Design of a Planting Module for an Automatic Device for Forest Regeneration

Forest regeneration by means of seedlings grown in container nurseries is usually performed manually with the use of the standard dibble bar or the tube dibble. Manual placement of a large number of seedlings in the soil requires a lot of work. Manual removal of the soil cover and digging the soil in spots with a diameter of 0.4 m requires, under average conditions, about 38 man-hours/ha, while planting with a dibble bar requires about 34 man-hours/ha. Additional work time is needed to carry seedlings over an area that is being afforested. At present, forestry does not have automatic planters that would enable the establishment of forest cultures. The aim of the paper is to present the concept of an autonomous robot and an innovative technology of performing forest regeneration and afforestation of former agricultural and reclaimed areas. The paper also presents the design solutions of the key working unit, which is a universal, openable dibble, cooperating with a three-toothed shaft to prepare a planting spot. The solution proposed enables continuous operation of the machine, i.e. without the need to stop the base vehicle

Autologous fat transfer to the subcutaneous tissue in the context of breast reconstructive procedures

Autologous fat transfer (AFT) is an appropriate technique for aesthetic rejuvenation of the face, aesthetic enhancement of hands, correction of the facial appearance in various disorders and constitutes a surgical alternative of treatment of numerous breast deformities ranging from distorting posttraumatic scars, post-eczema lesions, post-burn deformities to partial or total breast reconstruction. Our work is aimed to familiarize dermatologists with the technique of harvesting and implanting the aspirate of adipose cells in patients consulted for deformities of the breast. In addition, the review summarizes the most common applications of AFT in the breast reconstructive procedures. In summary, AFT is an oncologically safe, relatively complication-free, minimally invasive surgical technique, which can be used to correct a wide range of deformities, which are commonly seen by dermatologists, in the area of the face, trunk and extremities. The procedure can correct a wide range of breast deformities, from contour or single quadrant deformities up to the state after mastectomy

Autologous fat transfer to the subcutaneous tissue in the context of breast reconstructive procedures

A b s t r a c t Autologous fat transfer (AFT) is an appropriate technique for aesthetic rejuvenation of the face, aesthetic enhancement of hands, correction of the facial appearance in various disorders and constitutes a surgical alternative of treatment of numerous breast deformities ranging from distorting posttraumatic scars, post-eczema lesions, postburn deformities to partial or total breast reconstruction. Our work is aimed to familiarize dermatologists with the technique of harvesting and implanting the aspirate of adipose cells in patients consulted for deformities of the breast. In addition, the review summarizes the most common applications of AFT in the breast reconstructive procedures. In summary, AFT is an oncologically safe, relatively complication-free, minimally invasive surgical technique, which can be used to correct a wide range of deformities, which are commonly seen by dermatologists, in the area of the face, trunk and extremities. The procedure can correct a wide range of breast deformities, from contour or single quadrant deformities up to the state after mastectomy

Designing agricultural machinery on the example of tilling-and-sowing combined machine with a dispenser slurry

W artykule przedstawiono wybrane aspekty opracowania nowej konstrukcji agregatu uprawowo-siewnego, obejmujące weryfikację i ocenę wstępnego modelu konstrukcji agregatu metodą elementów skończonych. Przeprowadzono analizę występujących stanów naprężeń dla założonych warunków pracy agregatu z uwzględnieniem wpływu obciążeń dynamicznych oraz zaproponowano zmiany konstrukcyjne.The article presents selected aspects of the development of a new design of a tilling-and-sowing combined machine, including verification and evaluation of the initial model of the aggregate structure using the finite element method. An analysis of the occurrence of stress states for the assumed operating conditions of the aggregate was performed, taking into account the influence of dynamic loads. Also, structural changes were proposed

Vision systems in modern agriculture

W artykule zaprezentowano przegląd zastosowań systemów wizyjnych we współczesnym rolnictwie. Zostały one opisane w oparciu o przykładowe rozwiązania prezentowane przez producentów maszyn. Objaśniono czym są systemy wizyjne i jakie zadania realizują.The paper presents an overview of the use of vision systems in modern agriculture. They have been described on the basis of exemplary solutions presented by machine manufacturers. There was explain what the vision systems are and what tasks they perform

Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a comparative study of the algorithms in order to determine which algorithm has the highest prediction accuracy. The results showed that the value of the red color has a greater effect than the green and blue colors in predicting the sweetness of orange fruits, as there is a direct relationship between the value of the red color and the level of sweetness. In addition, the logistic regression model algorithm gave the highest degree of accuracy in predicting sweetness

Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a comparative study of the algorithms in order to determine which algorithm has the highest prediction accuracy. The results showed that the value of the red color has a greater effect than the green and blue colors in predicting the sweetness of orange fruits, as there is a direct relationship between the value of the red color and the level of sweetness. In addition, the logistic regression model algorithm gave the highest degree of accuracy in predicting sweetness