DSpace Communidade:https://repositorio.uema.br/jspui/handle/123456789/19152026-04-09T04:15:13Z2026-04-09T04:15:13ZUniversidade VoIP: do legado às redes totalmente IPhttps://repositorio.uema.br/jspui/handle/123456789/49702025-06-10T18:11:01Z2025-02-28T00:00:00ZTítulo: Universidade VoIP: do legado às redes totalmente IP
Abstact: Continuing the research on Universidade VoIP, this study expanded its application to
public sector institutions, focusing on E-TEC and IFMA - Advanced Campus of Rosário. The
study aimed to demonstrate the feasibility of IP telephony in these environments, considering
the need for adaptation of analog telephony, which is still present in various locations. To
achieve this, Asterisk was implemented and tested on two different operating systems,
Windows and Linux, evaluating its functionality on different platforms. Additionally, a
no-code based application was developed, enabling messaging, audio conferencing, and
video conferencing. As a result, a fully functional VoIP server was obtained, adaptable to both
local networks (LAN) and wide-area networks (WAN), ensuring efficient communication
between legacy systems and IP infrastructure. The solution demonstrated that IP telephony
can be progressively integrated, preserving connectivity and expanding institutional
communication possibilities. Thus, the potential of IP Telephony is reaffirmed as a modern
and accessible alternative for the evolution of communication systems2025-02-28T00:00:00ZUm algoritmo genético paralelo autoadaptável misto para a otimização multimodal com e sem restriçõeshttps://repositorio.uema.br/jspui/handle/123456789/48952025-05-27T13:35:46Z2017-08-14T00:00:00ZTítulo: Um algoritmo genético paralelo autoadaptável misto para a otimização multimodal com e sem restrições
Abstact: Genetic algorithms are search algorithms that use a set of parameters to find the best
solution to a given problem. These parameter’s choice is a challenge because different
problems can demand different sets. Most of the times, this choice is made using the trial
and error method that demands time and may not lead to the best possible setting. Other
option is to use the experiment design (factor n
k
) that further on limited to the amount
of k factors, demands that multiple simulations are done before the definition of the best
setting, which is also dependent of the problem that is being solved. In this context, the
self-adaptive algorithms arise, allowing the best selection of rates and genetic operators
within execution time. Thereby, this work develops a self-adaptive algorithm that in
addition of choosing between four different kinds of crossover and four mutation operators
also adapts in execution’s time the rates of crossover and mutation. Having overcome
the challenge of finding the best configuration, remains increasing the execution time,
because as more parameters are adjusted a higher computational power is required. To
solve this problem, it is used the parallel computing, which became acessible and popular
after the criation and cost reduction of multicore processors. In this work, the parallelism
is achieved using the OpenMp, which is an application programming interface (API)
that supplies a portable and scalable model that allows programmers to create parallel
applications. To evaluate the self-adaptive algorithm performance standard benchmark
functions were used, such as Schwefel, Griewank, Rastringin, Rosenbrock, variations of the
last two ones (Shifted Rastringin and Shifted Rosenbrock) and a real application called
Dynamic Economic Dispacth. The evaluation was made in terms of the solution’s quality
using ANOVA and Tukey’s test. In terms of parallelism, the evaluation was done using
speedup and eficiency metrics2017-08-14T00:00:00ZClassificação de libras em imagens através de redes neurais convolucionaishttps://repositorio.uema.br/jspui/handle/123456789/41472025-01-21T18:48:40Z2022-10-31T00:00:00ZTítulo: Classificação de libras em imagens através de redes neurais convolucionais
Abstact: The literacy of deaf people is currently a major challenge that has generated many
discussions in the educational context. Despite the existence of sign language (Libras),
the training of people to carry out teaching activities in this area is quite scarce, and this
has made the teaching and learning process of people with or without hearing problems
very difficult. With the increasing growth of the internet and computer technologies, it
was needed to create advanced artificial intelligence applications to improve this process.
A very important milestone was the emergence of Computer Vision, which is an area of
artificial intelligence that seeks to analyze, interpret and extract certain useful information
from images, also studying the use of emotions, recognition, and analysis of interactive
movements of human beings through computerized AI systems that simulate the thoughts
and actions of human beings. The main subject of this work addresses a research related
to the application of convolutional (or deep) neural network, which are similarly linked
to computer vision. Experiments were carried out using a Libras database that served as
support for the training of images through the YOLOv5 deep neural network algorithm
to perform the Classification of some groups of 6 and 7 images. Subsequently, the results
of the tests were compared, and it was observed which periods had a better performance
during the classification of Libras images2022-10-31T00:00:00ZDesenvolvimento de um aplicativo nas plataformas android e Ios utilizando comunicação segura para a solução voip UEMAhttps://repositorio.uema.br/jspui/handle/123456789/38082024-12-06T17:53:13Z2021-03-31T00:00:00ZTítulo: Desenvolvimento de um aplicativo nas plataformas android e Ios utilizando comunicação segura para a solução voip UEMA
Abstact: Seeking to overcome the deficiencies from Maranhão state in the technological area, as well
solving the communication problems that State University of Maranhão is currently facing,
the project VoIP UEMA was created to provide a telephone service with high quality
standards and low cost for the UEMA community to utilize. In this project, a freeware tool for
smartphones on Android and iOS platforms, capable of making audio and video calls through
TCP/IP network, while authenticating with SIGUEMA credentials. A marketing research has
been done looking for similar tools that could perform the same task, but none of the
available tools could provide an authentication with SIGUEMA, also, some of those
applications showed deficiencies and defects. The developed application allows
authentication with SIGUEMA, through the Web Service VoIP UEMA, a connection with VoIP
service provider, Asterisk, successfully making high quality calls while filling out the defects
of the evaluated applications2021-03-31T00:00:00Z