Clustering merupakan metode pengelompokan dalam suatu database informasi berdasarkan kondisi tertentu. Penelitian ini menerapkan masalah perhitungan k-means clustering dengan pendekatan jarak euclidean manhattan. Metode yang terbentuk bertujuan untuk membandingkan segi proses pengerjaan antara Hasil nya berupa perbandingan Euclidean Manhattan dapat menentukan titik-titik pusat penyebaran penyak...

School of Computing and Mathematical Sciences University of Greenwich London, United Kingdom {ie903, et701, M.Ghassemian}@greenwich.ac.uk This work is a simulation based comparison of three Mobile Ad Hoc Networks (MANETs) routing protocols – Destination Sequenced Distance Vector (DSDV), Ad hoc on demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The comparison is based on their pe...

High-dimensional vectors are ubiquitous in algorithms and this lecture seeks to introduce some common properties of these vectors. We encounter the so-called curse of dimensionality which refers to the fact that algorithms are simply harder to design in high dimensions and often have a running time exponential in the dimension. We also show that it is possible to reduce the dimension of a datas...

Phenotype MicroArray (PM) technology is high-throughput phenotyping system and is directly applicable to assay the effects of genetic changes in cells. In this study, we performed comprehensive PM analysis using single gene deletion mutants of central metabolic pathway and related genes. To elucidate the structure of central metabolic networks in Escherichia coli K-12, we focused 288 different ...

This paper considers performance of mobile ad hoc network (MANET) routing protocols with respect to group and entity mobility models. The three widely used routing protocols have been investigated and compared: Destination Sequenced Distance Vector (DSDV), Ad-hoc On-demand Distance Vector (AODV) and Dynamic Source Routing (DSR). Mobility models encompass: Reference Point Group Mobility (RPGM), ...

This paper addresses the issue of measuring similarity between pieces of uncertain information in the framework of possibility theory. In a first part, natural properties of such functions are proposed and a survey of the few existing measures is presented. Then, a new measure so-called Information Affinity is proposed to overcome the limits of the existing ones. The proposed function is based ...

We present an integer linear formulation that uses the so-called “distance variables” to solve the quadratic assignment problem (QAP). The model involves O(n) variables. Valid equalities and inequalities are additionally proposed. We further improved the model by using metric properties as well as an algebraic characterization of the Manhattan distance matrices that Mittelman and Peng [28] rece...

In the present research work, we deal with the problem of authorship attribution of ancient Arabic text documents, which were written by several ancient philosophers. For that purpose, we conducted several authorship attribution experiments applied with different text sizes. A special dataset, called “A4P” (Authorship Attribution for Ancient Arabic Philosophers), has been constructed by extract...

Drought resistance breeding provides a hopeful way to improve yield and quality of wheat in arid and semiarid regions. Constructing core collection is an efficient way to evaluate and utilize drought-resistant germplasm resources in wheat. In the present research, 1,683 wheat varieties were divided into five germplasm groups (high resistant, HR; resistant, R; moderate resistant, MR; susceptible...

We describe a data structure, a rectangular complex, that can be used to represent hyperconvex metric spaces that have the same topology (although not necessarily the same distance function) as subsets of the plane. We show how to use this data structure to construct the tight span of a metric space given as an n × n distance matrix, when the tight span is homeomorphic to a subset of the plane,...