We are rapidly approaching the time when zero carryback will be demanded by the environmentalists and OSHA. The carryback in reference is the fines that cling to the conveyor belt after the belt's cargo has been discharged over the head pulley. Having resisted the centrifugal force to be thrown off with the cargo, these fines are sticky enough to remain on the belt. As the belt returns to the tail pulley, the idlers that support the belt and the pulleys that bend the belt, dislodge this carried back material, causing it to fall and collect in piles and the very fine particles to become airborne. Recently I visited a plant that had a 42" wide conveyor belt carrying lignite from storage into the plant. An engineer was assigned to make a study determining if the fugitive material that was creating the "DURT" " problem was coming from the belt, and if it was, what to do about it. He was undecided if it was fugitive because of carryback or because of wind effect as the wind swept across the conveyor. If indeed the problem was from wind effect, a gallery would have to be built to enclose the conveyor. Assisting in this investigation, 1 placed a carryback gauge against the bottom of the return strand of the conveyor belt near the head pulley. This gauge is a measuring device with blades that will scrape a one inch wide area when pressed against the moving belt. Any particles clinging to the belt are scraped off and collected in the container of the device. The carryback gauge was placed against the belt at three different locations across the width of the belt; in the center and 10 inches left and right of center. The removed carryback material was measured. It was found to be an average of.08 ounces in a 10 second period. The belt was traveling at 592 feet per minute.

Briefs A noise filtering method that provides the lowest possible confidence interval for every data point. Abstract A method of noise filtering based on confidence interval evaluation is described. In the case of the approximation of a function, measured with error by a polynomial or other functions that allow estimation of the confidence interval, a minimal confidence interval is used as a criterion for the selection of the proper parameters of the approximating function. In the case of the polynomial approximation optimized parameters include the degree of the polynomial, the number of points (window) used for the approximation, and the position of the window center with respect to the approximated point. The Method is demonstrated using generated and measured chromatograms. The special considerations on confidence interval evaluation and quality of polynomial fit using noise properties of the 2 data array are discussed. The Method provides the lowest possible confidence interval for every data point.

This short letter adds informative discussions to our previous contribution, \Ultimate Solution to Authentication via Memorable Password"[1]. 1

. PACS numbers: 03.67.-a, 02.50.LeThe Ultimate Solution to the Quantum Battle of the Sexes game 2 1.

. The question is: could Quantum Cryptography be the ultimate solution to secure data transmission? This paper presents some recent developments in the field and investigates the guarantees offered by the proposed protocols. 1

rigorous comparison to the related protocols. The protocols described in this contribution are from the papers, Ultimate Solution to

Digital healthcare promises for better, efficient and cost effective solutions to existing health problems. The huge amount of data produced per hospital every year is increasing at an alarming rate, and there is a requirement for data to be preserved for decades for future references and study

of achetype. However, these solutions have proved unsuccessful in resolving semantic heterogeneity in healthcare. Ontologies have also been developed to resolve this problem by making explicit the meaning of terms used in healthcare. Ontologies provide a source of shared and precisely defined terms, resulting

Abstract — The demand for analysing the data has augmented drastically. Big data is large amount of information present in the digital world around us. The data present in various formats is made accessible and when managing and storing this data and retrieval of data ought to be dynamic and prompt. Hadoop is the technology used for secure, huge amount of data. This paper provides an overview of Big Data Analysis and Hadoop technologies used. data consists of structured and unstructured data that can yield insights in solving business issues and improve customer relations. The next generation storage system is a big issue to today’s world. Storage system should support multiple protocols, scale out and up, support business process, security, and flexible architecture and leverage thin and high efficient technologies.

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