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Publicações

2024

Aequitas Flow: Streamlining Fair ML Experimentation

Autores
Jesus, SM; Saleiro, P; Silva, IOe; Jorge, BM; Ribeiro, RP; Gama, J; Bizarro, P; Ghani, R;

Publicação
CoRR

Abstract

2024

On-demand 5G Private Networks using a Mobile Cell

Autores
Coelho, A; Ruela, J; Queirós, G; Trancoso, R; Correia, PF; Ribeiro, F; Fontes, H; Campos, R; Ricardo, M;

Publicação
CoRR

Abstract

2024

Understanding service ecosystem dynamics: a typology

Autores
As'ad, N; Patrício, L; Koskela-Huotari, K; Edvardsson, B;

Publicação
JOURNAL OF SERVICE MANAGEMENT

Abstract
PurposeThe service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this understanding by developing a typology of service ecosystem dynamics that explains the varying interplay between change and stability within the service environment through distinct behavioral patterns exhibited by service ecosystems over time. Design/methodology/approachThis study builds upon a systematic literature review of service ecosystems literature and uses system dynamics as a method theory to abductively analyze extant literature and develop a typology of service ecosystem dynamics. FindingsThe paper identifies three types of service ecosystem dynamics-behavioral patterns of service ecosystems-and explains how they unfold through self-adjustment processes and changes within different systemic leverage points. The typology of service ecosystem dynamics consists of (1) reproduction (i.e. stable behavioral pattern), (2) reconfiguration (i.e. unstable behavioral pattern) and (3) transition (i.e. disrupting, shifting behavioral pattern). Practical implicationsThe typology enables practitioners to gain a deeper understanding of their service environment by discerning the behavioral patterns exhibited by the constituent service ecosystems. This, in turn, supports them in devising more effective strategies for navigating through it. Originality/valueThe paper provides a precise definition of service ecosystem dynamics and shows how the identified three types of dynamics can be used as a lens to empirically examine change and stability in the service environment. It also offers a set of research directions for tackling service research challenges.

2024

Decision Aid Tool to Mitigate Quality of Service Asymmetries in Distribution Networks

Autores
Macedo, P; Fidalgo, JN;

Publicação
2024 20TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM 2024

Abstract
This article presents a methodology to estimate the evolution of QoS indices, based on investments and maintenance costs carried out in the DN. The indices were estimated at various disaggregated levels, including the global index, 3 different QoS zones (urban, semi-urban and rural) and 278 municipalities, thereby facilitating the mitigation of QoS asymmetries by allocating investments and maintenance actions to specific regions. To achieve this objective, an optimization problem was formulated to allocate investments and maintenance costs to municipalities with higher improvement benefit-cost ratios, potentially exhibiting lower levels of QoS. This methodology was adopted by the Portuguese DSO to establish the future investments plan from 2023 to 2027. The results demonstrate estimations of good performance, considering the stochastic nature of the phenomena affecting QoS (e.g. atmospheric conditions), which are included in this study, thus developing confidence levels for the global indices.

2024

Mammogram Retrieval System: Aggregating Image Classifiers for Enhanced Breast Cancer Diagnosis

Autores
Roriz, C; Moreira, I; Vasconcelos, V; Domingues, I;

Publicação
ACM International Conference Proceeding Series

Abstract
Breast cancer remains a significant global health concern. This study presents an image retrieval system to aid specialists in the analysis of mammogram images. The system employs individual classifiers for eight dimensions: laterality, view, breast density, BI-RADS classification, masses, calcifications, distortions, and asymmetries. Four pre-trained networks, ResNet50, VGG16, InceptionV3, and InceptionResNetV2, were used to train these classifiers. The retrieval model combines these classifiers through a weighted sum. Four weight assignment strategies were explored, ranging from equal weights to weights based on empirical, literature-based, and specialist-informed considerations. Results are illustrated using the INBreast database, which comprises 410 images. Besides the native annotations, ground truth to validate retrieval models had to be acquired. Classification accuracy is as high as 100% for some of the dimensions. Results also demonstrate the effectiveness of the proposed weighted-sum approach, with variations in weight assignments impacting model performance. © 2024 Owner/Author.

2024

Harnessing Parasitic Cavity as Reference for Low Coherence Systems

Autores
Robalinho P.; Rodrigues A.; Novais S.; Lobo Ribeiro A.B.; Silva S.; Frazão O.;

Publicação
2024 IEEE Photonics Conference, IPC 2024 - Proceedings

Abstract
This work presents an implementation of a reference optical cavity based on parasitic cavities on a low coherence interferometric system. This method allows a maximization of the number of sensors to be implemented without occupying additional reading channels.

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