Gabriel Spadon

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Verified

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• Doctor of Philosophy
• Professor (Assistant) at Dalhousie University

Time-series forecasting is one of the most active research topics in artificial intelligence. A still open gap in that literature is that statistical and ensemble learning approaches systematically present lower predictive performance than deep learning methods. They generally disregard the data sequence aspect entangled with multivariate data repr...

Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting ecosystems and inflicting substantial economic damages across agriculture, forestry, and fisheries. Due to the fast growth of global trade and transportation networks, NIS has been introduced and spread unintentionally in new environments. This study develops...

Predicting vessel trajectories is crucial for enhancing situational awareness and preventing collisions at sea. However, achieving accurate and efficient predictions is challenging due to the heterogeneity in vessel movement patterns and changes in vessel mobility modes during voyages. To address this, we propose a new approach that uses historical...

Efficiently handling Automatic Identification System (AIS) data is vital for enhancing maritime safety and navigation, yet is hindered by the system’s high volume and error-prone datasets. This paper introduces the Automatic Identification System Database (AISdb), a novel tool designed to address the challenges of processing and analyzing AIS data....

Efficiently handling Automatic Identification System (AIS) data is vital for enhancing maritime safety and navigation, yet is hindered by the system's high volume and error-prone datasets. This paper introduces the Automatic Identification System Database (AISdb), a novel tool designed to address the challenges of processing and analyzing AIS data....

Seaports play a crucial role in the global economy, and researchers have sought to understand their significance through various studies. In this paper, we aim to explore the common characteristics shared by important ports by analyzing the network of connections formed by vessel movement among them. To accomplish this task, we adopt a bottom-up ne...

Aquatic invasive species are a significant threat to biodiversity and ecosystems worldwide. Due to the fast growth of global trade and transportation networks, non-native species have been introduced and spread unintentionally in new environments. These invasive species can damage ecosystems by disrupting the balance, out-competing native species,...

The growing prevalence of location-based devices has resulted in a signicant abundance of location data from various tracking vendors. Nevertheless, a noticeable decit exists regarding readily accessible, extensive, and publicly available datasets for research purposes, primarily due to privacy concerns and ownership constraints. There is a pressin...

Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data play a significant role in tracking vessel activity and mapping mobility patterns such as those found during fishing activities. Accordingly, this paper proposes a geometric-driven se...

Sleep disorders pose serious cardiovascular threats if not treated effectively. However, adherence to Continuous Positive Airway Pressure (CPAP), the most recommended therapy, is known to be challenging to monitor. Telemonitored CPAP equipment has improved the follow-up of CPAP adherence (hours of use per night) by producing far larger amounts of d...

Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data plays a significant role in tracking vessel activity and mapping mobility patterns such as those found in fishing. Accordingly, this paper proposes a geometric-driven semi-supervised...

The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered. Such data comes from the oceans and their surface, such as Automatic Identification System (AIS) messages used for tracking vessels' trajectories. AIS messages are transmitted over radio or satellite at ideally periodic...

Graphs have often been used to answer questions about the interaction between real-world entities by taking advantage of their capacity to represent complex topologies. Complex networks are known to be graphs that capture such non-trivial topologies; they are able to represent human phenomena such as epidemic processes, the dynamics of populations,...

The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered. Such data comes from the oceans and their surface, such as Automatic Identification System (AIS) messages used for tracking vessels’ trajectories. AIS messages are transmitted over radio or satellite at ideally periodic...

The relationship between different entities is a property that can be represented as a graph, structured sets formed by entities (i.e., vertices) and relationships (i.e., edges). Graphs have often been used to answer questions about the interaction between entities from the real world by analyzing their vertices and edges (i.e., the graph's topolog...

Building a velocity model is essential in seismic exploration and is used at all stages, including acquisition, processing and interpretation of seismic data. Reconstructing a subsurface image from seismic wavefields recorded at the surface (seismograms) requires accurate knowledge of the propagation velocities between the recording location and th...

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...

The supplemental material contains material that is not included within the paper itself.

Pesticides have been heavily used in the cultivation of major crops, contributing to the increase of crop production over the past decades. However, in many cases their appropriate use and calibration of machines rely upon dated evaluation methodologies that cannot precisely estimate how well the pesticides' are being applied to the crop. A few str...

The interest for patient trajectory prediction, a sort of computer-aided medicine, has steadily increased with the pace of artificial intelligence innovation. Notwithstanding, the design of effective systems able to predict clinical outcomes based on the history of a patient is far from trivial. Works so far are based on neural architectures with l...

Pesticide application has been heavily used in the cultivation of major crops, contributing to the increase of crop production over the past decades. However, their appropriate use and calibration of machines rely upon evaluation methodologies that can precisely estimate how well the pesticides' spraying covered the crops. A few strategies have bee...

Time-series forecasting is one of the most active research topics in predictive analysis. A still open gap in that literature is that statistical and ensemble learning approaches systematically present lower predictive performance than deep learning methods as they generally disregard the data sequence aspect entangled with multivariate data repres...

Recursive queries are one of the main mechanisms in Relational Database Management Systems to process topology-aware, or graph-like, queries. However, existing works focus only on optimizing the recursive query statements and processing, disregarding the potential physical arrangements that might improve performance. In this work, we propose to use...

Pesticide application has been heavily used in the cultivation of major crops, contributing to the increase of crop production overthe past decades. However, their appropriate use and calibration of machines rely upon evaluation methodologies that can preciselyestimate how well the pesticides’ spraying covered the crops. A few strategies have been...

Automated medical prognosis has gained interest as artificial intelligence evolves and the potential for computer-aided medicine becomes evident. Nevertheless, it is challenging to design an effective system that, given a patient's medical history, is able to predict probable future conditions. Previous works, mostly carried out over private datase...

Human mobility has a significant impact on several layers of society, from infrastructural planning and economics to the spread of diseases and crime. Representing the system as a complex network, in which nodes are assigned to regions (e.g., a city) and links indicate the flow of people between two of them, physics-inspired models have been propos...

Human mobility has a significant impact on several layers of society, from infrastructural planning and economics to the spread of diseases and crime. Representing the system as a complex network, in which nodes are assigned to regions (e.g., a city) and links indicate the flow of people between two of them, physics-inspired models have been propos...

We propose an algebraic tool-set and related algorithms to track access problems not obviously observed in urban environments represented as street mashes. Our tool-set assumes that points of interest must be promptly accessible within the paths of a street network. Over that assumption, we introduce formalisms and computational tools to detect and...

As redes complexas contribuem para a pesquisa computacional por sua capacidade de projetar sistemas modelados por vértices e arestas. Eles fornecem meios para descrever estruturas urbanas por meio das malhas viárias, expressando predicados que se referem ao fluxo e ao transporte em zonas urbanas. Este trabalho tem o objetivo de descrever as interaç...

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis proces...

Databases and Distributed Systems have a fundamental relevance in Computer Science; they are usually presented in courses where the high-level of abstraction characterizes the teaching and learning processes. Consequently, the teaching method needs to evolve to fulfill the present requirements. Therefore, grounded in these concepts, the main goal o...

Pantanal is one of the most important biomes of the world, with a large number of wild animal species, some of them are in extinction. The automatic identification of wild animals is extremely important for the estimation of the species' population within Pantanal. However, digital processing techniques for the identification and tracking of specie...

Relational Database Management Systems (RDBMSs) are widely employed in several applications, including those that deal with data modeled as graphs. Existing solutions store every edge in a distinct row in the edge table, however, for most cases, such modeling does not provide adequate performance. In this work, we propose Edge-k, a technique to gro...

Relational Database Management Systems (RDBMSs) are widely employed in several applications, including those that deal with data modeled as graphs. Existing solutions store every edge in a distinct row in the edge table, however, for most cases, such modeling does not provide adequate performance. In this work, we propose Edge-k, a technique to gro...

Complex networks provide a means to describe cities through their street mesh, expressing characteristics that refer to the structure and organization of an urban zone. Although other studies have used complex networks to model street meshes, we observed a lack of methods to characterize the relationship between cities by using their topological fe...

Complex networks can be used for modeling street meshes and urban agglomerates. With such a model, many aspects of a city can be investigated to promote a better quality of life to its citizens. Along these lines, this paper proposes a set of distance-based pattern-discovery algorithmic instruments to improve urban structures modeled as complex net...

Complex networks provide a means to describe cities through their street mesh, expressing characteristics that refer to the structure and organization of an urban zone. Although other studies have used complex networks to model street meshes, we observed a lack of methods to characterize the relationship between cities by using their topological fe...

For a long time, data has been treated as a general problem because it just represents fractions of an event without any relevant purpose. However, the last decade has been just about information and how to get it. Seeking meaning in data and trying to solve scalability problems, many frameworks have been developed to improve data storage and its a...

The need for higher agricultural productivity has demanded the intensive use of pesticides. However, their correct use depends on assessment methods that can accurately predict how well the pesticides' spraying covered the intended crop region. Some methods have been proposed in the literature, but their high cost and low portability harm their wid...

Complex networks can be used for modeling street meshes and urban agglomerates. With such a model, many aspects of a city can be investigated to promote a better quality of life to its citizens. Along these lines, this paper proposes a set of distance-based pattern-discovery algorithmic instruments to improve urban structures modeled as complex net...

This paper aims at introducing a methodology focused on student-centered learning and aided by an educational collaborative and graphical tool. Through it, we enable students to interact with abstract topics as well as interact with each other. Our motivation was the lack of capability to represent knowledge and abstractions faced by students that...

Street networks are complex networks that represent the topology and geometry of cities; as so, they can be used to solve problems related to ill-designed urban structures. This application, in real urban scenarios, has been the focus of several types of research, from cities characterization to transportation enhancement. Nevertheless, these works...

Complex networks are commonly used to model urban street networks, which allows aiding the analysis of criminal activities in cities. Despite several works focusing on such application, there is a lack of a clear methodology focused in the analysis of crime behavior. In this sense, we propose a methodology for employing complex networks in the anal...

The need for higher agricultural productivity has demanded the intensive use of pesticides. However, their correct use depends on assessment methods that can accurately predict how well the pesticides' spraying covered the intended crop region. Some methods have been proposed in the literature, but their high cost and low portability harm their wid...

Presentation of the dissertation submitted to the Institute of Mathematics and Computer Sciences – ICMC-USP, in partial fulfillment of the requirements for the degree of the Master Program in Computer Science and Computational Mathematics.

Cities are complex systems of transportation and social activity; their structure can be used to model urban street networks - i.e. complex network that represents the geometry of a city - allowing analytical activities for data-driven decision-making. The geometry of a city holds intrinsic information that can support activities related to the ana...

Here we show that epidemic propagation models, allied with network mapping techniques and community-related measures, can aid in the characterization of criminal behavior and dispersion in a city.

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis proces...

Theoretical Computer Science area (TCS) stands out by being an important study field, and it is composed by Formal Languages and Automata Theory (FLA), Computer Science Theory (CST), and Theory of Compilers (TC). This area is responsible for introducing the beginnings of the Computer Science through formalisms - which represent a set of methods, te...

Formal languages and automata (FLA) theory have fundamental relevance to the base of knowledge in the computer science area, especially focusing on scientific education. Usually presented by a discipline, the teaching-learning process of FLA is characterized by the high level of abstraction, and it is considered difficult due to the complexity of l...

Having as starting point the study of accessibility and urban mobility of patients with Amyotrophic Lateral Sclerosis (ALS) we identify the importance of the internet in order to health promotion. As this disease affects motor neurons, making it impossible for the time, the movement of arms and legs as well as speech and breathing capabilities, the...

The usage of information technology, mainly space, are important methodological mechanisms to evaluate the impact and how different phenomenon act in space. Geography and epidemiology has made usage from space categories to explain the behavior of diseases, overlaying information composed by specialization of the phenomenon. The mainly goal of this...

One of many challenges in a web information systems is the capability of staying stable and available as the number of users and requests increase rapidly, what we call scalability. This paper provides a model based on development of events-oriented applications, non-blocking in the environment Node.JS with the non-relational database model (MongoD...

The data growth enhances the need of a method and paradigms responsible to deal with high scalability, reliability and fault tolerance in large amounts of data. Big Data generalize frameworks capable of dealing with this need. This research makes usage of Apache Hadoop, and a Virtual Private Server (VPS) to analyze the performance through benchmark...