scholarly journals A Concept of a Compact and Inexpensive Device for Controlling Weeds with Laser Beams

Agronomy ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1616
Author(s):  
Ildar Rakhmatulin ◽  
Christian Andreasen
Keyword(s):  
Neural Network ◽  
Decision Model ◽  
Control Device ◽  
Guidance System ◽  
Laser Beams ◽  
Laser Guidance ◽  
Couch Grass ◽  
Elytrigia Repens ◽  
Weed Plants ◽  
Plant Length

A prototype of a relatively cheap laser-based weeding device was developed and tested on couch grass (Elytrigia repens (L.) Desv. ex Nevski) mixed with tomatoes. Three types of laser were used (0.3 W, 1 W, and 5 W). A neural network was trained to identify the weed plants, and a laser guidance system estimated the coordinates of the weed. An algorithm was developed to estimate the energy necessary to harm the weed plants. We also developed a decision model for the weed control device. The energy required to damage a plant depended on the diameter of the plant which was related to plant length. The 1 W laser was not sufficient to eliminate all weed plants and required too long exposure time. The 5 W laser was more efficient but also harmed the crop if the laser beam became split into two during the weeding process. There were several challenges with the device, which needs to be improved upon. In particular, the time of exposure needs to be reduced significantly. Still, the research showed that it is possible to develop a concept for laser weeding using relatively cheap equipment, which can work in complicated situations where weeds and crop are mixed.

Model of a neural network adaptive system for a digital control loop of an electric drive

2021 ◽  
Author(s):  
O.V. Nepomnyashchiy ◽  
A.V. Tarasov ◽  
Yu.V. Krasnobaev ◽  
V.N. Khaidukova ◽  
D.O. Nepomnyashchiy
Keyword(s):  
Neural Network ◽  
Intelligent Control ◽  
Electric Drive ◽  
Electric Motor ◽  
Control Device ◽  
System Control ◽  
Electric Transport ◽  
Control Loop ◽  
Software Environment ◽  
Power System Control

The problem of increasing the efficiency of power units of autonomous electric transport vehicles is considered. The task of creating a promising power system control device has been singled out. It is determined that in creating such devices, significant results can be obtained by using an intelligent module in the control loop of the electric drive. Goal. It is necessary to develop a power plant model with intelligent control, allowing to obtain data sets about currents, voltages and engine speeds in different modes of operation. The architecture of an intelligent control device, a PID controller based on a neural network, has been proposed; it has been proposed to exclude rotor angular velocity sensors from the classical feedback loop. The type and architecture of the neural network is defined. In the software environment MatLab the model of neuroemulator of the engine for formation of a training sample of a neural network by a method of Levenberg – Marquardt is developed. The trained neural network is implemented in the developed model of the electric motor control loop. The results of simulation of the intelligent control device showed a good convergence of the output influences generated by the neuroemulator with the actual parameters of the electric motor.

Development of laser guidance system for UAV

2021 ◽  
Vol 2021.59 (0) ◽  
pp. 10a1
Author(s):  
Naoki KAMIO ◽  
Masafumi MIWA ◽  
Yusuke TAKEUCHI
Keyword(s):  
Guidance System ◽  
Laser Guidance

A neural network based technique for vibration characterization using Gaussian laser beams

Mechatronics ◽  
2015 ◽  
Vol 25 ◽  
pp. 44-54 ◽  
Author(s):  
Naveed A. Abbasi ◽  
Taha Landolsi ◽  
Rached Dhaouadi
Keyword(s):  
Neural Network ◽  
Laser Beams

scholarly journals Semiotic Aggregation in Deep Learning

Entropy ◽  
2020 ◽  
Vol 22 (12) ◽  
pp. 1365
Author(s):  
Bogdan Muşat ◽  
Răzvan Andonie
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Decision Model ◽  
Deep Neural Networks ◽  
Neural Model ◽  
Network Layers ◽  
Saliency Maps ◽  
Spatial Entropy ◽  
Insight Into

Convolutional neural networks utilize a hierarchy of neural network layers. The statistical aspects of information concentration in successive layers can bring an insight into the feature abstraction process. We analyze the saliency maps of these layers from the perspective of semiotics, also known as the study of signs and sign-using behavior. In computational semiotics, this aggregation operation (known as superization) is accompanied by a decrease of spatial entropy: signs are aggregated into supersign. Using spatial entropy, we compute the information content of the saliency maps and study the superization processes which take place between successive layers of the network. In our experiments, we visualize the superization process and show how the obtained knowledge can be used to explain the neural decision model. In addition, we attempt to optimize the architecture of the neural model employing a semiotic greedy technique. To the extent of our knowledge, this is the first application of computational semiotics in the analysis and interpretation of deep neural networks.

scholarly journals Isolation and Bioactivity of Secondary Metabolites from Solid Culture of the Fungus, Alternaria sonchi

Biomolecules ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 81
Author(s):  
Anna Dalinova ◽  
Leonid Chisty ◽  
Dmitry Kochura ◽  
Varvara Garnyuk ◽  
Maria Petrova ◽  
...  
Keyword(s):  
Antimicrobial Properties ◽  
Solid Substrate ◽  
Solid Culture ◽  
Couch Grass ◽  
Elytrigia Repens ◽  
Waste Solid ◽  
Low Cytotoxicity ◽  
Sonchus Arvensis ◽  
Related Compounds ◽  
Leaf Disks

The fungus, Alternaria sonchi is considered to be a potential agent for the biocontrol of perennial sowthistle (Sonchus arvensis). A new chlorinated xanthone, methyl 8-hydroxy-3-methyl-4-chloro-9-oxo-9H-xanthene-1-carboxylate (1) and a new benzophenone derivative, 5-chloromoniliphenone (2), were isolated together with eleven structurally related compounds (3–13) from the solid culture of the fungus, which is used for the production of bioherbicidal inoculum of A. sonchi. Their structures were determined by spectroscopic (mostly by NMR and MS) methods. Alternethanoxins A and B, which were reported in A. sonchi earlier, were re-identified as moniliphenone and pinselin, respectively. The isolated compounds were tested for phytotoxic, antimicrobial, insecticidal, cytotoxic and esterase-inhibition activities. They did not demonstrate high phytotoxicity (lesions up to 2.5 mm in diameter/length at a concentration of 2 mg/mL) when tested on leaf disks/segments of perennial sowthistle (Sonchus arvensis) and couch grass (Elytrigia repens). They did not possess acute toxicity to Paramecium caudatum, and showed moderate to low cytotoxicity (IC50 > 25 µg/mL) for U937 and K562 tumor cell lines. However, chloromonilicin and methyl 3,8-dihydroxy-6-methyl-4-chloro-9-oxo-9H-xanthene-1-carboxylate (4) were shown to have antimicrobial properties with MIC 0.5–5 µg/disc. Compound 4 and chloromonilinic acid B were found to have contact insecticidal activity to wheat aphid (Schizaphis graminum) at 1 mg/mL. Compounds 2 and methyl 3,8-dihydroxy-6-methyl-9-oxo-9H-xanthene-1-carboxylate displayed selective carboxylesterase inhibition activity at concentration of 100 µg/mL. Therefore, the waste solid substrate for production of A. sonchi spores can be re-utilized for the isolation of a number of valuable natural products.

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