V. G. Kaburlasos

Social robots for pedagogical rehabilitation in special education for the elderly – V-RITA2022

22/10/2022
humain
2022, Cybspeed, Publications

Abstract Numerous studies have reported social robot applications for children including both typical and special education. Similar applications for the elderly are underplayed. However, children grow to adults and, ultimately, to elderly. This preliminary work, based on our expertise with social robot NAO in special education applications for children, reports an approach for engaging social robots for elderly with Alzheimer’s disease. In particular, a social robot, equipped with a variety of electronic sensors and supported by suitable mathematical models implemented in software, is engaged as a…

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Considerations for a multi-purpose agrobot design toward automating skillful viticultural tasks: a study in northern Greece vineyards – HAICTA 2022, Athens, Greece

25/09/2022
humain
2022, Publications, Tegea

Abstract Seasonal labor shortages in agriculture are experienced throughout Europe and beyond especially, but not only, during the harvest time when the demand for hands is high as well as urgent. Agrobots have been established as a sustainable solution to support these growing demands due to their capacity to work incessantly, fast as well as with skillful precision.  In the aforementioned context, this work investigates the design of a single multi-purpose robotic system towards automation of a number of skillful…

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Variable selection for the prediction of TSS, pH and TA of intact berries of Thompson seedless grapes from their NIS reflection – SoftCOM 2022, Split, Croatia

24/09/2022
humain
2022, Publications, Tegea
Abstract Wavenumbers of high absolute value of correlation coefficient to Total Soluble Solids (TSS), pH, or Titratable Acidity (TA) were selected from reflection Fourier transform near infrared (FT-NIR) spectra of intact grape berries of the white variety Thompson Seedless. Multiple linear regression (MLR) and partial least squares (PLS) regression were applied to the spectra to construct trained regression models able to predict TSS, pH, and TA. Square Pearson’s correlation coefficient (R2) and the Mean Square Error (MSE) were used to…
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Variable Selection on Reflectance NIR Spectra for the Prediction of TSS in Intact Berries of Thompson Seedless Grapes – Agronomy 2022, vol. 12, no. 9, 2113

05/09/2022
humain
2022, Journals, Publications, ΕΒΤΑΡ

Abstract Fourier-transform near infrared (FT-NIR) reflection spectra of intact berries of the grape variety Thompson seedless were used to predict total soluble solids (TSS) content. From an initial dataset, 12 subsets were considered by applying variable selection to extract the reflectance values at wavenumbers most correlated to the chemometrically measured TSS content. The datasets were processed by both multiple linear regression (MLR) and partial least squares (PLS) methods towards predicting the TSS content from the reflection values of each spectrum.…

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Fuzzy lattice reasoning (FLR) for decision-making on an ontology of constraints toward agricultural robot harvest – FLINS 2022 on Machine learning, Multi agent and Cyber physical systems, Tianjin, China (Best Paper Award)

28/08/2022
humain
2022, Publications, Tegea
Abstract A sustainable production of high-quality agricultural products calls for personalized- rather than for massive- operations. The aforementioned (personalized) operations can be pursued by human-like reasoning applicable per case. The interest here is in agricultural grape robot harvest where a binary decision needs to be taken, given a set of ambiguous constraints represented by a Boolean lattice ontology of inequalities. Fuzzy lattice reasoning (FLR) is employed for decision making. Preliminary experimental results on expert data demonstrate the advantages of the…
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