Alvarado-Acuña, Luis Segundo
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Alvarado-Acuña
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Luis Segundo
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lualvar@ucn.cl
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Publicación Characterization of SLM Conversational Systems Models, Overview(Springer Nature, 2025-03-25) Vasconcelo-Mir, Yuniesky Orlando; Pérez-Pupo, Iliana; Yzquierdo-Herrera, Raykenler; Piñero-Pérez, Pedro Yobanis; Alvarado-Acuña, Luis Segundo; Bello-Pérez, RafaelThe development of Generative Artificial Intelligence is revolutionizing human–machine interaction models. In this context, large language models (LLMs) have emerged as tools capable of learning complex patterns. However, many of these technologies are highly resource intensive. An alternative to these complex models is the advent of Small Language Models (SLMs). These smaller models process fewer parameters but achieve acceptable performance in their responses, striking a balance between cost and quality. This study characterizes different SLMs to facilitate decision-making in their implementation. In the methods section, a systematic review is conducted, serving as a guide for researchers and professionals seeking to select the most suitable SLM for their specific needs. An analysis of the efficiency of these models contributes to the application of Artificial Intelligence techniques from a sustainability perspective. The results section presents a comparison of various SLMs available on the Ollama platform. The models compared include Qwen2.5, Phi3.5, Mistral-small, Llama3.1, and Gemma2. A comparative analysis evaluates these models based on their efficiency and effectiveness in terms of computational resources and the human effort required to develop task-specific conversational systems. The study demonstrates the feasibility of using these smaller models in various decision-making environments.Publicación A Efficient Model for Startups Creation with Low Risk and Uncertainty, Study Cases in IADES(Springer Nature, 2025-03-25) Pérez-Pupo, Iliana; Piñero-Pérez, Pedro Yobanis; Piñero-Ramírez, Pedro E.; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Piñero-Ramírez, Carlos ManuelSmall and medium-sized enterprises (SMEs) and startups are an essential part of the economy in many countries, having a significant economic and social impact. In this context, recent advances in Artificial Intelligence (AI) have fostered the creation of numerous companies supported by these technologies. However, the creation of such enterprises involves high risks, with 50% of initiatives failing. Multiple factors, coupled with a high degree of uncertainty in decision-making, contribute to this phenomenon. The methods section presents a model for building AI-supported startups. The proposed method facilitates the processes of implementation and governance during its application. This model can be generalized through the IADESPro platform. In the results analysis section, the authors validate the proposal using socio-economic indicators and word computing techniques. Furthermore, the results of applying the model in the IADES Commercial Society, a company dedicated to the development of new AI technologies for Sustainable Development, are presented. The IADES company adopted the proposed model and focused on applying AI in the fields of Sports, Sustainable Development, and Project Management. The application results are demonstrated.Publicación Ecosystem IADESCom for Conversational System Construction(Springer Nature, 2025-03-25) Pérez-Pupo, Iliana; Piñero-Pérez, Pedro Yobanis; Vasconcelo-Mir, Yuniesky Orlando; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Piñero-Ramírez, Pedro E.Conversational systems are rapidly changing and modifying the ways in which humans interact with machines. A basic classification divides these systems into two fundamental groups: classical systems based on NLU techniques and systems based on LLM models. In this context, the number of application scenarios for these systems and their impact on business efficiency is increasing. In this sense, opportunities for applications in reservation management, information retrieval and the execution of actions in information systems are identified. In this sense, it was identified that the construction of the training bases for these systems is costly in time and effort. In the methods section of this work, the IADESCom software ecosystem is presented. This ecosystem is made up of a set of COTS components that allow the application of conversational systems in different scenarios. In the results section, the different components are validated and the applicability of the ecosystem is demonstrated. Finally, the conclusions and future work are presented.Publicación Method for Revenue Assurance and Financial Fraud Alerting Supported by LDS Techniques(Springer Nature, 2025-03-25) Pérez-Pupo, Iliana; Piñero-Pérez, Pedro Yobanis; Yzquierdo Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Piñero-Ramírez, Carlos Manuel; Piñero-Ramírez, Pedro E.Revenue assurance and the issuance of Financial Fraud alerts are essential challenges that impact both financial institutions and businesses. This is a complex problem where new challenges and methods consistently arise, necessitating the continuous improvement of detection systems. In this context, the use of various computational intelligence techniques and elements from neutrosophic theory can assist in managing uncertainty and indeterminacy. The methods section includes a brief analysis of the state of the art in artificial intelligence for detecting financial fraud situations. Furthermore, an algorithm is proposed for detecting potential financial fraud situations, supported by data linguistic summarization techniques. These techniques are employed in combination with principles from neutrosophic theory. Subsequently, in the results section, the proposal is validated by comparing the proposed method with a rule-based approach reported in the literature. Additionally, the model is evaluated by subject matter experts, demonstrating the contributions of the proposed model.Publicación Sport Customized Training Plan Assisted by Linguistic Data Summarization(Springer Nature, 2025-03-25) Calderón, Carlos Amador; Pérez-Pupo, Iliana; Yzquierdo-Herrera, Raykenler; Piñero-Pérez, Pedro Yobanis; Palacios-Pulgarón, Rolando; Alvarado-Acuña, Luis SegundoPlanning high-performance sports training involves making decisions under uncertainty. There are no deterministic algorithms that allow handling the complexity of biological systems and individual variability in the construction of plans. For this reason, in this study, artificial intelligence techniques are applied to the construction of personalized training plans. In the methods section, the CACIA model is presented to construct training plans that combine linguistic data summarization techniques with elements of neutrosophic theory. The variables considered by the proposed model were anthropometric indicators, biorhythms, nutrition, and psychological factors. Then, in the results section, the proposal is validated based on an analysis of the performances of athletes at the national championships. The results were compared between the control and experimental groups using non-parametric tests and the SPSS tool. It was found that the CACIA model significantly improved the results of the experimental group compared with the control group. In this study, the use of linguistic summarization of the data allowed the creation of linguistic summaries that were used in the adaptation and improvement of the constructed plans.Publicación Measurement of Perceived Quality in Conversational Systems (Chatbots)(Springer Nature, 2025-03-25) Hernández-Pupo, Luis Gabriel; Yzquierdo-Herrera, Raykenler; Alvarado-Acuña, Luis Segundo; Piñero-Pérez, Pedro Yobanis; Pérez-Pupo, Iliana; Bello-Pérez, RafaelThe increase in the number of conversational systems (chatbots) applied to different scenarios in society is notable. However, the development of metrics and evaluation methods for chatbots still remains an open line of research. The aim is to create evaluation methods that are less and less invasive and that do not reduce the participation of users or other human agents. In this work, in the methods section, a systematic review is carried out on different evaluation methods for chatbots. Then, in the same section, new metrics for the evaluation of conversations with chatbots inspired by the neutrosophic theory are presented. In the results section, the validation of the proposed model is carried out. The applicability of the model is evaluated and the proposal is subjected to expert triangulation methods. In the work, it is possible to demonstrate that the application of neutrosophic logic can contribute to achieving a more natural response from chatbots. This effect can be useful to mitigate the presence of false responses or hallucinations.