Parkinson disease analysis using supervised and unsupervised techniques

Parkinson’s disease is classified as a disease of neurological origin, which is degenerative and chronic. Currently, the number of people affected by this disease has increased, one in 100 people over 60 years old, although it has been shown that the onset of this disease is approximately 60 years of age. Cases have also been identified of this disorder in patients as young as 18 years old suffer from this disease. Many tests have been developed throughout the literary review in order to identify patients tending to suffer from this disease that currently massifies its prevalence in the world. This article shows the implementation of different machine learning techniques such as LWL, ThresholdSelector, Kstar, VotedPercepton, CVParameterSelection, based on a test performed on experimental individuals and controls in order to identify the presence of the disease

Path Planning Approach for a Quadrotor Unmanned Aerial Vehicle

A path planning method for an unmanned aerial system type quadrotor is proposed in this work. It is based on Dubins curves. Therefore, different points (initial and ending) are set for generation of several paths. Additionally, to validate the proposed model a computational resource is applied. Also, some flight dynamics limits and orientation angles computations are considered to be able to determine a simplified Dubins model. Dubins paths are commonly divided into low, medium and high altitude gains. It will depend on the altitude established for the start and end points and other configurations

Teleagro: software architecture of georeferencing and detection of heat of cattle

The systems of livestock production contribute in a preponderant way to improve the quality of life of the communities, since it allows to support the production of the daily sustenance of the communities, to conserve the ecosystems, to promote the conservation of the wild life and to satisfy the values and traditions cultural Latin America, with its large wilderness areas, and a privileged climate favors the maintenance of livestock, to meet the demands of food and ensure regional and global food security. In Colombia, the agricultural sector contributes approximately 11.83% of the national GDP at current prices, according to the Bank of the Republic. Likewise, the livestock industry participates with 3.6%, in comparison with other sectors of the agricultural economy, the production of Colombian cattle doubles and triples to other sectors, such as poultry, coffee and floriculture. In addition, it contributes to the generation of employment in more than 25% of the total jobs generated in the agricultural sector and approximately 7% of the total employment of the Colombian economy (http://www.banrep.gov.co/is/pib). Within agricultural production, livestock occupy 38 million hectares, being 9 times larger than the area dedicated to agriculture. However, agriculture contributes 63% of the value of agricultural production, while livestock, mainly extensive, contributes 26% (FEDEGAN, Strategic Livestock Plan 2019). The large proportion of the área with agricultural vocation dedicated to precarious extensive livestock has explained the low agricultural productivity in Colombia, with very serious consequences for human and sustainable development. This document shows the results of the communications, software and hardware platforms to help the livestock sector to manage production

Using K-Means Algorithm for Description Analysis of Text in RSS News Format

This article shows the use of different techniques for the extraction of information through text mining. Through this implementation, the performance of each of the techniques in the dataset analysis process can be identified, which allows the reader to recommend the most appropriate technique for the processing of this type of data. This article shows the implementation of the K-means algorithm to determine the location of the news described in RSS format and the results of this type of grouping through a descriptive analysis of the resulting clusters

Implementation of the Eclipse Process Framework Composer Tool for the Documentation of Quality Management Systems: A Case Applied in Healthcare Services

This document presents the implementation of the Eclipse Process Framework Composer EPFC tool, in a company in the health sector, which where it were using physical documentation to register the processes QMS Quality Management Systems, in this one it is explained the process of adapting the tool, to migrate the documentary structure of the company, through the application of a model that correlates the attributes of the tool with the documentary structure. The proposed model allows the construction of document structures for the QMS that guide the user in their processes and procedures within the organization. Therefore, it is proposed that by promoting knowledge management and reducing the execution time of the processes, it will be possible for companies to be more productive, improve customer service, failure rates in the development of activities be minimized and, and reduces the lead time in the processes. Finally, it was obtained a documentary platform developed under a process approach that implements interactive diagrams that aim to facilitate the understanding of each of the elements that make up the QMS

OpenFOAM Numerical Simulations with Different Lid Driven Cavity Shapes

The finite volume method have been developed to solve the Navier-Stokes equations with primitive variables and non dimensional form. This work examine the classical benchmark problem of the lid-driven cavity at a different Reynolds range (Re = 10,100,400, 1000, 2000, 3200) and several cavity geometries. The cavity configurations include square cavity, skewed cavity, trapezoidal cavity and arcshaped cavity. The flow is assumed laminar and solved in a uniform mesh. A CFD tool with its solvers (icoFoam) will be used for this study

Technology Contribution to Improve Autistic Children Life Quality

To review published literature on the use of technology and how it has improved autistic children life style. A systematic review of the English literature was performed using the PRISMA guideline. Papers indexed in WOS and Scopus databases were included, adjusted to a timeline between 2016 and 2020 and focused on mobile technology, interventions, improvement of social behavior and communication and autism, aimed to describe the most used mechanism to improve autistic life style. Thirty two (32) papers were included in the review. We obtained 14 papers on the Scopus database and 18 on the WOS database. The majority of studies evidenced the use of virtual reality, mobile devices, video modelling and robots as the most common applications for autism therapies. Technology has caused an improvement in autistic children life quality. The development of mobile applications, virtual reality applications and robots have showed a positive impact reflected in the performance of daily activities and a better understanding of how they feel, how to behave, how to express themselves and interact with others. Technology gives the opportunity to monitor children status; and offers adaptability, safety, and accuracy of the information

SSwWS: structural model of information architecture

The Web Technologies allow a representation of a domain of knowledge. This facilitates the conversion of an explicit and tacit knowledge to the possibility of adding knowledge to the Web for automatic processing by the computer. For this reason, it has been designed to be an architecture known as SSwWS (Search Semantic with Web Services) or Search Semantic Web Services, to show how to extend the functionality of the Web search and semantic raised by Berners-Lee, on the meta-references, defined in a Web ontology, so that a user on the Internet can find the answers to their questions through Web services in a simple and fast

Enkephalon - technological platform to support the diagnosis of alzheimer’s disease through the analysis of resonance images using data mining techniques

Dementia can be considered as a decrease in the cognitive function of the person. The main diseases that appear are Alzheimer and vascular dementia. Today, 47 million people live with dementia around the world. The estimated total cost of dementia worldwide is US $ 818 billion, and it will become a trilliondollar disease by 2019 The vast majority of people with dementia not received a diagnosis, so they are unable to access care and treatment. In Colombia, two out of every five people presented a mental disorder at some point in their lives and 90% of these have not accessed a health service. Here it´s proposed a technological platform so early detection of Alzheimer. This tool complements and validates the diagnosis made by the health professional, based on the application of Machine Learning techniques for the analysis of a dataset, constructed from magnetic resonance imaging, neuropsychological test and the result of a radiological test. A comparative analysis of quality metrics was made, evaluating the performance of different classifier methods: Random subspace, Decorate, BFTree, LMT, Ordinal class classifier, ADTree and Random forest. This allowed us to identify the technique with the highest prediction rate, that was implemented in ENKEPHALON platform

Mathematical Modelling and Identification of a Quadrotor

Motivated by the important growth of VTOL vehicles research such as quadrotors and to a small extent autonomous flight, a quadrotor dynamical model is presented in this work. The purpose of this study is to get a better understanding of its flight dynamics. It is an underactuated system. So, a simplified and clear model is needed to implement controllers on these kind of unmanned aerial systems. In addition, a computational tool is used for validation purposes. For future works embedded or intelligent control systems can be developed to control them. Gyroscopic and some aerodynamics effects are neglected