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Hyper-spectral frequency selection for the classification of vegetation diseases

Reducing the use of pesticides by early visual detection of diseases in precision agriculture is important. Because of the color similarity between potato-plant diseases, narrow band hyper-spectral imaging is required. Payload constraints on unmanned aerial vehicles require reduc- tion of spectral bands. Therefore, we present a methodology for per-patch classification combined with hyper-spectral band selection. In controlled experiments performed on a set of individual leaves, we measure the performance of five classifiers and three dimensionality-reduction methods with three patch sizes. With the best-performing classifier an error rate of 1.5% is achieved for distinguishing two important potato-plant diseases.

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Hyper-spectral frequency selection for the classification of vegetation diseases

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Duurzaamheidsintelligentie als remedie voor het falen van duurzaamheid; Het duurzaamheids-IQ van Patagonia

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Magnificent Mind series

Sustainable Experience Design Professor Frans Melissen dialogues about Sustainability Intelligence with Joseph Roevens. Topics include: Initial interest in Sustainability? https://bit.ly/2G1RTz4 How do you live Sustainably? When do you ‘sin’? https://bit.ly/2IdGFsZGaia Zoo & “Sustainable Customer Experience Design” https://bit.ly/2UgtzlY 50 Shades of Green https://bit.ly/2IeH3Yf Breda University’s Sustainable Travel Policy https://bit.ly/2WN2DqE How to stimulate Sustainable behavior? https://bit.ly/2Kb2Hiv Sustainability Intelligence: Naïve, Native & Narrative https://bit.ly/2ONUBv7 1. Naïve Intelligence https://bit.ly/2YQXeAL 2. Native Intelligence https://bit.ly/2uPBVSc 3. Narrative Intelligence, e.g.Zappos Delivering Happiness https://bit.ly/2YUbHMa The Powers-that-be vs the Grass Roots. https://bit.ly/2FKNAqw The Sharing Economy & its abuse https://bit.ly/2TTKWE8 Sustainability as the Goal, not as an Instrument to continue the old system https://bit.ly/2YRXqzB Projects at Breda University: SCITHOS https://bit.ly/2U0yG4x Sustainable Customer Experience Design https://bit.ly/2G1TB3y Improving Sustainability in the Hospitality Industry https://bit.ly/2Uw1vu3

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An Agile Framework for Trustworthy AI

From the article: The ethics guidelines put forward by the AI High Level Expert Group (AI-HLEG) present a list of seven key requirements that Human-centered, trustworthy AI systems should meet. These guidelines are useful for the evaluation of AI systems, but can be complemented by applied methods and tools for the development of trustworthy AI systems in practice. In this position paper we propose a framework for translating the AI-HLEG ethics guidelines into the specific context within which an AI system operates. This approach aligns well with a set of Agile principles commonly employed in software engineering. http://ceur-ws.org/Vol-2659/

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Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine

This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at the core of the proposed DSS that enables to monitor, estimate, and classify clients’ sentiments in terms of polarity, as expressed in public comments on social media (SM) company channels. The SAE is built on machine learning (ML) text classification models that are cross-source trained and validated with real data streams from a platform like Trustpilot that specializes in user reviews and tested on unseen comments gathered from a collection of public company pages and channels on a social networking platform like Facebook. Such crosssource opinion analysis remains a challenge and is highly relevant in the disciplines of research and engineering in which a sentiment classifier for an unlabeled destination domain is assisted by a tagged source task (Singh and Jaiswal, 2022). The best performance in terms of F1 score was obtained with a multinomial naive Bayes model: 0,87 for validation and 0,74 for testing.

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Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine

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Future skills

Information about a research study on how data science and artificial intelligence can contribute to modern education aimed at identifying and developing talents of students. Het verslag is gepubliceerd onder de titel: Future skills of journalists and artificial intelligence in education

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An Artificial Intelligence–Based, Personalized Smartphone App to Improve Childhood Immunization Coverage and Timelines Among Children in Pakistan

Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI. Objective: The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement. Methods: A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage. Results: Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age. Conclusions: This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.

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An Artificial Intelligence–Based, Personalized Smartphone App to Improve Childhood Immunization Coverage and Timelines Among Children in Pakistan

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Developing fourth-generation sustainability-oriented business models: Towards naïve, native, and narrative intelligence

Our world is dealing with several pressing sustainability problems. Corporate social responsibility (CSR) initiatives seem to have failed: despite the actions firms have taken over the years to contribute to a better world in an ecological and social sense through directing their resources and competencies towards this goal, the world has been degrading on many important sustainability-related indicators. By implication, firms need to resort to other ways of integrating societal goals into their strategies, organizational architecture, and decision-making processes. Sustainability-oriented business models (SOBMs) may present a way to turn the tides. Adding to the developing discourse on this topic, this chapter identifies three generations of SOBMs and their limitations in realizing sustainable development as well as by presenting an interpretation of fourth generation SBOMs. In doing so, it integrates insights from evolutionary psychology and identifies three types of ‘sustainability intelligence’ firms need to develop in order to be successful in developing SOBMs.

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The three components of sustainability intelligence

This essay presents the concept of sustainability intelligence as a possible response to the current unsustainable course of society. We expound on the three components shaping this concept – naive intelligence, native intelligence, and narrative intelligence – and argue why they could thus serve as inspiration and key reference points for rising to our collective sustainability challenge. The essay ends with a brief exploration of the wider practical, policy and political implications of the concept.

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Hyper-spectral frequency selection for the classification of vegetation diseases