Cesar Leon, Iván Petrlik, Jorge Mayhuasca, Ciro Rodriguez, José Coveñas
The purpose of the study was to determine the effect of
the problem-solving method on the achievement of
mathematical competence in alternative basic education students. For
this purpose, a quasi-experimetric design
was used. The instrument applied is a 10-item questionnaire, which is an
adaptation of the PISA tests that was
validated by expert judgment, and its concordance was evaluated using
Fleiss' Kappa with a coefficient of 0.688
and Cronbach's Alpha reliability yielded a coefficient of 0.820. It was
concluded that the application of the
problem-solving method had a significant effect on the achievement of
mathematical competence of alternative
basic education students, with p=0.000
<0.05. Similarly, a significant effect was found in the achievement of
mathematical competence in the dimensions numbers and relations,
geometry and measurement, and statistics and probability in each of
the cases with p=0.00<0.05.
Keywords: M-Learning, Method, problem solving, problem
solving and mathematical competence.
Pratiksha P. Jawale and Dr. Shantipal S. Ohol
Speech recognition technology has emerged as a pivotal tool across
various industries, enabling
seamless and natural interactions between humans and robots. In the
field of Human-Robot Interaction (HRI),
it offers an intuitive and efficient means of controlling robots with
straightforward implementation and evident
usability, making it a valuable asset for improving communication in
collaborative settings. This research
focuses on developing a real-time, speech-driven external control system
for collaborative robots (cobots) by
integrating Python with the Google Speech-to-Text API, achieving precise
control of robot movements along
three axial directions and gripper operation. The study evaluates key
performance metrics,including latency,
speech recognition accuracy and user experience for highlighting the
system’s potential for enhancing humanrobot collaboration
Keywords: Speech Recognition, Collaborative Robot,
Human-Robot Collaboration
Santos Sotelo Antaurco, Julio Sotomayor Abarca Antaurco, Daniel Alejandro Yucra Sotomayor and Yeltsin Sotelo
This research project presents the problem of choosing or defining a
software architecture for the technological
waste management system of the Universidad Nacional Federico Villareal
and shows how it is possible to define
the process of Architecture Design based on Infrastructure as code that
is capable of being scalable, maintainable,
secure and interoperable as principles for the Design.
In addition, it presents the Design of an application architecture using
infrastructure as code - IaC, in the cloud and
is able to support the capabilities of the components and modules of the
Technological Waste Management System
of the Universidad Nacional Federico Villarreal.
This project also implies, to determine the favourable acceptance to
develop the Application Architecture Design
using infrastructure as code - IaC.
From the technological point of view, the most critical dimensions are
also presented to take into consideration the
architecture design based on the functional modules of the Technological
Waste Management System of the
Universidad Nacional Federico Villarreal.
At the end of the work the presentation of results and discussion based
on the instrument used is shown, to determine
in the final part the fulfillment of the objective describing the
conclusions and recommendations.
Keywords: Application architecture, Infrastructure as
code, Technological waste management Technological
waste; waste management; waste monitoring; monitoring system; software
architecture; environmental
contamination.
Shailesh S. Kadre, S. K. Vemuri, P.K. Mukka, R.G. Paspula and Vipin K. Tripathi
A Finite Element Analysis (FEA) code was developed in Python to solve shell problems under plane stress
conditions using constant strain triangles. The workflow involves mesh generation, computation of stiffness and
assembly matrices, and application of loads and boundary conditions. The analysis provides stresses and
displacements for different configurations. To enhance predictive accuracy, a Graph Neural Network (GNN) model
was implemented using a Python library. Node features, including coordinates and boundary conditions, were
incorporated, while edge indices were computed. The GNN utilized these inputs, with nodal stresses and
displacements from FEA serving as target variables in a supervised learning setup. A diverse dataset was generated
to capture various configurations. The results showed a high correlation between FEA-derived displacements and
stresses and the corresponding GNN predictions for test and validation data. This method has been successfully
generalized for different engineering applications, demonstrating its effectiveness in structural analysis.
Furthermore, this study extends GNN-based predictions to cases involving different discontinuity shapes, such as
circular, elliptical, semicircular, and bend radius geometries, further validating its robustness and applicability
across a range of structural problems.
Keywords: Graph Neural Network - GNN, FEM, Surrogate Models, Predictive Modeling.
Niraj Pankaj Torane and Shantipal Suresh Ohol
This paper presents a comprehensive dynamic modeling and simulation-based analysis
of a dual-arm robotic system, each arm consisting of seven degrees of freedom (DOF). The study employs the
Newton-Euler recursive formulation to perform inverse dynamic analysis, enabling the calculation of joint
torques required for executing coordinated motion. A 100 mm cubic object is considered as a shared payload
between the arms to simulate cooperative manipulation. Kinematic parameters such as joint angles, velocities,
and accelerations are generated using smooth sinusoidal trajectories to ensure realistic and continuous motion.
The resulting torque profiles are analyzed under dynamic loading conditions, including the influence of the
object's mass. Graphical results for both arms confirm that the system maintains smooth and synchronized
motion with torque values well within feasible limits. The analysis highlights the effectiveness of the NewtonEuler approach for accurately modeling complex dual-arm robotic systems and provides valuable insights for
real-time control and cooperative task execution
Keywords: dynamic modeling, robotic system, inverse dynamics, Newton-Euler
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