Abstract: This paper presents a novel method that allows an
agent host to delegate its signing power to an anonymous mobile
agent in such away that the mobile agent does not reveal any information about its host-s identity and, at the same time, can be authenticated by the service host, hence, ensuring fairness of service
provision. The solution introduces a verification server to verify the
signature generated by the mobile agent in such a way that even if colluding with the service host, both parties will not get more information than what they already have. The solution incorporates
three methods: Agent Signature Key Generation method, Agent
Signature Generation method, Agent Signature Verification method.
The most notable feature of the solution is that, in addition to allowing secure and anonymous signature delegation, it enables
tracking of malicious mobile agents when a service host is attacked. The security properties of the proposed solution are analyzed, and the solution is compared with the most related work.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: A novel adaptive fuzzy trajectory tracking algorithm of Stewart platform based motion platform is proposed to compensate path deviation and degradation of controller-s performance due to actuator torque limit. The algorithm can be divided into two parts: the real-time trajectory shaping part and the joint space adaptive fuzzy controller part. For a reference trajectory in task space whenever any of the actuators is saturated, the desired acceleration of the reference trajectory is modified on-line by using dynamic model of motion platform. Meanwhile an additional action with respect to the difference between the nominal and modified trajectories is utilized in the non-saturated region of actuators to reduce the path error. Using modified trajectory as input, the joint space controller incorporates compute torque controller, leg velocity observer and fuzzy disturbance observer with saturation compensation. It can ensure stability and tracking performance of controller in present of external disturbance and position only measurement. Simulation results verify the effectiveness of proposed control scheme.
Abstract: This paper evaluates the performance of a novel
algorithm for tracking of a mobile node, interms of execution time
and root mean square error (RMSE). Particle Filter algorithm is used
to track the mobile node, however a new technique in particle filter
algorithm is also proposed to reduce the execution time. The
stationary points were calculated through trilateration and finally by
averaging the number of points collected for a specific time, whereas
tracking is done through trilateration as well as particle filter
algorithm. Wi-Fi signal is used to get initial guess of the position of
mobile node in x-y coordinates system. Commercially available
software “Wireless Mon" was used to read the WiFi signal strength
from the WiFi card. Visual Cµ version 6 was used to interact with
this software to read only the required data from the log-file
generated by “Wireless Mon" software. Results are evaluated through
mathematical modeling and MATLAB simulation.
Abstract: Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.
Abstract: An Advance Driver Assistance System (ADAS) is a computer system on board a vehicle which is used to reduce the risk of vehicular accidents by monitoring factors relating to the driver, vehicle and environment and taking some action when a risk is identified. Much work has been done on assessing vehicle and environmental state but there is still comparatively little published work that tackles the problem of driver state. Visual attention is one such driver state. In fact, some researchers claim that lack of attention is the main cause of accidents as factors such as fatigue, alcohol or drug use, distraction and speeding all impair the driver-s capacity to pay attention to the vehicle and road conditions [1]. This seems to imply that the main cause of accidents is inappropriate driver behaviour in cases where the driver is not giving full attention while driving. The work presented in this paper proposes an ADAS system which uses an image based template matching algorithm to detect if a driver is failing to observe particular windscreen cells. This is achieved by dividing the windscreen into 24 uniform cells (4 rows of 6 columns) and matching video images of the driver-s left eye with eye-gesture templates drawn from images of the driver looking at the centre of each windscreen cell. The main contribution of this paper is to assess the accuracy of this approach using Receiver Operating Characteristic analysis. The results of our evaluation give a sensitivity value of 84.3% and a specificity value of 85.0% for the eye-gesture template approach indicating that it may be useful for driver point of regard determinations.
Abstract: We propose an integral tracking control method for a piezoelectric actuator system. The proposed method achieves the output tracking without requiring any hysteresis observer or schemes to compensate the hysteresis effect. With the proposed control law, the system is converted into the standard singularly perturbed model. Using Tikhonov-s theorem, we guarantee that the tracking error can be reduced to arbitrarily small bound. A numerical example is given to illustrate the effectiveness of our proposed method.
Abstract: This paper presents a robust proportionalderivative
(PD) based cerebellar model articulation
controller (CMAC) for vertical take-off and landing flight
control systems. Successful on-line training and recalling
process of CMAC accompanying the PD controller is
developed. The advantage of the proposed method is mainly
the robust tracking performance against aerodynamic
parametric variation and external wind gust. The
effectiveness of the proposed algorithm is validated through
the application of a vertical takeoff and landing aircraft
control system.
Abstract: GSM has undoubtedly become the most widespread
cellular technology and has established itself as one of the most
promising technology in wireless communication. The next
generation of mobile telephones had also become more powerful and
innovative in a way that new services related to the user-s location
will arise. Other than the 911 requirements for emergency location
initiated by the Federal Communication Commission (FCC) of the
United States, GSM positioning can be highly integrated in cellular
communication technology for commercial use. However, GSM
positioning is facing many challenges. Issues like accuracy,
availability, reliability and suitable cost render the development and
implementation of GSM positioning a challenging task. In this paper,
we investigate the optimal mobile position tracking means. We
employ an innovative scheme by integrating the Kalman filter in the
localization process especially that it has great tracking
characteristics. When tracking in two dimensions, Kalman filter is
very powerful due to its reliable performance as it supports
estimation of past, present, and future states, even when performing
in unknown environments. We show that enhanced position tracking
results is achieved when implementing the Kalman filter for GSM
tracking.
Abstract: This paper is focused on issues of process modeling
and two model based control strategies of a fed-batch sugar
crystallization process applying the concept of artificial neural
networks (ANNs). The control objective is to force the operation into
following optimal supersaturation trajectory. It is achieved by
manipulating the feed flow rate of sugar liquor/syrup, considered as
the control input. The control task is rather challenging due to the
strong nonlinearity of the process dynamics and variations in the
crystallization kinetics. Two control alternatives are considered –
model predictive control (MPC) and feedback linearizing control
(FLC). Adequate ANN process models are first built as part of the
controller structures. MPC algorithm outperforms the FLC approach
with respect to satisfactory reference tracking and smooth control
action. However, the MPC is computationally much more involved
since it requires an online numerical optimization, while for the FLC
an analytical control solution was determined.
Abstract: This study presents a novel means of designing a simple and effective torque controller for Permanent Magnet Synchronous Motor (PMSM). The overall stability of the system is shown using Lyapunov technique. The Lyapunov functions used contain a term penalizing the integral of the tracking error, enhancing the stability. The tracking error is shown to be globally uniformly bounded. Simulation results are presented to show the effectiveness of the approach.
Abstract: This paper proposes the method combining artificial neural network with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. With the measurements of wind speed, rotor speed of wind generator and output power, the artificial neural network can be trained and the wind speed can be estimated. The proposed control system in this paper provides a manner for searching the maximum output power of wind generator even under the conditions of varying wind speed and load impedance.
Abstract: The tracking allows to detect the tumor affections of cervical cancer, it is particularly complex and consuming time, because it consists in seeking some abnormal cells among a cluster of normal cells. In this paper, we present our proposed computer system for helping the doctors in tracking the cervical cancer. Knowing that the diagnosis of the malignancy is based in the set of atypical morphological details of all cells, herein, we present an unsupervised genetic algorithm for the separation of cell components since the diagnosis is doing by analysis of the core and the cytoplasm. We give also the various algorithms used for computing the morphological characteristics of cells (Ratio core/cytoplasm, cellular deformity, ...) necessary for the recognition of illness.
Abstract: This paper analysis the integrated use of safety monitoring with the domestic and international latest research on rail safety protection system, and focus on the implementation of an organic whole system, with the monitoring and early warning, risk assessment, predictive control and emergency rescue system. The system framework, contents and system structure of Security system is proposed completely. It-s pointed out that the Security system is a negative feedback system composed of by safety monitoring and warning system, risk assessment and emergency rescue system. Safety monitoring and warning system focus on the monitoring target monitoring, early warning, tracking, integration of decision-making, for objective and subjective risks factors. Risk assessment system analysis the occurrence of a major Security risk mechanism, determines the standard of the future short, medium and long term safety conditions, and give prop for development of safety indicators, accident analysis and safety standards. Emergency rescue system is with the goal of rapid and effective rescue work for accident, to minimize casualties and property losses.
Abstract: This paper describes WiPoD (Wireless Position
Detector) which is a pure software based location determination and
tracking (positioning) system. It uses empirical signal strength measurements from different wireless access points for mobile user
positioning. It is designed to determine the location of users having
802.11 enabled mobile devices in an 802.11 WLAN infrastructure
and track them in real time. WiPoD is the first main module in our
LBS (Location Based Services) framework. We tested K-Nearest
Neighbor and Triangulation algorithms to estimate the position of a
mobile user. We also give the analysis results of these algorithms for
real time operations. In this paper, we propose a supportable, i.e.
understandable, maintainable, scalable and portable wireless
positioning system architecture for an LBS framework. The WiPoD
software has a multithreaded structure and was designed and implemented with paying attention to supportability features and real-time constraints and using object oriented design principles. We also describe the real-time software design issues of a wireless positioning system which will be part of an LBS framework.
Abstract: The number of intrusions and attacks against critical
infrastructures and other information networks is increasing rapidly.
While there is no identified evidence that terrorist organizations are
currently planning a coordinated attack against the vulnerabilities of
computer systems and network connected to critical infrastructure,
and origins of the indiscriminate cyber attacks that infect computers
on network remain largely unknown. The growing trend toward the
use of more automated and menacing attack tools has also
overwhelmed some of the current methodologies used for tracking
cyber attacks. There is an ample possibility that this kind of cyber
attacks can be transform to cyberterrorism caused by illegal purposes.
Cyberterrorism is a matter of vital importance to national welfare.
Therefore, each countries and organizations have to take a proper
measure to meet the situation and consider effective legislation about
cyberterrorism.
Abstract: The ability to recognize humans and their activities by computer vision is a very important task, with many potential application. Study of human motion analysis is related to several research areas of computer vision such as the motion capture, detection, tracking and segmentation of people. In this paper, we describe a segmentation method for extracting human body contour in modified HLS color space. To estimate a background, the modified HLS color space is proposed, and the background features are estimated by using the HLS color components. Here, the large amount of human dataset, which was collected from DV cameras, is pre-processed. The human body and its contour is successfully extracted from the image sequences.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.
Abstract: This paper is focused on issues of nonlinear dynamic process modeling and model-based predictive control of a fed-batch sugar crystallization process applying the concept of artificial neural networks as computational tools. The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. A feed forward neural network (FFNN) model of the process is first built as part of the controller structure to predict the process response over a specified (prediction) horizon. The predictions are supplied to an optimization procedure to determine the values of the control action over a specified (control) horizon that minimizes a predefined performance index. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. However, the simulation results demonstrated smooth behavior of the control actions and satisfactory reference tracking.
Abstract: In this paper we present the algorithm which allows
us to have an object tracking close to real time in Full HD videos.
The frame rate (FR) of a video stream is considered to be between
5 and 30 frames per second. The real time track building will be
achieved if the algorithm can follow 5 or more frames per second. The
principle idea is to use fast algorithms when doing preprocessing to
obtain the key points and track them after. The procedure of matching
points during assignment is hardly dependent on the number of points.
Because of this we have to limit pointed number of points using the
most informative of them.