The anti-collision mechanism is an important part of RFID systems. Many algorithms were proposed in the literature, but most of them were designed based on the theory of Random Access (RA) systems. In this article, we...
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The anti-collision mechanism is an important part of RFID systems. Many algorithms were proposed in the literature, but most of them were designed based on the theory of Random Access (RA) systems. In this article, we review the various types of anti-collision systems and their corresponding algorithms. Different reading strategies are critically analyzed and compared by computer simulation. By comparing the different working mechanisms of RA and RFID systems, we show that a new theory is needed for the design and analysis of RFID anti-collision algorithm.
Fractal point processes have a potentially important role to play in the modeling of a wide range of natural and manmade phenomena. However, the lack of a suitable framework for their representation has frequently mad...
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Fractal point processes have a potentially important role to play in the modeling of a wide range of natural and manmade phenomena. However, the lack of a suitable framework for their representation has frequently made their application in many problems difficult. We introduce natural multiscale representations for an important class of these processes based on mixtures of Poisson processes. In turn, this framework leads to efficient new algorithms for both the synthesis and the analysis of such processes. These include algorithms for optimal fractal dimension and interarrival time estimation that are of interest in a range of applications. Several aspects of the performance of these algorithms are also addressed.
A simple, two-dimensional ray tracing scheme is developed and is applied to several propagation problems of importance to over-the-horizon radar. In particular, it is used as the basis of schemes for the simulation of...
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A simple, two-dimensional ray tracing scheme is developed and is applied to several propagation problems of importance to over-the-horizon radar. In particular, it is used as the basis of schemes for the simulation of oblique and backscatter ionograms. The efficiency of the scheme makes it ideal for applications where fast calculations are required, and an algorithm for inverting backscatter ionogram leading edges is developed as a particular example.
Methods are developed for design of electrical impedance tomographic reconstruction algorithms with specified properties. Assuming a starting model with constant conductivity or some other specified background distrib...
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Methods are developed for design of electrical impedance tomographic reconstruction algorithms with specified properties. Assuming a starting model with constant conductivity or some other specified background distribution, an algorithm with the following properties is found. 1) The optimum constant for the starting model is determined automatically. 2) The weighted least-squares error between the predicted and measured power dissipation data is as small as possible. 3) The variance of the reconstructed conductivity from the starting model is minimized. 4) Potential distributions with the largest volume integral of gradient squared have the least influence on the reconstructed conductivity, and therefore distributions most likely to be corrupted by contact impedance effects are deemphasized. 5) Cells that dissipate the most power during the current injection tests tend to deviate least from the background value. The resulting algorithm maps the reconstruction problem into a vector space where the contribution to the inversion from the background conductivity remains invariant, while the optimum contributions in orthogonal directions are found. For a starting model with nonconstant conductivity, the reconstruction algorithm has analogous properties.
We discuss a novel model for analyzing the working of Genetic algorithms (GA's), when the objective function is a function of unitation. The model is exact (not approximate), and is valid for infinite populations,...
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We discuss a novel model for analyzing the working of Genetic algorithms (GA's), when the objective function is a function of unitation. The model is exact (not approximate), and is valid for infinite populations, Functions of unitation depend only on the number of 1's in any string, Hence, we only need to model the variations in the distribution of strings with respect to the number of 1's in the strings, We introduce the notion of a Binomial Distributed Population (BDP) as the building block of our model, and we show that the effect of uniform crossover on BDP's is to generate two other BDP's, We demonstrate that a population with any general distribution may be decomposed into several BDP's, We also show that a general multipoint crossover may be considered as a composition of several uniform crossovers, Based on these results, the effects of mutation and crossover on the distribution of strings have been characterized, and the model has been defined, GASIM - a Genetic algorithm Simulator for functions of unitation - has been implemented based on the model, and the exactness of the results obtained from GASIM has been verified using actual Genetic algorithm runs, The time complexity of the GA simulator derived from the model is O(l(3)) (where l is the string length), a significant improvement over previous models with exponential time complexities, As an application of GASIM, we have analyzed the effect of crossover rate on deception in trap functions, a class of deceptive functions of unitation, We have obtained interesting results - we are led to believe that increasing values of pc, the crossover rate, increase the probability of the GA converging to the local optimum of the trap function.
This paper demonstrates how the accuracy, speed and flexibility of FDTD analysis may be improved for the modelling of MMIC structures. Correction factors, obtained from the known behavior of static fields close to dis...
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This paper demonstrates how the accuracy, speed and flexibility of FDTD analysis may be improved for the modelling of MMIC structures. Correction factors, obtained from the known behavior of static fields close to discontinuities, may be incorporated into the algorithm for application in the regions of high field variation where errors would otherwise occur. Application is made to both enclosed and open microstrip structures.
The control of communication networks is an important aspect from both the service provider and user points of view. There are several approaches to communication network control including game theory, genetic algorit...
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The control of communication networks is an important aspect from both the service provider and user points of view. There are several approaches to communication network control including game theory, genetic algorithms and Markov decision processes. Data mining methods have been successfully used to discover optimized solutions to this problem, and have the capability to learn the network behavior under different network conditions and during operation so that complete knowledge of the network behavior is not required a priori. This article identifies the concepts behind the idea of using data mining for communication network control, provides a structured survey of the results in this area, and discusses the guidelines for future applications.
In order to solve the "minimum trap" of Artificial Potential Field and the limitation of traditional path planning algorithm in dynamic obstacle environment, a path planning algorithm based on improved artif...
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In order to solve the "minimum trap" of Artificial Potential Field and the limitation of traditional path planning algorithm in dynamic obstacle environment, a path planning algorithm based on improved artificial potential field is proposed. Firstly, a virtual potential field detection circle model (VPFDCM) with adjustable radius is proposed to detect the "minimum trap" formed by the repulsion field of obstacles in advance. And the motion model of unmanned vehicle is established. Combined with the improved reinforcement learning algorithm based on Long Short-Term Memory(LSTM), the radius of virtual potential field detection circle is adjusted to achieve effective avoidance of dynamic obstacles. The reliable online collision free path planning of unmanned vehicle in semi closed dynamic obstacle environment is realized. Finally, the reliability and robustness of the algorithm are verified by MATLAB simulation. The simulation results show that the improved artificial potential field can effectively solve the problem of unmanned vehicle falling into the "minimum trap" and improve the reliability of unmanned vehicle movement. Compared with the traditional artificial potential field method, the improved artificial potential field method can achieve more than 90% success rate in obstacle avoidance.
Most electric motor predictive maintenance methods have drawbacks that limit their effectiveness in the mining environment, The U.S. Bureau of Mines (USBM) is developing an alternative approach to detect winding insul...
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Most electric motor predictive maintenance methods have drawbacks that limit their effectiveness in the mining environment, The U.S. Bureau of Mines (USBM) is developing an alternative approach to detect winding insulation breakdown in advance of complete motor failure. In order to evaluate the analysisalgorithms necessary for this approach, the USBM has designed and installed a system to monitor 120 electric motors in a coal preparation plant, The computer-based experimental system continuously gathers, stores, and analyzes electrical parameters for each motor. The results are then correlated to data from conventional motor-maintenance methods and in-service failures to determine if tile analysisalgorithms can detect signs of insulation deterioration and impending failure, This paper explains the on-line testing approach used in this research, and describes monitoring system design and implementation. At this writing data analysis is underway, but conclusive results are not yet available.
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