activity
20162022
most citedCharacterizing Classes of Potential Outliers through Traffic Data Set Data Signature 2D nMDS Projection

3 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

cs.DS20221 cited

Some Optimization Solutions for Relief Distribution

Jhoirene Clemente, Jessie James Suarez, Olivia Demetria +2

Humanitarian logistics remain a challenging area of application for operations research. In relief distribution, the main goal is to deliver all the supplies to those that are in n…

cs.DS2017

Reoptimization of the Closest Substring Problem under Pattern Length Modification

Jhoirene B. Clemente, Henry N. Adorna

This study investigates whether reoptimization can help in solving the closest substring problem. We are dealing with the following reoptimization scenario. Suppose, we have an opt…

cs.OH20173 cited

Characterizing Classes of Potential Outliers through Traffic Data Set Data Signature 2D nMDS Projection

Erlo Robert F. Oquendo, Jhoirene B. Clemente, Jasmine A. Malinao +1

This paper presents a formal method for characterizing the potential outliers from the data signature projection of traffic data set using Non-Metric Multidimensional Scaling (nMDS…

cs.DC2016

PROJECTION Algorithm for Motif Finding on GPUs

Jhoirene B. Clemente, Francis George C. Cabarle, Henry N. Adorna

Motif finding is one of the NP-complete problems in Computational Biology. Existing nondeterministic algorithms for motif finding do not guarantee the global optimality of results…

cs.DS2016

On Self-Reducibility and Reoptimization of Closest Substring Problem

Jeffrey Aborot, Henry Adorna, Jhoirene Clemente

In this paper, we define the reoptimization variant of the closest substring problem (CSP) under sequence addition. We show that, even with the additional information we have about…