ChatGPT and GeoGebra to Support the Learning of First-Order Linear Differential Equations in Engineering Students | Chapter 4 | Mathematics and Computer Science: Research Updates Vol. 5

 

In the teaching of mathematics, and particularly of differential equations, students often face multiple difficulties in understanding abstract concepts. To address these challenges, two powerful tools, GeoGebra and ChatGPT, have been integrated to enrich the learning of engineering students at the University of Antofagasta, Chile. GeoGebra, recognised for its dynamic and interactive potential, allows the construction of graphical and animated representations that make visible the behaviour of the solutions of first-order linear differential equations, while ChatGPT acts as a guide for students in the interpretation of concepts and the resolution of doubts. This combination of interactive visualisation and conversational support allows students not only to access a mix of innovative technological resources but also to reinforce their learning and strengthen their mathematical competencies through a methodology that is accessible and adapted to their needs.

 

Author (s) Details

Jorge Olivares
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

Melissa Sanchez
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

Pablo Martín
Department of Mathematics, Universidad de Antofagasta, Antofagasta, Chile.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/mcsru/v5/5176

Enhancing Chess Skills through Blindfolded Tactics: An Experimental Study on Cognitive and Performance Gains | Chapter 8 | An Overview of Literature, Language and Education Research Vol. 7

Blindfold chess is a game where both the board and pieces are not visible to its players. The objective of the project is to explore the cognitive and performance benefits of solving blindfolded tactics compared to traditional methods and to verify the didactic usefulness of these solving tactics in young and adult people, involving an experimental and a control group in the research. A sample of 27 students (14 -30 years old) has been formed and several training sessions with blindfold tactical exercises have been organized. In three months 12 lessons were organized. Then objective measures (not subjective evaluations) of the benefits of this method have been collected by measuring two performance parameters (solving times of exercises and FIDE elo rating change after training sessions) and comparing them with their results before using this method. We analyzed the performance x blindfolding tactics interaction, in particular the correlations between the performance improvement x training interaction and the experimental cognitive path with the three steps of training interaction, compared to participants in the control group. Significant are differences in the improvement in solving tactics times, that is increasing the response speed. Significant results were also found in Rapid FIDE Elo rating improvement, that is increasing the playing force as a function of FIDE rating under vs over 1900 Elo (p >0,05) with a greater improvement for males. In the control group, the interaction is not significant (p>0,5) both in solving tactic times (with an average reduction of 30 seconds for each move) and in FIDE Elo Rating change after the training sessions. The results of this pilot study encourage us to organize a new experimental design in the future with more significant samples to prepare a detailed “Blindfolded tactics training protocol” adaptable to different playing levels of the subjects.

 

Author (s) Details

 

Giovanni Marchesich
Sicura Mente-Young Non Profit Organization, Trieste 34141, Italy.

 

Laura Tamburini
Sicura Mente-Young Non Profit Organization, Trieste 34141, Italy, Department of Life Sciences, University of Trieste, Italy and Ministry of Education and Merit, Friuli Venezia Giulia 34124, Italy.

 

Please see the book here:- https://doi.org/10.9734/bpi/aoller/v7/2979

A Study on Interactive Proteomic Data Clustering: A Comparison between Self-Organizing Map and Neural Gas | Chapter 1 | Research and Applications Towards Mathematics and Computer Science Vol. 7

The interconnected system algorithms Self-Organizing Map (SOM) and Affecting animate nerve organs Gas (NG) use unsupervised competing learning. These methods have the fault-finding virtue of maintaining the topological structure of the data, that means that data that are enclose the input distribution are plan to neighboring positions in the network or output. This characteristic form them intriguing to search in terms of dossier clustering. A crucial characteristic resolving vast amounts of data manually maybe challenging and time-consuming. Suitable way, technologies for analyzing and visualizing large multidimensional data sets are necessary.  We introduce a order for comparing and visualizing the SOM and NG in this branch. We describe these algorithms first, and then we create a pictorial comparison betwixt them. The protein mass spectrometry dossier clustering is then elucidated using these imagination approaches.

Author(s) Details:

Terje Solsvik Kristensen,
Department of Informatics, Western Norway University of Applied Sciences, Bergen, Norway and BIC AS, Norway.

Please see the link here: https://stm.bookpi.org/RATMCS-V7/article/view/12831

Study on Waste Management Using Regression Analysis in Karnataka, India | Chapter 13 | Advances and Challenges in Science and Technology Vol. 8

 The waste-process and allure intricacy administration has obtained extreme attention in current years everywhere the globe and again it causes chain-linked weighty environmental and terrestrial problems. The potential of Multi Linear Regression (MLR)-model helps in indicator of waste-management, the data is changed into Waste Disposed in Tonnes (WDT), Waste Recycled Tonne (WRT), Waste Generated Tonne (WGT). These includes overall reusing rate every-period. The article primarily focuses on graphical representation of waste-administration and future-prediction of waste-administration. This model helps to state the difference middle from two points actual-principles and predicted-principles which gives united states of america best confirmation. This model maybe applicable each and every waste of state & envision the future-management of wastes. With the help of this model the total waste method can be surely segregated for-future-use.

Author(s) Details:

Mahalakshmi,
Department of Mathematics, School of Applied Sciences, REVA University, Bengaluru, Karnataka, India.

Naveen N.,
Department of Mathematics, School of Applied Sciences, REVA University, Bengaluru, Karnataka, India.

M. Rajeshwari,
Department of Mathematics, Presidency University, Bengaluru, Karnataka, India.

Please see the link here: https://stm.bookpi.org/ACST-V8/article/view/12392

The Peptide Visualizer and COVID-19 Protein Feature Captivation | Chapter 10 | Research Aspects in Biological Science Vol. 3

The peptide visualizer was created to capture the essential characteristics of coronavirus peptides using RGB colour and geometric forms that differed based on the amino acid type, molecular weight, charge, and polarity. The charts show the sequence and functional characteristics of the peptides in this fashion. It offers a unique perspective on peptide properties in different coronavirus species. The method effectively recognised the S protein RBD region in the four coronavirus subtypes: OC43, HKU1, MERS, and SARS, as shown in the study. The visualizer can detect minor changes in peptide sequences, which might help with coronavirus diagnosis, treatment, and prevention. More than only graphing coronavirus peptides can be done with the application. It may be used to see changes in peptide sequences, structures, and other things. In both prokaryotes and eukaryotes, it plays a role.

Author(s) Details:

Samuel Krem,
Buckingham Browne and Nichols School, Cambridge, MA 02138, United States.

Please see the link here: https://stm.bookpi.org/RABS-V3/article/view/7052

Manufacturing Bill-of-Materials Plus Operations Visualization Using D3 | Chapter 7 | Advanced Aspects of Engineering Research Vol. 6

 Given the complexity of many organisations' manufacturing settings, visualisation of factory production flow aids test optimization decision-making. Building production flow visualisations is challenging and time-consuming, and it frequently necessitates the use of expensive simulation tools. In this paper, we show how we used the free source D3.js visualisation toolkit to populate NIST CMSD Core Manufacturing Simulation Data from existing factory data to visualise factory flows. The open source visualisation toolkit represents a lower-cost mechanism for analysing and optimising test processes, as explained in this paper, by mapping existing factory test data using the CMSD standard. The visualisation was created by a small team and put into production at a large aerospace manufacturer in four months. It is now utilised by several business units for manufacturing flow improvements of their highly engineering products.

Author(s) Details

P. Bhat
Digital Technology Raytheon, USA.

S. Berryman
Digital Technology Raytheon, USA.

A. Burkhardt
Digital Technology Raytheon, USA.

M. Cho
Digital Technology Raytheon, USA.

S. Ferkau
Digital Technology Raytheon, USA.

H. Gharbiah
Digital Technology Raytheon, USA.

K. Johnston
Digital Technology Raytheon, USA.

A. Kaiser
Digital Technology Raytheon, USA.

K. Lynch
Digital Technology Raytheon, USA.

S. Mittman
Digital Technology Raytheon, USA.

Q. Risch
Digital Technology Raytheon, USA.

M. Swansen
Digital Technology Raytheon, USA.

View Book :- https://stm.bookpi.org/AAER-V6/article/view/1000

Review of Methods for Conditional-Probability Computations in Medical Disciplines | Chapter 7 | Highlights on Medicine and Medical Research Vol. 1

There is a definite need for conditional probability representations and methods that increase comprehension, simplify calculations, promote intuition, and encourage reasoning. In a wide range of scientific disciplines, such representations and instruments are desirable and useful, but their usefulness in medical contexts and applications is emphasized here, in order to address a clinical audience rather than a mathematical audience. We use a plethora of time-tested pedagogical representations or conditional probability methods, including: (a) Visualization of Venn diagrams or Karnaugh maps, (b) Reformulation as natural frequencies, (c) Entity interrelationships through Signal Flow Graphs, (d) Specification of certain problem formats, such as Trinomial Graphs format, and (e) Use of a pair of Karnaugh-map-like or complementary Karnaugh-maps Most of the new representations or instruments have well-known records of pedagogical benefits, but in the particular realm of conditional probability they are yet to be evaluated. Further evaluation of the novel representations or instruments proposed herein is needed. - of these is to be taught to a group of students, and the traditional representation must be used to teach a control group of students. Detailed statistical analysis of the findings is warranted. Earlier, similar inquiries were conducted, but they were on a small scale. The need arises, therefore, for an exploratory analysis that exhausts all suggested representations or instruments.

Author (s) Details

Rufaidah Ali Rushdi
Department of Pediatrics, Kasr Al-Ainy Faculty of Medicine, Cairo University, Cairo, 11562, Arab Republic of Egypt.

Ali Muhammad Rushdi
Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.

Fayez Ahmed Talmees
Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.

View Book :- https://stm.bookpi.org/HMMR-V1/issue/view/2