Discrimination of fungal disease infestation in oil-palm canopy hyperspectral reflectance data

This study focuses on the calibration of a statistical model of discrimination between different stages of a fungal disease attack on oil palm, based on field hyperspectral measurements at the canopy scale. Combinations of preprocessing, partial least square regression and factorial discriminant analysis are tested on a hundred of samples to prove the efficiency of canopy reflectance to provide information about the plant sanitary status. A robust algorithm is thus derived, allowing classifying oil palm in a 4-level typology, based on disease severity levels from the sane to the critically sick tree with a global performance of more than 92%. Applications and further improvements of this experiment are discussed. (Résumé d'auteur

Prediction of palm-tree ganoderma affection degree by reflectance spectroscopy: Proposed methodology

The aim of this study was thus to test the relevance of statistical methods to detect the variations in spectral signature of oil-palm trees correlated to Ganoderma disease, a fungus responsible of high loss of yield and trees in palm groves. The objective is too discriminate infected palm trees and to establish a ranking in the degree of infection. Some previous studies (Lanore, 2006; et Brégand, 2007) revealed that it is feasible, but the number of individuals was too small to lead to statistically reliable models; thus, it is still to confirm and validate. More especially, the present study focuses on the possibility of infected palm-tree discrimination in accordance to four sickness degrees: Healthy, Low, Medium and High infection. It will test this potential at several scales: the leaflet, the canopy, and by remote sensing. (Résumé d'auteur

Online estimation of rollator user condition using spatiotemporal gait parameters

Assistance to people during rehabilitation has to be adapted to their needs. Too little help can lead to frustration and stress in the user; an excess of help may lead to low participation and loss of residual skills. Robotic rollators may adapt assistance. The main challenge to cope with this issue is to estimate how much help is needed on the fly, because it depends not only on the person condition, but also on the specific situation that they are negotiating. Clinical scales provide a global condition based estimation, but no local estimator based on punctual needs. Condition also changes in time, so clinical scales need to be recalculated again and again. In this paper we propose a novel approach to estimate users’ condition in a continuous way via a robotic rollator. Our work focuses on predicting the value of the well known Tinetti Mobility test from spatiotemporal gait parameters obtained from our platform while users walk. This prediction provides continuous insight on the condition of the user and could be used to modify the amount of help provided. The proposed method has been validated with 19 volunteers at a local hospital that use a rollator for rehabilitation. All volunteers presented some physical or mental disabilities. Our results sucessfully show a high correlation of spatiotemporal gait parameters with Tinetti Mobility test gait (R2 = 0.7) and Tinetti Mobility test balance (R2 = 0.6).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Real-time monitoring of apples (Malus domestica var. Gala) during hot-air drying using NIR spectroscopy

Among commercial fruits, apple shows a growing trend to its worldwide consumption, where dried apple plays a major part in food industry as raw material to produce snacks, integral breakfast foods, chips, etc., which have become popular in the diet of modern consumers in parallel with the human consumption of organic products. Despite apple tissue exhibits extensive and non-homogeneous discoloration during drying, it is nowadays often dried by conventional methods which, however, are usually uncontrolled and then prone to product quality deterioration. However, because no all conventional drying treatments are allowed by the European Organic Regulation (i.e. EC No. 834/2007 and EC No. 889/2008), drying of organic apples should be carefully optimized to obtain comparable results to conventional methods. Therefore, the main objective of the proposed study was to investigate the feasibility of near-infrared (NIR) spectroscopy as smart drying technology to proactively and non-destructively detect and monitor quality change in organic apple wedges during hot-air drying

PENGARUH IKLIM ORGANISASI TERHADAP INTENTION TO STAY PADA PT MUSLA TRANS UTAMA DENGAN EMPLOYE ENGANGEMENT SEBAGAI VARIABEL INTERVENING

Penelitian bertujuan untuk mengetahui serta menganalisis pengaruh iklim organisasi terhadap intention to stay pada PT Musla Trans Utama dengan employee engangement sebagai variabel intervening. Teknik pengambilan sampel pada penelitian ini dengan menggunakan teknik proportionate random sampling dengan jumlah sampe sebanyak 98 karyawan. Teknik pengumpulan data menggunakan kuesioner. Teknik analisis data menggunakan analisis jalur dengan program Smart-PLS. Hasil penelitian ini menunjukkan bahwa iklim organisasi tidak berpengaruh terhadap intention to stay, iklim organisasi berpenagruh positif dan signifikan terhadap employee engangement, employe engangement berpengaruh positif dan signifikan terhadap intention to stay, iklim organisasi berpengaruh secara positif fan signifikan terhadap intention to stay dengan employee engangement sebagai variabel intervening

Trends in life cycle greenhouse gas emissions of future light duty electric vehicles

The majority of previous studies examining life cycle greenhouse gas (LCGHG) emissions of battery electric vehicles (BEVs) have focused on efficiency-oriented vehicle designs with limited battery capacities. However, two dominant trends in the US BEV market make these studies increasingly obsolete: sales show significant increases in battery capacity and attendant range and are increasingly dominated by large luxury or high-performance vehicles. In addition, an era of new use and ownership models may mean significant changes to vehicle utilization, and the carbon intensity of electricity is expected to decrease. Thus, the question is whether these trends significantly alter our expectations of future BEV LCGHG emissions. To answer this question, three archetypal vehicle designs for the year 2025 along with scenarios for increased range and different use models are simulated in an LCGHG model: an efficiency-oriented compact vehicle; a high performance luxury sedan; and a luxury sport utility vehicle. While production emissions are less than 10% of LCGHG emissions for today's gasoline vehicles, they account for about 40% for a BEV, and as much as two-thirds of a future BEV operated on a primarily renewable grid. Larger battery systems and low utilization do not outweigh expected reductions in emissions from electricity used for vehicle charging. These trends could be exacerbated by increasing BEV market shares for larger vehicles. However, larger battery systems could reduce per-mile emissions of BEVs in high mileage applications, like on-demand ride sharing or shared vehicle fleets, meaning that trends in use patterns may countervail those in BEV design