ABSTRACT
COVID-19 is currently a global pandemic with worldwide magnitude and transversal implications. In Sri Lanka, during several island-wide curfews imposed since March 2020 and up to now, the agriculture industry's stakeholders and consumers have been coming across several challenges such as food scarcity, dramatic price fluctuations of commodities, and difficulties in searching of market for both product buying and selling. Also, communities have faced challenges related to the timely purchase of planting materials and other agro-inputs (fertilizers and pesticides), loss of income, inadequacy of reliable advices and directions, and market uncertainties, which have demoralized them with no clear way forward. This blockage created a sudden imbalance of the entire value chain of agriculture industry affecting almost all stakeholders. Electronic representation of physical entities-such as local fairs and mega trading hubs driven by computer intelligence services-are believed in this study to be viable solutions to overcome most of the above-mentioned challenges. Therefore, this study proposes a smart-agriculture support system naming it as Electronic Partner for Agro Services (EPAS), which would seamlessly connect farmers, consumers, and other relevant stakeholders of the agriculture value chain in the virtual space electronically. The system intends to regulate price for goods and services while organizing a balanced supply and demand in more informative and intelligent manner, thus provisioning electronic financial accounting facilities for subscribers. Timely dissemination of knowledge, advice, financial services and linking agro-input suppliers are also embedded into the proposed model. The Design Science Research (DSR) Methodology was adopted in this study in developing the EPAS conceptual model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
ABSTRACT
The COVID-19 pandemic halted scientific research across the world, revealing the vulnerabilities of field-based disciplines to disruption. To ensure resilience in the face of future emergencies, archaeology needs to be more sustainable with international collaboration at the forefront. This article presents a collaborative data collection model for documenting lithics using digital photography and physical measurements taken in-situ by local collaborators. Data capture protocols to optimise standardisation are outlined, and guidelines are provided for data curation, storage and sharing. Adopting collaborative research strategies can have long-term advantages beyond the COVID-19 pandemic, by encouraging knowledge-sharing between international collaborators, decreasing emissions associated with archaeological research, and improving accessibility for those who are not able to travel for access to international samples. This article proposes that archaeology should use the COVID-19 pandemic as a catalyst for change through encouraging deeper collaborations and the development of remote models of science as a complement to in-person research.
ABSTRACT
This article presents the aims, technical processes, and initial results of the Arch-I-Scan Project, which is using artificial intelligence and machine learning to enhance the collection of Roman ceramic data so that these data can contribute more effectively to improved understandings of Roman foodways. The project is developing a system for the automated identification of ceramic types (fabrics, forms and sizes), and potentially the automated collation of the resulting datasets, to facilitate more holistic recording of these big archaeological data, and avoiding the current time-consuming and costly specialist process for classifying these artefacts. The particular focus of the project is to develop datasets that are suitable for inter- and intra-site analyses of eating and drinking behaviours in the Roman world which require more comprehensive recording of these remains than the current sampling practices used to date sites or to investigate production and trade practices. The article includes a brief overview of approaches to material culture, particularly ceramics, for improving understandings of cultural patterns in past food-consumption practices. We then outline the project's rationale and planned approaches to harnessing the potential of artificial intelligence and machine learning for artefact recording, specifically of Roman terra sigillata tablewares, and the processes used to develop a sufficiently large dataset to develop and test the AI system. The important aspect of this article is the changes made to these processes to mitigate the impact of the Covid pandemic on our ability to record large datasets of real ceramics. These changes involved the development of simulated datasets that substantially enhance our original real dataset and the accuracy of identification. Here we present our results to date, contextualised within the overall aims of the project and briefly discuss the steps we are taking to improve these. © 2022 Journal of Computer Applications in Archaeology. All rights reserved.
ABSTRACT
The COVID-19 pandemic halted scientific research across the world, revealing the vulnerabilities of field-based disciplines to disruption. To ensure resilience in the face of future emergencies, archaeology needs to be more sustainable with international collaboration at the forefront. This article presents a collaborative data collection model for documenting lithics using digital photography and physical measurements taken in-situ by local collaborators. Data capture protocols to optimise standardisation are outlined, and guidelines are provided for data curation, storage and sharing. Adopting collaborative research strategies can have long-term advantages beyond the COVID-19 pandemic, by encouraging knowledge-sharing between international collaborators, decreasing emissions associated with archaeological research, and improving accessibility for those who are not able to travel for access to international samples. This article proposes that archaeology should use the COVID-19 pandemic as a catalyst for change through encouraging deeper collaborations and the development of remote models of science as a complement to in-person research.
ABSTRACT
Extracorporeal membrane oxygenation (ECMO) is a form of cardiopulmonary support primarily used in cardiothoracic and intensive care unit (ICU) settings. The purpose of this review is to familiarise radiologists with the imaging features of ECMO devices, their associated complications and appropriate imaging protocols for contrast-enhanced CT imaging of ECMO patients. This paper will provide a brief introduction to ECMO and the imaging modalities utilised in ECMO patients, followed by a description of the types of ECMO available and cannula positioning. Indications and contraindications for ECMO will be outlined followed by a description of the complications associated with ECMO, which radiologists should recognise. Finally, the imaging protocol and interpretation of contrast-enhanced CT imaging in ECMO patients will be discussed. In the current clinical climate with millions of COVID-19 cases around the world and tens of thousands of critically ill patients, many requiring cardiopulmonary support in intensive care units, the use of ECMO in adults has increased, and thus so has the volume of imaging. Radiologists need to be familiar with the types of ECMO available, the correct positioning of the catheters depending on the type of ECMO being utilised, and the associated complications and imaging artefacts.