EXAMINING THE CRB INDEX AS AN INDICATOR FOR U.S. INFLATION

This paper analyzes historical movements in the commodity futures market and the relationship to inflation. Specifically, the relationship between the Commodity Research Bureau (CRB) Index and United States inflation is investigated. It is said that the relationship between the CRB index and the U.S. inflation rate was greater in the some periods than in another period. Then in recent times the CRB Index has proven to be a reliable early indicator of inflation. As the composition of the United States economy changes, the Commodity Research Bureau must make adjustments in order to provide a viable service.CRB index, Commodities Research Bureau, inflation, Vector Autoregression, Marketing, Public Economics, E00, E30,

Input and output of energy in processing gizzard pickle

Data were collected from seven replicates to quantify the input of commercial energy in manual processing of oil based (OB) as well as vinegar-based (VB) chicken gizzard pickles and output of caloric values from the products was calculated. Higher amounts of electrical (0.691 kWh) and total energy (9.792 kWh) with lesser inputs of human energy were required in preparation of VB pickle compared with 0.3 (0.597 kWh) and 8.731 M]lkg of raw gizzard products. However, more caloric outputs were obtained from OB product (282 Cal/l00g) compared with VB (261 Cal/l00g) pickle. Despite significant superiority of oil-based gizzard pickle for colour, juiciness and tenderness, the overall acceptability of pickles was insignificantly different. Proximate analysis revealed non significant variations in pH, moisture content and crude protein of the two pickles. Based on the input output energy relations, it is concluded that processing of experimental VB gizzard pickle is economically cost effective (67 Call rupee) over the oil-based (56 Cal/rupee) chicken gizzard pickle

QUASI-PARA-SASAKIAN MANIFOLD ADMITTING ZAMKOVOY CONNECTION

The purpose of the present study is to deduce some curvature properties of quasi-para-Sasakian manifold equipped with respect to Zamkovoy connection. In the present article we have studied Locally $\phi$-symmetric quasi-para-Sasakian manifold, $\phi$-recurrent quasi-para-Sasakian manifold, Locally projective $\phi$-symmetric quasi-para-Sasakian manifold, $\phi$-projectively flat quasi-para-Sasakian manifold, pseudo-quasi-conformally flat quasi-para-Sasakian manifold,  $\phi$-pseudo-quasi-conformally flat quasi-para-Sasakian manifold with respect to Zamkovoy connection. Also we have shown that the quasi-para-Sasakian manifold with respect to Zamkovoy connection $\bar{\nabla}$ satisfying $\bar{\tilde{V}}(\xi, U).\bar{S}=0,$ where $\bar{\tilde{V}}$ and $\bar{S}$ are the pseudo-quasi-conformal curvature tensor and Ricci tensor with respect to Zamkovoy connection respectively

A non destructive method to detect the incipient fault in rolling element bearing

It is essential to have prior warning of incipient fault (s) in any critical equipment occurring due to vibration. Vibration monitoring is good nondestructive technique to detect the fault of machines at an early stage. Capturing vibration signature of machines at slow speed is a difficult task due to impact of low energy, mostly absorbed by the structural path and falls much below the cut off frequency of the normally available accelerometer. To resolve the issue, a systematic proce-dure has been developed. It has the facility to break the signal in different level, envelope capturing and finally convert to frequency spectrum. The system has been tested under various operating condition that suits to industry to diagnose the problem of bearing. The method can predict the problem very well at its inception

Sentiment analysis and classification of Indian farmers’ protest using twitter data

Protests are an integral part of democracy and an important source for citizens to convey their demands and/or dissatisfaction to the government. As citizens become more aware of their rights, there has been an increasing number of protests all over the world for various reasons. With the advancement of technology, there has also been an exponential rise in the use of social media to exchange information and ideas. In this research, we gathered data from the microblogging website Twitter concerning farmers’ protest to understand the sentiments that the public shared on an international level. We used models to categorize and analyze the sentiments based on a collection of around 20,000 tweets on the protest. We conducted our analysis using Bag of Words and TF-IDF and discovered that Bag of Words performed better than TF-IDF. In addition, we also used Naive Bayes, Decision Trees, Random Forests, and Support Vector Machines and also discovered that Random Forest had the highest classification accuracy