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Introduction to the special section on advances of machine learning in cybersecurity (VSI-mlsec)
(Computers and Electrical Engineering, 2022)
With the rapid advancement of emerging technologies, such as Internet of Things (IoT), cloud computing, and many more, a huge amount of data is generated and processed in daily life. As these technologies are based on the ...
Corporate Exhibitions and Marketing as a Result of the Integration Project at the University of Cundinamarca
(Smart Innovation, Systems and Technologies, 2022)
The academic spaces united with marketing are developed in research processes, centers of creation and innovation by the student body of the University of Cundinamarca, generating strategic learning projects, building forms ...
Analysis of the Impact of Applying UX Guidelines to Reduce Noise and Focus Attention
(Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022)
This research work is the continuation of previous, in which a set of usability guidelines where proposed. These guidelines were obtained from various authors and recommendations. The common part of those guides was that ...
The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID19 Pandemic
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they ...
Analysis of the COVID19 Pandemic Behaviour Based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, ...
The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in ...
Probabilistic Forecasting Model for the COVID-19 Pandemic Based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System
(Epidemic Analytics for Decision Supports in COVID19 Crisis, 2022)
There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of ...
Classification of Breast Thermal Images into Healthy/Cancer Group Using Pre-Trained Deep Learning Schemes
(Procedia Computer Science, 2022)
In the women's community, Breast Cancer (BC) is a severe disease. The World Health Organization reported in 2020 that 2.26 million deaths occur due to BC. BC is curable if detected early. Since thermal imaging is non-invasive ...
Automatic detection of lung nodule in CT scan slices using CNN segmentation schemes: A study
(Procedia Computer Science, 2022)
The lung is one of the prime respiratory organs in human physiology, and its abnormality will severely disrupt the respiratory system. Lung Nodule (LN) is one of the abnormalities, and early screening and treatment are ...
Deep and handcrafted feature supported diabetic retinopathy detection: A study
(Procedia Computer Science, 2022)
The eye is the prime sensory organ in physiology, and the abnormality in the eye severely influences the vision system. Therefore, eye irregularity is commonly assessed using imaging schemes, and Fundus Retinal Image (FRI) ...