Facultad de Ingeniería - CampGDL
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Item type:Publication, Experimental and data-driven evaluation of transport-layer and application-layer security for MQTT-based IoT networks(Elsevier BV, 2026-12); ; ; Varela-Aldás, JoséThe rapid expansion of Internet of Things (IoT) deployments has intensified the need for secure and efficient communication mechanisms tailored to resource-constrained devices. Message Queuing Telemetry Transport (MQTT) is widely adopted due to its lightweight design; however, it lacks native security support, requiring external protection mechanisms that may significantly affect system performance. This paper presents a comprehensive experimental and data-driven evaluation of two security paradigms for MQTT-based IoT networks implemented on ESP32 microcontrollers: transport-layer security using TLS and application-layer encryption based on elliptic curve cryptography (ECC) for key exchange combined with AES symmetric encryption. The analysis jointly evaluates memory utilization, end-to-end latency, energy consumption, and resistance to passive traffic interception under identical experimental conditions. In addition to conventional metric-based comparisons, multivariate statistical analysis and unsupervised learning techniques are employed as exploratory tools to characterize the system-level behavior induced by each security scheme. Results show that Transport Layer Security (TLS) offers stronger confidentiality guarantees at the cost of higher memory overhead, while the ECC–(Advanced Encryption Standard) AES approach significantly reduces memory footprint with moderate latency penalties and comparable energy consumption. Multivariate analysis further reveals that each security mechanism induces a distinct performance regime, providing a compact joint characterization of the security–performance trade-offs across the evaluated configurations. © 2026 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multipath Routing Protocol: For Wireless Ad-hoc Networks Based on FibonacciA WANET, which stands for Wireless Ad hoc Network, is a temporary network in which nodes are connected to each other via wireless links and there is no central management. Due to its adaptive structure, WANET is very useful in situations when quick communication link setup is necessary. On the other hand, Channel Contention (CC), degrades the performance of WANET and is a major contributor to packet drops. To solve the CC problem, this paper proposes a routing protocol called Multipath Channel Contention Based Routing (MCCBR). Using MCCBR, several paths are discovered for data transmission that have minimal contention between the source and destination. Then the packets are distributed over the discovered routes based on the Fibonacci sequence. The process of searching for new paths for transmission is initiated when the number of found paths becomes less than 50%. The proposed routing protocol was tested and verified using NS2 simulator. The performance of MCCBR was evaluated against the Ad hoc On Demand Distance Vector (AODV) and Channel Contention Based Routing (CCBR) protocols. MCCBR outperformed AODV and CCBR in terms of Packet Delivery Ratio (PDR), End-to-End (E2E) delay, and normalized Media Access Control (MAC) overhead. © 2026, Zarka Private University. All rights reserved. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Hierarchical Modular Fuzzy Model for Instability Susceptibility Assessment and Stabilization Decision Support in Rock Slopes(MDPI AG, 2026-08-03); Díaz-Barriga, José ManuelTraditional rock mass evaluation methods have three main limitations: (1) their application depends largely on specialist judgment; (2) their discrete classification approach, such as RMR (Rock Mass Rating) and SMR (Slope Mass Rating), leads to abrupt transitions between categories; and (3) the interaction among geomechancial parameters is limited; these aspects reduce their ability to represent slope behavior in a gradual manner. The main objective of this research was to develop a model capable of representing gradual transitions between geomechanical conditions and the interaction among parameters related to susceptibility to instability. The model uses a hierarchical modular framework based on the Mamdani fuzzy inference mechanism, allowing the incorporation of expert knowledge through linguistic rules. It is implemented in a graphical environment that allows users to directly use geomechanical parameters obtained through conventional characterization or from three-dimensional digital models derived from UAV (Unmanned Aerial Vehicle) photogrammetry. Model consistency was evaluated through a sensitivity analysis, which verified the model’s response coherence across variations in input parameters. The graphical evaluation tool was then applied to three real case studies with different geomechanical configurations, and the results were compared with those from traditional methods (RMR and SMR). The results showed differences between traditional and fuzzy approaches, as our proposal links recommendations to specific geomechanical conditions across different evaluation levels, identifying conditions for potential intervention measures. In addition, the model enables the zonification of instability susceptibility, facilitating its use in future risk analyses. Our model is intended for application under normal slope conditions, without accounting for extreme events or external dynamic loads, such as seismic activity, groundwater level variations, infiltration, or high-mountain conditions. © 2026 by the authors. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Fiber–matrix interaction governs compressive strength in agave-bagasse-reinforced adobe: a factorial experiment with two-way ANOVA and competing mechanism analysis(Frontiers Media SA, 2026-07-31); ; ; Varela-Aldás, JoséNatural-fiber reinforcement is widely cited as a pathway to improve the mechanical performance of adobe, but reported effects on compressive strength are inconsistent across studies: some find improvement, others find degradation, and the choice of experimental conditions rarely disentangles the role of the fiber from that of the matrix. This study quantifies the coupling through a balanced factorial experiment. Forty-nine adobe specimens of (Formula presented) cm were manufactured with three granular compositions (sand-dominated, jal-dominated, and balanced, where jal is a regional non-plastic silt of Jalisco, Mexico) and four mass fractions of agave-bagasse fiber (0%, 0.5%, 1%, and 2%), and were tested under Mexican standard NMX-C-036-ONNCCE by an accredited external laboratory. Three complementary analytical tools are applied to the resulting dataset: (i) a two-way analysis of variance (ANOVA), (ii) a reinforcement efficiency index (Formula presented) with bootstrap confidence intervals, and (iii) a competing mechanism phenomenological descriptor (Formula presented) that separates a saturating reinforcement term from a linear disruption term. The two-way ANOVA reveals a highly significant mixture–fiber interaction ((Formula presented), (Formula presented), and partial (Formula presented)), which is stronger than either main effect and statistically demonstrates that the sign of the fiber effect is not an intrinsic property of the fiber but rather a property of the fiber–matrix pair. For sand-containing mixtures, the reinforcement efficiency index is (Formula presented) [M1, 95% bootstrap CI (0.96, 1.32)] and (Formula presented) [M3, (0.92, 1.59)] at the optimum (Formula presented); a non-parametric bootstrap over 5, 000 resamples places the optimum at (Formula presented) with posterior probability (Formula presented) (M1) and (Formula presented) (M3). For the jal-dominated mixture, fiber inclusion is net destructive [(Formula presented), (0.68, 0.95) at (Formula presented)], with Welch (Formula presented)-tests rejecting equivalence with the control at (Formula presented) (0.5%) and (Formula presented) (2%) and Cohen’s effect sizes (Formula presented). The best-performing conditions yield mean compressive strengths of 3.22 MPa, which exceeds the 2.0 MPa minimum required by NMX-C-441-ONNCCE-2011 for non-structural masonry by 60%. An immersion test shows that unstabilized specimens disintegrate within 2–3 min, bounding applications to non-exposed or externally protected uses and defining the primary direction for future work. Copyright © 2026 De-Obaldia-Escalante, Del-Valle-Soto, Acevedo-Parra, Montoya-Márquez and Varela-Aldás. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Multimodal Biometric Framework for Evaluating Emotional Impact of Chromatic Manipulation in Cinematic Content(MDPI AG, 2026-05-25); ; 8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, 16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hypnogram-Driven Automatic Sleep Staging and a Quality-Index Assessment Through a Two-Stage LSTM-DNN Ensemble Learning Approach Using Multi-Biosignal Features for Sleep Disorder Detection(MDPI AG, 2026-06-27); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Deep Learning Automated Measurements of Expanded Polystyrene Beads Size Using Low‐Resolution Micrography<jats:title>ABSTRACT</jats:title><jats:p>The analysis of microscopic characteristics of closed‐cell polymeric foams, particularly bead size, is relevant for understanding properties such as thermal insulation, energy absorption, and compressive structural strength of these materials. This study presents an automated method based on Deep Learning models to measure the bead size of Expanded Polystyrene foams in low‐resolution micrographs. The results of this approach were compared with manual measurements at two expanded polystyrene foam densities: 8.5 and 24 kg/m<jats:sup>3</jats:sup>. Hypothesis tests, including Student's <jats:italic>t</jats:italic>‐test, Levene's test, and Mann–Whitney <jats:italic>U</jats:italic> test, were conducted and showed no significant differences between manual and automatic measurements. Student's <jats:italic>t</jats:italic>‐test and Levene's test indicated that both methods have comparable means and variances, while the Two One‐Sided Test confirmed that they were equivalent for bead size measurement. Additionally, the Mann–Whitney <jats:italic>U</jats:italic> test revealed no differences in medians, and Bland–Altman plot analyses demonstrated no systematic bias between the methods. Taken together, these results suggest that the proposed Deep Learning‐based method is a reliable and precise substitute for the manual method in measuring the bead size of expanded polystyrene, making it suitable for practical use in the bead microstructural analysis of expanded polystyrene material.</jats:p>36 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Automating BIM Change Certification with Blockchain: A Case Study in Residential Building Design(International Association for Automation and Robotics in Construction (IAARC), 2026-06-22)