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Education of adults with intellectual disabilities in labor activities can help them to successfully and repeatedly carry out their work tasks and significantly help their self-realization. The problem is that the need for frequent repetition of already learned skills requires the constant presence of a teacher or caregiver since such a worker is not able to work independently. This situation increases the cost of employing people with disabilities. The aim is to find a way to reduce the necessary number of caregivers needed in this kind of activity and enable greater self-sufficiency of workers. The presented research intended to verify whether a web course could be an effective educational tool for people with intellectual disabilities. During the research, a group of ten participants with intellectual disabilities was educated to acquire basic skills in horticulture. The first teaching was realized through practical demonstrations at the workplace in the university production garden by professional gardeners. After these demonstrations skills of all participants were verified and so the basic level for further verification and comparison of knowledge was set. Subsequently, using three approaches of repeating the already learned practical curriculum (verbal repetition, no repetition, and repetition using the web course) and different time intervals, the level of knowledge of each participant was verified. Statistical methods were used to compare the results of different repetition approaches. Research results demonstrated that a web course, with specific content that consists of video or animation, combined with the use of pictograms for confident navigation, can be used by people with intellectual disabilities with good results. At the same time, in addition to practical teaching, this was the second best-rated approach of repeating knowledge. Using a web course, participants achieved similar work results as they did in practical teaching.

Non-invasive crop analysis through image-based methods holds great promise for applications in plant research, yet accurate and robust trait inference from images remains a critical challenge. Our study investigates the potential of AI model ensembling and hybridization approaches to infer sorghum crop traits from RGB images generated via unmanned aerial vehicle (UAV). In our study, we cultivated 21 sorghum cultivars in two independent seasons (2021 and 2022) with a gradient of fertilizer and water inputs. We collected 470 ground-truth N measurements and captured corresponding RGB images with a drone-mounted camera. We computed five RGB vegetation indices, employed several ML models such as MLR, MLP, and various CNN architectures (season 2021), and compared their prediction accuracy for N-inference on the independent test set (season 2022). We assessed strategies that leveraged both deep and handcrafted features, namely hybridized and ensembled AI architectures. Our approach considered two different datasets collected during the two seasons (2021 and 2022), with the training set from the first season only. This allowed for testing of the models' robustness, particularly their sensitivity to concept drifts, in the independent season (2022), which is fundamental for practical agriculture applications. Our findings underscore the superiority of hybrid and ensembled AI algorithms in these experiments. The MLP + CNN-VGG16 combination achieved the best accuracy (R2 = 0.733, MAE = 0.264 N% on an independent dataset). This study emphasized that carefully crafted AI-based models applied to RGB images can achieve robust trait prediction with accuracies comparable to the similar phenotyping tasks using more complex (multi- and hyper-spectral) sensors presented in the current literature. [ABSTRACT FROM AUTHOR]

Usability and user experience (UX) are emerging concerns around not only application development but everything designed to be used by people. Evaluation of the UX is, by nature, intensely subjective and time-consuming. The article focuses mainly on Eye Tracking, Usability, and User Experience from a general point of view, with an emphasis on automatic data processing. In recent years, new technological approaches have been emerging to quantify usability testing data and improve process automation. Eye tracking technology is a great way to analyze users' interaction with the product, allowing researchers to discover usability issues and even leverage the power of machine learning to recognize various kinds of emotions linked to users' interactions. Existing research concerned with these three main topics has been methodically explored. For this review, we extensively searched 1988 theme-related articles. One hundred and forty-four articles were selected based on meticulous screening, from which 90 were included in this systematic review. The outcomes reveal a significant shift toward a more technologically advanced evaluation of user experience and usability in various areas. The review proposes several opportunities for future research and missing areas connecting user experience, eye tracking, and machine learning into more products focused on problem pattern identification. [ABSTRACT FROM AUTHOR]

The paper focuses on the analysis of the applicability of usability and UX methods in the development of applications intended for use in the agrarian sector. In addition to an overview of methods and approaches suitable for this purpose, the process of advanced adoption of the UX methods in the development of agrarian software products is also described. The article also discusses ways to enable partially automated, timeefficient, and cost-effective solutions for the creation of interfaces for agricultural applications. Possibilities of future development and technologies related to the usability of products in agriculture are also outlined. The article thus covers the concept for optimizing the development of agricultural products. The main contribution is the input analysis for the future development of the agrarian design system. From such a synthesized system design, it is then possible to create application interfaces that should have seamless usability and good UX. [ABSTRACT FROM AUTHOR]

People are getting more and more used to consume a digital, online content. Many outlets switched to online publication or at least increased their online presence. Besides, online publication is not the only domain of publishing houses. Many different organisations and companies - including those from area of agriculture and rural development - provide online content in form of articles. Importance of semantic web is growing constantly. Together with metadata descriptions, it is necessary for all the current search engines, smart assistants and AI technologies. Public standards and open source software can significantly speed up development and reduce costs when it comes to the Internet and World Wide Web. The paper provides overview of an updated methodology for creation, storage and presentation of online information content in World Wide Web environment. The latest research was focused mainly on presentation and semantics. The whole research process is established as well as the final f ormulation of the methodology. [ABSTRACT FROM AUTHOR]

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