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A Novel Framework Design for Hybrid Research Methodologies in Engineering
No full textCivil engineering projects have specific technical requirements of high importance and requirements related to sustainability. These projects involve multi-level systems where quantitative models and laboratory-physical experiments must generate results with scientific consistency and with the agreement of all stakeholders. Another important and indispensable factor is the protection of the environment. When the third factor, the technological one, is added to these factors, then, for engineering research projects it is assumed that a hybrid methodological framework adapted to civil engineering is needed that systematically and quantitatively integrates engineering science, simulation, field data with the social part covered by qualitative research. The framework promotes reproducibility and transparency, supporting more robust decision-making in the design and complex evaluation of the process and product of construction engineering. This section is supported by an illustrative example in a smallscale civil system that highlights how the integration of qualitative knowledge together with numerical research models improves the accuracy of prediction and joint decision-making in this field. The conceptual model aims to support and advance hybrid practices of academic and engineering research
Analytical Design of Continuous Prestressed Concrete Beams – Methodology, Example, and Comparison with a Simply Supported Beam
No full textThis paper presents a complete analytical procedure for continuous prestressed concrete beams (two spans 15 + 15 m). The analysis covers moment distribution, loadbalancing method, prestress losses, thrust-line geometry, and shear verification in accordance with Eurocode 2. Continuity reduces positive bending moments in the spans to approximately wL²/24 while introducing negative moments over the internal support of about wL²/12 , compared to wL²/8 for a simply supported beam. An affine correction of the tendon profile allows fine adjustment of the thrust line without altering the equivalent load wₚ. A practical design example and comparison with numerical FEM results are provided
Analysing the Effect of Chloride Penetration on Corrosion
No full textThis experimental study is to evaluate the influence of various factors on the acceleration of steel reinforcement corrosion in concrete exposed to chlorides. The study focuses on chloride ingress through controlled cracks introduced in the concrete, simulating real-world damage conditions in reinforced structures. The main variables investigated include the type of concrete, the type of reinforcement (with or without epoxy coating), the concrete cover thickness, and the presence of cracks. A total of 162 cylindrical specimens (100 × 120 mm) with reinforcement were prepared, along with 24 additional specimens (150 × 300 mm) without reinforcement for compressive strength testing. Several tests were applied: the pull-out test to create controlled cracks, the chloride test to see the penetration of chloride, the split test, the half-cell potential test, and the compressive strength test. Preliminary results indicate that cracking significantly increases chloride ingress and poses a greater risk of reinforcement corrosion in reinforced concrete
Buduri_icbme2025-German Reddit Sentiment Analysis Using BERT and ML Techniques
No full textThis study presents a comprehensive workflow for collecting, preprocessing, and analyzing German-language comments from Reddit for sentiment analysis. Initially, a Pythonbased scraper using the Reddit API was developed to extract topic-specific comments, which were then cleaned by removing special characters, links, and irrelevant tokens. The dataset underwent tokenization, stopword removal, and normalization using stemming and lemmatization to produce a structured corpus suitable for machine learning tasks.Sentiment classification was performed using the German BERT model (oliverguhr/german-sentimentbert), categorizing comments as positive, negative, or neutral. To further evaluate performance, vectorization techniques such as Bag-of-Words and TF-IDF were applied, followed by machine learning classifiers including Logistic Regression, Random Forest, and Naive Bayes. Performance metrics were assessed using confusion matrices, classification reports, and error analysis.Additionally, visualizations were created to highlight the most influential words contributing to positive and negative sentiment classification, as well as graphical representations of prediction errors. This integrated approach demonstrates how structured preprocessing combined with advanced modeling can enhance the accuracy of sentiment analysis on social media data. The methodology provides a solid foundation for monitoring public opinion and extracting insights from user-generated content in German
Perceptions and needs of mental health professionals on the integration of Artificial Intelligence in clinical practice
No full textThis study investigates the perceptions, attitudes, and professional needs of mental health practitioners in Kosovo regarding the integration of Artificial Intelligence (AI) in clinical practice and mental health care services. Using a qualitative methodology, semi-structured interviews were conducted with 30 professionals from both public and private institutions. The analysis seeks to identify knowledge gaps, required competencies for effective AI utilization, and the main barriers hindering its adoption. The findings are expected to inform contextspecific training programs and strategic approaches that support ethical, sustainable, and comprehensive digital transformation in Kosovo’s mental health sector, ultimately enhancing care quality and strengthening professional capacities
Development of Advanced Algorithms for Autonomous Vehicle Navigation
No full textThis paper addresses the development of advanced algorithms for autonomous vehicle navigation, focusing on the creation of an intelligent platform capable of safely planning and managing vehicle movement without human intervention. The main objective is to design a functional and reliable system by applying modern artificial intelligence techniques, optimization methods, and sensor data processing (sensor fusion). The study begins with a review of the existing literature on autonomous navigation, identifying key approaches such as Machine Learning, Simultaneous Localization and Mapping (SLAM), and Path Planning. It then presents the development methods for the autonomous navigation system using machine learning through simulation, implemented with Python, Jupyter Notebook, and GitHub. The paper also provides system testing and performance evaluation in simulated environments. The results show significant improvements in navigation accuracy, obstacle avoidance, and overall safety. Finally, recommendations for future work are presented, including real-world testing and the integration of path planning algorithms with machine learning to achieve a safer and more reliable autonomous system
The Rise of Digital Therapists: A Survey of Artificial Intelligence in Mental Health Monitoring and Support*
No full textIn recent years, the intersection of artificial intelli- gence (AI) and mental health has emerged as a promising frontier for enhancing emotional well-being and psychological care. This survey explores the growing role of AI technologies—particularly natural language processing (NLP), machine learning, and affec- tive computing—in the detection, monitoring, and support of mental health conditions. We examine the current landscape of AI-driven tools such as conversational agents, sentiment anal- ysis platforms, emotion-aware systems, and digital therapeutic applications. The paper highlights key methodologies, including text-based sentiment classification, voice emotion recognition, and facial expression analysis, while discussing their implementation in mental health assessment and intervention. Furthermore, we review the effectiveness, ethical considerations, and limitations of these technologies, focusing on issues such as privacy, bias, trust, and clinical validation. Finally, we identify emerging trends and outline research gaps that must be addressed to ensure responsible and impactful integration of AI in mental health care. This survey aims to provide a comprehensive overview for researchers, practitioners, and developers working at the intersection of AI and digital mental health
Coupled Best Proximity Points for Noncyclic Maps in Uniformly Convex Banach Spaces
No full textThis paper studies coupled best proximity points for noncyclic maps in uniformly convex Banach spaces. While classical fixed point theory is well-established for self-maps, cyclic maps, and coupled fixed points, noncyclic maps, especially those of two variables, remain less explored. We generalize the notions of optimal points, best proximity points, and coupled fixed points to noncyclic maps of two variables, introducing the concept of optimal pairs of coupled fixed points. We provide sufficient conditions for the existence and uniqueness of such points in uniformly convex Banach spaces with convex subsets separated by a positive distance. Additionally, we present both a priori and a posteriori error estimates for iterative approximations, which are essential for practical applications where exact solutions are unattainable. Our results extend classical fixed point theory and offer effective tools for approximation methods in mathematical modeling, optimization, and applied mathematics, paving the way for further research on coupled noncyclic mappings in complex systems
The Role of Artificial Intelligence in Developing Interactive and Intelligent Web Applications
No full textThis study explores the integration of Artificial Intelligence (AI) into web programming, a field that has been rapidly transformed by the advancement of modern technologies. AI represents not only a relatively new and revolutionary innovation but also a crucial factor shaping the future of humanity, raising both opportunities for progress and concerns about potential workforce replacement in certain domains. The research begins with an overview of the history and evolution of AI, followed by an examination of its role in optimizing processes, addressing technical challenges, and enhancing user experiences in web development. With capabilities such as processing large datasets, learning from patterns, and making intelligent decisions, AI enables automation of repetitive tasks, real-time data analysis, personalized services, and advanced solutions in cybersecurity. Technologies including deep learning and computer vision have already shown significant impact through intelligent chatbots, recommendation systems, and adaptive user interfaces. This study further investigates the primary applications of AI in web programming, focusing on code optimization, user interface improvement, and the development of secure and adaptive platforms. It also discusses the challenges of AI integration, particularly in relation to data security, privacy, and interoperability across systems. The findings aim to provide insights into best practices for harnessing AI in the web programming industry, ultimately contributing to the creation of more efficient, secure, and user-centered digital solutions
Effectiveness of Different Irrigation Methods in Eliminating Bacterial Biofilm in Root Canal
No full text:Long-term success of endodontic treatment largely depends on the elimination of microorganisms and bacterial biofilm within the root canal system. The complex anatomy of root canals often hinders complete mechanical cleaning, making irrigation a critical step in disinfection. Recent studies have evaluated the effectiveness of various irrigation solutions and techniques in reducing bacterial load.To analyze the effectiveness of different irrigation methods in eliminating bacterial biofilm and to identify techniques that provide optimal results in endodontic practice.This study is based on a review of scientific literature published in PubMed, Scopus, and Google Scholar from 2010 to 2024. Included were laboratory studies, clinical trials, and systematic reviews comparing solutions such as sodium hypochlorite (NaOCl), EDTA, chlorhexidine, as well as active irrigation techniques including ultrasonic activation, sonic activation, and laser-assisted irrigation.Data indicate that sodium hypochlorite remains the most effective solution for biofilm elimination, especially when combined with EDTA for smear layer removal. Ultrasonic and laser activation significantly enhance the penetration and effectiveness of irrigants, reducing bacterial load substantially. However, no single method guarantees complete biofilm removal; therefore, combining irrigants with activation techniques represents the most successful approach in endodontic therapy