Sustainable Technologies Supported by Project-Based Learning in the Education of Engineers: A Case Study from Poland

The aim of the article is to examine technological innovations developed by engineers as part of Project-Based Learning at one of the Polish technical universities. We examined whether the innovations being developed meet the goals of sustainable development and whether they provide the basis for the introduction of sustainable business models. We analyzed reports from 49 projects implemented in the years 2018–2020 in which 146 scientists, 282 students of the Silesian University of Technology, and 126 experts from the university’s business environment were involved. We performed the analysis using content analysis and visualization techniques. The results show that the studied innovations implement the goals of sustainable development and most of them may become the basis of sustainable business models. The most frequently pursued goals are Industry, Innovation, and Infrastructure and Good Health and Well-Being. Most of the studied innovations can become the basis of the archetype of a sustainable business model called “maximize material and energy efficacy”. We also provide the characteristics of projects that implement the diagnosed goals of sustainable development.

Contralateral interhemispheric transfalcine approach to precuneal glioblastoma: fluorescein guided microsurgical resection and endoscopic microinspection tool

Maximum safe resection remains a primary goal in the treatment of glioblastoma, with gross-total resection conveying additional survival benefit. Multiple intraoperative visualization techniques have been developed to improve the extent of resection. Herein, the authors describe the use of fluorescein and endoscopic assistance with a novel microinspection device in achieving a gross-total resection of a deep seated precuneal glioblastoma. An interhemispheric transfalcine approach was utilized and microsurgical resection was completed with fluorescein guidance. A 45° endoscope was then used to inspect the resection bed, and remaining areas of concern were then resected under endoscopic visualization. The video can be found here: https://stream.cadmore.media/r10.3171/2021.10.FOCVID21195

Big Data Analytics and Visualization for Food Health Status Determination Using Bigmart Data

Being premature, the traditional data visualization techniques suffer from several challenges and lack the ability to handle a huge amount of data, particularly in gigabytes and terabytes. In this research, we propose an R-tool and data analytics framework for handling a huge amount of commercial market stored data and discover knowledge patterns from the dataset for conveying the derived conclusion. In this chapter, we elaborate on pre-processing a commercial market dataset using the R tool and its packages for information and visual analytics. We suggest a recommendation system based on the data which identifies if the food entry inserted into the database is hygienic or non-hygienic based on the quality preserved attributes. For a precise recommendation system with strong predictive accuracy, we will put emphasis on Algorithms such as J48 or Naive Bayes and utilize the one who outclasses the comparison based on accuracy. Such a system, when combined with R language, can be potentially used for enhanced decision making.

Construction and Application of Korean-English-Japanese Multilingual Teaching Aid System Based on Knowledge Map

This article describes the design and application of a computer-based system for simultaneously teaching Korean, English and Japanese languages in a classroom setting using knowledge visualization techniques to show the relationships between vocabularies, grammars and meanings. The system consists of a knowledge database of Korean, English, and Japanese which is then uploaded into the teaching module. Visualizations of this information in the form of knowledge maps based upon generally accepted rules of knowledge map can then be displayed and contrasted using the system interface to enter user queries. The system is then tested in a blended classroom of native Korean speakers. Data on student learning experiences are then gathered by means of a questionnaire and analyzed in order to assess the overall success of knowledge acquisition in this setting. Our findings show that this system evokes a personal initiative in the learning process, facilitates communication between teachers and learners, and supports the rapid acquisition of multilingual knowledge.

An Enhanced Image Segmentation From 3D to 2D by Using Modified Neural Network

Optical coherence tomography angiography (OCTA) is an imaging which can applied in ophthalmology to provide detailed visualization of the perfusion of vascular networks in the eye. compared to previous state of the art dye-based imaging, such as fluorescein angiography. OCTA is non-invasive, time efficient, and it allows for the examination of retinal vascular in 3D. These advantage of the technique combined with the good usability in commercial devices led to a quick adoption of the new modality in the clinical routine. However, the interpretation of OCTA data is not without problems commonly observed image artifacts and the quite involved algorithmic details of OCTA signal construction can make the clinical assessment of OCTA exams challenging. In this paper we describe the technical background of OCTA and discuss the data acquisition process, common image visualization techniques, as well as 3D to 2D projection using high pass filtering, relu function and convolution neural network (CNN) for more accuracy and segmentation results.

BONNIE: Building Online Narratives from Noteworthy Interaction Events

Nowadays, we have access to data of unprecedented volume, high dimensionality, and complexity. To extract novel insights from such complex and dynamic data, we need effective and efficient strategies. One such strategy is to combine data analysis and visualization techniques, which are the essence of visual analytics applications. After the knowledge discovery process, a major challenge is to filter the essential information that has led to a discovery and to communicate the findings to other people, explaining the decisions they may have made based on the data. We propose to record and use the trace left by the exploratory data analysis, in the form of user interaction history, to aid this process. With the trace, users can choose the desired interaction steps and create a narrative, sharing the acquired knowledge with readers. To achieve our goal, we have developed the BONNIE ( Building Online Narratives from Noteworthy Interaction Events ) framework. BONNIE comprises a log model to register the interaction events, auxiliary code to help developers instrument their own code, and an environment to view users’ own interaction history and build narratives. This article presents our proposal for communicating discoveries in visual analytics applications, the BONNIE framework, and the studies we conducted to evaluate our solution. After two user studies (the first one focused on history visualization and the second one focused on narrative creation), our solution has showed to be promising, with mostly positive feedback and results from a Technology Acceptance Model ( TAM ) questionnaire.

Digitalization and 3D Documentation Techniques Applied to Two Pieces of Visigothic Sculptural Heritage in Merida Through Structured Light Scanning

Technological advancements have a great impact on the dissemination and understanding of the cultural heritage reality due to innovative techniques. These innovations are based on high-precision and high-resolution technologies that allow for the geometric documentation of any object within the fields of history and the arts. Through these techniques, new proposals may be studied and objects can be placed in any historical context. Three-dimensional (3D) digitization allows one to obtain a digital 3D model, which can be handled virtually and recreated at any historical period, enabling the conservation and safeguarding of cultural heritage. Society currently demands new visualization techniques that allow interacting with architectural and artistic heritage, which have been applied in numerous virtual reconstructions of historical sites or singular archaeological pieces. This project allowed us to geometrically document a reused piece with two surfaces (shield and columns) and a plaque of the city of Merida using a structured light scanner from a theoretical-practical perspective. The 3D virtual reconstruction of the pieces was accomplished within this study. The generation of QR codes enabled the interactive display of the heritage pieces. Likewise, a proposal was made to reuse the aforementioned pieces through virtual archaeology. The initial hypothesis is based on the possible existence of a Visigothic niche as an original form. This research reports significant advances in the conservation and exploitation of cultural heritage.

Combining 2D and 3D Visualization with Visual Analytics in the Environmental Domain

The application potential of Visual Analytics (VA), with its supporting interactive 2D and 3D visualization techniques, in the environmental domain is unparalleled. Such advanced systems may enable an in-depth interactive exploration of multifaceted geospatial and temporal changes in very large and complex datasets. This is facilitated by a unique synergy of modules for simulation, analysis, and visualization, offering instantaneous visual feedback of transformative changes in the underlying data. However, even if the resulting knowledge holds great potential for supporting decision-making in the environmental domain, the consideration of such techniques still have to find their way to daily practice. To advance these developments, we demonstrate four case studies that portray different opportunities in data visualization and VA in the context of climate research and natural disaster management. Firstly, we focus on 2D data visualization and explorative analysis for climate change detection and urban microclimate development through a comprehensive time series analysis. Secondly, we focus on the combination of 2D and 3D representations and investigations for flood and storm water management through comprehensive flood and heavy rain simulations. These examples are by no means exhaustive, but serve to demonstrate how a VA framework may apply to practical research.

Dimensionality Reduction and Visualization of Bharatanatyam Mudras

Cultural dances are practiced all over the world. The study of various gestures of the performer using computer vision techniques can help in better understanding of these dance forms and for annotation purposes. Bharatanatyam is a classical dance that originated in South India. Bharatanatyam performer uses hand gestures (mudras), facial expressions and body movements to communicate to the audience the intended meaning. According to Natyashastra, a classical text on Indian dance, there are 28 Asamyukta Hastas (single-hand gestures) and 23 Samyukta Hastas (Double-hand gestures) in Bharatanatyam. Open datasets on Bharatanatyam dance gestures are not presently available. An exhaustive open dataset comprising of various mudras in Bharatanatyam was created. The dataset consists of 15[Formula: see text]396 distinct single-hand mudra images and 13[Formula: see text]035 distinct double-hand mudra images. In this paper, we explore the dataset using various multidimensional visualization techniques. PCA, Kernel PCA, Local Linear Embedding, Multidimensional Scaling, Isomap, t-SNE and PCA–t-SNE combination are being investigated. The best visualization for exploration of the dataset is obtained using PCA–t-SNE combination.