Publisher's Synopsis
Encyclopaedia of Operational Research in the Design of Electronic Data Processing Systems covers the use of automated methods to process commercial data. Electronic Data Processing Systems are used for account and customer master files, booking and ticketing transactions to an airline's reservation system, billing for utility services. Electronic data processing refers to the use of automated methods to process commercial data. The text Electronic Data Processing in Practice offers a broad range of coverages about electronic data processing beneficial to any professional services business that uses computers. Electronic data processing coverage includes items like hardware, software and communications equipment. A study on security technique of cloud data processing in electronic commerce has been revealed in first chapter. An application of online analytical processing (OLAP) technology for analyzing the bibliographic data has been presented in second chapter. In third chapter, we deal with probabilistic, statistical and algorithmic aspects of the similarity of texts and application to gospels comparison. In fourth chapter, we investigate the problem of efficient feature selection for classification on high dimensional datasets. A comparison of several existing texture feature extraction techniques when applied to several popular texture benchmark sets has been performed in fifth chapter. Time series modelling with application to Tanzania inflation data has been examined in sixth chapter. Seventh chapter discusses how to improve the optical character recognition (OCR) of low contrast, small fonts, and dark background forms using correlated zoom and resolution technique (CZRT). In eighth chapter, a new K-means clustering method has been proposed to evaluate the cluster customers' profitability in telecommunication industry in Sri Lanka. Ninth chapter focuses on improved algorithm for imbalanced data and small sample size classification. Sentiment analysis on the social networks using stream algorithms has been presented in tenth chapter. The objective of eleventh chapter is to perform a data driven calibration algorithm, which takes the data collected from two radars and derives the speed correction factor. A feature selection method for large-scale network traffic classification based on spark has been focused in twelfth chapter. Thirteenth chapter discusses the big data uses in the marketing information system and its contribution for decision-making. Fourteenth chapter presents a design of a data processing circuit for receiving digital signals from front end-electronic board chips of a specific nuclear detector, encoding and triggering them via specific optical links operating at a specific frequency. Fifteenth chapter compares the firm merging electronic data interchange (EDI) with just-in-time (JIT) inventory management, to the firm with traditional inventory methods for the purpose of determining the impact of both methods on reducing inventory cost. Sixteenth chapter introduces a data processing scheme for a wireless data transmission application via mud. The goal of seventeenth chapter is to present and discuss the concepts surrounding data modeling and data analytics, and their evolution for three representative approaches: operational databases, decision support databases and big data technologies. Last chapter describes the application of model-based data transmission (MBDT) to gravitational data and characterizes its utility and performance.
