Related papers: Towards a Resilient Information System for Agriculture Extension Information Service: An Exploratory Study

Towards a Resilient Information System for Agriculture Extension Information Service: An Exploratory Study

URL: http://arxiv.org/abs/2108.09748v1
Date: Sun, 22 Aug 2021 15:10:01 GMT
Title: Towards a Resilient Information System for Agriculture Extension Information Service: An Exploratory Study
Authors: Muluneh Atinaf, Alemayehu Molla and Salehu Anteneh
Abstract summary: This study addresses how stakeholders can ensure resilient information provision within the Agricultural Extension Information Service (AEIS) in Ethiopia. The findings show the robustness, self-organization, learning, redundancy, rapidity, scale, diversity and equality mechanisms. The study contributes to the conversation on the application of the IS resilience framework in analyzing local information provision practices.
Score: 0.0
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: Although digital technologies are contributing to human development, several information systems (IS) interventions for development especially in developing countries do not perform as expected nor deliver anticipated outcomes at scale. This raises questions about how to develop and enhance resilient IS for development, an area that requires more research attention. A sound and systematic understanding of the mechanisms local communities apply to maintain resilience and the key transformation areas for a resilient IS development will help to improve the situation. This study addresses how stakeholders can ensure resilient information provision within the Agricultural Extension Information Service (AEIS) and identifies the challenges in designing resilient IS. Conceptually, the study draws from the IS resilience framework. Empirically, it draws from interview data collected from the AEIS provision practice in Ethiopia. The findings show the robustness, self-organization, learning, redundancy, rapidity, scale, diversity and equality mechanisms, the challenges and the key transformations required to advance the resilience of IS for AEIS. The study contributes to the conversation on the application of the IS resilience framework in analyzing local information provision practices as well as to practice highlighting the key transformation areas to improve the effectiveness and impact of AEIS.

Related papers

Cooperative Resilience in Artificial Intelligence Multiagent Systems [2.0608564715600273]
This paper proposes a clear definition of cooperative resilience' and a methodology for its quantitative measurement. The results highlight the crucial role of resilience metrics in analyzing how the collective system prepares for, resists, recovers from, sustains well-being, and transforms in the face of disruptions.
arXiv Detail & Related papers (2024-09-20T03:28:48Z)
The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources [100.23208165760114]
Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications. To help shape responsible development practices, we introduce the Foundation Model Development Cheatsheet.
arXiv Detail & Related papers (2024-06-24T15:55:49Z)
Socialized Learning: A Survey of the Paradigm Shift for Edge Intelligence in Networked Systems [62.252355444948904]
This paper presents the findings of a literature review on the integration of edge intelligence (EI) and socialized learning (SL) SL is a learning paradigm predicated on social principles and behaviors, aimed at amplifying the collaborative capacity and collective intelligence of agents. We elaborate on three integrated components: socialized architecture, socialized training, and socialized inference, analyzing their strengths and weaknesses.
arXiv Detail & Related papers (2024-04-20T11:07:29Z)
PRIME: A CyberGIS Platform for Resilience Inference Measurement and Enhancement [1.4716925415659332]
Defining and quantifying resilience in the social domain is relatively subjective due to the intricate interplay of socioeconomic factors with disaster resilience. There is a lack of computationally rigorous, user-friendly tools that can support customized resilience assessment considering local conditions. This study aims to address these gaps through the power of CyberGIS with three objectives.
arXiv Detail & Related papers (2024-04-15T05:14:52Z)
Generative AI for Secure Physical Layer Communications: A Survey [80.0638227807621]
Generative Artificial Intelligence (GAI) stands at the forefront of AI innovation, demonstrating rapid advancement and unparalleled proficiency in generating diverse content. In this paper, we offer an extensive survey on the various applications of GAI in enhancing security within the physical layer of communication networks. We delve into the roles of GAI in addressing challenges of physical layer security, focusing on communication confidentiality, authentication, availability, resilience, and integrity.
arXiv Detail & Related papers (2024-02-21T06:22:41Z)
Machine Learning in Proton Exchange Membrane Water Electrolysis -- Part I: A Knowledge-Integrated Framework [36.74423086415903]
We propose to adopt a novel framework, Knowledge-integrated Machine Learning, for advancing Proton Exchange Membrane Water Electrolysis (PEMWE) development. We first identify the uncertainties originating from data acquisition conditions, data-driven model mechanisms, and domain expertise, highlighting their complementary characteristics in carrying information from different perspectives. We demonstrate a hierarchical three-level framework, termed the "Ladder of Knowledge-integrated Machine Learning", in the PEMWE context, applying it to three case studies within a context of cell degradation analysis.
arXiv Detail & Related papers (2024-01-24T04:41:03Z)
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis [71.2468615993246]
Building intelligent transportation systems requires an intricate combination of artificial intelligence and mobility analysis. The past few years have seen rapid development in transportation applications using advanced deep neural networks. This vision paper emphasizes research challenges in deep learning-based mobility analysis that require interpretability and robustness.
arXiv Detail & Related papers (2022-10-18T17:28:58Z)
Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review [62.997667081978825]
This review aims at providing a comprehensive vision of the main state-of-the-art libraries and frameworks for machine learning and data analytics available today. The main simulation, emulation, deployment systems, and testbeds for experimental research on the Edge-to-Cloud Continuum available today are also surveyed.
arXiv Detail & Related papers (2022-04-29T08:06:05Z)
Building Resilient Information Systems for Child Nutrition in Post-conflict Sri Lanka during COVID-19 Pandemic [0.0]
The study focuses on an implementation of a mobile-based nutrition information system in a post-conflict district in Sri Lanka. The longitudinal events in the study spans across several years into the period of COVID-19 pandemic. The case study reveals the long-standing capacity building, leadership and local governance, multisector collaboration, platform resilience and empowering of field health staff contribute in building resilience in everyday context.
arXiv Detail & Related papers (2021-08-22T13:56:56Z)
Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations. Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
arXiv Detail & Related papers (2021-01-15T10:43:10Z)

This list is automatically generated from the titles and abstracts of the papers in this site.