Identifying optimal course structures using topic models

This research project investigates whether there exists an optimal way to structure topics in educational course content that results in higher levels of engagement among students. It is implemented by fitting topic models to transcripts of educational videos contained in the Khan Academy platform. The fitted models were used to extract topic trajectories across time for each video and subsequently clustered based on whether they have similar “shapes”. The differences in mean engagement metrics per cluster suggest that some course shapes are more palatable to students regardless of subject matter. Additionally, the topic trajectories suggest a constant progression of topics with little repetition is optimal for student engagement. The results from this project provide new methodologies to improve educational quality by focusing on the sequence of themes within instructional material

Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning

Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality

Detection of regular boundaries in noisy and textured images : a multiscale active contour approach

This article deals with the detection of edges in noisy and textured images . After an overview of the shortcomings of local operators, we assess active contour models, which constrain the detection using a priori information . The implementation of active contours is difficult due to several problems . We suggest two methods which make this global approach more robust and easier to use . On one hand, the parameters are set using a calibration algorithm which relies on geometrical a priori . The value of the parameters depends upon the maximum curvature . On the other hand, a multiscale strategy reduces the need for an accurate initialization of active contours . The convergence is robust at coarse scales and the localization of edges is enhanced at fine scales . Several efficient algorithms are proposed to track contours over decreasing scale, using a prediction on the distorsion of boundaries caused by gaussian blurring . The experiments show the validity of our approach and the relevance of a cooperation between segmentation processes, especially to solve the initialization problem .Cet article traite de la détection de contours dans des images fortement bruitées et texturées. Après avoir exposé les limitations des opérateurs locaux, nous suggérons de contraindre la détection grâce aux modèles de contours actifs, qui introduisent des informations a priori sur la géométrie et la régularité des objets cherchés. La mise en oeuvre des contours actifs est difficile en raison de nombreux problèmes pratiques. Nous proposons deux techniques rendant cette approche globale plus robuste et plus facile d'emploi. D'une part, nous facilitons le choix des paramètres en adaptant un algorithme de calibrage ayant une explication géométrique : les paramètres dépendent de la valeur de la courbure maximale. L'association des contours actifs et d'une représentation multiéchelle permet d'autre part de réduire la dépendance vis-à-vis de l'initialisation. Après une convergence robuste vers une solution grossière, la localisation des contours est améliorée en diminuant progressivement l'échelle d'analyse. Nous proposons alors plusieurs techniques efficaces de suivi des contours dans l'espace-échelle, s'appuyant sur une prédiction du déplacement des frontières sous l'effet du lissage gaussien. Les résultats expérimentaux montrent la validité de notre approche, et mettent en évidence l'apport d'une collaboration entre processus de segmentation, en particulier pour automatiser l'initialisation

Study of antimicrobial and antioxidant properties of new materials for development of active food packaging

This work is focused on the design, production and characterization of sustainable active food packaging materials with antimicrobial and antioxidant properties to ensure the safety and quality of foods and prolong their shelf-life. Firstly, a microfluidic device combining dielectrophoresis (DEP) and Raman spectroscopy was developed for a fast and dynamic characterization of different bacterial strains, including food-related pathogens (i.e. E. coli and S. aureus), directly in planktonic suspension. Predictive models to identify bacterial cross-induced resistance to antibiotic within few hours were built using this method, overcoming the overnight incubation required by classical microbiological assays. Furthermore, Raman imaging was employed to detect the spatial distribution of different biomolecules at single cell level. Then, the antibacterial properties of innovative silver and carbon-based nanosystems and their inclusion in prototype packaging materials were studied. Differently sized silver nanoparticles, from 6 to 50 nm, were compared for their antibacterial efficacy in suspension and immobilized on glass. For the first time, the surface minimal bactericidal concentration (SMBC) of silver needed to kill 99.9999% of bacteria, was determined by ISO 22196, thereby facilitating the comparison between measurements and minimizing the amount of silver on the materials surface (0.023-0.034 μg/cm2) as well as their cost of production and toxicity. Colloidal carbon nanoparticles (CNP), obtained by a green chemistry synthesis, were tested against Gram + and a Gram – bacteria, by classical microbiological assays and the DEP-Raman system, revealing a rapid interaction with the bacteria but not significant bactericidal effects. Thus, CNP were loaded with an antimicrobial peptide which increased their antibacterial activity, especially against S. aureus. Finally, new antioxidant packaging modified with grape and olive industrial waste products and Moringa oleifera leaves obtained by different extractive procedures were produced and characterized. The antioxidant efficacy of many fractions of the plants extracts were analyzed by multiple standard assays and the results were correlated with their content of polyphenols obtaining higher values for anti-solvent and maceration extract fractions. The latter, resulting from a more sustainable extraction procedure, were included in cellulose-based active packaging systems. The antioxidant properties of such films were measured by indirect and direct analytical methods demonstrating good free radical scavenging properties for all the three kind of active agents and a higher radical reduction capacity of moringa. Additionally, the ability of the packaging coated with moringa (5% w/w) of delaying fresh ground beef oxidation was tested. This film was chosen as the best alternative to obtain the highest oxidative protection of meat on the basis of the in vitro results and ensuring a direct food-contact mechanism of action. This packaging revealed to prevent meat from lipid oxidation by at least 60% after 16 days compared to simple cellulose. Additionally, in situ analysis of the meat performed by vibrational spectroscopies evidenced also a protective action against protein and lipid degradation. This work could be considered valuable in the field of food packaging because the use of sustainable and degradable materials to prolong the food shelf-life perfectly fits in the actual compelling need to reduce pollution and global waste production. This is in accordance with the 12th Sustainable Development Goal of the European Green Deal purpose to halve the global food waste production per capita by 2030, ensuring an efficient and sustainable use of natural resources. Hence, an innovative way to recover food industry waste is proposed and their antioxidant efficacy in active food packaging was demonstrated even on real food matrices with many different techniques strengthening the reliability of the results

Web-Based Courses In Higher Education: Creating Active Learning Environments

Problem. As more and more adults seek to continue their education, alternate methods of course delivery Will be required to meet their needs. Web-based courses allow students to learn at times and places that are convenient for them. There is concern, however, about whether or not such courses can create effective, active learning experiences, and whether or not knowledge can be socially constructed in online interactions. In order for higher education to provide exemplary online courses, it is important to identify necessary elements and instructional strategies to create virtual learning environments. The goals of this study were to determine instructional practices in exemplary higher education Web based courses and their perceived effectiveness and to determine implications of new delivery models for higher education. Method. This qualitative study examined the 1998 Paul Allen Virtual Education Foundation\u27s Outstanding Online Course Award winner and five of the six Honorable Mentions. Typical qualitative tools were used to gather data including a Web-based questionnaire, email correspondence, video recordings of conference presentations by four of the instructors, observations, interviews, course Web pages, plus articles and Web sites published by the instructors. Each course was a case study. Results. Effective practices and design features of these exemplary online courses demonstrate multiple ways to facilitate active learning in Web-based instruction. The rich environments of these six courses included a variety of interactions between the instructor and students and among the students themselves. They model how innovative pedagogy guides the use of technology and that virtual learning communities can be created in any discipline. Faculty who have administrative support will be more likely to design, develop, and deliver effective Web-based instruction. Conclusions. The study demonstrated ways online courses can be designed to meet the criteria of the American Psychological Association\u27s Learner-Centered Psychological Principles. A number of implications for higher education emerged

Hypertools in image and volume visualization

This paper describes our experience in image and volume visualization at the Lawrence Livermore National Laboratory. After an introduction on visualization issues, we present a new software approach to the analysis and visualization of images and volumes. The efficiency of the visualization process is improved by letting the user combine small and reusable applications by the means of a machine-independent interpreted language such as Tcl/Tk. These hypertools can communicate with each other over a network, which has a direct impact on the design of graphical interfaces. We first describe the implementation of a flexible gray-scale image widget that can handle large data sets, provides complete control of the color palette and allows for manual and semi-interactive segmentation. This visualization tool can be embedded in a data-flow image processing environment to assess the quality of acquisition, preprocessing and filtering of raw data. This approach combines the simplicity of visual programming with the power of a high-level interpreted language. We show how hypertools can be used in surface and volume rendering and how they increase the interaction efficiency by performing complex or tedious tasks automatically. One biomedical application is presented