Automation - Science topic

To teach advanced laparoscopic knot-tying and suturing skills, the Advanced Training in Laparoscopic Suturing (ATLAS), a six-task proficiency-based curriculum was introduced. The Needle Handling task requires needle maneuvering through six holes on a circular platform. Performance is manually evaluated through video review for completion time and e...

The 2025 IEEE 1st International Conference on Materials, Robotics & Automation, Computer, and Control (ICMRACC-2025), which took place from March to 14-16, 2025, represents a significant milestone in advancing the convergence of cutting-edge technologies. This inaugural event, fully sponsored by the IEEE Robotics and Automation Society, is set to b...

MLOps (Machine Learning Operations) in healthcare is revolutionizing the deployment and management of AI models, but it also presents unique challenges. This paper explores the critical challenges faced when deploying AI models in healthcare environments, such as data privacy concerns, regulatory compliance, and the need for robust infrastructure....

MLOps (Machine Learning Operations) in healthcare is revolutionizing the deployment and management of AI models, but it also presents unique challenges. This paper explores the critical challenges faced when deploying AI models in healthcare environments, such as data privacy concerns, regulatory compliance, and the need for robust infrastructure....

Machine learning (ML) holds immense potential for enterprise data use cases, but a lack of skilled data scientists hinders its utilization. Automated ML (AutoML) aims to empower business users but often falls short, especially when domain knowledge influences model selection. It remains unclear how human-guided ML (HGML) systems can effectively emp...

Integrating data-driven methodologies with agent-based simulation presents an opportunity to automate modeling and enable Digital Twins for complex systems. This integration allows for utilization of real-world data to extract models that update with changes in the corresponding real systems and enhance our abilities to make informed decisions. We...

Current track-keeping systems used on real-world inland vessels do not consider obstacles and the fairway boundary and, therefore, cannot perform evasive maneuvers to avoid obstacles. Because of that, human operators must keep paying attention to anticipate critical situations to take over manual control. However, due to the high inertia of the und...

This article describes how the practical application of Nmap and Python can revolutionize the approach to cybersecurity, offering insight into specific techniques, scripts, and strategies for using these tools to enhance network security. Through in-depth analysis and use cases, this article aims not only to demonstrate the potential of combining t...

Crime continues to be a far too common occurrence in many of our communities. It leaves people feeling unsafe, even in their own neighborhoods. Law enforcement uses modern technology to try to be as effective as possible in combatting crime. However, police resources are limited and officers cannot respond to every incident. For this reason, we sho...

The article presents the possibilities of using artificial intelligence in the context of cybersecurity. It outlines the role of artificial intelligence in the face of increasing threats to network infrastructure. Section 1 discusses the justification for using artificial intelligence in cybersecurity, while Sections 2 and 3 explore the concept of...

Este trabalho analisa o Retorno sobre o Investimento (ROI), considerando que a implantação de Robôs Colaborativos (cobots) na indústria automotiva, mais especificamente na fabricante de caixas de engrenagens para veículos SEAT Componentes, exige agilidade nos processos, além de garantir qualidade e um ambiente seguro, visando uma solução de automaç...

Detecting structural cracks is critical for quality control and maintenance of industrial materials, ensuring their safety and extending service life. This study enhances the automation and accuracy of crack detection in microscopic images using advanced image processing and deep learning techniques, particularly the YOLOv8 model. A comprehensive r...

Resistance spot welding (RSW) is widely employed in the automotive and home appliance industries due to its high efficiency, low cost, and suitability for automation. However, traditional quality detection methods rely on destructive testing, leading to inefficiencies and resource wastage. This paper presents a novel quality inspection model for RS...

Hospital management systems (HMS) play a crucial role in ensuring the smooth operation of healthcare facilities, improving efficiency, and enhancing patient care. The integration of intelligent tools, such as artificial intelligence (AI), machine learning (ML), and data analytics, can significantly optimize hospital operations. By automating admini...

This paper presents a deep learning-based Scan-vs-BIM methodology for evaluating structural integrity through the extraction of features from As-Built scan and As-Planned Building Information Modeling (BIM) comparison data. Traditional Scan-vs-BIM frameworks often rely on Scan-to-BIM processes to generate point cloud-based mesh models for compariso...

This paper explores the integration of Big Data analytics in building condition assessments to enhance auditability, accuracy, and efficiency. Traditional methods of assessing building conditions are labor-intensive and prone to inconsistencies. By leveraging advanced analytics, vast amounts of data from diverse sources-such as IoT sensors, histori...

With increasing urbanization, traffic issues have become a significant challenge for cities worldwide. This study employs Propensity Score Matching (PSM) to analyze the impact of Adaptive Traffic Signal (ATS) systems on traffic congestion in Manhattan, using data from the "Midtown in Motion" initiative. Data from New York City's Automated Traffic V...

Este artigo aborda a automatização do processo de impressão de crachás dos funcionários de uma empresa utilizando ferramentas de programação low code. O problema foi estruturado segundo a metodologia Lean, especificadamente o ciclo PDCA. O Gemba Walk e o 5W2H foram utilizados para elencar os problemas identificados, que vão desde a demora para a en...

This paper highlights the challenges and opportunities introduced by disruptive technology for organizations. The convergence of emerging technologies holds the potential to enhance logistics and supply chain decision-making through heightened automation. The paper aims to conduct a multi-criteria assessment of readiness for implementing disruptive...

This research introduces a novel deep learning approach for keypoint detection in radiographs to objectively measure heart size. By employing a state-of-the-art convo-lutional neural network (EfficientNetB7), the model precisely identifies six key anatomical points, enabling accurate VHS calculation. The proposed method demonstrates exceptional per...

This paper presents the development of an algorithm for identifying shock waves formed during the supersonic combustion process, detonation, in a pulsed detonation chamber. The algorithm is based on image binarization techniques, followed by the identification of regions of interest in the images, the detection and isolation of the edges of these r...

Detection of surface defects in strip steel is crucial in industrial automation to ensure steel quality. Recently, learning-based detection methods have gained prominence among researchers for their robust capabilities. However, accurately delineating clear area boundaries remains a challenge, particularly in the complex backgrounds of steel surfac...

Implementing collaborative robots in warehouse operations requires employees to engage in order picking alongside robots, which raises concerns about employees’ perception of being ‘robotised’. This study explores the interplay between workload and autonomy in the context of Automated Guided Vehicle (AGV)-assisted order picking, aiming to understan...

A critical question about Large Language Models (LLMs) is whether their apparent deficiency in mathematical reasoning is inherent, or merely a result of insufficient exposure to high-quality mathematical data. To explore this, we developed an automated method for generating high-quality, supervised mathematical datasets. The method carefully mutate...

As automated vehicles (AVs) become increasingly popular, the question arises as to how cyclists will interact with such vehicles. This study investigated (1) whether cyclists spontaneously notice if a vehicle is driverless, (2) how well they perform a driver-detection task when explicitly instructed, and (3) how they carry out these tasks. Using a...

This research focuses on the iteration of architectural modeling using artificial intelligence (AI) as a solution to generate visualization concepts in the architectural iteration process. It examines the development of AI in architecture and highlights AI's position in current architectural practice. AI has revolutionized the way architectural des...

Resumo O presente artigo trata das potencialidades e riscos da Inteligência Artificial (IA). Com esse objetivo, posiciona a IA no alvorecer da IV Revolução Industrial, explica suas categorias essenciais e modo de operar. Aborda os benefícios trazidos pela nova tecnologia: ampliação da capacidade decisória humana, automação, avanços em pesquisa e in...

The prioritization of bug reports based on severity is a crucial aspect of bug triaging, enabling a focus on more critical issues. Traditional methods for assessing bug severity range from manual inspection to the application of machine and deep learning techniques. However, manual evaluation tends to be resource-intensive and inefficient, while co...

This document contains detailed information about the prompts used in the experimental process discussed in the paper "Toward Automating Agent-based Model Generation: A Benchmark for Model Extraction using Question-Answering Techniques". The paper aims to utilize Question-answering (QA) models to extract the necessary information to implement Agent...

Zusammenfassung Im Beitrag werden Praktiken der Automatisierung in der führenden chinesischen Messaging-Applikation WeChat untersucht. Die Applikation unterliegt ständigem Wandel, und die bisherigen Beschreibungen (v. a. Szurawitzki 2019; Szurawitzki 2022b) berücksichtigen Automatisierung kaum. Im Zentrum steht die Fragestellung, welche Praktiken d...

El artículo presenta el desarrollo de un aplicativo móvil (App) para el registro de lectura de los medidores de agua y sincronización del mismo en una base de datos centralizada, diseñada para la Junta de Saneamiento de Curuguaty. Actualmente, el proceso de recolección de datos se realiza de manera manual, con la aplicación de la tecnología el trab...

A evolução da tecnologia tem impressionado a comunidade mundial pela sua velocidade de expansão e transformação do trabalho. A substituição de mão de obra humana por robôs e inteligência artificial tem preocupado organismos internacionais. Pesquisas demonstram que algumas profissões desaparecerão nos próximos anos e a consequente desvalorização da...

This article presents two studies examining the relationship between induced creative mindsets and creative performance. Study 1, an online MTurk study, randomly assigned 85 participants to read one of two articles describing creativity as a growth/malleable or fixed/entity ability. Study 2 replicated Study 1 with an online Prolific study of 111 pa...

Streszczenie: W artykule przedstawiono zagadnienie projektowania systemu sterowania ruchem kolejowym w technologii BIM z zastosowaniem środowiska programowania Dynamo. Artykuł jest wynikiem prac badawczych i projektowych wykorzystujących skrypty przyspieszające i automatyzujące projektowanie w technologii BIM. Przedstawiono założenia przyjęte do r...

O presente estudo teve como objetivo geral analisar como a transformação digital influencia as funções e habilidades necessárias para os contadores no futuro, e quais as implicações dessas mudanças para a profissão contábil. E foram objetivos específicos: identificar as principais tecnologias digitais que estão impactando a prática contábil; descre...

Understanding part-whole relations is crucial in early mathematics education. However, both analogue and digital learning environments often lack systematic approaches to foster part-whole understanding. With the rising popularity of educational apps, it is essential to evaluate how they implement learning of part-whole relations. Accordingly, this...

This research presents the implementation of an object detection model using PyTorch to detect vertebral heart sizes in dogs. Accurate vertebral heart size (VHS) measurement is crucial for diagnosing cardiac issues in canines. In this study, a custom object detection model is trained to perform automatic VHS measurement. The paper details the metho...

Several parallel assembly lines are balanced simultaneously in the parallel assembly line balancing problem (PALBP), which lead to several advantages such as increased capacity and flexibility against the changes in demand. Recently, the parallel robotic assembly line balancing problem (PRALBP) has emerged in the literature, due to the increase in...

The emergence and growth of 5G and beyond 5G (B5G) networks has brought about the rise of so-called "programmable" networks, i.e., networks whose operational requirements are so stringent that they can only be met in an automated manner, with minimal/no human involvement. Any requirements on such a network would need to be formally specified via in...

Este estudo tem por objetivo identificar e categorizar as competências técnicas (hard skills) e comportamentais (soft skills) necessárias para os Engenheiros de Produção no contexto da Indústria 4.0. A metodologia adotada foi uma revisão de escopo seguindo o protocolo PRISMA, com buscas conduzidas nas bases Web of Science e Scopus. Os principais re...

Automated feature engineering (AutoFE) is used to automatically create new features from original features to improve predictive performance without needing significant human intervention and expertise. Many algorithms exist for AutoFE, but very few approaches exist for the federated learning (FL) setting where data is gathered across many clients...

The concept of green scheduling, which deals with the environmental impact of the scheduling process, is becoming increasingly important due to growing environmental concerns. Most green scheduling problem variants focus on modelling the energy consumption during the execution of the schedule. However, the dynamic unrelated machines environment is...

The classification of civil society organizations by their characteristics seems quite straightforward. But in practice there are real challenges in both agreeing and applying a classification system consistently, particularly if the process needs to be automated. In this chapter we explore what is meant by the classification of civil society, desc...

Successes and struggles of generative AI in automation development

The Houston Independent School District case has revealed the challenges of transparency, impartiality, and human review mechanisms that automated administrative systems face in practice. The case shows that the automated administrative system needs to solve the problems of insufficient transparency and impartiality challenges while enhancing effic...

Analysing interactions between niches and regimes is critically important for understanding sustainability transitions. What complicates interaction is the fact that sustainability is often understood and pursued differently in regimes compared to niches. That means the aims and criteria for innovation can be different on either side of the interac...

Os portais eletrônicos são ferramentas essenciais para promover a transparência e a eficiência na administração pública, especialmente no contexto da transformação digital. Este estudo analisa comparativamente os portais eletrônicos das prefeituras de Porto Velho, Ji-Paraná e Ariquemes, em Rondônia, para avaliar seus níveis de maturidade digital, i...

Syntactic complexity (SC) is an important construct for gauging L2 writing proficiency. Previous studies, including Biber et al. (2016) and Dong et al. (2023), have largely focused on syntactic elaboration and disregarded syntactic diversity. This study investigates how academic writing proficiency is associated with SC, through an evaluation of bo...

Artificial intelligence has, so far, largely automated routine tasks, but what does it mean for the future of work if Large Language Models (LLMs) show creativity comparable to humans? To measure the creativity of LLMs holistically, the current study uses 13 creative tasks spanning three domains. We benchmark the LLMs against individual humans, and...

O uso da Inteligência Artificial (IA) tem impulsionado mudanças profundas em diversos setores da sociedade, incluindo a Justiça do Trabalho. Este estudo examina os impactos que a IA vem trazendo para o sistema judiciário trabalhista, destacando tanto os benefícios quanto os desafios dessa transformação tecnológica. As principais mudanças envolvem a...

Proxy re-encryption (PRE) is a cryptographic primitive that extends public key encryption by allowing ciphertexts to be re-encrypted from one user to another without revealing information about the underlying plaintext. This makes it an essential privacy-enhancing technology, as only the intended recipient is able to decrypt sensitive personal info...

The automotive industry is undergoing a rapid transformation with the emergence of self-driving technologies and complex software systems ● The growth of vehicle automation necessitates a critical need for safety guidelines and standards implementation ● This paper focuses on the safety design features of complex automotive software, particularly f...

Resumo: No contexto empresarial, a gestão eficiente diante do avanço tecnológico e do crescimento exponencial do volume global de dados torna-se crucial. Este cenário não representa apenas um desafio, mas também uma oportunidade para as organizações implementarem melhorias e conquistarem vantagens competitivas. Este estudo concentra-se na otimizaçã...

Converting mathematical expressions into LaTeX is challenging. In this paper, we explore using newer transformer based architectures for addressing the problem of converting handwritten/digital mathematical expression images into equivalent LaTeX code. We use the current state of the art CNN encoder and RNN decoder as a baseline for our experiments...

The integration of artificial intelligence (AI) in diverse industries has amplified the demand for scalable and efficient computing environments. Cloud-native technologies, particularly Kubernetes and Docker, have emerged as essential tools in orchestrating and managing AI workloads. Docker enables containerization, encapsulating applications and t...

This paper presents Yankari, a large-scale monolingual dataset for the Yoruba language, aimed at addressing the critical gap in Natural Language Processing (NLP) resources for this important West African language. Despite being spoken by over 30 million people, Yoruba has been severely underrepresented in NLP research and applications. We detail ou...

Feedback is a key factor in motivating and consolidating learning, but in classroom teaching, a teacher needs to provide timely and effective feedback on the homework of dozens of students, which puts much pressure on the teacher. Meanwhile, existing automatic feedback systems are not suitable for open writing tasks. The emergence of ChatGPT has at...

Automated metrics for Machine Translation have made significant progress, with the goal of replacing expensive and time-consuming human evaluations. These metrics are typically assessed by their correlation with human judgments, which captures the monotonic relationship between human and metric scores. However, we argue that it is equally important...

This research examines how artificial intelligence, human capabilities, and task types influence organizational outcomes. By leveraging the frameworks of the Resource-Based View and Task Technology Fit theories, we executed two distinct studies to assess the effectiveness of a generative AI tool in aiding task performance across a spectrum of task...

Software services play a crucial role in daily life, with automated actions determining access to resources and information. Trusting service providers to perform these actions fairly and accurately is essential, yet challenging for users to verify. Even with publicly available codebases, the rapid pace of development and the complexity of modern d...

The rapid advancement of large language models (LLMs) has opened new boundaries in the extraction and synthesis of medical knowledge, particularly within evidence synthesis. This paper reviews the state-of-the-art applications of LLMs in the biomedical domain, exploring their effectiveness in automating complex tasks such as evidence synthesis and...

In this paper, we introduce the MediaSpin dataset aiming to help in the development of models that can detect different forms of media bias present in news headlines, developed through human-supervised and-validated Large Language Model (LLM) labeling of media bias. This corpus comprises 78,910 pairs of news headlines and annotations with explanati...

In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new task in this paper: image-conditioned autocorrection of inaccuracies within these reports. Using the MIMIC-CXR dataset, we first intentionally introduce a diverse range of errors into reports. Subseque...

Resumen La inteligencia artificial (IA) se está convirtiendo en una herramienta fundamental para la innovación empresarial. En la actualidad las empresas que utilizan IA cambian sus modelos de negocio, en áreas como la automatización y el análisis predictivo proporcionan una ventaja competitiva. Además, ayudado en un manejo eficiente para la atenci...

This study aims to investigate the effects of automation technology on income inequality with a growth model based on the automation capital approach. Our model adds automation capital as a third production factor alongside labor and traditional capital. We employ an infinite-horizon dynamic optimization model for capitalists and a two-period overl...

Coronary artery disease stands as one of the primary contributors to global mortality rates. The automated identification of coronary artery stenosis from X-ray images plays a critical role in the diagnostic process for coronary heart disease. This task is challenging due to the complex structure of coronary arteries, intrinsic noise in X-ray image...

Temporal logic specifications play an important role in a wide range of software analysis tasks, such as model checking, automated synthesis, program comprehension, and runtime monitoring. Given a set of positive and negative examples, specified as traces, LTL learning is the problem of synthesizing a specification, in linear temporal logic (LTL),...

Automated identification of cracks in concrete and pavement is gaining popularity today. Numerous ways have been suggested and put into practice in recent times. The primary goal is to mechanize the process with enhanced precision and efficiency. This study uses a Vision Transformer model to detect surface cracks. The primary goal is to assess the...

AlphaPulldown2 streamlines protein structural modeling by automating workflows, improving code adaptability, and optimizing data management for large-scale applications. It introduces an automated Snakemake pipeline, compressed data storage, support for additional modeling backends like UniFold and AlphaLink2, and a range of other improvements. The...

This paper explores the use of probabilistic and conventional qualitative spatial reasoning (QSR) in the context of geospatial question answering (GeoQA) systems. The paper presents a thorough empirical investigation of the performance of a probabilistic and a conventional qualitative spatial reasoner, across a range increasingly sophisticated scen...

O controle de temperatura é de fundamental importância nas indústrias metalúrgicas que produzem feixes de molas. A dureza das lâminas que compõem o feixe é uma característica significativa que é afetada diretamente pela temperatura do forno no qual a peça é processada. Por esta razão, este trabalho possui como finalidade realizar um projeto de auto...

Com o avanço da tecnologia, a automação tornou-se essencial para otimizar processos, aumentar a eficiência, reduzir custos e melhorar a qualidade dos produtos, permitindo a integração de diversos sistemas e equipamentos, como sensores, controladores lógicos programáveis (CLPs) e atuadores, para controlar e monitorar com eficiência os processos de f...

This contribution presents an improved low-order 3D finite element formulation with hourglass stabilization using automatic differentiation (AD). Here, the former Q1STc formulation is enhanced by an approximation-free computation of the inverse Jacobian. To this end, AD tools automate the computation and allow a direct evaluation of the inverse Jac...

A área de estudo desse trabalho se localiza na região Sudoeste do Rio Grande do Sul no município de Cacequi que se destaca pela alta ocorrência de voçorocas em seu território. O arcabouço geológico e morfoestrutural pode interferir na forma, intensidade e orientação das voçorocas em Cacequi. Assim, esse artigo busca analisar a relação entre os line...

The rapid advancements in artificial intelligence (AI), algorithms, and big data analytics have revolutionized various industries, leading to unprecedented efficiencies and capabilities. These technologies offer numerous benefits, such as enhancing productivity and enabling faster accomplishment of tasks. However, they also pose significant challen...