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Publications

2025

CountPath: Automating Fragment Counting in Digital Pathology

Authors
Vieira, AB; Valente, M; Montezuma, D; Albuquerque, T; Ribeiro, L; Oliveira, D; Monteiro, JC; Gonçalves, S; Pinto, IM; Cardoso, JS; Oliveira, AL;

Publication
CoRR

Abstract
Quality control of medical images is a critical component of digital pathology, ensuring that diagnostic images meet required standards. A pre-analytical task within this process is the verification of the number of specimen fragments, a process that ensures that the number of fragments on a slide matches the number documented in the macroscopic report. This step is important to ensure that the slides contain the appropriate diagnostic material from the grossing process, thereby guaranteeing the accuracy of subsequent microscopic examination and diagnosis. Traditionally, this assessment is performed manually, requiring significant time and effort while being subject to significant variability due to its subjective nature. To address these challenges, this study explores an automated approach to fragment counting using the YOLOv11 and Vision Transformer models. Our results demonstrate that the automated system achieves a level of performance comparable or even superior to that of experts, offering a reliable and efficient alternative to manual counting. Additionally, we present findings on interobserver variability, showing that the automated approach achieves an accuracy of 90.1%, surpassing the range observed among experts (82-88%). This result further supports its suitability for integration into routine pathology workflows. © 2025 IEEE.

2025

Intelligent Inventory Rotation and Revenue Optimization Using Integer Linear Programming: A Coffee Shop Case Study

Authors
Haghdadi, A; Zolfagharnasab, MH; Damari, S; Vakili, S;

Publication
OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, OL2A 2025, PT I

Abstract
This study employs Integer Linear Programming (ILP) to optimize gross profit for a local coffee shop, addressing challenges in inventory management and sale revenue optimization. A dataset comprising of 40 menu items and 34 ingredients was developed, incorporating constraints such as capital budget, ingredient availability, costs, and sales ratios to simulate monthly revenue. By applying the ILP methodology, the study achieved a gross profit margin of 42.28% of total sales revenue within a single month, underscoring its efficacy in improving profitability. The sensitivity analysis indicated that an increase in budget resulted in a proportional rise in sales revenue and gross profit, while inventory costs escalated at a comparatively slower pace. The research pinpointed high-performing items, including coffee, tea, and cold beverages, as significant contributors to profit, thereby highlighting the necessity for effective inventory management.

2025

A Comparison Between Decentralized Coordination Mechanisms for TSO-DSO Interaction: Hierarchical and Distributed Approaches

Authors
Simoes, M; Madureira, AG; Lopes, JAP;

Publication
2025 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE, ISGT EUROPE

Abstract
The deployment of a large number of Distributed Energy Resources (DERs) at the Distribution Network (DN) level brings a much needed level of demand-side flexibility that power systems characterized by a large integration level of Renewable Energy Sources (RESs) require, and will increasingly require in the future. However, until now, the potential of this growing flexibility is under-exploited, as it is not shared with the Transmission Network (TN) level. To harness this valuable flexibility for the benefit of the overall electric power system, efficient and effective coordination mechanisms must be established. This paper compares the two main categories of coordination approaches between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) proposed in the literature, hierarchical and distributed mechanisms. The comparison focuses on the computational effort, operational cost, and RES integration level, highlighting the respective advantages and drawbacks of each coordination model.

2025

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation

Authors
Eriksson, M; Purificato, E; Noroozian, A; Vinagre, J; Chaslot, G; Gómez, E; Llorca, DF;

Publication
CoRR

Abstract

2025

Standing on a common ground: a comparison of static stability approaches for pallet loading

Authors
Mazur, PG; Gamer, FC; Ramos, AG; Schoder, D;

Publication
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH

Abstract
At the practical level, the static stability constraint is one of the most important constraints in practical pallet loading problems, such as air cargo palletizing. Approaches to modeling static stability, which range from base support and mechanical equilibrium calculations to physical simulation, differ in workflow, focus, and assumptions, so choosing the right static stability approach has a substantial impact on the quality of the solution and, ultimately, on loading security. To date, little research has investigated the structural differences between approaches. The aim of this paper is to integrate knowledge and shed light on the applicability of the different approaches for the practical scenario of air cargo palletizing. We tackle this problem through (1) a reformulation and extension of static stability toward loading stability, (2) a conceptual analysis of current approaches, and (3) benchmarking that employs an independent multibody simulation on multiple heterogeneous datasets. Our results show that all approaches are prone to structure errors and vary significantly in their premises and information usage. Further, full base support is revealed to be the most restrictive approach by far, while physical simulation achieves the greatest accuracy. Given the trade-off between accuracy and runtime, the mechanical equilibrium approach is a good choice, while partial base support performs best for lower support values.

2025

Emotion-Enhanced Pain Assessment Protocol

Authors
Alves, B; Almeida, A; Silva, C; Pais, D; Ribeiro, RP; Gama, J; Fernandes, JM; Brás, S; Sebastiao, R;

Publication
HUMAN AND ARTIFICIAL RATIONALITIES. ADVANCES IN COGNITION, COMPUTATION, AND CONSCIOUSNESS, HAR 2024

Abstract
Pain is a highly subjective phenomenon that depends on multiple factors. The common methods used to evaluate pain require the person to be awakened and cooperative, which may not always be possible. Moreover, such methods are subject to non-quantifiable influences, namely the impact of an individual's emotional state on how pain is perceived or how negative emotions may exacerbate pain perception, while positive emotions may attenuate it. The goal of this study was to conduct a novel protocol for pain induction with emotional elicitation and assess its feasibility. In this protocol, the physiological responses were monitored, and collected, through Electrocardiogram, Electrodermal Activity, and surface Electromyogram signals. Along the protocol, the pain perception was evaluated using a 0-10 numerical rating scale and by registering the time from the pain stimulus beginning to the Pain and Tolerance Thresholds. This study comprised three emotional sessions, negative, positive, and neutral, which were performed through videos of excerpts of terror, comedy, and documentary films, respectively, followed by pain induction using the Cold Pressor Task (CPT). A total of 56 participants performed the study, with a CPT mean time of about 91.70 +/- 39.64 s among all the sessions. The conducted protocol was considered feasible and safe as it allowed the collection of physiological data, pain, and questionnaires' reports from 56 participants, without any harm to them. Moreover, the collected data can be further used to assess how emotional conditions influence pain perception and to provide better emotion-calibrated pain recognition systems based on physiological signals.

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