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Volume 1 Issue 3 May - July 2012

Article

An Overview of Class Imbalance Problem in Supervised Learning

Satuluri Naganjaneyulu* , Mrithyumjaya Rao Kuppa**

* Associate Professor, Lakireddy Bali Reddy College of Engineering, Mylavaram, India.

** Professor, Vaagdevi College of Engineering, Warangal, India.

Naganjaneyulu, S. and Kuppa, M. (2012). An Overview Of Class Imbalance Problem In Supervised Learning. i-manager’s Journal on Communication Engineering and Systems, 1(3), 1-10. https://doi.org/10.26634/jcs.1.3.1886

Abstract

In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es). This paper presents an updated literature survey of current class imbalance learning methods for inducing models which handle imbalanced datasets efficiently.

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Article

Transient Scattering by Dielectric bodies-A Comparison of TLM and TDIE Methods

R. Srinivasa Rao* , P.V. Subbaiah, B. Prabhakara Rao*

* Professor, Dept of ECE, SVEC, Tirupathi, A.P, India.

Principal, ASIST, Krishna Dist, A.P, India.

* Professor, College of Engineering, JNTUK, Kakinada, A.P, India.

Rao, R. S., Subbaiah, P. V., and Rao, B. P. (2012). Transient Scattering By Dielectric Bodies- A Comparison Of TLM And TDIE Methods. i-manager’s Journal on Communication Engineering and Systems, 1(3), 11-16. https://doi.org/10.26634/jcs.1.3.1890

Abstract

The radar signature calculations play an essential role in the design and functioning of today’s radars in detecting the surface and air targets. Radar interrogation is essentially a transient electromagnetic scattering process and direct transient analysis provides an opportunity to observe and to interpret scattering behavior. We present in this paper a comparison of two popular time domain numerical techniques widely used for direct transient analysis, namely, the transmission line matrix (TLM) method and the time-domain integral equation (TDIE) method. Both the methods belong to the category of time domain techniques; however, their modeling philosophy is quite different. Whereas the TLM method is based on the implementation of the Huygens principle by modeling the space with a system of interconnected transmission-lines, the TDIE is based on well known method of moments. The comparison is made via standard canonical shaped dielectric bodies, namely, a cube, and a sphere, mainly to address the factors affecting accuracy, efficiency, and the required computer resources.

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Research Paper

Offline Ancient Tamil Character Recognition System Based On Structural Features

S. Rajakumar* , V. Subbiah Bharathi**

* Research Scholar, Department of ECE, Sathiyabama University. Chennai. India.

** Principal, DMI College of Engineering, Chennai. India.

Rajakumar, S. and Bharathi, V. S. (2012). Offline Ancient Tamil Character Recognition System Based On Structural Features. i-manager’s Journal on Communication Engineering and Systems, 1(3), 17-24. https://doi.org/10.26634/jcs.1.3.1891

Abstract

In this paper we propose an approach for offline recognition of ancient Tamil characters using their structural features. Structural features are the features that are physically a part of the structure of the character, such as straight lines, arcs, circles, intersections etc. The features used for recognition are the positions of vertical lines, horizontal lines and branching in a character. Some other features, namely moments, zoning and number of transitions have also been explored to verify their utility in Tamil character recognition. For classification of the characters simple Euclidean distance was used. Ancient Tamil Character recognition is a classic problem in the field of image processing and neural networks. Lot of research has been done on recognition of handwritten Tamil characters but relatively less work has been done in the field of recognition of Ancient Tamil characters in Indian languages. In this paper we explore some structural features that can be used in offline Ancient Tamil character recognition. Structural features are insufficient to classify all the characters. Some other features along with the use of artificial neural networks can improve the performance of the system. The proposed algorithm obtained results in terms of accuracy (reaches 97.9% for some letters at average 80%) as well as in terms of time consuming.

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Research Paper

Evaluation Metric Standardization for Edge detection and Enhancement algorithms

Abhishek* , T. Ramashri**

* Assistant Professor, School of Electrical Engineering, VIT University, Vellore.

** Associate Professor, Dept. of ECE, Sri Venkateswara University College of Engineering, Tirupati.

Abhishek, G. and Ramashri, T. (2012). Evaluation Metric Standardization For Edge Detection And Enhancement Algorithms. i-manager’s Journal on Communication Engineering and Systems, 1(3), 25-30. https://doi.org/10.26634/jcs.1.3.1893

Abstract

Pattern recognition, Image enhancement, Feature extraction are the key research areas in image processing. It can be applied to many applications such as satellite, medical, military, infrared imaging and LIDAR. There are many existing algo in im pr, several image enhancement techniques have been developed, such as histogram equalization, contrast stretching, bit plane slicing, averaging, etc. but the ambiguity is because of missing evaluation metrics, which leads to uncertainity in deciding the algorithm that can perform better. There are some uncertainties regarding these above techniques such as edge detection, oversmoothing, blurring and deformation of edges. In this paper, we considered edge detection as one of the uncertainty and the evaluation metrics such as SSIM (Structural Similarity Index) and VIF(Visual Information Fidelity) has been applied to the images to measure the image quality. The SSIM and VIF have been applied to the different types of images such as Grayscale, Color, Infrared, LIDAR, Microscopic and Biomedical Images. In the present work evaluation metrics are applied to the original image and egde detected image, thus from experimental results it is observed that the proposed algorithm works well for measuring the quality of spatial resolution enhanced hyper spectral images.

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Research Paper

Estimation Of Moments For Low And High SNR Atmospheric Radar Data

PADMAJA* , G. Madhavi Latha, S. Varadarajan*

* Asst. Professor, Dept of ECE, S.V.E.C Tirupati.

Associate Professor, Dept of ECE, CREC, Tirupati.

* Professor, Dept of ECE, S.V.U college of Engg, Tirupati.

Madhavilatha, G., Padmaja, N., and Varadarajan, S. (2012). Estimation Of Moments For Low And High SNR Atmospheric Radar Data. i-manager’s Journal on Communication Engineering and Systems, 1(3), 31-38. https://doi.org/10.26634/jcs.1.3.1895

Abstract

Atmospheric Signal processing has been one field of signal processing where there is a lot of scope for development of new and efficient tools for Cleaning of the spectrum, detection and estimation of the desired parameters. Atmospheric signal processing deals with the processing of the signals received from the atmosphere. The signals, which are processed in the present work, have been obtained from the mesosphere - stratosphere- troposphere (MST) Radar. The MST radar facilities are situated at National Atmospheric research Laboratory, Gadanki, and Tirupati, India. The signal processing done in the present work concentrates mainly on the data collected from NARL located at Gadanki. This work deals with signal processing techniques used for the analysis of MST Radar signal and to extract better information about moments for wind profilling. The proposed algorithm estimates radar moments and signal to noise ratio. The performance of this method is tested practically with atmospheric wind profiler data ADP (Atmospheric Data Processor). Signal processing of recoded experimental data is performed using Matlab. Moments were estimated using five peak method and results are plotted.

References

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[13]. Rotteger, J., and M.F. Larsen, UHF/ VHF Radar techniques for atmospheric research and wind profiler.

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Volume 1 Issue 3 May - July 2012

An Overview of Class Imbalance Problem in Supervised Learning

Satuluri Naganjaneyulu* , Mrithyumjaya Rao Kuppa**

* Associate Professor, Lakireddy Bali Reddy College of Engineering, Mylavaram, India. ** Professor, Vaagdevi College of Engineering, Warangal, India.

Naganjaneyulu, S. and Kuppa, M. (2012). An Overview Of Class Imbalance Problem In Supervised Learning. i-manager’s Journal on Communication Engineering and Systems, 1(3), 1-10. https://doi.org/10.26634/jcs.1.3.1886

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Transient Scattering by Dielectric bodies-A Comparison of TLM and TDIE Methods

R. Srinivasa Rao* , P.V. Subbaiah**, B. Prabhakara Rao***

* Professor, Dept of ECE, SVEC, Tirupathi, A.P, India. ** Principal, ASIST, Krishna Dist, A.P, India. *** Professor, College of Engineering, JNTUK, Kakinada, A.P, India.

Rao, R. S., Subbaiah, P. V., and Rao, B. P. (2012). Transient Scattering By Dielectric Bodies- A Comparison Of TLM And TDIE Methods. i-manager’s Journal on Communication Engineering and Systems, 1(3), 11-16. https://doi.org/10.26634/jcs.1.3.1890

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Offline Ancient Tamil Character Recognition System Based On Structural Features

S. Rajakumar* , V. Subbiah Bharathi**

* Research Scholar, Department of ECE, Sathiyabama University. Chennai. India. ** Principal, DMI College of Engineering, Chennai. India.

Rajakumar, S. and Bharathi, V. S. (2012). Offline Ancient Tamil Character Recognition System Based On Structural Features. i-manager’s Journal on Communication Engineering and Systems, 1(3), 17-24. https://doi.org/10.26634/jcs.1.3.1891

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Evaluation Metric Standardization for Edge detection and Enhancement algorithms

Abhishek* , T. Ramashri**

* Assistant Professor, School of Electrical Engineering, VIT University, Vellore. ** Associate Professor, Dept. of ECE, Sri Venkateswara University College of Engineering, Tirupati.

Abhishek, G. and Ramashri, T. (2012). Evaluation Metric Standardization For Edge Detection And Enhancement Algorithms. i-manager’s Journal on Communication Engineering and Systems, 1(3), 25-30. https://doi.org/10.26634/jcs.1.3.1893

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Estimation Of Moments For Low And High SNR Atmospheric Radar Data

PADMAJA* , G. Madhavi Latha**, S. Varadarajan***

* Asst. Professor, Dept of ECE, S.V.E.C Tirupati. ** Associate Professor, Dept of ECE, CREC, Tirupati. *** Professor, Dept of ECE, S.V.U college of Engg, Tirupati.

Madhavilatha, G., Padmaja, N., and Varadarajan, S. (2012). Estimation Of Moments For Low And High SNR Atmospheric Radar Data. i-manager’s Journal on Communication Engineering and Systems, 1(3), 31-38. https://doi.org/10.26634/jcs.1.3.1895

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* Associate Professor, Lakireddy Bali Reddy College of Engineering, Mylavaram, India.

** Professor, Vaagdevi College of Engineering, Warangal, India.

R. Srinivasa Rao* , P.V. Subbaiah, B. Prabhakara Rao*

* Professor, Dept of ECE, SVEC, Tirupathi, A.P, India.

Principal, ASIST, Krishna Dist, A.P, India.

* Professor, College of Engineering, JNTUK, Kakinada, A.P, India.

* Research Scholar, Department of ECE, Sathiyabama University. Chennai. India.

** Principal, DMI College of Engineering, Chennai. India.

* Assistant Professor, School of Electrical Engineering, VIT University, Vellore.

** Associate Professor, Dept. of ECE, Sri Venkateswara University College of Engineering, Tirupati.

PADMAJA* , G. Madhavi Latha, S. Varadarajan*

* Asst. Professor, Dept of ECE, S.V.E.C Tirupati.

Associate Professor, Dept of ECE, CREC, Tirupati.

* Professor, Dept of ECE, S.V.U college of Engg, Tirupati.