MODARES TECHNICAL AND ENGINEERING
Year:2003 | Volume:- | Issue:13|Papers Count:16

An important task in the initial design stages of rapid-transit type systems or "metros" is the allocation of signals and control points. These are placed so as to achieve a specified minimum time-separation between trains (headway), whilst minimizing the amount of signaling equipment but maintaining the highest level of safety. Conventional signaling and control systems are based on the fixed-block principle, whereby the track (or guide way) is divided into sections of predetermined length. A train is only allowed to proceed into a block when that block and usually the next one is clear of traffic. With the moving-block concept, a train can follow a preceding train at a safe braking distance behind the tail of the train. In this paper, the transient performances of the two signaling systems are compared. A multi-train simulator which was originally developed at Birmingham University (U.K.) with a fixed-block algorithm, has been adopted and modified to accommodate the moving block algorithm. Both signaling systems were applied to Singapore Mass Transit Railway (MTR) and the results were compared in terms of train movement and transient performances including headway and station delay under safety and speed restrictions. Results have shown that with a pure moving-block system a considerable improvement in transient performance can be achieved.    

Logic analysis and attack construction methods are two major approaches in verification of cryptographic protocols. However, it is almost preferable to use both of them for a complete analysis. In this paper, a generic framework for the integration of the two verification approaches is presented. Using the framework we can propose analysis methods in which security properties and breach scenarios of the properties in a protocol can be verified in a unified manner. The focus on this paper is on a computational model of the protocols as the major component of the framework. The operational interpretation of the computational model with a term rewriting system (TRS) is presented too. To specify an intended protocol, we can represent it as a set of individual steps, and then using a transformation algorithm, a terminated and confluent TRS is generated automatically. This TRS is used to construct a special representation of the protocol named the protocol execution path, which can be used as the base of various verification schemes. Specification and verification of a sample protocol is presented too.      

Label switching technology is a flexible and high performance method for forwarding layer three packets that are mapped to layer two flows. Each label switch router, LSR, needs a specific label for every flow, where the number of labels depends on the mapping and granularity of flows. Data and control driven methods are the most significant and popular methods in label mapping policy. The above mentioned methods have been investigated. The possible pitfalls of each method are identified for an optimal operation and performance. One of the most significant difficulties is the rate of flows creation and deletion. This issue is vital in both scalability and implementation of networks and is more significant in data driven methods. In this paper, a new flow-Subnet Flow-has been proposed which increases the performance in data driven methods. The simulation results show fair improvement in performance and validity of the Subnet Flow.      

 In this paper we propose and simulate a new Heterostructure MESFET, Called δ-doped LDD HMESFET. To improve carrier velocity in vicinity of the source in channel of GaAs MESFET, one can replace source with AlxGa 1-x As. By increasing Al content, discontinuity of hetero-interface could be increased. Therefore, the velocity increases in the low field. However, increasing Al mole fraction in excess of some value forces the current to reduce, due to DX centers. To avoid this reduction, we suggest taking the advantage of δ-doped the source-channel hetero-interface. This increase discontinuity of hetero-interface, which is equivalent to increasing Al content. In this paper, we simulate the proposed transistor structure and compare it with the one proposed in [1], ignoring DX centers. In this comparison, we show that the average electron velocity in both transistors is identical.      

In this research using the theory of Induction Motor (UM), a UM with liquid as secondary part is planned and manufactured. The main objective for planning of this motor is to investigate the possibility of chemical liquids pumping such as liquid poison and acids. Results of many laboratory tests are shown to conclude that pumping force in the manufactured pump is dependent on many factors such as the magnetic characteristics of material of primary side and the electrical conductivity of liquid. In high magnetic permeability and high electrical conductivity, pumping force is fortified. Thus using the proposed method, pumps without mechanical moving parts can be manufactured      

Rotating machines in particular induction electrical machines are important industry instruments. In manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. In this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using motor vibration analysis. A three-phase induction motor with a special winding was used to create the faults artificially. The vibration signal of motor in different states such as working without fault, with various faults and with various loads was acquired. Some spectral analysis was done using the spectrum and the spectrograph of vibration signals and differences due to different states of motor were observed. Suitable features such as Linear Prediction Cepstral Coefficients and Fourier Transform Filter Bank Coefficients were extracted from vibration signals and were then applied to non-supervised (SOM) and supervised (LVQ) neural networks in order to classify motor faults and its load condition. Many experiments were conducted to evaluate the effect of neural network type, type and length of feature vector, length of training signal etc. In brief, using SOM and LVQ neural networks, 20 element Filter Bank feature vectors, and 600ms of the training data, performance of 93.6% and 94.2% were obtained for load and fault detection respectively.      

In this paper, behavior of teleoperation systems with modeling error and delay time error in Smith predictor is discussed. In teleoperation systems, modeling error is inevitable. This paper discusses stability of teleoperation systems with modeling error. First, error of delay time in teleoperation systems by using of Internet as communication channel is considered and the performance of Smith predictor in teleoperation systems with delay time error is discussed. Next, a new structure for teleoperation system is proposed. An adaptive filter is integrated into the new structure for determination of delay time in communication channel. The new structure augments wave variables and Smith predictor to provide an effective method for teleoperation systems. Along with the adaptive filter, this new structure is shown to overcome instability due to the variability of the delay times. Simulations results show significant improvements in the system performance.    

Future increase of mobile communication subscribers will require a great capacity expansion of the cellular systems. In order to accommodate the increasing number of subscribers, the cell size will have to be much smaller than current size. Therefore, it is predictable that the location updating and paging procedures will produce a major part of signaling traffic in these networks. This paper proposes a location management algorithm for cellular networks that dynamically extract the location and paging areas for every user, based on the user profile. The user profile contains the number of movements between cells and average duration spent in each visited cell. A mobility model is developed to simulate daily movements of the subscribers and used to compare the performance of the proposed dynamic algorithm with current strategy in GSM networks. The results of simulation indicate that the dynamic algorithms significantly outperform the static algorithm, in terms of total location management cost.      

Context-dependent modeling is a well-known approach to increase modeling accuracy in continuous speech recognition. The most common way to implement this approach is via triphone modeling. Nevertheless, the large number of such models results in several problems in model training, whilst the robust training of such models is often hardly obtained. One approach to solve this problem is via parameter tying. In this paper, clustering has been carried out on HMM state parameters and the states allocated to any cluster are tied to decrease the overall number of system parameters and achieve robust training. Two types of groupings, one based on the final trained model set parameters and their inter-model distances and the other based on the training data and a decision tree, have been carried out. In the implementation of the later, a decision tree based on the acoustic properties of the Persian (Farsi) language and the phonetic similarities and differences has been designed. The results obtained have shown the usefulness of both the approaches. However, the second approach has the advantage of making the estimation of unseen model parameters possible.