions can be drawn that suggest MAR is easy to use and useful for operators in the remote collaborative works.
Abstract: Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.
Abstract: There is great attention being paid in the field of development of first reading, thus early literacy skills in the Czech Republic. Yet inconclusive results of PISA and PIRLS force us to think over the teacher´s work, his/her roles in the education process and methods and forms used in lessons. There is also a significant importance to monitor the family environment and the pupil, themselves. The aim of the publishing output is to focus on one side dealing with methods of practicing reading technique and their results in the process of comprehension. In the first part of the contribution there are the goals of development of reading literacy and the methods used in reading practice in some EU countries and a follow-up comparison of research implemented by the help of modern technology of an eye tracker device in the year 2015 and a research conducted at the Institute of Education and Psychological Counselling of the Czech Republic in the year 2011/12. These are the results of a diagnostic test of reading in first classes of primary schools, taught by the genetic method and analytic-synthetic method. The results show that in the first stage of practice there are no statistically significant differences between any researched subjects taught by different methods of reading practice (with the use of several diagnostic texts focused on reading technique and its comprehension). Different results are shown at the end of Grade One and during Grade Two of primary school.
Abstract: The ionization yield of ion tracks in polymers and bio-molecular systems reaches a maximum, known as the Bragg peak, close to the end of the ion trajectories. Along the path of the ions through the materials, many electrons are generated, which produce a cascade of further ionizations and, consequently, a shower of secondary electrons. Among these, very low energy secondary electrons can produce damage in the biomolecules by dissociative electron attachment. This work deals with the calculation of the energy distribution of electrons produced by protons in a sample of polymethylmethacrylate (PMMA), a material that is used as a phantom for living tissues in hadron therapy. PMMA is also of relevance for microelectronics in CMOS technologies and as a photoresist mask in electron beam lithography. We present a Monte Carlo code that, starting from a realistic description of the energy distribution of the electrons ejected by protons moving through PMMA, simulates the entire cascade of generated secondary electrons. By following in detail the motion of all these electrons, we find the radial distribution of the energy that they deposit in PMMA for several initial proton energies characteristic of the Bragg peak.
Abstract: This paper presents a tracking control strategy based on Lyapunov approach for nonholonomic wheeled mobile robot. This control strategy consists of two levels. First, a kinematic controller is developed to adjust the right and left wheel velocities. Using this velocity control law, the stability of the tracking error is guaranteed using Lyapunov approach. This kinematic controller cannot be generated directly by the motors. To overcome this problem, the second level of the controllers, dynamic control, is designed. This dynamic control law is developed based on Lyapunov theory in order to track the desired trajectories of the mobile robot. The stability of the tracking error is proved using Lupunov and Barbalat approaches. Simulation results on a nonholonomic wheeled mobile robot are given to demonstrate the feasibility and effectiveness of the presented approach.
Abstract: This paper investigates and presents a cable-driven
robot to lower limb rehabilitation use in sagittal plane. The presented
rehabilitation robot is used for a trajectory tracking in joint space.
The paper covers kinematic and dynamic analysis, which reveals
the tensionability of the used cables as being the actuating source
to provide a rehabilitation exercises of the human leg. The desired
trajectory is generated to be used in the control system design in joint
space. The obtained simulation results is showed to be efficient in
this kind of application.
Abstract: A Fourier series based learning control (FSBLC)
algorithm for tracking trajectories of mechanical systems with
unknown nonlinearities is presented. Two processes are introduced to
which the FSBLC with PD controller is applied. One is a simplified
service robot capable of climbing stairs due to special wheels and
the other is a propeller driven pendulum with nearly the same
requirements on control. Additionally to the investigation of learning
the feed forward for the desired trajectories some considerations on
the implementation of such an algorithm on low cost microcontroller
hardware are made. Simulations of the service robot as well as
practical experiments on the pendulum show the capability of the used
FSBLC algorithm to perform the task of improving control behavior
for repetitive task of such mechanical systems.
Abstract: In this paper, a drift assist control system is proposed for remote control (RC) cars to get the perfect drift angle. A steering servo control scheme is given powerfully to assist the drift driving. A gyroscope sensor is included to detect the machine's tail sliding and to achieve a better automatic counter-steering to prevent RC car from spinning. To analysis tire traction and vehicle dynamics is used to obtain the dynamic track of RC cars. It comes with a control gain to adjust counter-steering amount according to the sensor condition. An illustrated example of 1:10 RC drift car is given and the real-time control algorithm is realized by Arduino Uno.
Abstract: A repetitive training movement is an efficient method
to improve the ability and movement performance of stroke survivors
and help them to recover their lost motor function and acquire new
skills. The ETS-MARSE is seven degrees of freedom (DOF)
exoskeleton robot developed to be worn on the lateral side of the
right upper-extremity to assist and rehabilitate the patients with
upper-extremity dysfunction resulting from stroke. Practically,
rehabilitation activities are repetitive tasks, which make the
assistive/robotic systems to suffer from repetitive/periodic
uncertainties and external perturbations induced by the high-order
dynamic model (seven DOF) and interaction with human muscle
which impact on the tracking performance and even on the stability
of the exoskeleton. To ensure the robustness and the stability of the
robot, a new nonlinear backstepping control was implemented with
designed tests performed by healthy subjects. In order to limit and to
reject the periodic/repetitive disturbances, an iterative estimator was
integrated into the control of the system. The estimator does not need
the precise dynamic model of the exoskeleton. Experimental results
confirm the robustness and accuracy of the controller performance to
deal with the external perturbation, and the effectiveness of the
iterative estimator to reject the repetitive/periodic disturbances.
Abstract: In this paper, a method for maximum power point tracking of a photovoltaic energy conversion system is presented. This method is based on using the difference between the power from the solar panel and an estimated power value to control the DC-DC converter of the photovoltaic system. The difference is continuously compared with a preset error permitted value. If the power difference is more than the error, the estimated power is multiplied by a factor and the operation is repeated until the difference is less or equal to the threshold error. The difference in power will be used to trigger a DC-DC boost converter in order to raise the voltage to where the maximum power point is achieved. The proposed method was experimentally verified through a PV energy conversion system driven by the OPAL-RT real time controller. The method was tested on varying radiation conditions and load requirements, and the Photovoltaic Panel was operated at its maximum power in different conditions of irradiation.
Abstract: In this paper, type-2 fuzzy logic control (T2FLC) and neuro-fuzzy control (NFC) for a doubly fed induction generator (DFIG) based on direct power control (DPC) with a fixed switching frequency is proposed for wind generation application. First, a mathematical model of the doubly-fed induction generator implemented in d-q reference frame is achieved. Then, a DPC algorithm approach for controlling active and reactive power of DFIG via fixed switching frequency is incorporated using PID. The performance of T2FLC and NFC, which is based on the DPC algorithm, are investigated and compared to those obtained from the PID controller. Finally, simulation results demonstrate that the NFC is more robust, superior dynamic performance for wind power generation system applications.
Abstract: Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.
Abstract: In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.
Abstract: Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.
Abstract: Self-driving vehicle require a high level of situational
awareness in order to maneuver safely when driving in real world
condition. This paper presents a LiDAR based real time perception
system that is able to process sensor raw data for multiple target
detection and tracking in dynamic environment. The proposed
algorithm is nonparametric and deterministic that is no assumptions
and priori knowledge are needed from the input data and no
initializations are required. Additionally, the proposed method is
working on the three-dimensional data directly generated by LiDAR
while not scarifying the rich information contained in the domain of
3D. Moreover, a fast and efficient for real time clustering algorithm
is applied based on a radially bounded nearest neighbor (RBNN).
Hungarian algorithm procedure and adaptive Kalman filtering are
used for data association and tracking algorithm. The proposed
algorithm is able to run in real time with average run time of 70ms
per frame.
Abstract: In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.
Abstract: In this work, we present a Bayesian non-parametric
approach to model the motion control of ATVs. The motion control
model is based on a Dirichlet Process-Gaussian Process (DP-GP)
mixture model. The DP-GP mixture model provides a flexible
representation of patterns of control manoeuvres along trajectories
of different lengths and discretizations. The model also estimates the
number of patterns, sufficient for modeling the dynamics of the ATV.