Empirical analysis of algorithms for the shortest negative cost cycle problem

2019 ◽  
Vol 253 ◽  
pp. 167-184 ◽  
Author(s):  
Matthew Anderson ◽  
Matthew Williamson ◽  
K. Subramani
Keyword(s):  
Empirical Analysis ◽  
Analysis Of Algorithms ◽  
Negative Cost Cycle

Teaching empirical analysis of algorithms

2002 ◽  
Vol 34 (1) ◽  
pp. 321-325
Author(s):  
Ian Sanders
Keyword(s):  
Empirical Analysis ◽  
Analysis Of Algorithms

scholarly journals Análise de Complexidade do Método de Eliminação Gaussiana em GPU Através da Ferramenta EMA

2016 ◽  
Author(s):  
Anderson Zudio ◽  
Raquel De Souza ◽  
Igor Coelho ◽  
Cristiane Faria ◽  
Fabiano Oliveira
Keyword(s):  
Empirical Analysis ◽  
Analysis Of Algorithms

Neste trabalho é apresentada uma análise empírica utilizando uma nova ferramenta chamada EMA (Empirical Analysis of Algorithms). O objetivo da EMA é fornecer análises empíricas sobre o uso de recursos (tempo e espaço) de um determinado algoritmo, através de execuções iterativas sobre a implementação fornecida como entrada. Como aplicação, consideramos a resolução de sistemas lineares através do algoritmo de Eliminação Gaussiana, dividido em duas etapas. Para a primeira etapa, apresentamos uma comparação com a literatura utilizando o paralelismo das GPUs (Unidade de Processamento Gráficos), enquanto que na segunda etapa propomos um algoritmo inovador que explora o paralelismo entre threads de um mesmo bloco, de forma a obter reduções no número de passos total. A análise de complexidade de cada etapa do método em sua versão sequencial e paralela são determinadas com os recursos oferecidos pela ferramenta EMA, e também o comportamento das operações de transferência de memória entre dispositivo e hospedeiro. Palavras-Chave: Análise Empírica de Algoritmos, Sistemas de Grande Porte, Eliminação Gaussiana, Computação GPU.

An Empirical Analysis of the Obtrusiveness of and Participants' Compliance with the Electronically Activated Recorder (EAR)

2007 ◽  
Vol 23 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Matthias R. Mehl ◽  
Shannon E. Holleran
Keyword(s):  
Empirical Analysis ◽  
Sampling Method ◽  
Daily Life ◽  
Assessment Method ◽  
Data Confidentiality ◽  
Short Term ◽  
Naturally Occurring ◽  
Two Samples ◽  
Audio Recorder ◽  
Term Monitoring

Abstract. In this article, the authors provide an empirical analysis of the obtrusiveness of and participants' compliance with a relatively new psychological ambulatory assessment method, called the electronically activated recorder or EAR. The EAR is a modified portable audio-recorder that periodically records snippets of ambient sounds from participants' daily environments. In tracking moment-to-moment ambient sounds, the EAR yields an acoustic log of a person's day as it unfolds. As a naturalistic observation sampling method, it provides an observer's account of daily life and is optimized for the assessment of audible aspects of participants' naturally-occurring social behaviors and interactions. Measures of self-reported and behaviorally-assessed EAR obtrusiveness and compliance were analyzed in two samples. After an initial 2-h period of relative obtrusiveness, participants habituated to wearing the EAR and perceived it as fairly unobtrusive both in a short-term (2 days, N = 96) and a longer-term (10-11 days, N = 11) monitoring. Compliance with the method was high both during the short-term and longer-term monitoring. Somewhat reduced compliance was identified over the weekend; this effect appears to be specific to student populations. Important privacy and data confidentiality considerations around the EAR method are discussed.

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