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Empirical characterization of graph sampling algorithms
Graph sampling allows mining a small representative subgraph from a big graph. Sampling algorithms deploy different strategies to replicate the...
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An empirical study of task infections in Ansible scripts
ContextDespite being beneficial for managing computing infrastructure at scale, Ansible scripts include security weaknesses, such as hard-coded...
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On Empirical Regularities in the JSM Method of Automated Research Support
Abstract —This article defines the set of inference rules for JSM reasoning. Hypotheses concerning the causes generated by these rules form empirical...
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Come for syntax, stay for speed, understand defects: an empirical study of defects in Julia programs
Julia has emerged as a popular programming language to develop scientific software, in part due to its flexible syntax akin to scripting languages...
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Empirical study on meta-feature characterization for multi-objective optimization problems
Algorithm recommendation based on meta-learning was studied previously. The research on the meta-features extraction, which is a key for the success...
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On Rank r Empirical Regularities in the JSM Method of Automated Research Supporta
AbstractThe article deals with extensions of empirical regularities (ER) for r periods, where r > 1. Various types of ER constitute a lattice....
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Efficient Characterization of Cough Sounds Using Statistical Analysis
Cough serves as a principal symptom in respiratory conditions. Variations in cough sound characteristics provide valuable diagnostic insights. There...
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An ensemble deep learning model with empirical wavelet transform feature for oral cancer histopathological image classification
Oral squamous cell carcinoma (OSCC) has become quite prevalent across many countries, and poor prognosis is one of the major reasons for the ensuing...
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Machine learning experiment management tools: a mixed-methods empirical study
Machine Learning (ML) experiment management tools support ML practitioners and software engineers when building intelligent software systems. By...
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An Empirical Analysis of Machine Learning Efficacy in Anti-Ransomware Tools
Researchers attempt to develop more competent anti-ransomware tools that assisted by machine learning classifiers to mitigate the threats of...
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Remote sensing image classification using modified random forest with empirical loss function through crowd-sourced data
Environmental changes are captured as satellite images and stored in datasets for monitoring a particular location. These remote sensing images can...
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Bayesian active learning approach for estimation of empirical copula-based moment-independent sensitivity indices
The moment-independent global sensitivity method is an important branch among the prosperous developments of global sensitivity analysis. It can...
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How far are we with automated machine learning? characterization and challenges of AutoML toolkits
Automated Machine Learning aka AutoML toolkits are low/no-code software that aim to democratize ML system application development by ensuring rapid...
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An empirical characterization of community structures in complex networks using a bivariate map of quality metrics
Community detection emerges as an important task in the discovery of network mesoscopic structures. However, the concept of a “good” community is...
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Machine learning based altitude-dependent empirical LoS probability model for air-to-ground communications
Line-of-sight (LoS) probability prediction is critical to the performance optimization of wireless communication systems. However, it is challenging...
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A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation
Understanding the microstructure–property relationships of porous media is of great practical significance, based on which macroscopic physical...
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Performance characterization of containerization for HPC workloads on InfiniBand clusters: an empirical study
Containerization technology offers an appealing alternative for encapsulating and operating applications (and all their dependencies) without being...
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An empirical study of vulnerabilities in edge frameworks to support security testing improvement
Edge computing is a distributed computing paradigm aiming at ensuring low latency in modern data intensive applications (e.g., video streaming and...
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The Multiscale Maximum Change Algorithm for Subsurface Characterization
The characterization of subsurface formations is a formidable task due to the high dimension of the stochastic space involved in the solution of...
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An Empirical Study on the Urgent Self-admitted Technical Debt
Technical Debt (TD) refers to the phenomenon of taking shortcuts to achieve short-term gains at the cost of higher maintenance effort in the future....