Fluctuations in crude oil price significantly impact the global economic market. A rise or a fall leads to redistribution of wealth in both oil-exporting and importing countries. Under such background, efficient and accurate predictions for crude oil price are critical for a stable economic development. However, crude oil price forecasting has been proved to be an extremely tough task, due to i...

Sheet metal is one of the most important semi-finished products used in automobiles, domestic appliances, aircraft and other familiar products. Therefore sheet metal forming technology is an important engineering discipline in the area of mechanical engineering. In sheet metal forming, wipe bending process plays a major role in which the sheet metal tries to return to its original shape after r...

A zinc oxide nanorod ammonia microsensor integrated with a readout circuit on-a-chip fabricated using the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process was investigated. The structure of the ammonia sensor is composed of a sensitive film and polysilicon electrodes. The ammonia sensor requires a post-process to etch the sacrificial layer, and to coat the sensitive fil...

While much research work has been devoted to analysis and prediction of individuals’ behavior in social networks, very few studies about the analysis of business networks are conducted. Empowered by recent research on automated mining of business networks, this paper illustrates the design of a novel business network-based model called Energy Cascading Model (ECM) for the analysis and predictio...

The menu-cost interpretation of sticky prices implies that the probability of a price change should depend on the past history of prices and fundamentals only through the gap between the current price and the frictionless price. We find that this prediction is broadly consistent with the behavior of 9 Philadelphia gasoline wholesalers. We nevertheless reject the menu-cost model as a literal des...

In the last decade, prediction markets became popular forecasting tools in areas ranging from election results to movie revenues and Oscar nominations. One of the features that make prediction markets particularly attractive for decision support applications is that they can be used to answer “what if” questions and estimate probabilities of complex events. Traditional approach to answering suc...

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor’s gains. This paper proposes a machine learning model to predict stock market price. The proposed algorithm integrates Particle swarm optimization (PSO) and least squ...

Data Mining is being actively applied to stock market since 1980s. It has been used to predict stock prices, stock indexes, for portfolio management, trend detection and for developing recommender systems. The various algorithms which have been used for the same include ANN, SVM, ARIMA, GARCH etc. Different hybrid models have been developed by combining these algorithms with other algorithms li...

We conducted preference assessments with 4 typically developing children to identify potential reinforcers and assessed the reinforcing efficacy of those stimuli. Next, we tested two predictions of economic theory: that overall consumption (reinforcers obtained) would decrease as the unit price (response requirement per reinforcer) increased and that the cost and benefit components that defined...