The article presents the Flipped Classroom approach and its application at the Faculty of Techniques and Technologies (FTT) - Yambol, based on the training in the subjects "Programming and Use of Computers", "Food Contaminants", and "Object-Oriented Programming" in the 2016-2018 academic years. For the students, the problem is to filter some sources that are not reliable. In the new digital age, the lecturers expect them to be creative and to prepare their assignment using new approaches. When students follow their lecturers’ instructions concerning the literature and resources their projects tend to be more successful. This is one of the issues we encounter in preparing students for their classes. The second problem that we want to solve is the presentation of information using the "pouring in the bank" approach, where students are offered lectures and tutorials without being able actively to participate in the learning process. The students are trained to acquire knowledge without placing and solving problems and looking for new solutions. The article goals are to analyze the approach that we apply to the students' training to stimulate their activity in learning the material and filling the gaps in their knowledge. The first part of the article reviews the theory and the application of the Flipped Classroom approach by other authors in different subject areas. We present different taxonomic models and qualities that they build for the student’s learning process. The following part analyses the application of the approach in the mentioned fields of study for students of Bachelor's and Master’s degrees. In the article, we present steps for Flipped classrooms. We discuss also the key elements of The Flipped classroom and the benefits and limitations of using it. In conclusion, the article outlines the results achieved and the prospects for enhancing the engagement of the students in learning.
At the current level of science and technology is used semi-automatic measurement of body parts of the bees, yielding images taken with a reference object via a camera or a scanner and then perform measurement by software using a pointing device. There are attempts to fully automated process of measuring the morphological characteristics of bees, at this stage there are conversions for Measuring wings, but this process for other parts are still made by manual way. The informative colour features for the separation of tergite and probotics from background in the image are selected by distance functions and correspondence analysis. Distances are determined between the values of the colour components of the object and background. From statistical analysis is found that appropriate for the separation of an object from background are S and V colour components of the HSV colour model. Algorithms and program in Matlab environment for separating tergite and proboscis from the background of the image and definition of their main sizes are developed. From the analysis of the results is found that the major influence on the accuracy of the measurement is the angle at the disposal of the bee body part in the image.
The use of Big data related to the breeding of honey bees, when administered and processed effectively, will encourage the development of knowledge-based beekeeping, create new markets and business opportunities and further encourage the development of this industry. There have been attempts to fully automate the process of measuring the morphological characteristics of bees (at this stage there are conversions for Measuring wings), but this process for other parts are still completed manually. A survey was made of the possibilities to automate the process of measuring the morphological characteristics in honeybees and the proposed algorithm and program to implement it. Color characteristics of parts of the bee body -tergite and proboscis, through which they can be separated from the background of the image, are analyzed and measured.Distances are determined between the values of the colour components of the object and background. From statistical analysis, it is found that S and V colour components of the HSV colour model are appropriate for the separation of an object from the background . Algorithms and a program in Matlab environment for separating tergite and proboscis from the background of the image and definition of their main sizes are developed. From the analysis of the results, it is found that the major influence on the accuracy of the measurement is of the bee in the image..
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