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Computer Science and Education in Computer Science de Georgi Tuparov

Computer Science and Education in Computer Science: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Editat de Georgi Tuparov, Tanya Zlateva
en Limba Engleză Paperback – 28 oct 2026
This book constitutes the refereed post-conference proceedings of the 19th International Conference on Computer Science and Education in Computer Science, CSECS 2023, held in June 2023 in Boston, MA, USA. The 23 full papers and 9 short papers were carefully reviewed and selected from 88 submissions. The papers cover many systems technologies, applications, and services as well as solutions. Multiple topics have been addressed including the theory of computation, models of computation, computational complexity and cryptography, logic, design, and analysis of algorithms, network architectures, performance evaluation, network services, software engineering, software creation, and management, applied computing, machine learning, and education.
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Specificații

ISBN-13: 9783032331229
ISBN-10: 3032331226
Pagini: 384
Dimensiuni: 155 x 235 mm
Editura: Springer Nature Switzerland AG
Colecția Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Seria Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Cuprins

.- Education in Computer Science.

.- AI-Powered Storytelling and Game-Based Learning: A Framework for Digital Competence in ICT Education.

.- Block-Based Learning: A Gamified Simulator for GPU Programming Education.

.- Oratio Homomorphico: Creating a Lecture for Homomorphic Encryption by applying Design-Based Research.

.- Linear Optimal Test Design Under D-Scoring.

.- Value-Added Assessment for AI-Assisted Assignments.

.- Comparative Study: Evaluating the Performances of OpenAI’s GPT Models and Google’s Gemini Models in RAG Framework.

.- The Tree of Thingies: An Interactive Approach to Taxonomy-based Learning in Software Engineering.

.- Reimagining Business Analytics Laboratories for Reproducibility.

.- Financial Literacy – Generative AI-Powered Learning.

.- Computer Science Technologies.

.- AI-Driven Reverse Engineering Approach for Semantic Analysis of Applications with Multilayer Architecture Style.

.- Theoretical settings for the software engineering process’s complexity and the software quality.

.- Comparative Analysis of Popular Deep Learning Libraries: TensorFlow, PyTorch, and Keras.

.- Comparative Forecasting of Sustainability Pathways: Deep Learning Architectures for Emerging and Advanced Economies.

.- DNA-like Genetic Algorithm Encoding.

.- Computer Science Implementation in Medicine.

.- Fine tuning of small LLM for medical data extraction.

.- Transforming Patient Recruitment and Retention in Clinical Trials with Artificial Intelligence: A Review and Comparative Study.

.- AI-Driven Protein Prediction in Healthcare and Drug Discovery: AlphaFold Revolutionizing Structural Biology.

.- SwimScan: An Intelligent Attendance System for Swimmers Powered by Face Recognition.

.- Optimizing Hospital Ward Load through Data-Driven Approaches.

.- Computer Science Implementation in Industry.

.- Applying Feature Extraction from Deep Learning Models for Vibration Analysis.

.- Analysis And Detection of False-Negative Injection Attacks in IIoT Environments.

.- Server Room Cooling Optimization Techniques.

.- Extending the Functionalities of a Simulation Model in NetLogo to Adapt to the Architecture of Telecommunication Systems with Drones.

.- Generating photorealistic 360-degree-panoramic images using AI.

.- Enhancing Robotic Simulations in Webots Using AI-Driven Decision Making.