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Europass CV for Industrial Electronics and Automation Engineering
No full textThis resource provides an English-language learning activity and template to create a Europass CV tailored to Industrial Electronics and Automation Engineering. It includes a guidance video and multiple-choice questions covering account setup, required profile sections, formatting, and recommended download type. A detailed, non-HTML template outlines personal information, work experience, education, language proficiency, skills, and additional information to help students structure a professional CV
Electric power generation, transmission and distribution
No full textResource to learn the basics of electric power generation, transmission, and distribution. It includes pre-watching questions, a YouTube video, and multiple-choice questions about the grid, substations, step-up/step-down transformers, high-voltage transmission, and differences between transmission and distribution. It also provides a 45-minute talk show-style oral activity for students to role-play grid stakeholders, reinforcing concepts through communication and reflection
Analogue computing
No full textThis resource introduces analog computing through historical and conceptual content and guided practice. It explains how analog computers use continuous physical quantities, traces milestones from the Antikythera mechanism and astrolabe to tide-predicting machines and differential analyzers, and highlights their legacy and resurgence. It includes reading comprehension, vocabulary with audio, sentence completion, speaking prompts, videos with quizzes, grammar practice on past tenses, and a classroom debate to consolidate understanding
Safety and health
No full textEducational unit in English introducing fundamentals of construction safety, regulatory frameworks (OSHA, NFPA, Spanish laws), and key risk areas such as fall protection, scaffolding stability, electrical safety, excavations, and hazard communication. Includes reading comprehension with 10 questions, pronunciation of keywords with audio terms, sentence-completion activity, speaking prompts, a watching activity with a video and quizzes, grammar practice on conditionals, and a Kahoot review
Project management
No full textThis resource is an English-language learning unit on project management within construction contexts. It includes a reading text explaining definitions, roles, resources, and consequences of poor management; multiple-choice comprehension questions; keyword pronunciation with audio; fill-in-the-blank vocabulary practice; speaking prompts; a watching activity with a related YouTube video and questions; grammar practice on first and second conditionals; a Kahoot review; and a debate-based practice activity integrating communication, resources, risks, and budget concepts
Industrial design
No full textThis English-language learning resource introduces the concept, history, and scope of industrial design and contrasts it with craft design and engineering. It includes a reading passage with ten multiple-choice comprehension questions, a pronunciation section with audio glossary terms, a gap-fill vocabulary activity, discussion prompts with an embedded video on product vs industrial design, a watching activity with pre- and post-viewing questions tied to a second video, a grammar practice section on past tenses, and a Kahoot review link
What are minerals? How identify minerals?
No full textThis resource introduces the definition of minerals and how to identify them using physical properties such as luster, streak, hardness, and crystal habit. It combines explanatory text, reading comprehension quizzes, pronunciation practice with audio terms, cloze activities, speaking prompts linked to videos, and a watching activity with MCQs. Additional grammar exercises contextualize past tenses. It supports foundational understanding and practice in identifying minerals and applying the Mohs hardness scale
Aplicación de la inteligencia artificial generativa en la robótica colaborativa para mejorar la eficiencia y flexibilidad en entornos industriales
Get PDF[SPA] Esta tesis doctoral se sitúa en la convergencia de dos líneas de investigación de gran actualidad: la inteligencia artificial generativa (IAG) y la robótica colaborativa en entornos industriales. La investigación aborda el desafío de trasladar las capacidades sorprendentes de los modelos generativos para interpretar y generar lenguaje natural hacia sistemas embebidos que operen en dispositivos con recursos limitados, garantizando precisión, eficiencia térmica y robustez frente a variaciones dialectales. Para ello, se persiguieron cuatro objetivos fundamentales: investigar las técnicas actuales de inteligencia artificial generativa y su potencial aplicación en la robótica colaborativa; desarrollar algoritmos y modelos de IAG adaptados a las necesidades específicas de la robótica colaborativa en entornos industriales; implementar y evaluar prototipos de robots colaborativos mejorados con IAG en casos de uso reales; y analizar el impacto de la IAG en la eficiencia, flexibilidad y seguridad de los procesos industriales. La metodología adoptó un enfoque mixto que combina análisis, diseño, implementación y evaluación, proponiendo una arquitectura cognitiva modular basada en cinco capas funcionales interconectadas: interfaz multimodal, procesamiento del lenguaje natural, razonamiento y planificación, control y retroalimentación. La validación experimental involucró 15 participantes distribuidos equitativamente según acentos del español colombiano (santandereano, costeño y paisa), quienes emitieron 10 comandos de voz cada uno dirigidos a un robot colaborativo UR3. Se evaluaron cinco modelos de IAG: Claude (en la nube), Mistral-7B, LLama-2-7B, Phi-2 y TinyLLaMA-1.1B (locales), analizando métricas de tiempo de respuesta, precisión de interpretación, diferencial térmico y tiempo de carga inicial mediante análisis estadísticos inferenciales (ANOVA, Chi-cuadrado) para evaluar el rendimiento individual y la interacción modelo-acento. Los resultados experimentales evidenciaron diferencias significativas entre modelos, donde Claude demostró el mejor desempeño con la menor latencia y máxima precisión (100% aciertos), sin generar variaciones térmicas al ejecutarse remotamente. Entre los modelos locales, Mistral-7B emergió como la opción más equilibrada, combinando alta precisión, buen tiempo de respuesta y mínima variación térmica, aunque presentó el mayor tiempo de carga inicial. Se identificó una interacción significativa entre modelo y acento del hablante, afectando principalmente el tiempo de respuesta y comportamiento térmico, aunque el acento no impactó directamente la precisión. La investigación valida la viabilidad técnica de integrar modelos generativos como núcleo funcional para el control e interacción de robots en entornos reales, proporcionando evidencia empírica sobre la importancia de considerar el contexto operativo (conectividad, disipación térmica, autonomía) en la selección de modelos IAG. La arquitectura cognitiva desarrollada es escalable y replicable, contribuyendo al avance de la industria mediante sistemas robóticos más adaptativos, intuitivos y colaborativos que transforman fundamentalmente la interacción humano-máquina en entornos industriales complejos.[ENG] This doctoral thesis is situated at the convergence of two highly relevant research lines: generative artificial intelligence (GAI) and collaborative robotics in industrial environments. The research addresses the challenge of transferring the remarkable capabilities of generative models for interpreting and generating natural language to embedded systems operating on devices with limited resources, ensuring precision, thermal efficiency, and robustness against dialectal variations. To achieve this, four fundamental objectives were pursued: investigating current generative artificial intelligence techniques and their potential application in collaborative robotics; developing GAI algorithms and models adapted to the specific needs of collaborative robotics in industrial environments; implementing and evaluating collaborative robot prototypes enhanced with GAI in real use cases; and analyzing the impact of GAI on efficiency, flexibility, and safety of industrial processes.The methodology adopted a mixed approach combining analysis, design, implementation, and evaluation, proposing a modular cognitive architecture based on five interconnected functional layers: multimodal interface, natural language processing, reasoning andplanning, control, and feedback. The experimental validation involved 15 participants distributed equally according to Colombian Spanish accents (Santanderean, coastal, and Paisa), who issued 10 voice commands each directed to a UR3 collaborative robot. Five GAI models were evaluated: Claude (cloud-based), Mistral-7B, LLama-2-7B, Phi-2, and TinyLLaMA-1.1B (local), analyzing metrics of response time, interpretation accuracy, thermal differential, and initial loading time through inferential statistical analyses (ANOVA, Chi-square) to evaluate individual performance and model-accent interaction.The experimental results evidenced significant differences between models, where Claude demonstrated the best performance with the lowest latency and maximum precision (100% accuracy), without generating thermal variations when executed remotely. Among local models, Mistral-7B emerged as the most balanced option, combining high precision, good response time, and minimal thermal variation, although it presented the highest initial loading time. A significant interaction between model and speaker accent was identified, primarily affecting response time and thermal behavior, although accent did not directly impact precision. The research validates the technical feasibility of integrating generative models as a functional core for robot control and interaction in real environments, providing empirical evidence on the importance of considering operational context (connectivity, thermal dissipation, autonomy) in GAI model selection. The developed cognitive architecture is scalable and replicable, contributing to industrial advancement through more adaptive, intuitive, and collaborative robotic systems that fundamentally transform human-machine interaction in complex industrial environments.Escuela Internacional de DoctoradoUniversidad Politécnica de CartagenaTecnologías Industriale
The Intel 4004 microprocessor
No full textThis resource introduces the Intel 4004, the first CPU on a single silicon chip, and explores its origins in a calculator contract, the shift from a multi‑chip design to the MCS‑4 four‑chip system, and the pivotal role of design expertise and MOS technology. Learners practice reading comprehension, vocabulary pronunciation with audio, cloze activities, speaking prompts, a short video with quizzes, and a grammar focus on future forms, consolidating both technical knowledge and English skills
Digital electronics
No full textThis resource introduces fundamental concepts of digital electronics and computer logic for English learners. It explains decimal, binary, octal, and hexadecimal systems; positional value; conversions via decimal; two’s complement for negatives; and ASCII for text. Activities include reading comprehension with MCQs, vocabulary pronunciation with audio, fill-in-the-blank practice, class discussion prompts, a pre-watching task and video on logic gates and truth tables with follow-up MCQs, grammar exercises on relative clauses, and a Kahoot review