Informatics Publishing Limited

S. S. Padmapriya ¹, S. Venkatalakshmi ¹

Affiliations
1 PG and Research Department of Zoology, Government College for Women (Autonomous), Kumbakonam–612 001, IN

Abstract

Gomutra has been recorded for its high prophylactic and therapeutic values since Vedic times in India. Its application in Aquaculture has not been explored so far. Hence the present study has been aimed to assess the effect of different breeds of cow urine on the growth and biochemical parameters of Cirrhinus mrigala fingerlings. Urine from different breeds of cow like Haryana, Gir, Jercy was collected. Fingerlings were treated with 0.1% concentrations of different breeds of cow urine for a period of seven days. The control and treated groups were sacrificed on the 30^th day post cow urine treatment and the growth and biochemical parameters were analysed, the results show significant effect of cow urine on the nutrient value of the Indian major carp Cirrhinus mrigala.

Keywords

Gomutra, Vedic Times, Cow Urine, Cirrhinus mrigala, Biochemical Parameters.

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S. Venkatalakshmi ¹, J. Janet ²

Affiliations
1 Department of CSE, Panimalar Institute of Technology, Chennai, IN
2 Sri Krishna College of Engineering and Technology, Coimbatore, IN

Abstract

Cancer is a life-threatening disease, which consumes numerous human lives. However, the lifespan of the patients can be extended, when the disease is treated properly at the right time. This article renders a small contribution to the medical world for detecting the abnormalities in the mammograms. The research goal is attained by four important phases such as mammogram pre-processing, segmentation, feature extraction and classification. In the pre-processing phase, median filter is utilized to enhance the quality of an image. The pre-processed image is then segmented by FCM. The features are extracted from the image by Gaussian Hermite Moments, which are proven to be simple, efficient and noise resistant. Finally, multiclass SVM classifies between the normal, malignant and benign kinds of cancer. The performance of the proposed approach is evaluated against several analogous approaches in terms of accuracy, sensitivity and specificity. The proposed approach shows convincing results.

Keywords

CAD System, Breast Cancer Detection, Mammogram Segmentation, Multi-Class SVM, Classification, Abnormality Detection, Gaussian Hermite Moments.

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S. Anusha ¹, T. R. Shanmugapriya ¹, S. Venkatalakshmi ¹, Har Narayan Upadhyay ², V. Elamaran ²

Affiliations
1 Department of Electronics and Communication Engineering, School of EEE, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
2 Department of ECE, School of EEE, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN

Abstract

In the current semiconductor technology evolution, there is a huge demand in designing a low power, high speed adders with less area. As adders are essential components in the data-path of any computer system, adder modules are needed to be enhanced for better performance. One such efficient adder implementation is the Carry Look-Ahead Adder (CLA) which is designed to overcome the latency introduced by rippling effect of carry bits in a conventional Ripple Carry Adder (RCA). Further, the use of this CLA module in the place of Ripple Carry Adder module inside a Carry Select Adder (CSEA) is proposed for increased speed. Also, a novel implementation of adder, making use of the fact that the sum and carry are compliment of one another, except when all the inputs are same is presented. Simulation results show that a 4-bit carry select adder provides a better performance at the cost of power dissipation as 89.211 μW compared with 38.414 μW by a ripple carry adder with 0.12 μm technology processes. In this study, these high speed adders are implemented with the help of the Digital Schematic (DSCH) software tool, Micro wind layout editor tool and Quartus II synthesis software tool. This Quartus II synthesis tool is used for the implementation of adders on Altera EP2C20F484C7 FPGA device. These kinds of adders are further to be extended to build high-speed multipliers which are most important for the applications like digital signal processors, microprocessors, etc.

Keywords

Altera FPGA, Carry Look-Ahead Adders, High Speed Adders, Reduced Full Adder, VLSI.

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S. Venkatalakshmi ¹, J. Janet ²

Affiliations
1 Department of Computer Science Engineering, Panimalar Institute of Technology, IN
2 Sri Krishna College of Engineering and Technology, IN

Abstract

Breast cancer is a serious life threat to the womanhood, worldwide. Mammography is the promising screening tool, which can show the abnormality being detected. However, the physicians find it difficult to detect the affected regions, as the size of microcalcifications is very small. Hence it would be better, if a CAD system can accompany the physician in detecting the malicious regions. Taking this as a challenge, this paper presents a CAD system for mammogram classification which is proven to be accurate and reliable. The entire work is decomposed into four different stages and the outcome of a phase is passed as the input of the following phase. Initially, the mammogram is pre-processed by adaptive median filter and the segmentation is done by GHFCM. The features are extracted by combining the texture feature descriptors Completed Local Binary Pattern (CLBP) and contourlet to frame the feature sets. In the training phase, Extreme Learning Machine (ELM) is trained with the feature sets. During the testing phase, the ELM can classify between normal, malignant and benign type of cancer. The performance of the proposed approach is analysed by varying the classifier, feature extractors and parameters of the feature extractor. From the experimental analysis, it is evident that the proposed work outperforms the analogous techniques in terms of accuracy, sensitivity and specificity.

Keywords

Breast Cancer, Microcalcification, Mammogram, Classification.

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