Joseph Alexander Brown

AI
h-index12
3papers
13citations
Novelty10%
AI Score12

3 Papers

6.1AIAug 11, 2021
Snakes AI Competition 2020 and 2021 Report

Joseph Alexander Brown, Luiz Jonata Pires de Araujo, Alexandr Grichshenko

The Snakes AI Competition was held by the Innopolis University and was part of the IEEE Conference on Games2020 and 2021 editions. It aimed to create a sandbox for learning and implementing artificial intelligence algorithms in agents in a ludic manner. Competitors of several countries participated in both editions of the competition, which was streamed to create asynergy between organizers and the community. The high-quality submissions and the enthusiasm around the developed framework create an exciting scenario for future extensions.

2.7SEApr 24, 2018
Toward a Better Understanding of How to Develop Software Under Stress - Drafting the Lines for Future Research

Joseph Alexander Brown, Vladimir Ivanov, Alan Rogers et al.

The software is often produced under significant time constraints. Our idea is to understand the effects of various software development practices on the performance of developers working in stressful environments, and identify the best operating conditions for software developed under stressful conditions collecting data through questionnaires, non-invasive software measurement tools that can collect measurable data about software engineers and the software they develop, without intervening their activities, and biophysical sensors and then try to recreated also in different processes or key development practices such conditions.

2.4SDNov 22, 2016
MOMOS-MT: Mobile Monophonic System for Music Transcription

Munir Makhmutov, Joseph Alexander Brown, Manuel Mazzara et al.

Music holds a significant cultural role in social identity and in the encouragement of socialization. Technology, by the destruction of physical and cultural distance, has lead to many changes in musical themes and the complete loss of forms. Yet, it also allows for the preservation and distribution of music from societies without a history of written sheet music. This paper presents early work on a tool for musicians and ethnomusicologists to transcribe sheet music from monophonic voiced pieces for preservation and distribution. Using FFT, the system detects the pitch frequencies, also other methods detect note durations, tempo, time signatures and generates sheet music. The final system is able to be used in mobile platforms allowing the user to take recordings and produce sheet music in situ to a performance.