The determination of molecular structures is of growing importance in modern chemistry and biology. This thesis presents two practical, systematic algorithms for two structure determination problems. Both algorithms are branch-and-bound techniques adapted to their respective domains. The rst problem is the determination of structures of multimers given rigid monomer structures and (potentially ...

In this paper, we propose an analytical and methodological comparison between two of the most known distance-based methods in the evaluation of the geographic concentration of economic activity. These two methods are Ripley’s K function, a cumulative function popularised by Marcon and Puech (2003) that counts the average number of neighbours of each point within a circle of a given radius, and ...

We improve by an exponential factor the best known asymptotic upper bound for the density of sets avoiding 1 in Euclidean space. This result is obtained by a combination of an analytic bound that is an analogue of Lovász theta number and of a combinatorial argument involving finite subgraphs of the unit distance graph. In turn, we straightforwardly obtain an asymptotic improvement for the measu...

plant population density (ppd) and nitrogen (n) have large effects on chickpea growth and yield. to study these effects on chickpea (var. kourosh) a factorial experiment (4×3) in randomized complete block design with four replications was carried out at research farm of college of agriculture & natural science, karaj (iran) in 2006. four ppd treatments were 16, 32, 48 and 64 plant m-2 and n amo...

Clustering is an important data exploration task. Its use in data mining is growing very fast. Traditional clustering algorithms which no longer cater to the data mining requirements are mod#ed increasingly. Clustering algorithms are numerous which can be divided in several categories. Two prominent categories are distance-based and density-based (e.g. K-means and DBSCAN, respectively). While K...

Line transects have been widely applied for the estimation of animal abundance because they are regarded as simple, economical, and relatively precise. The recent development of automated techniques for the estimation of animal density from distance sampling data allows greater potential for ®eld biologists and wildlife managers to become involved in the analytical summary of their research. An...

Estimating a discrepancy between two probability distributions from samples is an important task in statistics and machine learning. There are mainly two classes of discrepancy measures: distance measures based on the density difference, such as the Lp-distances, and divergence measures based on the density ratio, such as the φ-divergences. The intersection of these two classes is the L1-distan...

Distance or similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that are applicable to compare two probability density functions, pdf in short, are reviewed and categorized in both syntactic and semantic relationships. A correlation coefficient and a hierarchical clustering ...

The mixing of sea and river water can be used as a renewable energy source. The Gibbs free energy that is released when salt and fresh water mix can be captured in a process called reverse electrodialysis (RED). This research investigates the effect of the intermembrane distance and the feedwater flow rate in RED as a route to double the power density output. Intermembrane distances of 60, 100,...