Authors - Marco Vinicio Lopez R., Maria Cristina Espin Melendez, Jeanette Elizabeth Jordan Buenano, Santiago Vayas Castro, Segundo Moises Toapanta Toapanta, Ruben Nogales Portero, Juan Escobar Naranjo, Diego Gustavo Andrade Armas, Rodrigo Del Pozo Durango Abstract - Connecting more devices to monitor energy and the environment creates serious hurdles for data security, integrity, and scale. This research presents a system merging blockchain with IoT, built specifically to respect Ecuador’s Organic Law on Personal Data Protection (LOPDP). The setup uses ESP32 microcontrollers and sensors to track environmental and power data, sending it over the MQTT protocol to a database. Digital fingerprints created with SHA-256 are locked onto a private blockchain using Proof-of-Authority to keep every record permanent and unchangeable. A 10-day experiment in two indoor spaces generated roughly 96,000 records to test how the system holds up in the real world. Results demonstrate the system's viability, achieving a median end-to-end latency of 182 ms (P95 < 240 ms), a Node Availability Index (NAI) of 98.6%, and an Anomaly Detection Rate (ADR) of 91.4%. Furthermore, the blockchain integration introduced a computational and energy overhead of less than 7%. The study concludes that this architecture provides a verifiable link between physical sensors and digital records, highlighting the bidirectional need for technology to comply with national privacy laws while urging regulatory frameworks to evolve and formalize smart contract applications.
Authors - Mohammed Rasol Al Saidat, Khaled Shaalan, Suleiman Y. Yerima Abstract - This paper presents a technical bibliometric review of artificial intelligence for bilingual Arabic–English smishing detection. It maps the evolution of machine learning, deep learning, and NLP for SMS phishing detection, identifies Arabic–English linguistic and security challenges, and grounds the review in an empirical audit of a public Arabic SMS spam corpus. The methodology pairs a PRISMA-style protocol and bibliometric mapping with the parsing of 1,494 SMS records (747 ham, 747 spam) from a public GitHub dataset. The field has shifted from rules and classical feature engineering to CNN, LSTM, Bi-LSTM, transformer, and large language model approaches. The dataset audit reveals strong class-conditional cues: spam messages are far longer and far richer in digits, phone numbers, short codes, URLs, currency markers, and Latin residues. A reproducible bilingual character TF-IDF baseline with a Linear SVM reached 0.9779 mean accuracy and 0.9775 F1 under stratified three-fold validation, matching the referenced CNN-Bi-LSTM model (0.9699 accuracy, 0.9707 F1). Robust bilingual smishing detection therefore requires hybrid text–security features, Arabic morphology-aware normalization, Unicode safety screening, external validation, and explainable deployment.
Authors - Rodrigo Del Pozo Durango, Moises Toapanta T., Antonio Orizaga T., Rocio Maciel A., Victor Larios Rosillo, Jeanette Elizabeth Jordan Buenano, María Cristina Espin Melendez, Santiago Vayas Castro, Pamela Toapanta Pavon, Andres Hermann-Acosta Abstract - Cybersecurity governance in Higher Education Institutions (HEIs) in Ecuador faces persistent challenges: Information and Communication Technologies are regarded merely as operational tools, without adequate integration of international standards or a legal foundation within institutional processes. This situation generates high vulnerability to threats such as phishing, ransomware, and data breaches. The objective of this research is to define an integrated model for cybersecurity governance, public administration, and legal foundations for an HEI in Ecuador. A deductive method with a mixed quantitative–qualitative approach was employed, structured into four phases: systematic literature review indicator design, model construction, and scenario simulation. The main result is an integrated model structured into three hierarchical and interrelated levels: the Technical Level, comprising incident management, security infrastructure, and technological maturity, aligned with NIST CSF 2.0 and EGSI v3.0; the Administrative Level, focused on ICT strategic planning, organizational governance, and continuous improvement, based on COBIT 2019; and the Legal Foundation Level, grounded in the 2024 Constitution, the 2026 Organic Law on Cybersecurity, the 2021 Organic Law on Personal Data Protection, and the 2025 Comprehensive Organic Criminal Code. The model incorporates 15 weighted indicators and was validated through simulation across four scenarios, using an optimality threshold of ≥ 75 points. It is concluded that three-dimensional integration technical, administrative, and legal is a necessary condition for Ecuadorian HEIs to achieve ICT strategic alignment, resource optimization, and digital resilience, thereby positioning them as key actors in national cybersecurity public policy.
Authors - Eric Khang Heng Ooi, Yit Yin Wee Abstract - Printed circuit boards (PCBs) are increasingly dense and visually complex, making reliable component detection important for automated optical inspection and manufacturing quality control. This paper presents a modified R-CNN framework for integrated-circuit (IC) component detection in PCB images. The framework consists of PCB region extraction, colour-guided region proposal generation, Bayesian convolutional neural network (BCNN) feature extraction, and support vector machine (SVM) classification. Candidate regions are produced using colour masks that emphasize dark and silver IC-like regions. Each candidate is resized, represented by the BCNN, and classified by the SVM as IC or background. Experiments on a PCB component dataset show that the proposed method achieves an mAP of 0.613, outperforming R-CNN with Selective Search Fast (0.392) and Selective Search Quality (0.430). YOLO obtains the highest mAP of 0.686; however, the proposed framework remains useful as an interpretable region-based pipeline for PCB inspection.
Authors - Chandravadan Goritiyal, Aditi Bairolu Abstract - The engine of the world is energy. Fossil fuels continue to be the primary source of energy generation. Nonetheless, several of the world's most important organizations and nations banded together to address the greatest sustainability challenge facing humanity: climate change caused by greenhouse gas emissions. It has been noted that the most workable approach would be to refocus attention from fossil-fuel energy production to renewable energy. However, there are year-round availability issues with renewable energy as well. For instance, solar energy can only be produced during the day, and in India, during the monsoon season hardly solar energy produced. Similar issues are noted in other nations as well. When there is not enough wind to support its spin, wind power frequently stands still and is entirely dependent on air currents. Therefore, the study focuses on what India as a nation should do. For example, investigating clean base load electricity, such as nuclear, to guarantee a constant demand for grid power; solar and wind power will support this, making the total power supply sustainable and environmentally friendly. Also Industry requires continuous and reliable power all the time.
Authors - Monica Cruz, Abilio Oliveira, Ricardo Dias Abstract - Although immersive technologies such as VR, AR, MR and XR are increasingly integrated into university teaching, existing research remains conceptually fragmented and technologically heterogeneous. This study examines how the Metaverse is represented, characterised, and applied in higher‑education contexts through a meta-analysis using Voyant tools for text analysis. To address this gap, the study investigates recent publications to answer the research question: How is the Metaverse being represented, characterised, and applied within higher‑education contexts? Three objectives guided the analysis: identifying how the Metaverse is conceptualised in educational literature, examining the dimensions that facilitate or hinder its adoption, and mapping the leading Metaverse‑related technologies used in higher‑education environments. The findings show that adoption is shaped by perceived usefulness, immersion, social presence and technological readiness, while challenges persist regarding accessibility, infrastructure and conceptual clarity. The study contributes to the scientific literature by consolidating dispersed definitions, clarifying adoption‑related factors and identifying the immersive technologies most frequently associated with Metaverse‑based learning. The results provide a structured foundation for future research and offer higher‑education institutions insights into the opportunities and constraints of integrating Metaverse technologies into teaching and learning.
