Abstract

The demand for efficient and reliable high rate communication is ever increasing. In recent years orthogonal frequency division multiplexing (OFDM) has gone from a promising data transmission technique. In this paper we present a technique for  carrier frequency offsets (CFOs) estimation in OFDM systems that is based on locating the spectral minimas within so-called null or virtual subcarriers embedded in the spectrum. The spectral minimas are found iteratively over a number of symbols and is therefore mainly useful for frequency offset tracking or in systems where an estimate is not immediately required. A goal for many years has been to be able to implement as much as possible of a radio system in the digital domain, the ultimate goal being so called software defined radio (SDR).

Abstract

This paper presents a simple novel technique, where the formulation for radiation characteristic of an array antenna is carried out and plotted using a simplified computer simulation modeling of the field pattern.

The pattern of an array antenna can be designed and directed by controlling the spacing between the array elements and the excitation phase difference. The proposed algorithm plots the field pattern of the array antenna in polar and rectangular coordinates under different operating conditions. Typical field patterns are obtained in which the array antenna has a maximum radiation in certain direction and minimum radiation (nearly null) in the other directions. This simple technique is also capable of  determining the field pattern for different types of array antennas with sidelob cancellation.

Abstract

A computer aided design (CAD) using optimization methods for the ion optical system has been developed, by mixing the dynamic programming procedure and artificial intelligence technique. CADION ANALYZER has been designed as an expert system, written in Java expert system shell (JESS 6.1) and Visual Basic 6 (VB6) for optimizing and analyzing full calculation processes. By using this rule based engine, the optimized axial potential distributions for electrostatic fields under imposed constraints have been used in the optical column setup. Spot size measurements were calculated in nano scales, which have values closed to (3.0) nm applicable in nano technology applications.

Abstract

A theoretical model was developed to evaluate the performance, characteristics and combustion parameters of vegetable oil esters like Jatropha, Mahua and Neem Oil esters. The predicted results of these fuels are compared with result of diesel fuel. The vegetable oil esters are produced   by transesterification method. In this process, the raw vegetable oil reacts with methanol and forms esterified vegetable oil in the presence of NaOH (or) KOH that acts as a catalyst. A four zone model based on the existing two zone model is developed to predict the pressures, various zone temperatures and volumes at various crank angle positions. The combustion characteristics and performance parameters such as heat release, heat transfer, work done, mean effective pressure, thermal efficiency, specific fuel consumption and power are predicted for different vegetable oil esters and for various engine conditions such as injection timing, spray cone angle and load conditions. The maximum performance is predicted for all fuels at an optimum engine conditions. The optimum engine conditions include three fourth of load, injection timing of 14oBTDC, spray cone angle of 18o. From the predicted results, the heat release and work done are reduced by about 5% for Jatropha, 19% for Mahua and 25% for Neem oil esters when compared to diesel. There is a slight drop in the values of pressure, thermal efficiency, power and mean effective pressure for vegetable oil esters when compared to diesel.  However SFC shows an increase. The performance is considerably increased with respect to increase of cone angle from 14o to 20o. The optimum performance is found at cone angle of 18o for all fuels. From the investigation, it is concluded that performance of vegetable oil esters such as Jatropha, Mahua and Neem oil esters are in good agreement with diesel performance at optimum engine conditions.  Thus the developed model is highly compatible for simulation work with bio diesel as an alternative fuel.

Abstract

Many steganographic techniques are extremely vulnerable to attacks, and even detection of the information in the image file is quite easy. So a microcontroller is used for the sake of security where it transmits a pre-programmed password at the beginning of each process. The steganalysis algorithm continued only if the received password is correct at the destination otherwise retrieving the secure information from the cover image is impossible.

Abstract

The accuracy of the speaker identification systems is degraded in the adverse acoustical environments by different kinds of interferences in the speech being input to the system. This corrupted speech contains portions, which are usable towards improvement in speaker identification. Usable speech is a novel concept of processing degraded speech data where the idea is to identify and extract these usable portions of degraded speech; as traditionally established by Spectral Autocorrelation Peak Valley Ratio (SAPVR) and Adjacent Peak Period Comparison (APPC). Unfortunately, the above-mentioned measures only detect about 74% usable speech with 26% false alarms. However, Usable speech has a harmonic structure whereas unusable speech has a noise-like structure. The information about the harmonics can be obtained using the ESPRIT (estimation of signal parameters via rotational invariance technique) short-time spectral envelope of the speech signal. The dominant peaks in the short-time spectra are the harmonic power for that spectral envelope. Consequently, the harmonic power originating from the periodic source is higher compared to the aperiodic unstructured source. This paper shows that this harmonic model-based usable speech approach has 82% success in identifying the usable speech frames with 18% false alarms.

Abstract

Image fusion is the process of   producing a single image from a set of input images. The fused image should have more complete information which is more useful for human or machine perception. The fusion of images is an important  technique  within many desperate fields such as remote sensing, robotics, manufacturing, intelligent Systems, medical applications etc. With the evolution of imaging technology, an increasing number of image modalities becomes available such as CT, SPECT, PET, MRI etc. Each modality has its strengths and weakness. For example, SPECT is able to image functional behavior of organs but has low resolution with diffuse boundaries. Because of this it is difficult to identify specific organs or tissues. On the other hand, X-ray Computed Tomography (CT) and MRI provide images with high resolution and sharp boundary information. To preserve all the complementary informations provided by different modalities in a single image, image fusion is performed, which is useful for human visual and machine perception and for better data interpretation.

An intensity based fusion method is  developed using JAVA for fusing multimodal medical images. This fusion method are applicable for fusing images that is obtained from two different modalities (Computer Tomograhy- CT and magnetic resonance imaging (MRI). This image fusion software reads two   images and combines them into a single highly informative image with maximum content.. The program is tested using CT-MRI images that is fused using  methods like wavelet pyramid, fast point based fusion using matlab platform etc.

Abstract

This paper describes the artificial  neural  network application to short term load forecasting of an electrical utility. Load forecasting plays an important role in power system operation, planning and control. It has long been recognized that accurate short term load forecast represents a great savings potential for electric utility corporations. Various approaches like time series, regression, expert systems and artificial neural networks have been envisaged in power system operation. A case study using  ANN based load forecasting was developed. The capability of Back Propagation algorithm and Kohonen Network have been applied for load forecasting. The performance of the above two methods is tested with the data obtained from Tamilnadu Electricity Board. The design procedure are demonstrated and a sample results are presented.

Abstract

Conventional Solar charge controllers have many drawbacks. These cannot track maximum sun irradiation and ambient temperature. An attempt has been made to over come these drawbacks by developing a technique called MPPT (Maximum Power Point Tracking), which recovers the loss of power due to varying panel out put and improper matching between the panel and battery. This technique utilizes pulse width Modulation, Micro controller, dc/dc (buck) converter for efficient charging of Load or battery. Under various test conditions numerical results have been obtained for the proposed technique and shows that proposed technique is an efficient with comparison of existing technique.

Abstract

In this paper, formulation and solution technique using Simulated Annealing for optimizing the moment capacity of steel fiber reinforced concrete beams, with random orientated steel fibers, is presented along with identification of design variables, objective function and constraints. Steel fibers form an expensive constituent of steel fiber concrete and therefore it is important to determine ways and means of using these fibers in a judicial way with care consistent with economy for achieving the desired benefits. The most important factors which influence the ultimate load carrying capacity of FRC are the volume percentage of the fibers, their aspect ratios and bond characteristics. Hence an attempt has been made to analyze the effective contribution of fibers to bending of reinforced fiber concrete beams. Equations are derived to predict the ultimate strength in flexure of SFRC beam with uniformly dispersed and randomly oriented steel fibers. Predicted strengths using the derived expressions have been compared with the experimental data. A reasonable agreement (within the range of ± 20 percent!) was evident with different types of steel fibers, aspect ratio, and material characteristics. A computer coding has been developed based on the formulations and the influence of various parameters on the ultimate flexural strength is discussed.  A computer algorithm that conducts a random search in the space of four variables- beam width, beam depth, fiber content and aspect ratio- to yield an optimum solution for a given objective function (ultimate moment (Mu))is presented. The outlined methods provide a simple and effective tool to assess the optimum flexural strength of steel fiber reinforced concrete beams. Using the results obtained the influence of various parameters on the ultimate strength are discussed. Particular attentions are given to the construction practice as well as the reduction of searching space. It has been shown that within a reasonable and finite number of searching the developed algorithm is able to yield optimum solutions for the given objective function.

Abstract

In this paper, a Max-Plus algebra model via the Timed Petri Net (TPN) model for a class of robotic assembly cell is developed. The paper describes the basic concepts of max-plus algebra which can be used for online control of manufacturing systems. The method presented in this paper, first model the given robotic assembly cell problem of assembling two parts using a timed Petri nets and generates a firing sequence for it. The detailed operational sequence for the assembly cell is explained and a reachability matrix for the Petri net model is also given. The complete cycle of the timing diagram required for the max-plus algebra model is presented by plotting a graph between location number and time. Based on the generated firing sequence of the petri net model, a max-plus algebra model is formulated. The formulated max-plus algebra model can be used for online computation and to schedule the operations of robotic assembly cell.

Abstract

Technology is major stimulus for change and has become synonymous with economic progress. Technology is imbibed in various forms; the most common of this could be identified in the field of medical devices and bio-medical instruments used in life and death situations. Cardiotocograph (CTG), a fetal heart rate and uterine contraction monitoring and measurement machine, is a valuable tool in the process of childbirth. The Quality Function Deployment(QFD) is an engineering technique with the number one priority being to satisfy the customer, QFD is a method for supporting customer satisfaction by accurately translating customer requirements into system requirements throughout the entire production phase. The aim of using QFD in this paper is to highlight the limitations and complexities of the present instrument through house of quality(HOQ). The paper attempts to first discuss out the operational details of the instrument and then its functional analysis is carried out through QFD a TQM tool. The resultant outcome enlists CTG functions with their Raw Weight and Priority Score. A detailed theoretical analysis of results pinpoints the basic functional limitation of the existing machine. Alternative techniques to overcome these limitations are discussed, which if further worked upon will lead to a very cost effective and optimal solution.