López-Pimentel, Juan Carlos

Main Affiliation

Facultad de Ingeniería - CampGDL

Preferred name

Official Name

López Pimentel, Juan Carlos

ORCID

0000-0002-7844-3261

Researcher ID

T-3594-2018

Scopus Author ID

57221468168

Now showing 1 - 10 of 23

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Audio’s Impact on Deep Learning Models: A Comparative Study of EEG-Based Concentration Detection in VR Games
(MDPI AG, 2025-10-29)
Gomez Romero Borquez, Jesus Alberto
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Del-Valle-Soto, Carolina
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López-Pimentel, Juan Carlos
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Del-Puerto-Flores, J. Alberto
;
Francisco R. Castillo-Soria
This study investigates the impact of audio feedback on cognitive performance during VR puzzle games using EEG analysis. Thirty participants played three different VR puzzle games under two conditions (with and without audio) while their brain activity was recorded. To analyze concentration levels and neural engagement patterns, we employed spectral analysis combined with a preprocessing algorithm and an optimized Deep Neural Network (DNN) model. The proposed processing stage integrates feature normalization, automatic labeling based on Principal Component Analysis (PCA), and Gamma band feature extraction, transforming concentration detection into a supervised classification problem. Experimental validation was conducted under the two gaming conditions in order to evaluate the impact of multisensory stimulation on model performance. The results show that the proposed approach significantly outperforms traditional machine learning classifiers (SVM, LR) and baseline deep learning models (DNN, DGCNN), achieving a 97% accuracy in the audio scenario and 83% without audio. These findings confirm that auditory stimulation reinforces neural coherence and improves the discriminability of EEG patterns, while the proposed method maintains a robust performance under less stimulating conditions.
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Efficient Deep Learning-Based M-PSK Detection for OFDM V2V Systems Using MobileNetV3
(MDPI AG, 2026-03-11)
Tonix-Gleason, Luis E.
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Del-Puerto-Flores, J. Alberto
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Peña-Campos, Fernando
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del Puerto-Flores, Dunstano
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López-Pimentel, Juan Carlos
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RootLogChain: Registering Log-Events in a Blockchain for Audit Issues from the Creation of the Root
(2021)
López-Pimentel, Juan Carlos
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Luis Alberto Morales-Rosales
;
Raúl Monroy
<jats:p>Logging system activities are required to provide credibility and confidence in the systems used by an organization. Logs in computer systems must be secured from the root user so that they are true and fair. This paper introduces RootLogChain, a blockchain-based audit mechanism that is built upon a security protocol to create both a root user in a blockchain network and the first log; from there, all root events are stored as logs within a standard blockchain mechanism. RootLogChain provides security constructs so as to be deployed in a distributed context over a hostile environment, such as the internet. We have developed a prototype based on a microservice architecture, validating it by executing different stress proofs in two scenarios: one with compliant agents and the other without. In such scenarios, several compliant and non-compliant agents try to become a root and register the events within the blockchain. Non-compliant agents simulate eavesdropper entities that do not follow the rules of the protocol. Our experiments show that the mechanism guarantees the creation of one and only one root user, integrity, and authenticity of the transactions; it also stores all events generated by the root within a blockchain. In addition, for audit issues, the traceability of the transaction logs can be consulted by the root.</jats:p>
Scopus© Citations 2 41 1
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NFT-Vehicle: A Blockchain-Based Tokenization Architecture to Register Transactions over a Vehicle’s Life Cycle
(2023)
López-Pimentel, Juan Carlos
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Luis Alberto Morales-Rosales
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Ignacio Algredo-Badillo
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Del-Valle-Soto, Carolina
<jats:p>The sale of second-hand vehicles is a popular trade worldwide, and vehicle fraud is currently a common issue, mainly because buyers can lack a complete view of the historical transactions related to their new acquisition. This work presents a distributed architecture for stakeholders to register transactions over a vehicle’s life cycle in a blockchain network. The architecture involves a non-fungible token (NFT) linked to a physical motorized vehicle after a tokenization process, which denote as the NFT-Vehicle. The NFT-Vehicle is a hierarchical smart contract designed using an object-oriented paradigm and a modified version of the ERC721 standard. Every stakeholder engages with the NFT-Vehicle through distinct methods embedded within a smart contract. These methods represent internal protocols meticulously formulated and validated based on a finite-state machine (FSM) model. We implemented our design as a proof of concept using a platform based on Ethereum and a smart contract in the Solidity programming language. We carried out two types of proof: (a) validations, following the FSM model to ensure that the smart contract remained in a consistent state, and (b) proofs, to achieve certainty regarding the amount of ETH that could be spent in the life cycle of a vehicle. The results of the tests showed that the total transaction cost for each car throughout its life cycle did not represent an excessive cost considering the advantages that the system could offer to prevent fraud.</jats:p>
Scopus© Citations 7 9 2
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Sustainable Project-Based Learning Methodology Adaptable to Technological Advances for Web Programming
(2021)
López-Pimentel, Juan Carlos
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Alejandro Medina-Santiago
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Del-Valle-Soto, Carolina
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Alcaraz Rivera, Miguel
<jats:p>The fast pace of development of the Internet and the Coronavirus Disease (COVID-19) pandemic have considerably impacted the educative sector, encouraging the constant transformation of the teaching/learning strategies and more in technological areas as Educational Software Engineering. Web programming, a fundamental topic in Software Engineering and Cloud-based applications, deals with various critical challenges in education, such as learning continuous emerging technological tools, plagiarism detection, generating innovative learning environments, among others. Continual change and even more change with the current digitization becomes a challenge for teachers and students who cannot depend on traditional educational methods. The article presents a sustainable teaching/learning methodology for web programming courses in Engineering Education using project-based learning adaptable to the continuous web technological advances. The methodology has been developed and improved during 9 years, 15 groups, and 3 different universities. Our results demonstrate that the methodology is adaptable with new technologies that might arise; it also presents the advantages of avoiding plagiarism in students and a personalized induction for every specific student in the learning process.</jats:p>
Scopus© Citations 14 28 1
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Automating the avocado supply chain with Blockchain and Off-chain
(2020)
López-Pimentel, Juan Carlos
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Rojas, Omar
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Alcaraz Rivera, Miguel
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Sosa-Gómez, Guillermo
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Verteramo-Chiu, L.
69 1
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Blockchain and off-chain: A Solution for Audit Issues in Supply Chain Systems
(2020)
López-Pimentel, Juan Carlos
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Rojas, Omar
;
Raul Monroy
Scopus© Citations 17 8 1
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Trade-Off Analysis of Hardware Architectures for Channel-Quality Classification Models
(2022)
Alan Torres-Alvarado
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Luis Alberto Morales-Rosales
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Ignacio Algredo-Badillo
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Francisco López-Huerta
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Mariana Lobato-Baez
<jats:p>The latest generation of communication networks, such as SDVN (Software-defined vehicular network) and VANETs (Vehicular ad-hoc networks), should evaluate their communication channels to adapt their behavior. The quality of the communication in data networks depends on the behavior of the transmission channel selected to send the information. Transmission channels can be affected by diverse problems ranging from physical phenomena (e.g., weather, cosmic rays) to interference or faults inherent to data spectra. In particular, if the channel has a good transmission quality, we might maximize the bandwidth use. Otherwise, although fault-tolerant schemes degrade the transmission speed by solving errors or failures should be included, these schemes spend more energy and are slower due to requesting lost packets (recovery). In this sense, one of the open problems in communications is how to design and implement an efficient and low-power-consumption mechanism capable of sensing the quality of the channel and automatically making the adjustments to select the channel over which transmit. In this work, we present a trade-off analysis based on hardware implementation to identify if a channel has a low or high quality, implementing four machine learning algorithms: Decision Trees, Multi-Layer Perceptron, Logistic Regression, and Support Vector Machines. We obtained the best trade-off with an accuracy of 95.01% and efficiency of 9.83 Mbps/LUT (LookUp Table) with a hardware implementation of a Decision Tree algorithm with a depth of five.</jats:p>
18 1
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Task-Oriented Adversarial Attacks for Aspect-Based Sentiment Analysis Models
(2025)
Monserrat Vázquez-Hernández
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Ignacio Algredo-Badillo
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Luis Villaseñor-Pineda
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Mariana Lobato-Báez
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López-Pimentel, Juan Carlos
<jats:p>Adversarial attacks deliberately modify deep learning inputs, mislead models, and cause incorrect results. Previous adversarial attacks on sentiment analysis models have demonstrated success in misleading these models. However, most existing attacks in sentiment analysis have applied a generalized approach to input modifications, without considering the characteristics and objectives of the different analysis levels. Specifically, for aspect-based sentiment analysis, there is a lack of attack methods that modify inputs in accordance with the evaluated aspects. Consequently, unnecessary modifications are made, compromising the input semantics, making the changes more detectable, and avoiding the identification of new vulnerabilities. In previous work, we proposed a model to generate adversarial examples in particular for aspect-based sentiment analysis. In this paper, we assess the effectiveness of our adversarial example model in negatively impacting aspect-based model results while maintaining high levels of semantic inputs. To conduct this evaluation, we propose diverse adversarial attacks across different dataset domains, target architectures, and consider distinct levels of victim model knowledge, thus obtaining a comprehensive evaluation. The obtained results demonstrate that our approach outperforms existing attack methods in terms of accuracy reduction and semantic similarity, achieving a 65.30% reduction in model accuracy with a low perturbation ratio of 7.79%. These findings highlight the importance of considering task-specific characteristics when designing adversarial examples, as even simple modifications to elements that support task classification can successfully mislead models.</jats:p>
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Traceability of Mexican Avocado Supply Chain: A Microservice and Blockchain Technological Solution
(2022)
López-Pimentel, Juan Carlos
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Alcaraz Rivera, Miguel
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Rafael Granillo-Macías
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Olivares-Benitez, Elias
<jats:p>Currently, the Mexican avocado supply chain has some social limitations that make the traceability process a difficult task and severely limits the regions that can add their harvest to the international market. We hypothesize that modernizing the traceability process and improving the trust of the final user could help in opening the market to other regions. This paper describes the Mexican avocado supply chain characteristics, identifies the actors involved in the supply chain, and emphasizes the problems that the current actors have when exporting them to the US market. On this basis, we propose a technological solution system to automate the traceability process. The system was designed to comply with the authority and consumer requirements. It proposes a combination of the benefits of traditional data traceability using Microservices architecture with a new layer of Blockchain auditing that will add value to current and new actors in every step of the supply chain. We contribute by proposing a model that adds value to the avocado supply chain with the following characteristics: Integrity, auditing service, dual traceability, transparency, and a front-end application with trust user-oriented. Our proofs demonstrate that the blockchain layer does not represent a considered high extra transaction cost; it could be regarded as despicable for the economy of the consumer considering costs and benefits.</jats:p>
Scopus© Citations 8 18 1

López-Pimentel, Juan Carlos

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