Tunnel-Based Artificial Neural Network Technique to Calculate the Resonant Frequency of a Thick-Substrate Microstrip Antenna

The mathematical formulation of empirically developed formulas Jirr the calculation of the resonant frequency of a thick-substrate (h s 0.08151 A,,) microstrip antenna has been analyzed. With the use qt' tunnel-based artificial neural networks (ANNs), the resonant frequency of antennas with h satisfying the thick-substrate condition are calculated and compared with the existing experimental results and also with the simulation results obtained with the use of an IE3D software package. The artificial neural network results are in very good agreement with the experimental results

Microwave dielectric properties of MO -La2O3-TiO2 (M = Ca, Sr, Ba) ceramics

Single-phase polycrystalline ceramics in the MO-La2O3-Ti02 (M = Ca, Sr, Ba) system, such as cation-deficient hexagonal perovskites CaLa4Ti4O15, SrLa4Ti4O15, BaLa4Ti4O15, and Ca2La4Ti5O18 and the orthorhombic phases CaLa4Ti5O17 and CaLa8Ti9O31, were prepared through the solid-state ceramic route. The phases and structure of the ceramics were analyzed through x-ray diffraction and scanning electron microscopy. The microwave dielectric properties of the ceramics were studied using a network analyzer. The investigated ceramics show high Er in the range 42 to 54, high quality factors with Q x f in the range 16,222 to 50,215 GHz, and low Tf in the range -25 to +6 ppm3/°C. These high dielectric constant materials with high Q x f up to 50,215 GHz are suitable for applications where narrow bandwidth and extremely low insertion loss is necessary, especially at frequencies around 1.9 GHz

Photothermal deflection measurement on heat transport in GaAs epitaxial layers

In this paper, we report the in-plane and cross-plane measurements of the thermal diffusivity of double epitaxial layers of n-type GaAs doped with various concentrations of Si and a p-type Be-doped GaAs layer grown on a GaAs substrate by the molecular beam epitaxial method, using the laser-induced nondestructive photothermal deflection technique. The thermal diffusivity value is evaluated from the slope of the graph of the phase of the photothermal deflection signal as a function of pump-probe offset. Analysis of the data shows that the cross-plane thermal diffusivity is less than that of the in-plane thermal diffusivity. It is also seen that the doping concentration has a great influence on the thermal diffusivity value. Measurement of p-type Be-doped samples shows that the nature of the dopant also influences the effective thermal diffusivity value. The results are interpreted in terms of a phonon-assisted heat transfer mechanism and the various scattering process involved in the propagation of phonons.

Photothermal deflection measurement on heat transport in GaAs epitaxial layers

In this paper, we report the in-plane and cross-plane measurements of the thermal diffusivity of double epitaxial layers of n-type GaAs doped with various concentrations of Si and a p-type Be-doped GaAs layer grown on a GaAs substrate by the molecular beam epitaxial method, using the laser-induced nondestructive photothermal deflection technique. The thermal diffusivity value is evaluated from the slope of the graph of the phase of the photothermal deflection signal as a function of pump-probe offset. Analysis of the data shows that the cross-plane thermal diffusivity is less than that of the in-plane thermal diffusivity. It is also seen that the doping concentration has a great influence on the thermal diffusivity value. Measurement of p-type Be-doped samples shows that the nature of the dopant also influences the effective thermal diffusivity value. The results are interpreted in terms of a phonon-assisted heat transfer mechanism and the various scattering process involved in the propagation of phonons

Photothermal deflection measurement on heat transport in GaAs epitaxial layers

In this paper, we report the in-plane and cross-plane measurements of the thermal diffusivity of double epitaxial layers of n-type GaAs doped with various concentrations of Si and a p-type Be-doped GaAs layer grown on a GaAs substrate by the molecular beam epitaxial method, using the laser-induced nondestructive photothermal deflection technique. The thermal diffusivity value is evaluated from the slope of the graph of the phase of the photothermal deflection signal as a function of pump-probe offset. Analysis of the data shows that the cross-plane thermal diffusivity is less than that of the in-plane thermal diffusivity. It is also seen that the doping concentration has a great influence on the thermal diffusivity value. Measurement of p-type Be-doped samples shows that the nature of the dopant also influences the effective thermal diffusivity value. The results are interpreted in terms of a phonon-assisted heat transfer mechanism and the various scattering process involved in the propagation of phonons

AN ARTIFICIAL NEURAL NETWORK FOR SONAR TARGET DETECTION

Neural Network has emerged as the topic of the day. The spectrum of its application is as wide as from ECG noise filtering to seismic data analysis and from elementary particle detection to electronic music composition. The focal point of the proposed work is an application of a massively parallel connectionist model network for detection of a sonar target. This task is segmented into: (i) generation of training patterns from sea noise that contains radiated noise of a target, for teaching the network;(ii) selection of suitable network topology and learning algorithm and (iii) training of the network and its subsequent testing where the network detects, in unknown patterns applied to it, the presence of the features it has already learned in. A three-layer perceptron using backpropagation learning is initially subjected to a recursive training with example patterns (derived from sea ambient noise with and without the radiated noise of a target). On every presentation, the error in the output of the network is propagated back and the weights and the bias associated with each neuron in the network are modified in proportion to this error measure. During this iterative process, the network converges and extracts the target features which get encoded into its generalized weights and biases.In every unknown pattern that the converged network subsequently confronts with, it searches for the features already learned and outputs an indication for their presence or absence. This capability for target detection is exhibited by the response of the network to various test patterns presented to it.Three network topologies are tried with two variants of backpropagation learning and a grading of the performance of each combination is subsequently made.

Photothermal deflection studies of GaAs epitaxial layers

Photothermal beam deflection studies were carried out with GaAs epitaxial double layers grown on semi-insulating GaAs substrates. The impurity densities in thin epitaxial layers were found to influence the effective thermal diffusivity of the entire structure.

Photoacoustic study of the effect of doping concentration on the transport properties of GaAs epitaxial layers

We report a photoacoustic (PA) study of the thermal and transport properties of a GaAs epitaxial layer doped with Si at varying doping concentration, grown on GaAs substrate by molecular beam epitaxy. The data are analyzed on the basis of Rosencwaig and Gersho’s theory of the PA effect. The amplitude of the PA signal gives information about various heat generation mechanisms in semiconductors. The experimental data obtained from the measurement of the PA signal as a function of modulation frequency in a heat transmission configuration were fitted with the phase of PA signal obtained from the theoretical model evaluated by considering four parameters—viz., thermal diffusivity, diffusion coefficient, nonradiative recombination time, and surface recombination velocity—as adjustable parameters. It is seen from the analysis that the photoacoustic technique is sensitive to the changes in the surface states depend on the doping concentration. The study demonstrates the effectiveness of the photoacoustic technique as a noninvasive and nondestructive method to measure and evaluate the thermal and transport properties of epitaxial layers.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

Photoacoustic measurement of transport properties in doped GaAs epitaxial layers

The photoacoustic technique under heat transmission configuration is used to determine the effect of doping on both the thermal and transport properties of p- and n-type GaAs epitaxial layers grown on GaAs substrate by the molecular beam epitaxial method. Analysis of the data is made on the basis of the theoretical model of Rosencwaig and Gersho. Thermal and transport properties of the epitaxial layers are found by fitting the phase of the experimentally obtained photoacoustic signal with that of the theoretical model. It is observed that both the thermal and transport properties, i.e. thermal diffusivity, diffusion coefficient, surface recombination velocity and nonradiative recombination time, depend on the type of doping in the epitaxial layer. The results clearly show that the photoacoustic technique using heat transmission configuration is an excellent tool to study the thermal and transport properties of epitaxial layers under different doping conditions.

Studies,Design and Development of Network Security Enhancement Services Using Novel Cryptographic Algorithms

Internet today has become a vital part of day to day life, owing to the revolutionary changes it has brought about in various fields. Dependence on the Internet as an information highway and knowledge bank is exponentially increasing so that a going back is beyond imagination. Transfer of critical information is also being carried out through the Internet. This widespread use of the Internet coupled with the tremendous growth in e-commerce and m-commerce has created a vital need for infonnation security.Internet has also become an active field of crackers and intruders. The whole development in this area can become null and void if fool-proof security of the data is not ensured without a chance of being adulterated. It is, hence a challenge before the professional community to develop systems to ensure security of the data sent through the Internet.Stream ciphers, hash functions and message authentication codes play vital roles in providing security services like confidentiality, integrity and authentication of the data sent through the Internet. There are several ·such popular and dependable techniques, which have been in use widely, for quite a long time. This long term exposure makes them vulnerable to successful or near successful attempts for attacks. Hence it is the need of the hour to develop new algorithms with better security.Hence studies were conducted on various types of algorithms being used in this area. Focus was given to identify the properties imparting security at this stage. By making use of a perception derived from these studies, new algorithms were designed. Performances of these algorithms were then studied followed by necessary modifications to yield an improved system consisting of a new stream cipher algorithm MAJE4, a new hash code JERIM- 320 and a new message authentication code MACJER-320. Detailed analysis and comparison with the existing popular schemes were also carried out to establish the security levels.The Secure Socket Layer (SSL) I Transport Layer Security (TLS) protocol is one of the most widely used security protocols in Internet. The cryptographic algorithms RC4 and HMAC have been in use for achieving security services like confidentiality and authentication in the SSL I TLS. But recent attacks on RC4 and HMAC have raised questions about the reliability of these algorithms. Hence MAJE4 and MACJER-320 have been proposed as substitutes for them. Detailed studies on the performance of these new algorithms were carried out; it has been observed that they are dependable alternatives.

Hexagonal dielectric resonator antenna - A novel DR antenna for wireless communication

In this thesis, the author proposes a new geometry DR antenna-the Hexagonal Dielectric Resonator Antenna(HDRA)-capable of multiple frequency operation on a single feed of excitation.This avoids the conventional use of miniaturizes the structure.The properties of the HDRA on microstrip as well as coaxial feeding have been studied.The analysis of radiation characteristics indicates a gain comparable with other shapes.The antenna is capable of providing efficiency around 98%.The simulation using HFSS also yields results in conformity with the experimental results.Mode analysis is carried out and the modes are identified.The determination of the reflection characteristics through theoretical analysis using FDTD validates the multifrequency operation of the antenna,The antenna finds application in DCT,PCS and WLAN bands.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Development and Deployment of Wireless Sensor Network in Paddy Fields of Kuttanad

The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

MicroRNA–mRNA interaction network using TSK-type recurrent neural fuzzy network

MicroRNAs are short non-coding RNAs that can regulate gene expression during various crucial cell processes such as differentiation, proliferation and apoptosis. Changes in expression profiles of miRNA play an important role in the development of many cancers, including CRC. Therefore, the identification of cancer related miRNAs and their target genes are important for cancer biology research. In this paper, we applied TSK-type recurrent neural fuzzy network (TRNFN) to infer miRNA–mRNA association network from paired miRNA, mRNA expression profiles of CRC patients. We demonstrated that the method we proposed achieved good performance in recovering known experimentally verified miRNA–mRNA associations. Moreover, our approach proved successful in identifying 17 validated cancer miRNAs which are directly involved in the CRC related pathways. Targeting such miRNAs may help not only to prevent the recurrence of disease but also to control the growth of advanced metastatic tumors. Our regulatory modules provide valuable insights into the pathogenesis of cancer