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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Andrade-Arenas, Laberiano
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Mobile application: awareness of the population on the environmental impact Andrade-Arenas, Laberiano; Giraldo-Retuerto, Margarita; Molina-Velarde, Pedro; Yactayo-Arias, Cesar
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6131

Abstract

Nowadays, pollution keeps increasing due to social, political, economic, cultural, and environmental factors. Environmental awareness is close to zero because people prioritize personal activities. In that sense, the objective of this investigation is to raise environmental awareness in the population regarding the impact of pollution and support this through a mobile application (APP) that helps reduce pollution. The methodology used was the cascade, and through its phases, it was developed the prototype design of the mobile APP. The results obtained from this hybrid research were through a survey using ATLAS.ti 22; it concluded that environmental awareness begins at home and is taught by the parents, also it should be promoted from elementary school to high school and even in college. Moreover, in a survey, the users stated by 89% that the use of this mobile APP can help reduce the environmental impact. Also, in the validation through expert judgment, all the attributes were accepted with an average of 81%, that of functionality was the lowest, and the highest was that of consistency and integration with 83%. Finally, environmental education should be a priority policy in any country, as this will benefit its population.
Expert systems in mental health: innovative approach for personalized treatment Andrade-Arenas, Laberiano; Rubio-Paucar, Inoc; Celis, Domingo Hernández; Yactayo-Arias, Cesar
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp414-427

Abstract

Custom classification of mental illnesses has emerged as a challenge for mental health specialists, often minimized by patients' lack of awareness of symptoms and the importance of early intervention. Therefore, the purpose of this research is to provide a comprehensive understanding of personalized treatment, encompassing both pharmacological and non-pharmacological options, specifically tailored to mental disorders, considering factors such as the patient's age and gender, among other relevant characteristics. In this context, the Buchanan methodology has been chosen as the framework for structuring a web-based expert system. This approach covers everything from problem identification to system implementation and subsequent evaluation. The survey results, with a total of 50 responses, reveal that the category "Good" leads with 70%, closely followed by "Fair" and "Poor," both at 14%. 71.4% of responses reflect a positive evaluation, with 85.7% combining "Good" or "Fair" responses, and all categories reaching 100%. These results support the feasibility and effectiveness of implementing a web-based expert system under the Buchanan methodology. A positive response in the survey suggests that this methodology can significantly contribute to personalizing and recommending appropriate treatments, both pharmacological and non-pharmacological, thereby benefiting a broad spectrum of patients with mental disorders.
The crucial role of artificial intelligence in addressing climate change Andrade-Arenas, Laberiano; Hernández Celis, Domingo; Yactayo-Arias, Cesar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i1.pp1-11

Abstract

Addressing climate change is one of the fundamental priorities at a global level, given its significant impact on both the environment and society. This systematic literature review explores the role of artificial intelligence (AI) in addressing climate change. It identified applications, contributions to predicting extreme events, techniques used, ethical challenges, and associated biases. The rapid systematic literature review (RSL) was conducted using databases such as Scopus, Dimensions, directory of open access journals (DOAJ), and IEEE Xplore. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement was used to ensure the completeness and transparency of the analysis. 40 articles were selected that were published between 2018 and 2023 and addressed AI in climate change. The findings show that AI is being used to predict and mitigate extreme climate events, estimate the greenhouse effect, and predict temperatures. In addition, innovative techniques such as hybrid machine learning models, convolutional neural networks, artificial neural networks, support vector machines, and logistic regression. In conclusion, AI offers a promising approach to addressing climate change, with transformative potential in predicting and mitigating its effects. However, continuous ethical considerations are required to guarantee its conscientious and efficient utilization.
Implementation of a prototype to prevent childhood accidents in dangerous domestic environments using ESP 32 Wi-Fi module Lavalle-Sandoval, Jenner; Córdova-Cardenas, Paul; Rivera-Quispe, Sheyla; Andrade-Arenas, Laberiano
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 1: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i1.pp88-98

Abstract

Robotics has significantly advanced human evolution by optimizing tasks in fields such as medicine, engineering, and mechanics, enhancing daily life through various robotic prototypes. These innovations help prevent accidents and injuries, whether at home or in hazardous environments. For instance, sensors can detect gas leaks, fires, and other potential disasters. This research aims to design a prototype adaptable to any home environment that poses risks to infants, such as kitchens, bathrooms, or stairs. The proposed prototype incorporates gas, motion, and sound sensors connected to a Wi-Fi ESP 32 module, which alerts parents to any potential danger to their children. The research is developed in six phases: component selection, circuit simulation, prototype design, three-dimensional (3D) printing, code programming, and final testing. The results demonstrate a positive impact, improving the control and care of infants by alerting parents to hazards such as gas leaks, crying, or movement in risky areas. The conclusion confirms the effectiveness of the prototype in providing timely alerts to safeguard infants in potentially dangerous situations.
Design of an educational platform based on an innovative model of research in secondary school students Andrade-Arenas, Laberiano; Corzo-Zavaleta, Janet Ivonne; Alvarado-Paucar, Ada; Baldeón-Vilca, Cecilia; Segovia-Fernández, Luis; Reyes-Vilca, Nelly; López-Tolentino, Giovana; Villarreal-Chumbes, Verónica; Canturín-Narrea, Jhon
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i2.pp2000-2021

Abstract

The development of research skills worldwide is more emphasized in postgraduate programs; however, the training of these skills should be carried out from basic education; that is, from elementary school. In this sense, this research aims to formulate a proposal to develop research skills in secondary school students through an innovative model. The methodology was carried out through student surveys and interviews with teachers and authorities. The ATLAS.ti 22 software was used for network analysis and SPSS 23 for statistical analysis. The results obtained in the survey show that the dimensions of reading comprehension, writing and argumentation, academic writing, and scientific writing are within the acceptable average. However, in the interviews, some students show difficulties in scientific writing, but they show a critical position in their arguments. It is concluded that the authorities should incorporate the proposed model of research skills in the curricular plan, adding it to their annual plan; for this purpose, teachers should be trained to transmit it to their students. In addition, an innovative model is proposed during the 5 years of high school studies to develop students' research skills. The beneficiaries of the proposal are the entire educational community and therefore the country.
Data mining and cardiac health: predicting heart attack risks Paucar, Inoc Rubio; Andrade-Arenas, Laberiano
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1010-1023

Abstract

In a context where heart attacks continue to be a global health concern, the lack of precision in predicting who is at higher risk poses a critical challenge due to the variability of risk factors and complex interactions among them. The research aims to develop predictive models for heart attack risks using data mining techniques, employing the knowledge discovery in databases methodology (KDD) and the k-means algorithm with RapidMiner studio. The primary objective is to identify patterns and risk profiles, allowing for early identification of at-risk individuals, considering factors like obesity, diabetes, alcoholism, and stress, to reduce preventable deaths and improve cardiac healthcare. This innovative approach combines cardiac health, data mining, and KDD methodology to address the challenge of predicting heart attack risks and has the potential to enhance medical care and save lives. The predominant results obtained were that cluster 1 with a fraction of 0.312 and a percentage of 31.2% of the attribute diabetes was one of the most prevalent causes of cardiac risk. Finally, the research concluded that people with diabetes are more likely to have cardiac risk associated with dietary factors or consumption of other substances.
Diagnosis and treatment of Guillain-Barre using the prolog expert system Andrade-Arenas, Laberiano; Molina-Velarde, Pedro; Pucuhuayla-Revatta, Félix; Yactayo-Arias, Cesar

Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp333-342

Abstract

This research is mostly about Guillain-Barre syndrome (GBS), a complicated neurological condition with many subtypes that make diagnosis and treatment hard, even though medical care is always getting better. The main goal of this study is to build and test an expert system that can correctly diagnose these subtypes, with a focus on early detection and personalized treatments. The evaluation of the system was carried out using a dataset composed of 20 cases (12 positive and 8 negative). A confusion matrix was used to evaluate key metrics such as precision, sensitivity, and specificity. The findings demonstrate precision and sensitivity of 83% and specificity of 75%. These findings unambiguously demonstrate the efficacy of the system in correctly identifying positive Guillain-Barre cases while substantially reducing false negatives. In conclusion, this expert system offers a potentially useful tool to improve the accuracy of the diagnosis and treatment of Guillain-Barre patients. However, to take advantage of its full potential in clinical practice, it should be used as diagnostic support and not replace the medical staff, and it should be updated periodically to reflect new findings in medicine.
Public health challenges in the Cuzco region: a decade of anemia in vulnerable populations applying data mining Rubio Paucar, Inoc; Andrade-Arenas, Laberiano
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8381

Abstract

The objective of the research is to carry out an exhaustive analysis of anemia in the province of Cusco using the Rapid Miner Studio tool that allows an analysis of the number of most concurrent cases in each district of the province of Cusco. Different sources of information were consulted to take as a reference the impact of the disease in different parts of the world. Likewise, information was introduced about how information technologies manifest positive responses in certain diseases around the world. The knowledge discovery in databases (KDD) methodology was used, which consists of several phases proposed in the project, such as data selection, data preprocessing, data mining and evaluation of results. Consequently, this research will help to recognize the most abundant cases in the districts of the province of Cusco. The results obtained were that 348 confirmed cases of anemia occurred in the district of Espinar, being the most affected district. Finally, it was concluded that in different provinces, not only in Cusco, there is a high prevalence of the disease due to factors associated with its treatment.
System dynamics modeling for strategic management of information technologies in universities Andrade-Arenas, Laberiano; Giraldo Retuerto, Margarita; Yactayo-Arias, Cesar
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10618

Abstract

This study seeks to answer the question: how can system dynamics (SD) modeling contribute to the strategic management of information technology (IT) in universities? The objective of the research is to analyze the importance of incorporating IT into university strategic management through the application of SD methodology. To this end, a model was designed that integrates variables related to resource allocation, the quality of the educational process, and the interaction between institutional actors. The methodology made it possible to simulate technological implementation scenarios and examine their effects on operational efficiency and academic performance. The results show that the strategic integration of IT promotes better resource planning, optimizes the interaction between administrative and academic processes, and contributes to raising the quality of teaching. In conclusion, the proposed model demonstrates that SD is an effective tool for anticipating and understanding the internal dynamics of universities, facilitating more efficient strategic management in today's digital context.
Co-Authors Alvarado-Paucar, Ada Baldeón-Vilca, Cecilia Canturín-Narrea, Jhon Celis, Domingo Hernández Córdova-Cardenas, Paul Corzo-Zavaleta, Janet Ivonne Giraldo Retuerto, Margarita Giraldo-Retuerto, Margarita Hernández Celis, Domingo Jáuregui-Velarde, Raúl Lavalle-Sandoval, Jenner López-Tolentino, Giovana Molina-Velarde, Pedro Paucar, Inoc Rubio Pucuhuayla-Revatta, Félix Retuerto, Margarita Giraldo Reyes-Vilca, Nelly Rivera-Quispe, Sheyla Rubio Paucar, Inoc Rubio-Paucar, Inoc Segovia-Fernández, Luis Villarreal-Chumbes, Verónica Yactayo Arias, Cesar Yactayo-Arias, Cesar