2022
Autores
Reis, D; Piedade, B; Correia, FF; Dias, JP; Aguiar, A;
Publicação
IEEE ACCESS
Abstract
Cloud computing and Infrastructure-as-Code (IaC), supported by technologies such as Docker, have shaped how many software systems are built and deployed. Previous research has identified typical issues for some types of IaC specification but not why they come to be, or they have delved into collaboration aspects but not into technical ones. This work aims to characterize the activities around two particular kinds of IaC specification-Dockerfiles and docker-compose.yml files. We seek to know how they can be better supported and therefore study also what approaches and tools practitioners employ. We used an online questionnaire to gather data. The first part of the study reached 68 graduate students from a study program on informatics engineering, and the second one 120 professional software developers. The results show that most of the activities of the process of developing a Dockerfile are perceived as time-consuming, especially when the respondents are beginners with this technology. We also found that solving issues using trial-and-error approaches is very common and that many developers do not use ancillary tools to support the development of Dockerfiles and docker-compose.yml files.
2022
Autores
Carvalho, G; Pereira, ME; Silva, C; Deuermeier, J; Kiazadeh, A; Tavares, V;
Publicação
AIP ADVANCES
Abstract
This study explores the resistive switching phenomena present in 4 mu m(2) amorphous Indium-Gallium-Zinc Oxide (IGZO) memristors. Despite being extensively reported in the literature, not many studies detail the mechanisms that dominate conduction on the different states of IGZO-based devices. In this article, we demonstrate that resistive switching occurs due to the modulation of the Schottky barrier present at the bottom interface of the device. Furthermore, thermionic field emission and field emission regimes are identified as the dominant conduction mechanisms at the high resistive state of the device, while the bulk-limited ohmic conduction is found at the low resistive state. Due to the high complexity associated with creating compact models of resistive switching, a data-driven model is drafted taking systematic steps. (C) 2022 Author(s).
2022
Autores
Bamber, D; Collins, HE; Powell, C; Goncalves, GC; Johnson, S; Manktelow, B; Ornelas, JP; Lopes, JC; Rocha, A; Draper, ES;
Publicação
BMC MEDICAL RESEARCH METHODOLOGY
Abstract
Background The small sample sizes available within many very preterm (VPT) longitudinal birth cohort studies mean that it is often necessary to combine and harmonise data from individual studies to increase statistical power, especially for studying rare outcomes. Curating and mapping data is a vital first step in the process of data harmonisation. To facilitate data mapping and harmonisation across VPT birth cohort studies, we developed a custom classification system as part of the Research on European Children and Adults born Preterm (RECAP Preterm) project in order to increase the scope and generalisability of research and the evaluation of outcomes across the lifespan for individuals born VPT. Methods The multidisciplinary consortium of expert clinicians and researchers who made up the RECAP Preterm project participated in a four-phase consultation process via email questionnaire to develop a topic-specific classification system. Descriptive analyses were calculated after each questionnaire round to provide pre- and post- ratings to assess levels of agreement with the classification system as it developed. Amendments and refinements were made to the classification system after each round. Results Expert input from 23 clinicians and researchers from the RECAP Preterm project aided development of the classification system's topic content, refining it from 10 modules, 48 themes and 197 domains to 14 modules, 93 themes and 345 domains. Supplementary classifications for target, source, mode and instrument were also developed to capture additional variable-level information. Over 22,000 individual data variables relating to VPT birth outcomes have been mapped to the classification system to date to facilitate data harmonisation. This will continue to increase as retrospective data items are mapped and harmonised variables are created. Conclusions This bespoke preterm birth classification system is a fundamental component of the RECAP Preterm project's web-based interactive platform. It is freely available for use worldwide by those interested in research into the long term impact of VPT birth. It can also be used to inform the development of future cohort studies.
2022
Autores
Duarte Silva; Nuno A. Silva; Tiago D. Ferreira; Carla C. Rosa; Ariel Guerreiro;
Publicação
EPJ Web of Conferences
Abstract
2022
Autores
Santo, A; Santos, A; Mamede, HS;
Publicação
2022 17TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)
Abstract
IoT devices that perform translation are often closed proprietary systems which offer no, or very limited, possibilities of being freely integrated with other IoT devices or systems/platforms and cannot be easily updated. The objective of this paper is to offer a Systematic Literature Review (SLR) approach to find and synthesise articles on IoT applications in machine translation and potential integration and interoperability functionalities, along with challenges that arise from it. This research identified IoT based projects/devices that implemented machine translation solutions, including ones that resorted to low-cost devices such as the raspberry pi, as well as challenges faced by IoT devices when it comes to integration/interoperability. The findings in this paper provide a way to become more familiar with IoT based machine translation devices/projects and IoT integration/interoperability challenges, as well as proposing new paths for research.
2022
Autores
Teixeira, AC; Ribeiro, J; Neto, A; Morais, R; Sousa, JJ; Cunha, A;
Publicação
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022)
Abstract
Insect pests are the main cause of loss of productivity and quality in crops worldwide. Insect monitoring becomes necessary for the early detection of pests and thus avoiding the excessive use of pesticides. Automatic detection of insects attracted by traps is a form of monitoring. Modern data-driven methods present great results for object detection when representative datasets are available, but public datasets for insect detection are few and small. Pest24 public dataset is extensive, but noisy resulting in a poor detection rate. In this work, we aim to improve insect detection in the Pest24 dataset. We propose the creation of three sub-datasets selecting the highest represented classes, the highest colour discrepancy, and the one with the highest relative scale, respectively. Several Faster R-CNN and YOLOv5 architectures are explored, and the best results are achieved with the YOLOv5 with an mAP of 95.5%.
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