Spin dynamics and frequency dependence of magnetic damping study in soft ferromagnetic FeTaC film with a stripe domain structure

Perpendicular magnetic anisotropy (PMA) and low magnetic damping are the key factors for the free layer magnetization switching by spin transfer torque technique in magnetic tunnel junction devices. The magnetization precessional dynamics in soft ferromagnetic FeTaC thin film with a stripe domain structure was explored in broad band frequency range by employing micro-strip ferromagnetic resonance technique. The polar angular variation of resonance field and linewidth at different frequencies have been analyzed numerically using Landau-Lifshitz-Gilbert equation by taking into account the total free energy density of the film. The numerically estimated parameters Land\'{e} $g$-factor, PMA constant, and effective magnetization are found to be 2.1, 2$\times10^{5}$ erg/cm$^{3}$ and 7145 Oe, respectively. The frequency dependence of Gilbert damping parameter ($\alpha$) is evaluated by considering both intrinsic and extrinsic effects into the total linewidth analysis. The value of $\alpha$ is found to be 0.006 at 10 GHz and it increases with decreasing precessional frequency.Comment: 5 Pages, 6 Figures, Regular Submissio

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

An Exploratory Study on the Difficulties Faced by First-Generation Learners in Writing Skills

Language is a complex process, especially its written mode. To write better, one must be well acquainted with vocabulary and contextual expressions. The difficulties faced by the first generation learners of English in India are numerous because exposure is a bigger issue. The remedies for their difficulties are elaborately discussed in this paper. The aim is to throw light on the obstacles of the first generation learners at the tertiary level who had studied English as the second language or as a medium of instruction at the school level. Eighty such participants were selected using random sampling technique and a semistructured interview was conducted. A mixed-method approach was used and a questionnaire was administered. The present study identifies difficulties in writing skills faced by first generation learners. And also, this paper focuses on the impact of difficulties in writing skills on them. Additionally, remedial measures to enhance writing skills are also discussed

Brain Tumour Extraction Based On Segmentation

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Structured and Unstructured Information Extraction Using Text Mining and Natural Language Processing Techniques

Information on web is increasing at infinitum. Thus, web has become an unstructured global area where information even if available, cannot be directly used for desired applications. One is often faced with an information overload and demands for some automated help. Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents by means of Text Mining and Natural Language Processing (NLP) techniques. Extracted structured information can be used for variety of enterprise or personal level task of varying complexity. The Information Extraction (IE) in also a set of knowledge in order to answer to user consultations using natural language. The system is based on a Fuzzy Logic engine, which takes advantage of its flexibility for managing sets of accumulated knowledge. These sets may be built in hierarchic levels by a tree structure. Information extraction is structured data or knowledge from unstructured text by identifying references to named entities as well as stated relationships between such entities. Data mining research assumes that the information to be “mined” is already in the form of a relational database. IE can serve an important technology for text mining. The knowledge discovered is expressed directly in the documents to be mined, then IE alone can serve as an effective approach to text mining. However, if the documents contain concrete data in unstructured form rather than abstract knowledge, it may be useful to first use IE to transform the unstructured data in the document corpus into a structured database, and then use traditional data mining tools to identify abstract patterns in this extracted data. We propose a novel method for text mining with natural language processing techniques to extract the information from data base with efficient way, where the extraction time and accuracy is measured and plotted with simulation. Where the attributes of entities and relationship entities from structured and semi structured information .Results are compared with conventional methods

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

Preparation and properties of zinc doped cadmium selenide compounds by e-beam evaporation

Cd1 – xZnxSe films with different zinc content were deposited by electron beam evaporation technique onto glass substrates for the application of solid-state photovoltaic devices. The structural, surface morphological and optical properties of Cd1 – xZnxSe films have been studied in the present work. The host material, Cd1 – xZnxSe, have been prepared by the physical vapor deposition method of electron beam evaporation technique (PVD: EBE) under a pressure of 1 10 – 5 mbar. The X-ray diffractogram indicates that these alloy films are polycrystalline in nature, hexagonal structure with strong preferential orientation of the crystallites along (002) direction. Linear variation of lattice constant with composition (x) is observed. The optical properties shows that the band gap (Eg) values varies from 2.08 to 2.64 eV as zinc content varies from 0.2 to 0.8. The surface morphological studies show the very small, fine and hardly distinguishable grains smeared all over the surface. It is observed that the grain size is decreasing with increasing zinc content. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/2299