Brain Tumour Extraction Based On Segmentation

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Ensemble Classifications of Wavelets based GLCM Texture Feature from MR Human Head Scan Brain Slices Analysis

This paper presents an automatic image analysis of multi-model views of MR brain using ensemble classifications of wavelets based texture feature. Primarily, an input MR image has pre-processed for an enhancement process. Then, the pre-processed image is decomposed into different frequency sub-band image using 2D stationary and discrete wavelet transform. The GLCM texture feature information is extracted from the above low-frequency sub band image of 2D discrete and stationary wavelet transform. The extracted texture features are given as an input to ensemble classifiers of Gentle Boost and Bagged Tree classifiers to recognize the appropriate image samples. Image abnormality has extracted from the recognized abnormal image samples of classifiers using multi-level Otsu thresholding. Finally, the performance of two ensemble classifiers performance has analyzed using sensitivity, specificity, accuracy, and MCC measures of two different wavelet based GLCM texture features. The resultant proposed feature extraction technique achieves the maximum level of accuracy is 90.70% with the fraction of 0.78 MCC value

Poetical discourse analysis of a Tamil song Ovvoru Puukkalumee

This study is an attempt to analyze the Tamil movie song ‘Ovvoru PuukkaLumee ’ meaning ‘every flower’ from the Tamil movie 'Autograph'. This song is one of the popular songs of P. Vijay, a Tamil lyricist. The texture discourse of this song will be analyzed in terms of grammatical and lexical usages found by making use of discourse analysis

An Enhanced Cluster based Multi-hop Routing Technique in Wireless Sensor Network Using AODV Protocol

Wireless Sensor Network is one of main extent in physical environmental inquiry. The Cluster based multi-hop routing for the capable network to improve the life time data transmission and energy saving for the network progress. In this Research paper based on Flat Multi-Hop Routing Technique is used to LEACH protocol using reduced overall network power utilization. Hierarchical Multi-hop routing Technique is one of the methods using M-LEACH protocol, while using this method user is able to get the large number of data and packet losses also reduced. Hybrid multi-hop routing Technique using PEACH protocol used by the users are able to get Energy saving is high. My Research contribution going to Enhanced Hybrid Multi-hop Routing(EHYMN) for improve the data transmission with less time , reduced the packet losses and also minimum power utilization for this Ad-hoc On Demand Distance Vector (AODV) protocol is used for the implementation in network simulation tool 2.34 version for get a good Results

ILAT (Software as a Service): Interactive Learning Application Tool for Autism Screening and Assessment in children with Autism Spectrum Disorder

Autism is a type of neurological disorder usually noticeable during the early stage of childhood, especially between one to three years and occurs in all social groups. The common problem experienced by the autism subjects includes lack in social interaction, poor communication skill, overexcited, unable to express their emotions. While these disorders are not fully curable, early detection can reduce the severity with proper therapy. Even though there are no appropriate medications and treatments, still we can improve the lifestyle of the autism subject through various supportive therapies. If this disorder is not detected at early stages, the severity rate may probably increase during the later stage.  Developing countries like India witness 0.2 percentage of the autism population in the overall community based on the information provided by the Rehabilitation Council of India. Express growth in the Information and Communication Technologies allows developing various assistive tools to enhance the lifestyle of the autism people. Fourth Generation Technologies like the Internet of Things, Wearable Devices, Cloud Computing, Big Data Analytics, and Artificial Intelligence, Mobile devices, Location-aware technology, Sensors, Augmented and Virtual Reality together provide a smart solution to all the sufferers. The objective of Interactive Learning Application Tool is used for Autism Screening and Assessment in children with Autism Spectrum Disorder and extended to explore the assistive technologies available to serve the community. This will enhance the social interaction, learning and communication skills in children, a tool for analysing the aggressive level, a tool for caregivers and supportive and ranking tool for psychiatrist dealing with autism subject

Effective Teachers of Multilingual Learners: A Mixed-Method Study of UK and US Critical Sociocultural Teaching Practices

This convergent parallel mixed-method study (quan + QUAL) relies on systematic classroom observations of mainstream teachers considered highly effective with multilingual learners in the United Kingdom and the United States (N = 9). Using a critical sociocultural theoretical lens, we use an established quantitative observation rubric and lesson field notes to capture real-world teaching practices. Using deductive reasoning to merge closed- and open-ended observation data, we illuminate the features of highly effective teaching for multilingual students. Evidence demonstrates that elements of challenge in activity design and teacher presentation, prioritizing language and literacy development, and modeling, were practices with the highest consistency across countries. At the same time, other features leave room for future growth. Lesson analysis unpacked various ways teachers enact effective teaching based on country context. Despite educational policies that may conflict with strong teaching for multilingual students, linguistically responsive teachers in both countries transcend curricular and testing constraints by intentionally enacting lessons that richly scaffold learning

Standardisation and Validation of Cytogenetic Markers to Quantify Radiation Absorbed Dose

The amounts of radiation exposure received by radiation workers are monitored generally by physical dosimeters like thermoluminescence dosimeter (TLD) and film badge. However, in practice the over-exposure recorded by physical dosimeters need to be confirmed with biological dosimeters. In addition to confirming the dose recorded by physical dosimeters, biological dosimeters play an important role in estimating the doses received during accidental exposures. Exposure to high levels of radiation induces certain  biochemical, biophysical, and immunological changes (biomarkers) in a cell. Measurement of these changes are generally precise but cannot be effectively used to assess the dose, as the level of these changes return to normalcy within hours to months after exposure. Thus, among various biological indicators, cytogenetic indicators are considered practical and reliable for dose estimation. The paper highlights the importance and establishment of biodosimetry facility using genetic markers such as the sensitive dicentric chromosomes, rapid micronucleus assay and stable translocations measured using fluorescence in situ hybridisation and GTG banding for retrospective dose estimation. Finally, the development of gH2AX assay, as a potential marker of triage dosimeter, is discussed.Defence Science Journal, 2011, 61(2), pp.125-132, DOI:http://dx.doi.org/10.14429/dsj.61.83