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On the Use of Deep Learning Models for Automatic Animal Classification of Native Species in the Amazon
Camera trap image analysis, although critical for habitat and species conservation, is often a manual, time-consuming, and expensive task. Thus,... -
Spatial Shrinkage Prior: A Probabilistic Approach to Model for Categorical Variables with Many Levels
One of the most commonly used methods to prevent overfitting and select relevant variables in regression models with many predictors is the penalized... -
Efficient Motor Learning Through Action-Perception Cycles in Deep Kinematic Inference
How does the brain adapt to slow changes in the body’s kinematic chain? And how can it perform complex operations that need tool use? Here, we... -
Dynamical Perception-Action Loop Formation with Developmental Embodiment for Hierarchical Active Inference
To adapt an autonomous system to a newly given cognitive goal, we propose a method to dynamically combine multiple perception-action loops. Focusing... -
Contextual Qualitative Deterministic Models for Self-learning Embodied Agents
This work presents an approach for embodied agents that have to learn models from the least amount of prior knowledge, solely based on knowing which... -
Comparative Analysis of Uppaal SMC, ns-3 and MATLAB/Simulink
IoT networks connect everyday devices to the internet to communicate with one another and humans. It is more cost-effective to analyse and verify the... -
Machine Learning Data Suitability and Performance Testing Using Fault Injection Testing Framework
Creating resilient machine learning (ML) systems has become necessary to ensure production-ready ML systems that acquire user confidence seamlessly.... -
A Literature Survey of Assertions in Software Testing
Assertions are one of the most useful automated techniques for checking program’s behaviour and hence have been used for different verification and... -
Formalization and Verification of MQTT-SN Communication Using CSP
The MQTT-SN protocol is a lightweight version of the MQTT protocol and is customized for Wireless Sensor Networks (WSN). It removes the need for the... -
Learning in Uppaal for Test Case Generation for Cyber-Physical Systems
We propose a test-case generation method for testing cyber-physical systems by using learning and statistical model checking. We use timed game... -
A Software Package (in progress) that Implements the Hammock-EFL Methodology
This poster paper presents a software package (in progress) that implements the Hammock-EFL approach for Project Management and Parallel Programming,... -
A Federated Learning Algorithms Development Paradigm
At present many distributed and decentralized frameworks for federated learning algorithms are already available. However, development of such a... -
The Importance of Knowing the Arrival Order in Combinatorial Bayesian Settings
We study the measure of order-competitive ratio introduced by Ezra et al. [16] for online algorithms in Bayesian combinatorial settings. In our... -
Nash Stability in Fractional Hedonic Games with Bounded Size Coalitions
We consider fractional hedonic games, a natural and succinct subclass of hedonic games able to model many real-world settings in which agents have to... -
Online Nash Welfare Maximization Without Predictions
The maximization of Nash welfare, which equals the geometric mean of agents’ utilities, is widely studied because it balances efficiency and fairness... -
Equilibrium Analysis of Customer Attraction Games
We introduce a game model called “customer attraction game” to demonstrate the competition among online content providers. In this model, customers... -
Target-Oriented Regret Minimization for Satisficing Monopolists
We study a robust monopoly pricing problem where a seller aspires to sell an item to a buyer. We assume that the seller, unaware of the buyer’s... -
AutomaTutor: An Educational Mobile App for Teaching Automata Theory
Automata theory is one of the core theories in computer science because it allows scientists and practitioners to understand the complexity of... -
An Embodied Conversational Agent to Support Wellbeing After Injury: Insights from a Stakeholder Inclusive Design Approach
Embodied conversational agents (ECAs) are increasingly being included in digital health and wellbeing programs. Whilst initial evaluations of ECAs in... -
DROP DASH: A Persuasive Mobile Game to Promote Healthy Hydration Choices Using Machine Learning
The increasing consumption of unhealthy beverages is a significant public health concern, contributing to a range of health issues. Recognized as...