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Tarcisio H. C. Pequeno

dblp:69/3857 · DBLP profile ↗
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7ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 2Databases, data management, data science and information retrieval · 2 · 1 first-authorTheory of computation · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorComputer networks · 1Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Knowledge representation and reasoning · 100%
Theoretical computer science
1 paper
Logic in computer science · 100%
Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 77% Programming languages and type systems · 23%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › logic in computer science › logical foundations › non-classical logics
epistemic logic
0.011991
The Logic of Epistemic Inconsistency · KR 1991
Compilers and program optimization › program transformation
program derivation
0.011979
Program Derivation Using Data Types: A Case Study · IEEE Trans. Software Eng. 1979
YearPublicationVenuePosition
2019 Pareto set as a model for dispatching resources in emergency Centres
Ricardo Guedes, Vasco Furtado, Tarcisio H. C. Pequeno, Joel J. P. C. Rodrigues
Peer-to-Peer Netw. Appl.3
2015 Multi-objective evolutionary algorithms and multiagent models for optimizing police dispatch
abstract
In this article we investigate Multi-agent simulation and Multi-objective Evolutionary Algorithms for optimizing resource allocation in Public Safety. We describe a tool that helps Law Enforcement authorities to evaluate, in a controlled environment, different strategies for allocating and dispatching resources, aiming at reducing conflicting goals such as response time, the number of unattended calls and cost of displacement of police cars. This tool is a multi-agent model to represent police cars that lives in a grid in which emergency occurrences appear. A comparison of the strategies for resource dispatch in this environment shows that serving first those calls with low estimated attendance times delivers the best overall performance in terms of waiting time. However this is practically impossible since prioritization of certain crime types is necessary leading to the increase of the waiting time in the queue. Instead of manually trying to identify the best allocation strategy to apply, we have coupled a multi-objective evolutionary algorithm to the simulation model in order to uncover automatically a function to rank the calls in the best order for attendance satisfying multiple and sometimes conflicting goals.
Ricardo Guedes, Vasco Furtado, Tarcisio H. C. Pequeno
ISI3
2010 Natural Language Processing based on Semantic inferentialism for extracting crime information from text
abstract
This article describes an architecture for Information Extraction systems on the web, based on Natural Language Processing (NLP) and especially geared toward the exploration of information about crime. The main feature of the architecture is its NLP module, which is based on the Semantic Inferential Model. We demonstrate the feasibility of the architecture through the implementation thereof to provide input for a collaborative web-based system of registering crimes called WikiCrimes.
Vládia Pinheiro, Vasco Furtado, Tarcisio H. C. Pequeno, Douglas Nogueira
ISI3
2009 Information Extraction from Text Based on Semantic Inferentialism
Vládia Pinheiro, Tarcisio H. C. Pequeno, Vasco Furtado, Douglas Nogueira
FQAS2
1991 The Logic of Epistemic Inconsistency
Tarcisio H. C. Pequeno, Arthur Buchsbaum
KR1
1979 An Approach for Data Type Specification and Its Use in Program Verification
Tarcisio H. C. Pequeno, Carlos José Pereira de Lucena
Inf. Process. Lett.1
1979 Program Derivation Using Data Types: A Case Study
abstract
The present paper discusses some issues in program synthesis by relating the idea of systematic program derivation with the concepts of data type and correctness of data representation. The notion of an incomplete definition of a data type at a high level of abstraction is introduced. The ideas are illustrated through an example previously discussed in the literature by D. Gries.
Carlos José Pereira de Lucena, Tarcisio H. C. Pequeno
IEEE Trans. Software Eng.2