Abstract

The primary aim of the paper is to provide the guidance for railway engineers and operators to employ safety assessment approaches for safety design and maintenance railways. This will support the industry’s efforts to run the rail network with normal service while keeping risks as low as reasonably practicable (ALAPR). A secondary aim is to encourage railway engineers and managers to develop novel safety assessment and management approaches to improve railway safety performance. The methodologies described in this paper can not only be used in railways, but can be also used in design and maintenance for safety for other engineering products.

Abstract

This article discusses the structure of the manufacturing engineering education, in light of recent changes; rise of competitive markets and globalization. The discussion focuses on the technical skills and the outlining methodology needed to help the industrial enterprises cope with such changes. An integrated perspective on manufacturing education is presented in contrast to the classical, current treatment of manufacturing discipline.

Abstract

Nowadays virtual Instrumentation systems (Software based Instrumentation) are used in various fields, such as Business Core Transactions, Modern Cars, Automated Teller Machines (ATM), Aircraft Control Systems, Nuclear Power Plants, Manufacturing industries etc. In the modern buildings, it is very essential to predict the various parameters such as temperature, humidity, vibration, length, breadth and height accurately to control the various problems like acoustics, overload, over heat etc. The virtual Instrumentation technique is software based measurement and control system which is used to control the quality of products and processes. Here, it is proposed to identify the building parameters using various sensors. Then the signal conditioning is done by using various electronic principles. Then the analysis of various parameters is done by the software Lab VIEW. To measure the linear parameter such as Length, breadth and height of the buildings are done by using image processing technique. To identify these linear parameters, a high resolution camera is used to take a photograph of the building. Then the linear parameters are identified and analyzed using Image acquisition module which is available in Lab VIEW software. This method will give a high accurate measurement system and possess a highly reliable data and also provide a new direction in the area of building measurement.

Abstract

Any manufacturing system has to attain the key performance measures for its successful operation. Quality Function Deployment (QFD) is to convert the customer requirements into “quality characteristics” and develop a schedule for the jobs by systematically deploying the relationships between the due date and the completion time by adopting the just in time concept. A generalized model for analyzing the manufacturing system is essential to improve the performance measures. Non - traditional optimization technique such as Simulated Annealing (SA) technique provides a complete solution methodology for solving the shop floor scheduling problems. The problem considered in this study consists of identical and non-identical machines arranged in parallel. Jobs ranging from 10 to 100 are to be processed on the machines and the objective is to reduce the multiple objectives such as the earliness and the tardiness measures of the completed jobs. The proposed simulated annealing technique identifies the optimal sequences for the different weighted, earliness and tardiness combinations. It has been observed that the suggested optimization procedure arrives at the optimal solution at a reasonable computation time. The performance of the proposed method has been compared with the existing heuristics and is found to outperform it.

Abstract

Adequacy assessment of composite power system is a complex task, which involves the two aspects of power system analysis and practical considerations in selecting a system state. Monte Carlo Simulation is a technique currently used for power system composite reliability assessment due to its flexibility and the possibility of obtaining the probability distribution of variables of interest. In the present paper, three basic sampling techniques are employed using Monte Carlo Simulation and the Reliability Indices are computed for a 5-Bus Composite Power System and IEEE RTS 24-Bus System. The results are compared and discussed.

Abstract

Face recognition has a wide range of applications such as personal identification and authentication, criminal identification, security and surveillance, image and film processing, and human-computer interaction. Although many methods exist, this paper proposes recent face recognition using a dynamic programming algorithm for image recognition and classification. Method based on a new mapping network called wavelet-network namely Wavenet transform (WN). WN was employed to make approximation to the images before passing through the discrete wavelet transform decomposition to extract the image descriptive features. These features are used in the proposed image identification algorithm for enhancing the accuracy of recognition at pixel level and to minimize the additive cost function.

The proposed hybrid transform is based on the combination of the Wavenet (WN) and the Inverse Discrete Wavelet Transform (IDWT) followed by a Neural Network (NN) to be considered as feature extractor for the given image. In this paper the neural network (NN) classifier is combined with the wavelet transform. A reference set of 100 images are used and collected from different data images. This method gave an excellent and a successful identification rate of 99%.  Gaussian noise was added for further testing; the proposed algorithm for the same collected images and identification rate of 95% was achieved with level of up to 0.10.

The algorithm was implemented using MATLAB programming languages version 7.

Abstract

This paper introduces the main design principles and  methods for asynchronous VLSI systems, with an emphasis on Advanced Microcontroller Bus Architecture (AMBA) communication. SoC design will require asynchronous techniques as the large parameter variations across the chip will make it impossible to control delays in clock networks and other global signals efficiently. Initially, SoCs will be globally asynchronous and locally synchronous (GALS). But the complexity of the numerous asynchronous/synchronous interfaces required in a GALS will eventually lead to entirely asynchronous solutions. and synchronization. Asynchronous circuits with the only delay assumption of isochronic forks   are called quasi-delay-insensitive (QDI). The asynchronous design has been described and implemented to achieve high performance in comparison with the synchronous design. This implementation justifies the claimed performance through the Field Programmable  Gate Array (FPGA) implementation results. Experimental results show that the techniques are indeed effective for IP development/verification and fast prototyping. This technique will reduce the power consumption and improve the speed by at least 50% without big impact on the system performance.

Abstract

This paper proposes an observer based indirect adaptive sliding mode controller with neural networks for a certain class of unknown nonlinear dynamic systems. For these systems not all the state variables are available for measurements. To design the proposed controller, we first construct neural network models to describe system nonlinear dynamics. Then, an observer is employed to estimate the tracking error vector, and a neuro-sliding mode controller is developed to achieve the tracking performances. Adaptive laws are proposed to adjust parameters of neural models. The stability of the overall control system is analyzed based on the Lyapunov method. Simulation results illustrate the design procedures and show the tracking performance of the proposed controller in the presence of external disturbances.

Abstract

An eigendecomposition technique (Pisarenko technique) is used as a high resolution technique to model the holographic imaging (detecting) problem. Ultrasonic waves are used for imaging a buried object. The in-line holography is employed. The performance has been investigated for different values of signal to noise ratio(SNR). The results demonstrate the enhanced performance capability of the combination of Pisarenko and holographic methods. Also the method showed much better performance compared with Fourier transform.