Low Cost Swarm Based Diligent Cargo Transit System

The goal of this paper is to present the design and development of a low cost cargo transit system which can be adapted in developing countries like India where there is abundant and cheap human labour which makes the process of automation in any industry a challenge to innovators. The need of the hour is an automation system that can diligently transfer cargo from one place to another and minimize human intervention in the cargo transit industry. Therefore, a solution is being proposed which could effectively bring down human labour and the resources needed to implement them. The reduction in human labour and resources is achieved by the use of low cost components and very limited modification of the surroundings and the existing vehicles themselves. The operation of the cargo transit system has been verified and the relevant results are presented. An economical and robust cargo transit system is designed and implemented.Comment: 6 pages, 9 figures, 1 block diagra

A New Feature Selection Method based on Intuitionistic Fuzzy Entropy to Categorize Text Documents

Selection of highly discriminative feature in text document plays a major challenging role in categorization. Feature selection is an important task that involves dimensionality reduction of feature matrix, which in turn enhances the performance of categorization. This article presents a new feature selection method based on Intuitionistic Fuzzy Entropy (IFE) for Text Categorization. Firstly, Intuitionistic Fuzzy C-Means (IFCM) clustering method is employed to compute the intuitionistic membership values. The computed intuitionistic membership values are used to estimate intuitionistic fuzzy entropy via Match degree. Further, features with lower entropy values are selected to categorize the text documents. To find the efficacy of the proposed method, experiments are conducted on three standard benchmark datasets using three classifiers. F-measure is used to assess the performance of the classifiers. The proposed method shows impressive results as compared to other well known feature selection methods. Moreover, Intuitionistic Fuzzy Set (IFS) property addresses the uncertainty limitations of traditional fuzzy set

On some new mixed modular equations involving Ramanujan's theta-functions

In his second notebook, Ramanujan recorded altogether 23 P–Q modular equations involving his theta functions. In this paper, we establish several new mixed modular equations involving Ramanujan’s theta-functions ϕ and ψ which are akin to those recorded in his notebook

A Convolution Neural Network Engine for Sclera Recognition

The world is shifting to the digital era in an enormous pace. This rise in the digital technology has created plenty of applications in the digital space, which demands a secured environment for transacting and authenticating the genuineness of end users. Biometric systems and its applications has seen great potentials in its usability in the tech industries. Among various biometric traits, sclera trait is attracting researchers from experimenting and exploring its characteristics for recognition systems. This paper, which is first of its kind, explores the power of Convolution Neural Network (CNN) for sclera recognition by developing a neural model that trains its neural engine for a recognition system. To do so, the proposed work uses the standard benchmark dataset called Sclera Segmentation and Recognition Benchmarking Competition (SSRBC 2015) dataset, which comprises of 734 images which are captured at different viewing angles from 30 different classes. The proposed methodology results showcases the potential of neural learning towards sclera recognition system

Phospholipase, proteinase, esterase and haemolytic activity of Candida species isolated from oral cavity and its antifungal susceptibility pattern

Background: Candida species is a normal commensal flora of human body inhabiting the skin, mucous membrane and gastro intestinal tract but may be associated with superficial and deep-seated fungal infections. The switch of Candida species from commensal to a potent pathogen, is facilitated by various extracellular hydrolytic enzymes. The aim of this study was to estimate the phospholipase, proteinase, haemolysin and esterase activity of Candida species and to determine the antifungal susceptibility. Methods: Total 100 isolates of Candida spp. were collected from diagnostic microbiology laboratories in central Kerala. Phospholipase, proteinase, esterase and haemolytic activity was determined by early defined methods of Price et al, Aoki et al, Walter Rudek and Manns et al, respectively. Results: C. tropicalis exhibited highest phospholipase, proteinase and esterase activity followed by C. albicans and C. krusei. C.albicans shows highest haemolytic activity followed by C. tropicalis and C. krusei. Conclusions: Extracellular enzymes, phospholipase, proteinase, esterase and haemolysin was detected among Candida species in the present study