he most frequently employed versions of the sit-to-stand test (STST) are the 5 times STSΤ and the 30 seconds STST. However, it is not known whether a variation with different number of repetitions or time could be more appropriate for older adults. The objective of this study was to investigate the reliability of STST at different time points and number of repetitions. The test was performed in 33 older adults (73±6.1 years) for 40 seconds. The participants performed the procedure twice with a day interval between the sessions. The test was video-taped and the data were processed by two examiners. The highest test-retest reliability was found for the 4th (ICC=0.73, SEM=1.48, SDD=1.68), 5th (ICC=0.76, SEM=1.73, SDD=1.97) and 6th repetition (ICC=0.78, SEM=1.78, SDD=2.03). The inter-rater reliability was excellent independently of the number of trials (ICC>0.9). The correlation of the time at the 4th and 6th repetition with the time at the traditionally selected 5th repetition was excellent (r>0.9). The termination of the STST at the 4th repetition seems to provide equally reliable and valid estimations with the termination at the 5th repetition. Future studies should examine a 4 times STST since the reduction of the number of repetitions may be less tiring and safer for older adults.
This paper examines whether or not there is convergence in defence burdens across the world. To this effect, σ-convergence and β-convergence methodologies are employed. The sample consists of 128 countries and covers the period 1988–2008. Initial findings reported herein point to a process of convergence in defence burdens possibly reflecting the emergence of defence policies that share similar characteristics at least in terms of the allocation of resources.
Data pre-processing is an important step in the data mining process. Data preparation and filtering steps can take considerable amount of processing time. Data pre-processing includes cleaning, normalization, transformation, feature extraction and selection. In this paper, Iliou and PCA data preprocessing methods evaluated in a data set of 103 students, aged 18-25, who were experiencing anxiety problems. The performance of Iliou and PCA data preprocessing methods was evaluated using the 10-fold cross validation method assessing seven classification algorithms, IB1, J48, Random Forest, MLP, SMO, JRip and FURIA, respectively. The classification results indicate that Iliou data preprocessing algorithm consistently and substantially outperforms PCA data preprocessing method, achieving 98.6% against 92.2% classification performance, respectively.
<p>Population rise and economic growth put additional pressure on global water resources, especially in the Mediterranean Island states that have a long history of aridity and water management challenges. In Crete, Greece, 81.2% of total water consumption is attributed to the agricultural sector, with olive trees covering 64.2% of the total cultivated land. Simulation and applied studies have shown that Irrigation Decision Support Systems (IDSS) can reduce water consumption from 10 (Fotia et al., 2021) to 34% (Phogat et al., 2014). Here we examine the feasibility of optimizing such a IDSS for deficit irrigation while maintaining olive crop yield. Experiments are conducted in the DRIP Project infrastructure (Daliakopoulos et al., 2020; Petousi et al., 2018) including an olive grove of 90 10 year-old trees and 5 20m3 lysimeters planted with olive trees from the same olive grove. The infrastructure includes a precision irrigation system comprised of FDR soil moisture sensors, microclimatic stations, and smart irrigation schedulers. The CROPWAT model (Smith et al., 2002) is calibrated using data from 5 irrigation treatments ranging from overirrigation to rainfed cultivation. Field measurements included stomatal conductance [mmol cm-2 s-1], relative chlorophyl fluorescence [Fv/Fm], leaf relative water content [%], leaf area [%], pruning weight [kg], and yield [kg]. Results clearly highlight the differences in olive tree physiological parameters in deficit irrigation treatments and the lack of significant yield benefit in over-irrigation, while the modeling study can estimate exact irrigation scheduling for incorporation with the IDSS.</p><p><strong>Acknowledgments</strong></p><p>This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (project code: T1EDK-03372)</p><p><strong>References</strong></p><p>Daliakopoulos, I. &#925;., Papadimitriou, D., Matsoukas, T., Zotos, N., Moysiadis, H., Anastasopoulos, K., Mavrogiannis, I., & Manios, T. (2020). Development and Preliminary Results from the Testbed Infrastructure of the DRIP Project. Proceedings, 30(1), 64. https://doi.org/10.3390/proceedings2019030064</p><p>Doorenbos, J., & Pruitt, W. O. (1975). Guidelines for predicting crop water requirements. Irrigation and Drainage Paper.</p><p>Fotia, K., Mehmeti, A., Tsirogiannis, I., Nanos, G., Mamolos, A. P., Malamos, N., Barouchas, P., & Todorovic, M. (2021). Lca-based environmental performance of olive cultivation in northwestern greece: from rainfed to irrigated through conventional and smart crop management practices. Water (Switzerland), 13(14). https://doi.org/10.3390/w13141954</p><p>Petousi, I., Daliakopoulos, I. N., Matsoukas, T., Zotos, N., Mavrogiannis, I., & Manios, T. (2018). DRIP: Development of an Advanced Precision Drip Irrigation System for Tree Crops. TERRAENVISION Abstracts, 1, 2018&#8211;2. https://terraenvision2018.eu/abstracts/export.php?id=269</p><p>Phogat, V., Skewes, M. A., Cox, J. W., Sanderson, G., Alam, J., & &#352;im&#367;nek, J. (2014). Seasonal simulation of water, salinity and nitrate dynamics under drip irrigated mandarin (Citrus reticulata) and assessing management options for drainage and nitrate leaching. Journal of Hydrology, 513, 504&#8211;516. https://doi.org/10.1016/j.jhydrol.2014.04.008</p><p>Smith, M., Kivumbi, D., & Heng, L. K. (2002). Use of the FAO CROPWAT model in deficit irrigation studies. In Deficit irrigation practices.</p>
As real world data tends to be incomplete, noisy and inconsistent, data preprocessing is an important issue for data mining. Data preparation includes data cleaning, data integration, data transformation and data reduction. In this paper, Iliou preprocessing method is compared with Principal Component Analysis in suicide prediction according to family history. The dataset consists of 360 students, aged 18 to 24, who were experiencing family history problems. The performance of Iliou and Principal Component Analysis data preprocessing methods was evaluated using the 10-fold cross validation method assessing ten classification algorithms, IB1, J48, Random Forest, MLP, SMO, JRip, RBF, Naïve Bayes, AdaBoostM1 and HMM, respectively. Experimental results illustrate that Iliou data preprocessing algorithm outperforms Principal Component Analysis data preprocessing method, achieving 100% against 71.34% classification performance, respectively. According to the classification results, Iliou preprocessing method is the most suitable for suicide prediction.
Striving to tackle a common water resource scarcity problem, the Drip Irrigation Precise (DRIP) Project aims to develop a state-of-the-art integrated system that will optimize tree crop irrigation (Petousi et al. 2018). To this end, we have developed 5 free lysimeters measuring 3 m in height and 3 m in diameter, each with a total effective volume of ca. 20 m3. Lysimeters were planted with 5 10-year-old olive trees, including their root ball to a depth of 1 m, monolithically transplanted from the experimental olive orchard of the Hellenic Mediterranean University, Greece. The remaining volume was layered with soil from the same source and a gravel filter to allow leaching. Each lysimeter is equipped with IoT sensors relevant to the modeling of the soil-plant-water system; 12 measuring soil moisture, temperature, and electrical conductivity, and one measuring leachate flow. Additionally, meteorological parameters are monitored for the entire infrastructure. Sensors provide real time data to an on-line system, through a network of 15 telecommunication nodes that, together with an edge-gateway, form a local wireless 6LoWPAN mesh network, thus implementing a state-of-the-art Internet of Things (IoT) system. Experimental data collected from the lysimeters are used to model water movement using the HYDRYS 2D/3D model. Modeling output will be used for the development the commercial DRIP system, an advanced irrigation scheduler designed for the harsh conditions of the agricultural environment that utilizes feedback from environmental sensors for optimal irrigation.
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