Query Based Location Aware Energy Efficient Secure Multicast Routing for Wireless Sensor Networks Using Fuzzy Logic

In Wireless Sensor Networks (WSNs), balancing authentication and energy is a major concern while deploying for wireless applications. Due to the presence of attackers, node consumes excessive energy for packet replication or transmission. In existing work, it is observed that attention was not done on balancing energy and data authentication. Location aided routing will also support for achieving high network lifetime. Fuzzy decision approach was widely used in sensor network for ensuring quality of routing and transmission. In the proposed work, Fuzzy enhanced query based secure energy efficient multicast routing is implemented. Query based location based cluster formation is done for quick packet arrival. Optimal multicast routes are found to forward the packets with reliability. The reliable routes are identified using reliable index. Fuzzy decision model is integrated to provide secure and energy based network model for packet transmission. Network Simulator (NS2.35) is used for simulation for analyzing the performance of proposed protocol in terms of various network parameters

Ethno-Cultural Identity of Northeast India with Reference to Temsula Ao’s Select Poems

Northeast part of India is known for its ethnogenic significance which has many roots of civilization, and it is distinct from the other part of the country. Therefore, the culture of Northeast India faces tremendous challenges due to its vast ethnographic diversity. Temsula Ao, is one of the most widely read and studied women writers of North-East India. She has been the recipient of many awards including the Padma Shri in 2007 and the Sahitya Akademi award in 2013.  She is also a pioneer writer from Nagaland. The main aim of this study is to explore ethno-cultural aesthetics of the Northeast Indian region which exists in Temsula Ao’s poetry. For that purpose, fifteen of her poems are selected from her anthology titled Books of Songs. The select poems were analysed qualitatively.  This descriptive qualitative research methodology deals how Ao-Naga regional people know about human values, beliefs, behavious, and social conditions within their own environmental contexts. The major finding of this paper is in what way Temsula Ao revitalizes Ao-Naga culture and tradition by picturising her region, history and condition of women relating them with nature through her poems. Implications were identified for the people of diverse cultural backgrounds. And, it is concluded that the beauty of a region is retained by the people who have a staunch belief in their traditional cultural values and ethics

Cancer Diagnosis through Contour Visualization of Gene Expression Leveraging Deep Learning Techniques

Prompt diagnostics and appropriate cancer therapy necessitate the use of gene expression databases. The integration of analytical methods can enhance detection precision by capturing intricate patterns and subtle connections in the data. This study proposes a diagnostic-integrated approach combining Empirical Bayes Harmonization (EBS), Jensen–Shannon Divergence (JSD), deep learning, and contour mathematics for cancer detection using gene expression data. EBS preprocesses the gene expression data, while JSD measures the distributional differences between cancerous and non-cancerous samples, providing invaluable insights into gene expression patterns. Deep learning (DL) models are employed for automatic deep feature extraction and to discern complex patterns from the data. Contour mathematics is applied to visualize decision boundaries and regions in the high-dimensional feature space. JSD imparts significant information to the deep learning model, directing it to concentrate on pertinent features associated with cancerous samples. Contour visualization elucidates the model’s decision-making process, bolstering interpretability. The amalgamation of JSD, deep learning, and contour mathematics in gene expression dataset analysis diagnostics presents a promising pathway for precise cancer detection. This method taps into the prowess of deep learning for feature extraction while employing JSD to pinpoint distributional differences and contour mathematics for visual elucidation. The outcomes underscore its potential as a formidable instrument for cancer detection, furnishing crucial insights for timely diagnostics and tailor-made treatment strategies

Cancer Diagnosis through Contour Visualization of Gene Expression Leveraging Deep Learning Techniques

Prompt diagnostics and appropriate cancer therapy necessitate the use of gene expression databases. The integration of analytical methods can enhance detection precision by capturing intricate patterns and subtle connections in the data. This study proposes a diagnostic-integrated approach combining Empirical Bayes Harmonization (EBS), Jensen–Shannon Divergence (JSD), deep learning, and contour mathematics for cancer detection using gene expression data. EBS preprocesses the gene expression data, while JSD measures the distributional differences between cancerous and non-cancerous samples, providing invaluable insights into gene expression patterns. Deep learning (DL) models are employed for automatic deep feature extraction and to discern complex patterns from the data. Contour mathematics is applied to visualize decision boundaries and regions in the high-dimensional feature space. JSD imparts significant information to the deep learning model, directing it to concentrate on pertinent features associated with cancerous samples. Contour visualization elucidates the model’s decision-making process, bolstering interpretability. The amalgamation of JSD, deep learning, and contour mathematics in gene expression dataset analysis diagnostics presents a promising pathway for precise cancer detection. This method taps into the prowess of deep learning for feature extraction while employing JSD to pinpoint distributional differences and contour mathematics for visual elucidation. The outcomes underscore its potential as a formidable instrument for cancer detection, furnishing crucial insights for timely diagnostics and tailor-made treatment strategies