Abstract. In this article intelligent systems are placed in the context of accelerated Turing machines. Although such machines are not currently a reality, the very real gains in computing power made over previous decades require us to continually reevaluate the potential of intelligent systems. The economic theories of Adam Smith provide us with a useful insight into this question.
Abstract. The defects in macro traffic model research are pointed out firstly. In order to remedy these defects, traffic movements at the grid intersection were analyzed, and with the basic framework of the traffic transmission model, the new macro traffic model used in the paper for control simulation and evaluation has been proposed. Secondly, the bi-level optimization control model is proposed, using minimal delay and maximal throughput as its upper objectives, and optimal traffic coordination on both sides as the lower objective. A corresponding heuristic ant algorithm is subsequently designed to solve the control model. Finally, the proposed method is tested at a suppositional road network, under three different demand scenarios, compared with Transyt-7F. The results show that the proposed method has better performance, especially under high demand scenarios.
Abstract. A new spatial-frequency image enhancement algorithm via wavelet homomorphic filtering transform is proposed to enhance the contrast of an image. The wavelet analysis coefficients are processed using a high-pass filter to amplify the high spatial frequencies and attenuate the low spatial frequencies. So the object features can be emphasized while the undesired contributions within the image due to light source nonuniformity can be reduced. Experimental results show that this new algorithm can gain better performance in enhancing the local contrast of an image while maintaining its global appearance, in contrast to some representative algorithms.
Abstract. Prediction of crop yield is significant in order to accurately meet market requirements and proper administration of agricultural activities directed towards enhancement in yield. Several parameters such as weather, pests, biophysical and physio morphological features merit their consideration while determining the yield. However, these parameters are uncertain in their nature, thus making the determined amount of yield to be approximate. It is exactly here that the fuzzy logic comes into play. This paper elaborates an attempt to develop fuzzy inference systems for crop yield prediction. Physio morphological features of Sorghum were considered. A huge database (around 1000 records) of physio morphological features such as days of 50 percent flowering, dead heart percentage, plant height, panicle length, panicle weight and number of primaries and the corresponding yield were considered for the development of the model. In order to find out the sensitivity of parameters, one-to-one, two-to-one and three-to-one combinations of input and output were considered. The results have clearly shown that panicle length contributes for the yield as the lone parameter with almost one-to-one matching between predicted yield and actual value while panicle length and panicle weight in combination seemed to play a decisive role in contributing for the yield with the prediction accuracy reflected by very low RMS value.
