A new nonlinear neural mapping (N2M) technique based on the combined use of Kohonen self-organizing map (KSOM), minimum spanning tree (MST), and nonlinear mapping (NLM) is introduced for optimal test series selection. With the N2M method, KSOM results are enhanced by the visualization of the actual distances between the loaded neurons from MST and NLM. N2M provides an easily interpretable and c...

We present a novel self-stabilizing algorithm for minimum spanning tree (MST) construction. The space complexity of our solution is O(log n) bits and it converges in O(n) rounds. Thus, this algorithm improves the convergence time of all previously known selfstabilizing asynchronous MST algorithms by a multiplicative factor Θ(n), to the price of increasing the best known space complexity by a fa...

We introduce the weak gap property as a variant of the gap property. We show that in any metric space of bounded doubling dimension, any directed graph whose vertex set S has size n and which satisfies the weak gap property has total weight O(wt(MST (S)) log n), where wt(MST (S)) denotes the weight of a minimum spanning tree of S. We show that 2-optimal TSP tours and greedy spanners satisfy the...

We show how to compute single-source shortest paths in undirected graphs with non-negative edge lengths in O( p nm/B logn+ MST (n, m)) I/Os, where n is the number of vertices, m is the number of edges, B is the disk block size, and MST (n, m) is the I/O-cost of computing a minimum spanning tree. For sparse graphs, the new algorithm performs O((n/ √ B) logn) I/Os. This result removes our previou...

Given a 2-node connected, undirected graph G = (V,E), with n nodes and m edges with real weights, and given a minimum spanning tree (MST) T = (V, ET ) of G, we study the problem of finding, for every node v ∈ V , the MST of G− v = (V \ {v}, E \ Ev), where Ev is the set of edges incident to v in G. We show that this problem can be solved in O(min(m ·α(n, n),m+ n log n)) time and O(m) space. Our ...

The Innovation of Artifacts is somewhat can be seen as a process of evolution. The paper presents an endeavor to view the evolution of artifact by using evolutionary concept of memetics. We showed the ways to build a phlyomemetic tree based on memes constituting an artifact to infer or estimate the evolutionary history and relationship between artifacts. UPGMA algorithm and the Shortest Tree Me...

This paper describes a new framework for microarray gene-expression data clustering. The foundation of this framework is a minimum spanning tree (MST) representation of a set of multi-dimensional gene expression data. A key property of this representation is that each cluster of the expression data corresponds to one subtree of the MST, which rigorously converts a multi-dimensional clustering p...

The Steiner problem is an NP-hard optimization problem which consists of finding the minimal-length tree connecting a set of N points in the Euclidean plane. Exact methods of resolution currently available are exponential in N , making exact minimal trees accessible for only small size problems (up to N ≈ 100). An acceptable suboptimal solution is provided by the minimum spanning tree (MST) whi...

The sensor nodes used in Wireless Sensor Networks (WSN) perform close-range sensing in any environment and are compact, battery-powered, light-weight devices. The overall network performance depends on the routing protocols in the network layer and the flow control protocols at the data link layer. This study proposes a novel routing protocol by adapting the Minimum Spanning Tree (MST), Low-Ene...

We present a set of analyses aiming at quantifying the amount of information filtered by di↵erent hierarchical clustering methods on correlations between stock returns. In particular we apply, for the first time to financial data, a novel hierarchical clustering approach, the Directed Bubble Hierarchical Tree (DBHT), and we compare it with other methods including the Linkage and k-medoids. In p...