Niklas Freund, Zekiye Ilknur-Öz, Tobias Klockau
et al.
The monitoring of the route and track environment plays an important role in automated driving. For example, it can be used as an assistance system for route monitoring in automation level Grade of Automation (GoA) 2, where the train driver is still on board. In fully automated, driverless driving at automation level GoA4, these systems finally take over environment monitoring completely independently. With the help of artificial intelligence (AI), they react automatically to risks and dangerous events on the route. To train such AI algorithms, large amounts of training data are required, which must meet high-quality standards due to their safety relevance. In this publication we present an automatic method for assuring the quality of training data, significantly reducing the manual workload and accelerating the development of these systems. We propose an open-source tool designed to detect nine common errors found in multi-sensor datasets for railway vehicles. To evaluate the performance of the framework, all detected errors were manually validated. Six issue detection methods achieved 100% precision, while three additional methods reached precision rates 96% and 97%.
DevOps automation can accelerate software delivery, yet many organizations still struggle to justify and prioritize automation work in terms of strategic project-management outcomes such as waste reduction, delivery predictability, cross-team coordination, and customer-facing quality. This paper presents \textit{VSM--GQM--DevOps}, a unified, traceable framework that integrates (i) Value Stream Mapping (VSM) to visualize the end-to-end delivery system and quantify delays, rework, and handoffs, (ii) the Goal--Question--Metric (GQM) paradigm to translate stakeholder objectives into a minimal, decision-relevant measurement model (combining DORA with project and team outcomes), and (iii) maturity-aligned DevOps automation to remediate empirically observed bottlenecks through small, reversible interventions. The framework operationalizes traceability from observed waste to goal-aligned questions, metrics, and automation candidates, and provides a defensible prioritization approach that balances expected impact, confidence, and cost. We also define a multi-site, longitudinal mixed-method validation protocol that combines telemetry-based quasi-experimental analysis (interrupted time series and, where feasible, controlled rollouts) with qualitative triangulation from interviews and retrospectives. The expected contribution is a validated pathway and a set of practical instruments that enables organizations to select automation investments that demonstrably improve both delivery performance and project-management outcomes.
Carlos Alberto Fernández-y-Fernández, Jorge R. Aguilar-Cisneros
The rapid evolution and inherent complexity of modern software requirements demand highly flexible and responsive development methodologies. While Agile frameworks have become the industry standard for prioritizing iteration, collaboration, and adaptability, software development teams continue to face persistent challenges in managing constantly evolving requirements and maintaining product quality under tight deadlines. This article explores the intersection of Artificial Intelligence (AI) and Software Engineering (SE), to analyze how AI serves as a powerful catalyst for enhancing agility and fostering innovation. The research combines a comprehensive review of existing literature with an empirical study, utilizing a survey directed at Software Engineering professionals to assess the perception, adoption, and impact of AI-driven tools. Key findings reveal that the integration of AI (specifically through Machine Learning (ML) and Natural Language Processing (NLP) )facilitates the automation of tedious tasks, from requirement management to code generation and testing . This paper demonstrates that AI not only optimizes current Agile practices but also introduces new capabilities essential for sustaining quality, speed, and innovation in the future landscape of software development.
Blerina Xhelaj, Shefqet Dinaj, Olena Tymoshenko
et al.
Technological breakthroughs shaped economic, political, and social changes in Albania, Kosovo, and Ukraine, according to this study. The research sought to link important technology advances to major historical shifts in these countries. The methodology examines how technology advances from industrialization to the digital era affected governance, warfare, and economic institutions. Industrialization in Albania in the 20th century increased manufacturing output, while Kosovo’s post-war reconstruction focused on energy and telecommunications advances. Technological improvements in agriculture and aerospace helped Ukraine expand economically, increasing agricultural production by 25%. Digital revolution has increased economic integration in all three nations, with Ukraine becoming a key IT outsourcing hub and Kosovo witnessing growing digital entrepreneurship. These trends can be quantified using GDP growth, employment movements, and technological adaption data. The study shows how technology has affected political stability, economic development, and social transformation in various locations. The paper discusses the long-term effects of technology progress on human civilization and how Albania, Kosovo, and Ukraine may use innovation for sustainable development.
Laura Minkova, Jessica López Espejel, Taki Eddine Toufik Djaidja
et al.
As businesses increasingly rely on automation to streamline operations, the limitations of Robotic Process Automation (RPA) have become apparent, particularly its dependence on expert knowledge and inability to handle complex decision-making tasks. Recent advancements in Artificial Intelligence (AI), particularly Generative AI (GenAI) and Large Language Models (LLMs), have paved the way for Intelligent Automation (IA), which integrates cognitive capabilities to overcome the shortcomings of RPA. This paper introduces Text2Workflow, a novel method that automatically generates workflows from natural language user requests. Unlike traditional automation approaches, Text2Workflow offers a generalized solution for automating any business process, translating user inputs into a sequence of executable steps represented in JavaScript Object Notation (JSON) format. Leveraging the decision-making and instruction-following capabilities of LLMs, this method provides a scalable, adaptable framework that enables users to visualize and execute workflows with minimal manual intervention. This research outlines the Text2Workflow methodology and its broader implications for automating complex business processes.
Every new generation of mobile networks brings significant advances in two segments, enhancement of the network parameters within the legacy technologies and introduction of new technologies enabling new paradigms in designing the networks. In the first class of enhancements the effort is to increase data rates, improve energy efficiency, enhance connectivity, reduce data transmission latency etc. In the second class of innovations for 6G and 7G, we anticipate focus on optimum integration of advanced ML and AI in general, and quantum computing with the continuous interest in the satellite networks for optimal quantum key distribution . By introducing quantum technology 7G will be able to speed up computing processes in the net, enhance network security as well as to enable distributed QC, which is a new paradigm in computer sciences. Using advanced networks as a basic ingredient of inter system integration, here we focus only on the second segment of anticipated innovations in networking and present a survey of the subset of potential technology enablers for the above concept with special emphasis on the inter dependency of the solutions chosen in different segments of the network. In Section II, we present several anticipated 6G/7G (system of systems type) network optimization examples resulting in a new paradigm of network optimization indicating a need for quantum computing and quantum computing based optimization algorithms. In Section III we survey work on quantum cryptography and QKD.
The last decade has been marked by the evolution of cryptocurrencies, which have captured the interest of the public through the offered opportunities and the feeling of freedom, resulting from decentralization and lack of authority to oversee how cryptocurrency transactions are conducted. The innovation in crypto space is often compared to the impact internet had on human life. There is a new term called Web 3.0 for denoting all new computing innovations arising due to the blockchain technologies. Blockchain has emerged as one of the most important inventions of the last decade with crypto currencies or financial use case as one of the domains which progressed most in the last 10 years. It is very important to research about Web 3 technologies, how it is connected to crypto economy and what to expect in this field for the next several decades.
Science prizes purportedly reward innovation and explorations of new phenomena. Yet, in practice prizes may inadvertently divert resources from similarly impactful but less celebrated scholars. Despite this paradox, knowledge of how prizewinning relates to innovation is nascent even as prizes proliferate widely. Analyzing 2,460 worldwide prizes, we compared the innovativeness of over 23,000 prizewinners and matched non-prizewinners whose performance records were statistically equivalent up to the prize year. First, we find that prizewinners are more innovative. Their research is more likely to combine existing ideas in new ways, integrate a topic's historical and contemporary thinking, and incorporate interdisciplinary perspectives. Second, although prizewinners and matched non-prizewinners have statistically equivalent impact and productivity records up to the prize year, at about five years before the prize, prizewinners' papers become more innovative than their matched peers, a difference that widens each year, peaks during the prize year, and then persists for the remainder of their careers. Third, network embeddedness predicts unusual innovativeness. Compared to non-prizewinners, prizewinners' collaborations are shorter in duration, encompass wider exposure to unfamiliar topics, and involve coauthors whose networks minimally overlap with each other. The implications of the findings for the efficacy of reward systems and innovation in science are discussed.
O presente artigo aborda definições referentes à habitação de interesse social e carga de incêndio, relacionando a importância da norma de desempenho de edificações habitacionais à dificuldade em propor moradia inclusiva para a população. Foi proposta uma pesquisa documental sobre a ação do fogo em núcleos habitacionais de cunho social, listando elementos estruturais da construção, comportamento dos materiais em relação ao fogo e sistemas de proteção dos elementos estruturais, bem como as principais ocorrências de incêndios do tema em questão no Brasil. A segurança estrutural contra incêndio está diretamente relacionada à tipologia das habitações de interesse social que possuem especificações técnicas e custos pré-definidos, visando a estabelecer padrões mínimos e máximos que atendam ao perfil do beneficiário do programa social. Concluiu-se que há grandes desafios, entre os quais se destacam: o estudo da dinâmica e do comportamento das estruturas em situação de incêndio, pois as soluções adotadas poderão garantir, ou não, a qualidade do projeto arquitetônico e o atendimento aos requisitos de desempenho; a garantia de que a habitação seja inclusiva para a população de baixa renda e favoreça a segurança dos ocupantes na relação permanência versus desocupação dos espaços; e a escassez de banco de dados que possam ser comparados entre os Corpos de Bombeiros, reforçando a necessidade de um anuário padronizado que venha a identificar as ocorrências nessas habitações.
Victor M. Yurov, Vladimir I. Goncharenko, Vladimir S. Oleshko
et al.
The surface layer determines the physical properties of aviation materials and, based on these properties, the calculation of surface energy anisotropy can be implemented. Moreover, the value of the surface energy determines the service time and the destruction of aircraft structures surface layer, while the surface layer thickness determines the distance at which this process usually takes place. In this work, a new atomically smooth crystal empirical model is built without considering the surface roughness. This model can be used to theoretically predict the surface energy anisotropy and surface layer thickness of metals and other compounds, in particular the aviation materials. The work shows that the surface layer of an atomically smooth metal, like other compounds, consists of two nanostructured layers: d(I) and d(II). Having sufficient accuracy, the proposed model would allow the prediction of aviation materials performance properties without the need for ultrahigh vacuum or other complicated theoretical methods to analyze the surfaces of nanosystem atomic structures.
Engineering machinery, tools, and implements, Technological innovations. Automation
Voice recognition technology enables the execution of real-world operations through a single voice command. This paper introduces a voice recognition system that involves converting input voice signals into corresponding text using an Android application. The text messages are then transmitted through Bluetooth connectivity, serving as a communication platform. Simultaneously, a controller circuit, equipped with a Bluetooth module, receives the text signal and, following a coding mechanism, executes real-world operations. The paper extends the application of voice recognition to real-time surveillance and automation, incorporating obstacle detection and avoidance mechanisms, as well as control over lighting and horn functions through predefined voice commands. The proposed technique not only serves as an assistive tool for individuals with disabilities but also finds utility in industrial automation, enabling robots to perform specific tasks with precision.
The financial crisis of 2008-2009 has changed an approach to conducting monetary and fiscal policy. Changing economic conditions forced the economic authorities to make decisions that influenced an interaction between the central bank and the government (policy mix) in the European Union countries. The article aims to identify the impact of variables in the area of monetary and fiscal policy on the economy in the EU countries in existing economic conditions. The article verifies the hypothesis that variables from the monetary and fiscal policy have a statistically significant impact on the GDP per capita growth rate in the EU countries. To achieve the goal and verify the hypothesis, the following research methods were used: presentation of statistical data as well as statistical and econometric research methods (panel model). The rationale for the adoption of this topic was to examine the impact of central bank policy and government in the EU countries on their economies. The contribution of this article is to present the role of monetary and fiscal policy in the economic growth of the EU countries in 2000-2019. The results of the study indicate that the GDP per capita growth rate in 28 European Union countries in the period of 2000-2019 was statistically significantly affected by such variables as: interest rate (from the monetary policy area), GG deficit/surplus (the variable from the area of fiscal policy). This is important information in the context of conducting monetary policy and fiscal policy by relevant decision-makers, i.e., monetary authorities and fiscal authorities in the EU countries.
У місті Вейхай (провінція Шаньдун, Китай) відбулося «Онлайн-відео роуд-шоу», присвячене підбору зарубіжних талантів високо класу. Понад 20 підприємців і кілька українських науковців із захопленням спілкувалися через онлайн-відео, обговорюючи стикування технологій у сферах сільського господарства, медичного лікування, автоматизації тощо. Було розпочато нову спробу хмарного міжнародного роуд-шоу – прелюдію до «China Weihai International Talents, Innovation and Entrepreneurship Conference».
Захід був організований Вейхайським муніципальним бюро кадрових ресурсів та соціального забезпечення та проведення Управлінням людських ресурсів та соціального забезпечення (Weihai Talent Work). Після чисельних відборів і поєднання з виробничою ситуацією та реальними потребами парку підприємств було визначено план заходів для онлайн-стикування з українською командою науковців. Україна має міцну науково-дослідну базу, достатній запас висококласних талантів та потужну технічну силу. У спільних роботах брали участь п'ять академіків і спеціалістів, які зацікавили підприємства Вейхаю своїми технічними досягненнями.
Sign language is designed as a natural communication method for the deaf community to convey messages and connect with society. In American sign language, twenty-six special sign gestures from the alphabet are used for the fingerspelling of proper words. The purpose of this research is to classify the hand gestures in the alphabet and recognize a sequence of gestures in the fingerspelling using an inertial hand motion capture system. In this work, time and time-frequency domain features and angle-based features are extracted from the raw data for classification with convolutional neural network-based classifiers. In fingerspelling recognition, we explore two kinds of models: connectionist temporal classification and encoder-decoder structured sequence recognition model. The study reveals that the classification model achieves an average accuracy of 74.8% for dynamic ASL gestures considering user independence. Moreover, the proposed two sequence recognition models achieve 55.1%, 93.4% accuracy in word-level evaluation, and 86.5%, 97.9% in the letter-level evaluation of fingerspelling. The proposed method has the potential to recognize more hand gestures of sign language with highly reliable inertial data from the device.
Engineering machinery, tools, and implements, Technological innovations. Automation
Living Lab is an umbrella term used for referring to a methodology of user-centric innovation in real-life environments within a wider network of relevant stake holders. Real-life environment refers to living houses and hospitals inter wined and connected together in a way which promotes direct usability of research by the end users. It primarily consists of three stages, Design thinking to actual Conceptualisation, Evaluation and Prototyping and Final product prototyping to commercialisation. The increasing demand of cutting age healthcare system is in itself a challenge and requires user involvement to mobilise knowledge to build a patient centered and knowledge-based economy. Innovations are constantly needed to reduce the problematic barriers to efficient knowledge exchange and improve collaborative problem solving. Living Innovation Lab, as open knowledge system, have immense potential to address these gaps that are underexplored in the healthcare system.