Informatics Publishing Limited

Mutum Silpa Devi ¹, S. Jaya ¹

Affiliations
1 Department of Human Development, Avinashilingam Institute of Home Science and Higher Education for Women, University, Coimbatore, IN

Abstract

Today, globally the reproductive health of adolescents is of growing concern undeniably due to the alarming increases of sexual and reproductive health problems. Even though reproductive health care is a relatively new concept it is undoubtedly proven to be a very important component in general health. Reproductive health care is needed throughout life span of every individual specially women and precisely during adolescence since it is crucial during this period. Yet in most culture it is most prominently addressed during adulthood. Adolescence being the period of pubertal changes, sexual maturation, curiosity and experimentation make them vulnerable. Despite being acknowledge the special needs of adolescents are largely ignored due to the perpetuate idea of discussing anything related to sex is taboo. Without any or little knowledge from unreliable sources adolescents are exploring themselves in this field resulting in adolescent pregnancies, unsafe abortion, contracting STIs including HIV/AIDS further hinder in social and economic development of nation. The findings of various studies recommend one of the key actions needed to improve reproductive health is the empowerment of adolescents especially through education programmes. This paper draws attention to the urgent need of the intervention strategies aimed at enhancing adolescents' knowledge and bring desirable changes in their attitude thus to strengthen the quality of practices on reproductive health care.

Keywords

Adolescents, Sexual Health, Reproductive Health, Sex Education.

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S. Jaya ¹, R. Vinodha ²

Affiliations
1 Department of Electronics & Communication Engg., V.R.S College of Engineering & Technology, Arasur & Research Scholar, Annamalai University, Chidambaram, Tamil Nadu, IN
2 Department of Electronics & Instrumentation Engg., Annamalai University, Chidambaram, Tamil Nadu, IN

Abstract

In digital communication system, symbols are generated in a source and transmitted over a channel to a receiver. Noise gets added during the transition of symbols over the channel from source to the destination. In practice the symbols are corrupted with nonlinear distortion, Inter Symbol Interference (ISI) and noise. One possibility to reduce the effect of this problem is to use a channel equalizer at the receiver. The function of the equalizer is to reconstruct the original signal from the received signal or to generate a reconstructed version of the transmitted signalo as close as possible to it. The addition of an equalizer usually reduces the bit error rate (BER): the ratio of received bits in error to total transmitted bits. The most preferred technique is adaptive equalization. Traditional adaptive equalization uses linear transversal filter to reduce the effect of ISI. This filter is generally adjusted using a known training sequence at the beginning of the transmission and Least Square Estimation or gradient descent to determine the optimal set of coefficients for the filter. In the literature many adaptive algorithms such as Least Mean Square Algorithms have been developed which are effective under the assumption that the output is a linear function of the inputs. In practice this situation is rare and when nonlinear distortion and ISI are severe, nonlinear equalizers such as neural nets, the use of particle swarm optimization (PSO) can give a better performance. The objective of this paper is to discuss some of the adaptive equalization techniques available in the literature and put forth some ideas to improve the performance of PSO based adaptive equalization techniques.

Keywords

Particle Swarm Optimization, PSO, Adaptive Channel Equalization, Adaptive Equalization.

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M. Latha ¹, S. Jaya ¹

Affiliations
1 Department of Computer Science, Sri Sarada College for Women, IN

Abstract

Identification and classification of the plant leaf is efficient way to preventing loss occurred in agricultural field. The Septoria leaf spot is mainly affect the leaves which caused by a fungus, flu, bacteria. The Production of blueberry fruit is decreasing due to the disease affected on its stem and leaf. Small brown spots are frequently visible on blueberry leaves at specific period in the year. The spots, generally surrounded by bright yellow halos, start on the lower leaves and slowly appear on upper leaves over time. Image processing technology has been proved to be an efficient analysis to identify and detect the disease on a leaf. This proposed paper intends to focus to detect and classify a Septoria leaf spot on blueberry using Image Processing techniques such as, k-means clustering (k-nearest neighbor) for Segmentation, Gray-Level Co-occurrence Matrix for feature extraction and Support Vector Machine classifier to detect the leaf stage whether it is affected by Septoria spot or not. Totally 13 features have been extracted from each Blueberry leaf images where dataset of 40 images were taken for training and testing process partially and obtained the accuracy level was 96.77% using F-measure.

Keywords

Septoria Leaf Spot, K-means Clustering, Segmentation, Feature Extraction, GLCM, SVM.

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