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1
capítulo de libro
Publicado 2019
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This work proposes a semi-automated analysis and modeling package for Machine Learning related problems. The library goal is to reduce the steps involved in a traditional data science roadmap. To do so, Sparkmach takes advantage of Machine Learning techniques to build base models for both classification and regression problems. These models include exploratory data analysis, data preprocessing, feature engineering and modeling. The project has its basis in Pymach, a similar library that faces those steps for small and medium-sized datasets (about ten millions of rows and a few columns). Sparkmach central labor is to scale Pymach to overcome big datasets by using Apache Spark distributed computing, a distributed engine for large-scale data processing, that tackle several data science related problems in a cluster environment. Despite the software nature, Sparkmach can be of use for local ...
2
artículo
Publicado 2023
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With the increase of the university population, the individual psychological care service by psychologists in universities has been affected. Which has caused discomfort among students to access the psychological consulting service. Therefore, this project aims to implement a data analysis system to control the psychological variables that affect university students, improving attention to them through the use of artificial intelligence (AI). We present a system that allows the visualization of data related to the mental health of the students who developed a psychological test, with which the psychologist will be able to diagnose the student's mental state and determine if he or she requires personalized attention. Finally, with this research, we achieved an improvement in the speed of attention and quality of service for the student.
3
artículo
Publicado 2023
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Currently, type 2 diabetes mellitus is one of the world's most prevalent diseases and has claimed millions of people's lives. The present research aims to know the impact of the use of machine learning in the diagnostic process of type 2 diabetes mellitus and to offer a tool that facilitates the diagnosis of the dis-ease quickly and easily. Different machine learning models were designed and compared, being random forest was the algorithm that generated the model with the best performance (90.43% accuracy), which was integrated into a web platform, working with the PIMA dataset, which was validated by specialists from the Peruvian League for the Fight against Diabetes organization. The result was a decrease of (A) 88.28% in the information collection time, (B) 99.99% in the diagnosis time, (C) 44.42% in the diagnosis cost, and (D) 100% in the level of difficulty, concluding that the appl...
4
artículo
Publicado 2023
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Currently, type 2 diabetes mellitus is one of the world's most prevalent diseases and has claimed millions of people's lives. The present research aims to know the impact of the use of machine learning in the diagnostic process of type 2 diabetes mellitus and to offer a tool that facilitates the diagnosis of the dis-ease quickly and easily. Different machine learning models were designed and compared, being random forest was the algorithm that generated the model with the best performance (90.43% accuracy), which was integrated into a web platform, working with the PIMA dataset, which was validated by specialists from the Peruvian League for the Fight against Diabetes organization. The result was a decrease of (A) 88.28% in the information collection time, (B) 99.99% in the diagnosis time, (C) 44.42% in the diagnosis cost, and (D) 100% in the level of difficulty, concluding that the appl...
5
artículo
Publicado 2022
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so, machine learning techniques are being developed to improve performance and maintenance prediction. Increasing our knowledge of the relationship between humans and algorithms, Because data is so valuable, improving strategies for intelligently having to manage the now-ubiquitous content infrastructures is a necessary part of the process toward completely autonomous agents. Numerous researchers recently developed numerous computer-aided diagnostic algorithms employing various supervised learning approaches. Early identification of sickness may help to reduce the number of people who die as a result of these illnesses. Using machine learning techniques, this research creates an efficient automated illness diagnostic algorithm. We chose three key disorders in this paper: coronavirus, cardiovascular diseases, and diabetes. The data are inputted into a mobile application in the suggested m...
6
artículo
The problem that is approached in the present article is the following one: How to elaborate a communication fast and easy to understand and, simultaneously, oriented to the process control with a automated mixer? During the research development it will appreciate the main criterias to consider for its design, as well as the type of programming will be used. As result obtained a software SCADA whose Human Machine Interface (HMI) will be the contact of man with the process to control.
7
artículo
The problem that is approached in the present article is the following one: How to elaborate a communication fast and easy to understand and, simultaneously, oriented to the process control with a automated mixer? During the research development it will appreciate the main criterias to consider for its design, as well as the type of programming will be used. As result obtained a software SCADA whose Human Machine Interface (HMI) will be the contact of man with the process to control.
8
artículo
Publicado 2023
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Machine learning is a branch of artificial intelligence that uses scientific computing, mathematics and statistics through automated techniques to solve problems based on classification, regression and clustering. Social demand refers to the need for service and product of the professional training process, expressed by interest groups, aimed at contributing to national development, as established by the quality assurance policy of university higher education and national licensing and accreditation models. In this context, this paper conducts research based on job positions of IT professionals posted n web portals, designs a machine learning process with an unsupervised approach, extracts occupational profiles, designs a multidimensional model, applies k-means clustering when determining clusters of job positions by similarity, and reports the results obtained.
9
artículo
Publicado 2020
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Commonly the searching and identification of new particles, requires to reach highest efficiencies and purities as well. It demands to apply a chain of cuts that reject the background substantially. In most cases the processes to extract signal from the background is carried out by hand with some assistance of well designed and intelligent codes that save time and resources in high energy physics experiments. In this paper we present one application of the Mitchell’s criteria to extract efficiently beyond Standard Model signal events yielding an error of order of 1.22%. The usage of Machine Learning schemes appears to be advantageous when large volumes of data need to be scrutinized.
10
artículo
Publicado 2024
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This study presents Datalyzer, a system designed for data extraction, visualization, and prediction in the mining sector using advanced NLP and machine learning, specifically GPT-3.S Turbo. The system enhances operational efficiency through rigorous data preprocessing and specialized fine-tuning, validated on a simulated mining dataset. Results show significant improvements: data extraction time reduced by 94 % and visualization time by 97.6%. These improvements indicate a transformation in efficiency, usability, and user satisfaction. Despite limitations in data variability and complexity, this pioneering approach highlights the potential of NLP and machine learning in modernizing the mining industry and supporting data-driven decision-making.
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12
revisión
Publicado 2024
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Artificial intelligence (AI) and machine learning (ML) are disruptive technologies nowadays. It is well known that many important organizations use them to improve their productivity and processes, and many new applications are being developed as well. In Latin America, the adoption of new technologies is slower than in other parts of the world, limited by budget and trained personnel. The present research is a systematic literature review (SLR) conducted to analyze the implementation status of AI and ML technologies in Latin America, analyzing the improvements that these technologies bring to organizations. The methodology used in this literature review was PRISMA, a popular method widely used in this type of research. The findings were that the most relevant areas using these types of technologies are education and health, identifying also that their implementation improves operative e...
13
artículo
Publicado 2023
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A dissatisfied customer with a product and/or service is motivated to express a complaint. Classifying complaints manually is a process that represents high costs in human and material resources. Artificial Intelligence (AI) allows the use of various algorithms to perform tasks that can simulate human intelligence, a branch of this is Natural Language Processing (NLP), its objective is that machines have the capacity to understand human language, allowing, for example, to classify and categorize data automatically. This article provides a systematic review of the literature addressing challenges in the classification of complaint texts, such as the lack of class balance, the presence of unlabeled data, and the interpretation of model results. Preprocessing techniques are explored, such as tokenization, stopword removal, and lemmatization, which influence model performance. Additionally, ...
14
artículo
This paper reviews the most recent literature on experiments with different Machine Learning, Deep Learning and Natural Language Processing techniques applied to predict judicial and administrative decisions. Among the most outstanding findings, we have that the most used data mining techniques are Support Vector Machine (SVM), K Nearest Neighbours (K-NN) and Random Forest (RF), and in terms of the most used deep learning techniques, we found Long-Term Memory (LSTM) and transformers such as BERT. An important finding in the papers reviewed was that the use of machine learning techniques has prevailed over those of deep learning. Regarding the place of origin of the research carried out, we found that 64% of the works belong to studies carried out in English-speaking countries, 8% in Portuguese and 28% in other languages (such as German, Chinese, Turkish, Spanish, etc.). Very few works of...
15
tesis de grado
Publicado 2023
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In this work, it is necessary to analyze the increase of Back Order in the attention of crossdocking orders in the attention of Homecenter customers due to the lack of definition of purchase planning processes, resulting in logistics costs, fill rate charges and low service level. Thus, it is intended the companies that handle high volumes of inventory and constant orders should have a forecast plan to cover possible stock-outs. The main purpose of the research is to explain a way to prevent stock-outs using an artificial intelligence model, based on historical sales data of a medium-sized company that manages inventories, as well as to determine the machine earning model to predict and reduce backorders. For the data analysis, the Orange software was used, where the data was trained with different artificial intelligence models such as Decision Tree, Support Vector Machine, Random Fores...
16
tesis de grado
Publicado 2022
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In the present investigation of the design of a processing machine for hybrid compounds based on coconut and maguey fibers, using the non-experimental quantitative method, under the German VDI 2221 and 2225 methodology, using mathematical models of machine elements and mechanical design and selection. of electronic components, where the main objective was the design of the hybrid compound processing machine, which consists of four processes: material transport, crushing process, mixing and compacting process, to obtain boards agglomerated, with the purpose of reusing usable solid waste and transforming it into fibers, in order to avoid the use of wood and to reduce the logging that occurs in the central jungle of Peru, for which it is essential to know the mechanical characteristics of coconut and maguey fiber, coconut fiber has a tensile strength of 220 Mpa and fiber Maguey has a tensil...
17
artículo
Publicado 1999
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In this article is on H. Greenberg algorithm that is used to facilitate b'squeda a graphical solution for determining the order of execution of n jobs
18
artículo
Publicado 1999
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In this article is on H. Greenberg algorithm that is used to facilitate b'squeda a graphical solution for determining the order of execution of n jobs
19
artículo
Publicado 2023
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“Investing in children's well-being and supporting high-quality pre-school education is a significant component of its promotion (ECE). All children have the right to participate. ECE teachers' thoughts about children's participation were examined to see if they were linked to children's perceptions of their participation. On the other hand, current studies focus on a single categorization method with lower overall accuracy. The findings of this study provided the basis for the development of an ensemble machine learning (ML) approach for measuring the participation of children with learning disabilities in educational situations that were specifically developed for them. Visual and auditory data are collected and analyzed to determine whether or not the youngster is engaged during the robot-child interaction in this manner. It is proposed that an ensemble ML technique (Enhanced Deep N...
20
artículo
Publicado 2022
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In this research, we want to present the concepts and techniques used in a big data project for a European supermarket company, through a customer segmentation proposal, using the k-means algorithm, and a recommender system, via Light FM library. The main conclusions include the importance of adequately defining the problem to be solved, the correct use of the big data infrastructure, the relevance of the exploratory analysis of the dataset and its pre-processing, as well as the use of the TDSP methodology (Team Data Science Process), oriented to big data projects.
