Detection of microcalcifications in mammograms using local maxima andadaptive wavelet transform analysis

A method for computer- aided diagnosis of micro calcification clusters in mammograms images presented . Micro calcification clus.eni which are an early sign of bread cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is lint detected and they are ranked according to it higher-order statistical test performed over the sub band domain data

Use of photoacoustic effect for the detection of phase transitions in liquid crystal mixtures

We report on a laser induced photoacoustic study of the nematic-to-isotropic transition in certain commercial nematic liquid crystal mixtures, namely BL001, BL002, BL032 and BL035. A simple analysis of the experimental data using the Rosencwaig–Gersho theory shows that the heat capacities of all these compounds exhibit a sharp peak as the temperature of the sample is varied across the transition region. Also, substantial differences in the photoacoustic signal amplitudes in nematic and isotropic phases have been noticed for all the mixtures. The increased light scattering property of the nematic phase may be the reason for the enhanced photoacoustic signal amplitude in this phase.

Use of photoacoustic effect for the detection of phase transitions in liquid crystal mixtures

We report on a laser induced photoacoustic study of the nematic-to-isotropic transition in certain commercial nematic liquid crystal mixtures, namely BL001, BL002, BL032 and BL035. A simple analysis of the experimental data using the Rosencwaig–Gersho theory shows that the heat capacities of all these compounds exhibit a sharp peak as the temperature of the sample is varied across the transition region. Also, substantial differences in the photoacoustic signal amplitudes in nematic and isotropic phases have been noticed for all the mixtures. The increased light scattering property of the nematic phase may be the reason for the enhanced photoacoustic signal amplitude in this phase

Use of photoacoustic effect for the detection of phase transitions in liquid crystal mixtures

We report on a laser induced photoacoustic study of the nematic-to-isotropic transition in certain commercial nematic liquid crystal mixtures, namely BL001, BL002, BL032 and BL035. A simple analysis of the experimental data using the Rosencwaig–Gersho theory shows that the heat capacities of all these compounds exhibit a sharp peak as the temperature of the sample is varied across the transition region. Also, substantial differences in the photoacoustic signal amplitudes in nematic and isotropic phases have been noticed for all the mixtures. The increased light scattering property of the nematic phase may be the reason for the enhanced photoacoustic signal amplitude in this phase.

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.

Laser Induced Photoacoustic Technique for the Detection of Phase Transitions in Liquid Crystals

In this paper we report the use of a laser induced phoroacoustic technique for the detection of multiple phase transitions in heptyl-oxy-cyanobiphenyl (70CB) and octyl-oxy-cyanobiphenyl (80CB) liquid crystals. The observed photoacoustic signal amplitude profile carries clear signatures of two tirst order transitions in 70CB and two tirst order and a second order transitions in 80CB. Analysis of the experimental data using Rosencwaig-Gersho theory shows that the sudden decrease in the photoacoustic (PA) signal amplitude during phase transitions is due to a sharp increase in the heat capacity of the samples near the transition temperatures.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Active Microwave Imaging for Breast Cancer Detection

Active microwave imaging is explored as an imaging modality for early detection of breast cancer. When exposed to microwaves, breast tumor exhibits electrical properties that are significantly different from that of healthy breast tissues. The two approaches of active microwave imaging — confocal microwave technique with measured reflected signals and microwave tomographic imaging with measured scattered signals are addressed here. Normal and malignant breast tissue samples of same person are subjected to study within 30 minutes of mastectomy. Corn syrup is used as coupling medium, as its dielectric parameters show good match with that of the normal breast tissue samples. As bandwidth of the transmitter is an important aspect in the time domain confocal microwave imaging approach, wideband bowtie antenna having 2:1 VSWR bandwidth of 46% is designed for the transmission and reception of microwave signals. Same antenna is used for microwave tomographic imaging too at the frequency of 3000 MHz. Experimentally obtained time domain results are substantiated by finite difference time domain (FDTD) analysis. 2-D tomographic images are reconstructed with the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles.

Anomaly Detection Using System Call Sequence Sets.

This paper discusses our research in developing a generalized and systematic method for anomaly detection. The key ideas are to represent normal program behaviour using system call frequencies and to incorporate probabilistic techniques for classification to detect anomalies and intrusions. Using experiments on the sendmail system call data, we demonstrate that concise and accurate classifiers can be constructed to detect anomalies. An overview of the approach that we have implemented is provided.

Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience

In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced

A Compiler Integrated Assistance for Optimum Data Allocation in Banked Memory Embedded Processors

Bank switching in embedded processors having partitioned memory architecture results in code size as well as run time overhead. An algorithm and its application to assist the compiler in eliminating the redundant bank switching codes introduced and deciding the optimum data allocation to banked memory is presented in this work. A relation matrix formed for the memory bank state transition corresponding to each bank selection instruction is used for the detection of redundant codes. Data allocation to memory is done by considering all possible permutation of memory banks and combination of data. The compiler output corresponding to each data mapping scheme is subjected to a static machine code analysis which identifies the one with minimum number of bank switching codes. Even though the method is compiler independent, the algorithm utilizes certain architectural features of the target processor. A prototype based on PIC 16F87X microcontrollers is described. This method scales well into larger number of memory blocks and other architectures so that high performance compilers can integrate this technique for efficient code generation. The technique is illustrated with an example