Amilcar Soares

Amilcar Soares
Memorial University of Newfoundland · Department of Computer Science

PhD in Computer Science
Assistant Professor at Memorial University of Newfoundland

About

60
Publications
15,639
Reads
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435
Citations
Introduction
I am an Assistant Professor in the Department of Computer Science at the Memorial University of Newfoundland. Before joining MUN I was a Postdoctoral fellow at the Institute for Big Data Analytics. My research interests include spatiotemporal data enrichment, segmentation, classification, clustering, and visualization.
Additional affiliations
August 2016 - April 2020
Dalhousie University
Position
  • PostDoc Position
Description
  • Research associate at the Institute for Big Data Analytics
Education
January 2012 - March 2016
Federal University of Pernambuco
Field of study
  • Computer Science
January 2011 - December 2011
Universidade Federal da Paraíba
Field of study
  • Computer Science

Publications

Publications (60)
Preprint
Full-text available
In this report, we briefly present the technical procedure and simulation steps for the 2D soccer simulation of team Cyrus. We emphasize on this document on how the prediction of teammates' behavior is performed. In our proposed method, the agent receives the noisy inputs from the server, and predicts the ball holder full state behavior. Taking adv...
Conference Paper
Full-text available
Mobility data mining has received significant interest in the literature in the last few years since social media, sensor networks, IoT, and GPS devices generate a vast amount of data. Its growth was also boosted by the growing availability of machine learning algorithms and Python libraries for trajectory analysis. However, we believe that a prope...
Technical Report
Full-text available
Soccer Simulation 2D League is one of the major leagues of RoboCup competitions. In a Soccer Simulation 2D (SS2D) game, two teams of 11 players and one coach compete against each other. The players are only allowed to communicate with the server that is called Soccer Simulation Server. This paper introduces the previous and current research of the...
Preprint
Full-text available
Soccer Simulation 2D League is one of the major leagues of RoboCup competitions. In a Soccer Simulation 2D (SS2D) game, two teams of 11 players and one coach compete against each other. The players are only allowed to communicate with the server that is called Soccer Simulation Server. This paper introduces the previous and current research of the...
Technical Report
Full-text available
Soccer Simulation 2D League is one of the major leagues of RoboCup competitions. In a Soccer Simulation 2D (SS2D) game, two teams of 11 players and one coach compete against each other. The players are only allowed to communicate with the server that is called Soccer Simulation Server. This paper introduces the previous and current research of the...
Article
Full-text available
In this paper we model spatio-temporal data describing the fishing activities in the Northern Adriatic Sea over four years. We build, implement and analyze a database based on the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and fish catch...
Preprint
Full-text available
This paper aims to model the Automatic Identification System (AIS) message transmission behavior through neural networks for forecasting the upcoming AIS messages' content for multiple vessels simultaneously in the face of messages' irregular timing. We present a set of experiments comprising tens of algorithms used for forecasting tasks with horiz...
Preprint
The environmental similarity scores between two locations are essential in ballast water risk assessment (BWRA) models used to estimate the potential for non-indigenous species introduction and guide management strategies aiming to minimize biodiversity loss and economic impacts. Previous BWRA models incorporate annual-scale environmental data, whi...
Preprint
Full-text available
This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data. It fills a void, as the existing survey articles are either much narrower in their scope or are dated. We included two important aspects that currently gain importance in mining and modeling...
Article
Full-text available
Global ballast water management aims to reduce the transport and introduction of non-indigenous species through practices such as ballast water exchange and ballast water treatment. Comprehensive enforcement to ensure vessels are meeting ballast water management requirements are a key part of success, but such activities are limited by available re...
Article
Full-text available
Recent studies on maritime traffic model the interplay between vessels and ports as a graph, which is often built using automatic identification system (AIS) data. However, only a few works explicitly study the evolution of such graphs and, when they do, generally consider coarse-grained time intervals. Our goal is to fill this gap by providing a c...
Conference Paper
Full-text available
The RoboCup competition was started in 1997, and is known as the oldest RoboCup league. The RoboCup 2D Soccer Simulation League is a stochastic, partially observable soccer environment in which 24 autonomous agents play on two opposing teams. In this paper, we detail the main strategies and functionalities of CYRUS, the RoboCup 2021 2D Soccer Simul...
Preprint
Full-text available
Trajectory data represent a trace of an object that changes its position in space over time. This kind of data is complex to handle and analyze, since it is generally produced in huge quantities, often prone to errors generated by the geolocation device, human mishandling, or area coverage limitation. Therefore, there is a need for software specifi...
Article
Full-text available
Nowadays, urban data such as demographics, infrastructure, and criminal records are becoming more accessible to researchers. This has led to improvements in quantitative crime research for predicting future crime occurrence by identifying factors and knowledge from instances that contribute to criminal activities. While crime distribution in the ge...
Preprint
Full-text available
Maritime autonomous transportation has played a crucial role in the globalization of the world economy. Deep Reinforcement Learning (DRL) has been applied to automatic path planning to simulate vessel collision avoidance situations in open seas. End-to-end approaches that learn complex mappings directly from the input have poor generalization to re...
Conference Paper
Full-text available
Soccer Simulation 2D (SS2D) is a simulation of a real soccer game in two dimensions. In soccer, passing behavior is an essential action for keeping the ball in possession of our team and creating goal opportunities. Similarly, for SS2D, predicting the passing behaviors of both opponents and our teammates helps manage resources and score more goals....
Article
Full-text available
With the recent increase in the use of sea transportation, the importance of maritime surveillance for detecting unusual vessel behavior related to several illegal activities has also risen. Unfortunately, the data collected by surveillance systems are often incomplete, creating a need for the data gaps to be filled using techniques such as interpo...
Article
Full-text available
Corrosion identification and repair is a vital task in aircraft maintenance to ensure continued structural integrity. Regarding fuselage lap joints, typically, visual inspections are followed by non-destructive methodologies, which are time-consuming. The visual inspection of large areas suffers not only from subjectivity but also from the variable...
Article
Full-text available
Trajectory mining aims to provide fundamental insights into decision-making tasks related to moving objects. A fundamental pre-processing step for trajectory mining is trajectory segmentation, where a raw trajectory is divided into several meaningful consecutive sub-sequences. In this work, we propose an unsupervised trajectory segmentation algorit...
Conference Paper
Full-text available
With the recent increase in sea transportation usage, maritime surveillance's importance to detect unusual vessel behavior related to several illegal activities has also risen. Unfortunately, the data collected by the surveillance systems are often incomplete, creating a need for the data gaps to be filled using techniques such as interpolation met...
Article
Full-text available
Building a rich and informative model from raw data is a hard but valuable process with many applications. Ship routing and scheduling are two essential operations in the maritime industry that can save a lot of resources if they are optimally designed, but still, need a lot of information to be successful. Past and recent works in the field assume...
Technical Report
Full-text available
In this report, we briefly present the technical procedure and simulation steps for the 2D soccer simulation of team Cyrus. We emphasize on this document on how the prediction of teammates' behavior is performed. In our proposed method, the agent receives the noisy inputs from the server, and predicts the ball holder full state behavior. Taking adv...
Preprint
Full-text available
Finding the factors contributing to criminal activities and their consequences is essential to improve quantitative crime research. To respond to this concern, we examine an extensive set of features from different perspectives and explanations. Our study aims to build data-driven models for predicting future crime occurrences. In this paper, we pr...
Chapter
Unmanned Surface Vehicles technology (USVs) is an exciting topic that essentially deploys an algorithm to safely and efficiently performs a mission. Although reinforcement learning is a well-known approach to modeling such a task, instability and divergence may occur when combining off-policy and function approximation. In this work, we used deep r...
Chapter
Large amounts of mobility data are being generated from many different sources, and several data mining methods have been proposed for this data. One of the most critical steps for trajectory data mining is segmentation. This task can be seen as a pre-processing step in which a trajectory is divided into several meaningful consecutive sub-sequences...
Chapter
Full-text available
The global expansion of maritime activities and the development of the Automatic Identification System (AIS) have driven the advances in maritime monitoring systems in the last decade. Given the enormous volume of vessel data continuously being generated, real-time analysis of vessel behaviors is only possible because of decision support systems pr...
Preprint
Full-text available
The global expansion of maritime activities and the development of the Automatic Identification System (AIS) have driven the advances in maritime monitoring systems in the last decade. Monitoring vessel behavior is fundamental to safeguard maritime operations, protecting other vessels sailing the ocean and the marine fauna and flora. Given the enor...
Conference Paper
Full-text available
Unmanned Surface Vehicles technology (USVs) is an exciting topic that essentially deploys an algorithm to safely and efficiently performs a mission. Although reinforcement learning is a well-known approach to modeling such a task, instability and divergence may occur when combining off-policy and function approximation. In this work, we used deep...
Article
Full-text available
Trajectory data allow the study of the behavior of moving objects, from humans to animals. Wireless communication, mobile devices, and technologies such as Global Positioning System (GPS) have contributed to the growth of the trajectory research field. With the considerable growth in the volume of trajectory data, storing such data into Spatial Dat...
Conference Paper
Full-text available
The availability of a large amount of Automatic Identification System (AIS) data has fostered many studies on maritime vessel traffic during recent years, often representing vessels and ports relationships as graphs. Although the continuous research effort, only a few works explicitly study the evolution of such graphs and often consider coarse-gra...
Chapter
Full-text available
In this paper we explore a unique, high-value spatio-temporal dataset that results from the fusion of three data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed), the corresponding fish catch reports (i.e., the quantity and type of fish caught), and relevant environmental data...
Preprint
Full-text available
The worldwide growth of maritime traffic and the development of the Automatic Identification System (AIS) has led to advances in monitoring systems for preventing vessel accidents and detecting illegal activities. In this work, we describe research gaps and challenges in machine learning for vessel behavior change and event detection, considering s...
Conference Paper
Full-text available
The detection of anomalies in vessel trajectories is a problem of great interest for all maritime surveillance systems, since it may uncover strange, suspicious or difficult situations for vessels. All the existing works in the field examine specific aspects of the problem and propose case specific tools that can hardly generalize or scale-up to a...
Conference Paper
Full-text available
Most of the trajectory datasets only record the spatio-temporal position of the moving object, thus lacking semantics and this is due to the fact that this information mainly depends on the domain expert labeling, a time-consuming and complex process. This paper is a contribution in facilitating and supporting the manual annotation of trajectory da...
Preprint
Full-text available
Transportation modes prediction is a fundamental task for decision making in smart cities and traffic management systems. Traffic policies designed based on trajectory mining can save money and time for authorities and the public. It may reduce the fuel consumption and commute time and moreover, may provide more pleasant moments for residents and t...
Preprint
Full-text available
Trajectory mining is a research field which aims to provide fundamental insights into decision-making tasks related to moving objects. One of the fundamental pre-processing steps for trajectory mining is its segmentation, where a raw trajectory is divided into several meaningful consecutive sub-sequences. In this work, we propose an unsupervised tr...
Conference Paper
Full-text available
Information deluge is a continual issue in today's military environment, creating situations where data is sometimes underutilized or in more extreme cases, not utilized, for the decision-making process. In part, this is due to the continuous volume of incoming data that presently engulf the ashore and afloat operational community. However, better...
Conference Paper
Full-text available
A first fundamental step in the process of analyzing movement data is trajectory segmentation, i.e., splitting trajecto-ries into homogeneous segments based on some criteria. Although trajectory segmentation has been the object of several approaches in the last decade, a proposal based on a semi-supervised approach remains inexistent. A semi-superv...
Article
Full-text available
Our study aims to build a machine learning model for crime prediction using geospatial features for different categories of crime. The reverse geocoding technique is applied to retrieve open street map (OSM) spatial data. This study also proposes finding hotpoints extracted from crime hotspots area found by Hierarchical Density-Based Spatial Cluste...
Article
Full-text available
Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features genera...
Conference Paper
Full-text available
Understanding transportation mode from GPS (Global Positioning System) traces is an essential topic in the data mobility domain. In this paper, a framework is proposed to predict transportation modes. This framework follows a sequence of five steps: (i) data preparation, where GPS points are grouped in trajectory samples; (ii) point features gene...
Thesis
Full-text available
The popularization of technologies for geolocated data increased the amount of trajectory data available for analysis. Moving objects’ trajectories are generated from the positions of an object that moves in the geographical space during a certain amount of time. For many applications, it is necessary to partition trajectories into smaller pieces,...
Article
Full-text available
The increasing availability and use of positioning devices has resulted in large volumes of trajectory data. However, semantic annotations for such data are typically added by domain experts, which is a time-consuming task. Machine-learning algorithms can help infer semantic annotations from trajectory data by learning from sets of labeled data. Sp...
Article
Full-text available
An important problem in the knowledge discovery of trajectories is segmentation in subparts (subtrajectories). Existing algorithms for trajectory segmentation generally use explicit criteria to create segments. In this article, we propose segmenting trajectories using a novel, unsupervised approach, in which no explicit criteria are predetermined....
Conference Paper
Full-text available
A major challenge in trajectory data analysis is the definition of approaches to enrich it semantically. In this paper, we consider machine learning and context information to enrich trajectory data in three steps: (1) the definition of a context model for trajectory domain; (2) the generation of rules based on that context model; (3) the implement...