Profiling (information science)

In information science, profiling refers to the process of construction and application of s generated by computerized data analysis. This is the use of algorithms or other mathematical techniques that allow the discovery of patterns or correlations in large quantities of data, aggregated in databases. When these patterns or correlations are used to identify or represent people, they can be called profiles. Other than a discussion of profiling technologies or population profiling, the notion of profiling in this sense is not just about the construction of profiles, but also concerns the application of s to individuals, e. g., in the cases of credit scoring, price discrimination, or identification of security risks . Profiling is being used in fraud prevention, ambient intelligence, and consumer analytics. Statistical methods of profiling include Knowledge Discovery in Databases (KDD). The profiling process The technical process of profiling can be separated in sev

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Optimizing Java on Truffle

Ekaterina Goltsova

Java on Truffle is an early-stage implementation of a Java Virtual Machine in Java. So far its development has focused on compatibility and functionality, not addressing performance in a systematic way. This thesis presents a series of experiments on Java on Truffle performance, namely adding Class Hierarchy Analysis, improving receiver profiling at callsites of virtual and interface methods, splitting methods per-callsite, delaying the collection of profiling information, and investigating and improving System.arraycopy performance.

2022

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INCLASS: Incremental Classification Strategy for Self-Aware Epileptic Seizure Detection

Giovanni Ansaloni, David Atienza Alonso, Renaud Marquis, Tomas Teijeiro Campo

Wearable Health Companions allow the unobtrusive monitoring of patients affected by chronic conditions. In particular, by acquiring and interpreting bio-signals, they enable the detection of acute episodes in cardiac and neurological ailments. Nevertheless, the processing of bio-signals is computationally complex, especially when a large number of features are required to obtain reliable detection outcomes. Addressing this challenge, we present a novel methodology, named INCLASS, that iteratively extends employed feature sets at run-time, until a confidence condition is satisfied. INCLASS builds such sets based on code analysis and profiling information. When applied to the challenging scenario of detecting epileptic seizures based on ECG and SpO2 acquisitions, INCLASS obtains savings of up to 54%, while incurring in a negligible loss of detection performance (1.1% degradation of specificity and sensitivity) with respect to always computing and evaluating all features.

2022

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Platform-independent profiling in a virtual execution environment

Philippe Moret

Virtual execution environments, such as the Java virtual machine, promote platform-independent software development. However, when it comes to analyzing algorithm complexity and performance bottlenecks, available tools focus on platform-specific metrics, such as the CPU time consumption on a particular system. Other drawbacks of many prevailing profiling tools are high overhead, significant measurement perturbation, as well as reduced portability of profiling tools, which are often implemented in platform-dependent native code. This article presents a novel profiling approach, which is entirely based on program transformation techniques, in order to build a profiling data structure that provides calling-context-sensitive program execution statistics. We explore the use of platform-independent profiling metrics in order to make the instrumentation entirely portable and to generate reproducible profiles. We implemented these ideas within a Java-based profiling tool called JP. A significant novelty is that this tool achieves complete bytecode coverage by statically instrumenting the core runtime libraries and dynamically instrumenting the rest of the code. JP provides a small and flexible API to write customized profiling agents in pure Java, which are periodically activated to process the collected profiling information. Performance measurements point out that, despite the presence of dynamic instrumentation, JP causes significantly less overhead than a prevailing tool for the profiling of Java code.

2008

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CS-486: Interaction design

This course focuses on goal-directed design and interaction design, two subjects treated in depth in the Cooper book (see reference below). To practice these two methods, we propose a design challenge, which is further divided into mini-projects evenly spaced throughout the semester.

Ciblage

Le ciblage (en marketing) est une politique consistant à choisir des populations et produits sur lesquels concentrer l'effort de l'entreprise. Le processus de choix et d'action Dans la pr

Trace numérique

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Internet privacy

Internet privacy involves the right or mandate of personal privacy concerning the storage, re-purposing, provision to third parties, and display of information pertaining to oneself via the Internet.