Efficient computation of Morse-Smale complexes for three-dimensional scalar functions

The Morse-Smale complex is an efficient representation of the gradient behavior of a scalar function, and critical points paired by the complex identify topological features and their importance. We present an algorithm that constructs the Morse-Smale complex in a series of sweeps through the data, identifying various components of the complex in a consistent manner. All components of the complex, both geometric and topological, are computed, providing a complete decomposition of the domain. Efficiency is maintained by representing the geometry of the complex in terms of point sets.     

Scalable parallel data mining for association rules

The authors propose two new parallel formulations of the Apriori algorithm (R. Agrawal and R. Srikant, 1994) that is used for computing association rules. These new formulations, IDD and HD, address the shortcomings of two previously proposed parallel formulations CD and DD. Unlike the CD algorithm, the IDD algorithm partitions the candidate set intelligently among processors to efficiently parallelize the step of building the hash tree. The IDD algorithm also eliminates the redundant work inherent in DD, and requires substantially smaller communication overhead than DD. But IDD suffers from the added cost due to communication of transactions among processors. HD is a hybrid algorithm that combines the advantages of CD and DD. Experimental results on a 128-processor Cray T3E show that HD scales just as well as the CD algorithm with respect to the number of transactions, and scales as well as IDD with respect to increasing candidate set size     

Residual phosphate fertilizer compounds in soils

A variety of P compounds can accumulate in soils as residues of fertilizer and may influence soil test versus plant yield relationships. This work evaluates specific chemical extractants for their capacity to identify such Al, Fe and Ca phosphates in soils as a basis for increasing the precision of yield prediction. Aluminium phosphate, iron phosphate, calcium phosphate (apatite) and P sorbed onto gibbsite, goethite and calcite were added to four Western Australian lateritic soils. These soils were then subjected to sequential selective extraction using a modified Chang and Jackson procedure in order to evaluate the selectivity of these extractants for the different forms of P with the sequence of extraction: 1 M NH₄Cl, 0.5 M NH₄F, 0.1 M NaOH + 1 M NaCl, citrate-dithionite-bicarbonate (CDB), 1 M NaOH and 1 M HCl. The results show that the procedure is not sufficiently specific and thus might be of little value for estimating the forms and amounts of residues of phosphate rock fertilizers in soils.     

Analysis of temporal jitter in a copper vapor laser system

Temporal jitter in a magnetic pulse compression based copper vapor laser (CVL) system is analyzed by considering ripple present in the input dc power supply and ripple present in the magnetic core resetting power supply. It is shown that the jitter is a function of the ratio of operating voltage to the designed voltage, percentage ripple, and the total propagation delay of the magnetic pulse compression circuit. Experimental results from a CVL system operating at a repetition rate of 9 kHz are presented.     

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.     

Composite indicator for railway infrastructure management

Railway Engineering Science - The assessment and analysis of railway infrastructure capacity is an essential task in railway infrastructure management carried out to meet the required quality and...