96 documents found, page 1 of 10
MSBN-SPose: A Multi-Scale Bayesian Neuro-Symbolic approach for sitting posture ...
Tavares, Adriano; Carlos Lima; Lima, Carlos; Gomes, Tiago Manuel Ribeiro; Liang, YanchunPosture recognition is critical in modern educational and office environments for preventing musculoskeletal disorders and maintaining cognitive performance. Existing methods based on human keypoint detection typically rely on convolutional neural networks (CNNs) and single-scale features, which limit representation capacity and suffer from overfitting under small-sample conditions. To address these issues, we ...
RAOCSL: a BERT-based strategy for identifying learner confusion under class imb...
Zhao, Tongyu; Gao, Jiaying; Feng, Yu; Zu, Yatong; Tavares, Adriano; Gomes, Tiago Manuel Ribeiro; Pinto, Sandro; Xu, HaoUnderstanding and identifying the nature of learner confusion is important for online learning platforms. In this study, we address this problem by analyzing forum posts from large-scale online courses. However, due to the large volume of comments and frequent interactions, confusion posts are often overlooked. Existing methods and models, while capable of detecting confusion, typically rely on linguistic featu...
An improved public key cryptographic algorithm based on chebyshev polynomials a...
Zhang, Chunfu; Liang, Yanchun; Tavares, Adriano; Wang, Lidong; Gomes, Tiago Manuel Ribeiro; Pinto, SandroDue to its very desirable properties, Chebyshev polynomials are often used in the design of public key cryptographic systems. This paper discretizes the Chebyshev mapping, generalizes the properties of Chebyshev polynomials, and proposes an improved public key encryption algorithm based on Chebyshev chaotic mapping and RSA, i.e., CRPKC −Ki. This algorithm introduces alternative multiplication coefficients Ki, t...
EmoPrompt-ECPE: emotion knowledge-aware Prompt-tuning for Emotion-Cause Pair Ex...
Gu, Xue; Zhou, Zhihan; Meng, Ziyao; Li, Jian; Gomes, Tiago Manuel Ribeiro; Tavares, Adriano; Xu, HaoEmotion-cause pair extraction (ECPE) main focus is on extracting all potential emotion clauses and corresponding cause clauses from unannotated documents. Existing methods achieve promising results with the help of fine-tuning and prompt paradigms, but they present three downsides. First, most approaches cannot distinguish between the emotion-cause pairs that belong to different types of emotions, limiting the ...
GEML: a graph-enhanced pre-trained language model framework for text classifica...
Yu, Tao; Song, Rui; Pinto, Sandro; Gomes, Tiago Manuel Ribeiro; Tavares, Adriano; Xu, HaoLarge-scale Pre-trained Language Models (PLMs) have become the backbones of text classification due to their exceptional performance. However, they treat input documents as independent and uniformly distributed, thereby disregarding potential relationships among the documents. This limitation could lead to some miscalculations and inaccuracies in text classification. To address this issue, some recent work expl...
EEEC: Emotion-Experiencer-Event-Cause multi-step chain reasoning for Emotion-Ca...
Gu, Xue; Meng, Ziyao; Gomes, Tiago Manuel Ribeiro; Tavares, Adriano; Xu, HaoEmotion-cause pair extraction (ECPE) aims to identify all emotion and cause clauses in documents, forming emotion-cause pairs (ECPs). Although existing methods have achieved some success, they face issues such as overlooking the impact of emotion experiencers, failing to leverage specific domain knowledge, and tending to spurious correlations. To address these issues, we transform the ECPE task into a multi-ste...
Design of an energy supply and demand forecasting system based on web crawler a...
Lin, Gang; Liang, Yanchun; Tavares, AdrianoAn energy supply and demand forecasting system can help decision-makers grasp more comprehensive information, make accurate decisions and even plan a carbon-neutral future when adjusting energy structure, developing alternative energy resources and so on. This paper presents a hierarchical design of an energy supply and demand forecasting system based on web crawler and a grey dynamic model called GM(1,1) which...
ChamelIoT: a tightly- and loosely-coupled hardware-assisted OS framework for lo...
Silva, Miguel; Gomes, Tiago; Ekpanyapong, Mongkol; Tavares, Adriano; Pinto, SandroThe evergrowing Internet of Things (IoT) ecosystem continues to impose new requirements and constraints on every device. At the edge, low-end devices are getting pressured by increasing workloads and stricter timing deadlines while simultaneously are desired to minimize their power consumption, form factor, and memory footprint. Field-Programmable Gate Arrays (FPGAs) emerge as a possible solution for the increa...
SecureQNN: introducing a privacy-preserving framework for QNNs at the deep edge
Costa, Miguel Ângelo Peixoto; Gomes, Tiago; Cabral, Jorge; Monteiro, João L.; Tavares, Adriano; Pinto, SandroRecent concerns about real-time inference and data privacy are making Machine Learning (ML) shift to the edge. However, training efficient ML models require large-scale datasets not available for typical ML clients. Consequently, the training is usually delegated to specific Service Providers (SP), which are now worried to deploy proprietary ML models on untrusted edge devices. A natural solution to increase th...
Social behavioral sensing: an exploratory study to assess learning motivation a...
Yu Feng; Tongyu Zhao; Jian Li; Yatong Zu; Tavares, Adriano; Gomes, Tiago Manuel RibeiroLearning motivation plays a crucial role in student’s daily study life since it greatly affects academic performance and engagement. Perceived relatedness, based on self-determined theory, is an important predictor of learning motivation. Today, assessment for both of them still relies on subjective evaluations and self-reports, which is time-consuming and onerous. Hence, we propose a novel approach blended wit...