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Number of results: 4
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Abstract

Over the past two decades, artificial neural networks (ANN) have exhibited a significant progress in predicting and modeling non-linear hydrological applications, such as the rainfall-runoff process which can provide useful contribution to water resources planning and management. This research aims to test the practicability of using ANNs with various input configurations to model the rainfall-runoff relationship in the Seybouse basin located in a semi-arid region in Algeria. Initially, the ANNs were developed for six sub-basins, and then for the complete watershed, considering four different input configurations. The 1st (ANN IP) considers only precipitation as an input variable for the daily flow simulation. The 2nd (ANN II) considers the 2nd variable in the model input with precipitation; it is one of the meteorological parameters (evapotranspiration, temperature, humidity, or wind speed). The third (ANN IIIP,T,HUM) considers a combination of temperature, humidity, and precipitation. The last (ANN VP,ET,T,HUM,Vw) consists in collating different meteorological parameters with precipitation as an input variable. ANN models are made for the whole basin with the same configurations as specified above. Better flow simulations were provided by (ANN IIP,T) and (ANN IIP,Vw) for the two stations of Medjez-Amar II and Bordj-Sabath, respectively. However, the (ANN VP,ET,T,HUM,Vw)’s application for the other stations and also for the entire basin reflects a strategy for the flow simulation and shows enhancement in the prediction accuracy over the other models studied. This has shown and confirmed that the more input variables, as more efficient the ANN model is.
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Authors and Affiliations

Yamina Aoulmi
1
ORCID: ORCID
Nadir Marouf
1
ORCID: ORCID
Mohamed Amireche
1
ORCID: ORCID

  1. University of Larbi-Ben-M’hidi, Faculty of Sciences and Applied Sciences, Department of Hydraulic, Laboratory of Ecology and Environment, PO Box 358, 04000 Oum El Bouaghi, Algeria
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Abstract

By 2050, global crop demand is projected to rise by 60–110%. Crop yields have also been impacted by climate change in some nations, and these impacts are likely to continue. To prevent the influence of climate change on crop output, it is critical to adjust planting times in weather-related open fields to meet food security concerns. Present study was carried out at Experimental Farm of Faculty of Agriculture, Al-Azhar University, Assiut, Egypt, during two successive seasons, 2019 and 2020. It was aimed to study the effect of different sowing times (1st and 15th October, 1st and 15th November), and plant spacings (25, 20, and 15 cm) on growth, fruit yield, and oil production of caraway ( Carum carvi L.) plants. The results showed that sowing caraway plants on 15th October with plant spacing of 25 cm gave the highest dry weight (72.6 g∙plant –1), fresh weight (266.15 g∙plant –1), seed yield (37.43 g∙plant –1), and oil yield (0.659 cm3∙plant –1). The maximum umbels (50.83 number per plant) and essential oil (1.78%) were also recorded in the plants receiving same treatment. On the other hand, plants sown at 15th November with spacing of 15 cm exhibited the minimum values of recorded traits. While the highest value of plant height gave with sowing caraway plants on 15th October with plant spacing of 15 cm (135.35 cm). In conclusion, the plants sowed on October 15th with a maximum plant spacing of 25 cm had the highest values of the evaluated morphological, biochemical, and yield attributes of caraway.
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Authors and Affiliations

Mostafa Fathi Ibrahim
1
ORCID: ORCID
Muhammad Moaaz Ali
2
ORCID: ORCID
Sobhi F. Lamlom
3
ORCID: ORCID
Hazem M. Kalaji
4 5
ORCID: ORCID
Ahmed F. Yousef
1
ORCID: ORCID

  1. University of Al-Azhar (branch Assiut), College of Agriculture, Department of Horticulture, Assiut 71524, Egypt
  2. Fujian Agricultural and Forestry University, College of Horticulture, Fuzhou, China
  3. Alexandria University, Faculty of Agriculture Saba Basha, Plant Production Department, Alexandria, Egypt
  4. Warsaw University of Life Sciences (SGGW), Institute of Biology, Department of Plant Physiology, Warsaw, Poland
  5. Institute of Technology and Life Sciences – National Research Institute, Falenty, Poland
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Abstract

Industry 4.0 (I4) as a concept offers powerful opportunities for many businesses. The set of Industry 4.0 technologies is still discussed, and boundaries are not perfectly clear. However, implementation of Industry 4.0 concept becomes strategic principle, and necessary condition for succeeding on turbulent markets. Radio Frequency Identification (RFID) was used before I4 emerged. However, it should be treated as its important part and even enabler. The question arises how adoption of RFID was impacted by I4 paradigm. Therefore, to answer this question a set of technology management tools was selected and applied to forecast RFID potential development in forthcoming years. Moreover, case studies were conducted for technology management tools and their applications for RFID for qualitative discussion of its relevance. It aimed to prove that existing toolset should be applied for modern technologies related to I4. Tools were proven to be necessary and successful. However, some specific challenges were observed and discussed.
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Authors and Affiliations

Bartlomiej Gladysz
1
Donatella Corti
2
Elias Montini
2

  1. Warsaw University of Technology, Institute of Production Systems Organization, Warsaw, Poland
  2. University of Applied Science and Arts of Southern Switzerland, Department of Innovative Technologies
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Abstract

History has shown different approaches to improving productivity the way of companies do business. Since the early 1900s, the development of different production systems has played an increasingly remarkable role in global manufacturing countries. It seems, that the growth of understanding has widened the ideology of production systems used up to current ones. This article examines the development path of business development. It evaluates the suitability of the key tools used to support change in a modern business model in a customer-driven project business environment.
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Authors and Affiliations

Jyri Vuorela
1
Mikael Ollikainen
1
Vesa Salminen
2
Juha Varis
1

  1. Energy Systems, LUT University, Finland
  2. Smart Research Center, Häme University of Applied Sciences, Finland

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