Recrystallization Texture Development in CP-Titanium

Most of the structural components are subjected to annealing as a final forming operation for different applications. It is therefore very important to understand/know the texture development during annealing of a material. This will decide the mechanical property of the component. Annealing texture of cubic crystal system has been widely researched, but little work has been done for the hexagonal close-packing materials. In the present study recrystallization texture development in CP-titanium was investigated. CP-titanium plates were subjected to cold rolling of 90% reduction in thickness. The rolled samples were then subjected to isochronal annealing at 5000C, 6000C and 7000C for 30minutes to obtain the recrystallization temperature, determined by EBSD analysis. Final annealing was carried out at 600oC for different soaking time: 10sec, 20sec, 1min, 2min, 5min, 10min, 20min and 30min to establish the texture development during annealing. These annealed samples were subsequently characterized under XRD (X-ray Diffraction) for bulk texture measurement. The initial deformation texture i.e. (1 1 -2 4) got attenuated with time and development of new basal orientation i.e. (0 0 0 1) and non-basal orientations i.e. (2 1 -3 7), (3 1 -4 9) and (5 1 -6 15) were observed

Sentiment Classification using Machine Learning: A Survey

The World Wide Web has brought a new way of expressing the reactions of people about any product, things, and topics, etc. The sentiment Analysis of written textual content on the web is one of the text mining areas used to find out sentiments in a given text. The process of sentiment analysis is a task of detecting, extracting and classifying critiques and sentiments expressed in texts. Twitter is also a medium with the huge amount of information wherein users can view the opinion of other users that labeled into different sentiment classes such as positive, negative, and neutral and are increasingly more developing as a key element in decision making. ?Till now, there are few extraordinary problems predominating in this research community, namely, sentiment classification, feature-based classification and dealing with negations. This paper presents a survey covering the strategies and techniques of sentiment classification and demanding situations appear within the area.

Software Effort Prediction - A Fuzzy Logic Approach

Accuracy in the estimation of software Effort/Cost is one of the desirable criteria for any software cost estimation model. The estimation of effort or cost before the actual development of any software is the most crucial task of the present day software development project managers. Software project attributes are often measured in terms of linguistic values such as very low, low, Average, high and very high. The imprecise nature of such attributes constitutes uncertainty and vagueness in their subsequent interpretation. In this paper we propose a Fuzzy logic based model for software effort prediction. We feel that fuzzy Software cost estimation Model should be able to deal with imprecision and uncertainty associated with various parameter values. Fuzzy analogy model has been developed and validated upon student data

PhishSim: Aiding Phishing Website Detection with a Feature-Free Tool

In this paper, we propose a feature-free method for detecting phishing websites using the Normalized Compression Distance (NCD), a parameter-free similarity measure which computes the similarity of two websites by compressing them, thus eliminating the need to perform any feature extraction. It also removes any dependence on a specific set of website features. This method examines the HTML of webpages and computes their similarity with known phishing websites, in order to classify them. We use the Furthest Point First algorithm to perform phishing prototype extractions, in order to select instances that are representative of a cluster of phishing webpages. We also introduce the use of an incremental learning algorithm as a framework for continuous and adaptive detection without extracting new features when concept drift occurs. On a large dataset, our proposed method significantly outperforms previous methods in detecting phishing websites, with an AUC score of 98.68%, a high true positive rate (TPR) of around 90%, while maintaining a low false positive rate (FPR) of 0.58%. Our approach uses prototypes, eliminating the need to retain long term data in the future, and is feasible to deploy in real systems with a processing time of roughly 0.3 seconds.Comment: 34 pages, 20 figure

Systemic Variety of Anaplastic Large - Cell Lymphoma

We present a case report of a patient with very aggressive course of anaplastic large-cell lymphoma. The patient had nonspecific complaints of easy fatigability and progressive breathlessness and had generalized lymphadenopathy. Initial investigations revealed pancytopenia. Bone marrow examination revealed presence of atypical cells. Liver biopsy showed portal tracts infiltrated by atypical lymphoid cells. Fine-needle aspiration of the lymph node finally confirmed anaplastic large-cell lymphoma. Patient succumbed to the illness

Giant retroperitoneal liposarcoma: report of a rare case

Retroperitoneal liposarcoma is an uncommon malignant mesenchymal tumour of adipocytic differentiation. Giant retroperitoneal liposarcoma is a rare entity which achieves such a large tumour bulk without any significant clinical symptoms due to deep seated location of the tumour. Though incidence of distant metastasis is less but local recurrence is fairly common. Surgical management is the key of management in retroperitoneal liposarcoma in spite of its large size and local invasion to vital organs. We are reporting a case of giant retroperitoneal liposarcoma of 27.5 Kg in a 45 year old female patient

Effect of seaweed saps on growth, yield, nutrient uptake and economic improvement of maize (sweet corn)

A field experiment was conducted during the rabi season of 2012-13 at Research cum Instructional Farm of Indira Gandhi Krishi Vishwavidyalaya, Raipur (Chhattisgarh) to study the effects of seaweed saps on growth, yield, nutrient uptake and economic of maize (sweet corn) in Matasi soil of Chhattisgarh. The foliar spray of two different species (namely Kappaphycus and Gracilaria) was applied thrice at different interval of crop with different concentrations (0, 2.5, 5.0, 7.5, 10.0 and 15% v/v) of seaweed extracts. Foliar applications of seaweed extract significantly enhanced the growth, yield, nutrient uptake and B:C ratio parameters. The green cob yield (189.97 q ha-1) and fodder yield (345.19 q ha-1) were recorded highest under treatment (T8) 15% G Sap + recommended dose of fertilizer (RDF) which was significant similar with treatment 15% K Sap + RDF (185.24 q ha-1) in case of green cob yield. The highest N, P and K uptake by green cob and fodder were observed under 15% G Sap + RDF (T8). Treatment 15% G Sap + RDF (T8), recorded maximum gross return (Rs. 2,07,230 ha-1), net return (Rs. 1,38,756 ha-1) and B:C ratio (2.0), which was followed by treatment 15% K Sap + RDF (T4) with net return (Rs. 1,33,199 ha-1) and B:C ratio (1.95). Treatment 15% G Sap + RDF (T8) gave Rs. 45,996 ha-1 more as compared to Water spray + RDF (T9)