Hasil untuk "Industrial relations"

Rongfei Li, Francis Assadian

Image-based visual servoing (IBVS) methods have been well developed and used in many applications, especially in pose (position and orientation) alignment. However, most research papers focused on developing control solutions when 3D point features can be detected inside the field of view. This work proposes an innovative feedforward-feedback adaptive control algorithm structure with the Youla Parameterization method. A designed feature estimation loop ensures stable and fast motion control when point features are outside the field of view. As 3D point features move inside the field of view, the IBVS feedback loop preserves the precision of the pose at the end of the control period. Also, an adaptive controller is developed in the feedback loop to stabilize the system in the entire range of operations. The nonlinear camera and robot manipulator model is linearized and decoupled online by an adaptive algorithm. The adaptive controller is then computed based on the linearized model evaluated at current linearized point. The proposed solution is robust and easy to implement in different industrial robotic systems. Various scenarios are used in simulations to validate the effectiveness and robust performance of the proposed controller.

Matthieu Mastio, Paul Saves, Benoit Gaudou et al.

Industrial symbiosis fosters circularity by enabling firms to repurpose residual resources, yet its emergence is constrained by socio-spatial frictions that shape costs, matching opportunities, and market efficiency. Existing models often overlook the interaction between spatial structure, market design, and adaptive firm behavior, limiting our understanding of where and how symbiosis arises. We develop an agent-based model where heterogeneous firms trade byproducts through a spatially embedded double-auction market, with prices and quantities emerging endogenously from local interactions. Leveraging reinforcement learning, firms adapt their bidding strategies to maximize profit while accounting for transport costs, disposal penalties, and resource scarcity. Simulation experiments reveal the economic and spatial conditions under which decentralized exchanges converge toward stable and efficient outcomes. Counterfactual regret analysis shows that sellers' strategies approach a near Nash equilibrium, while sensitivity analysis highlights how spatial structures and market parameters jointly govern circularity. Our model provides a basis for exploring policy interventions that seek to align firm incentives with sustainability goals, and more broadly demonstrates how decentralized coordination can emerge from adaptive agents in spatially constrained markets.

Rochana Chaturvedi, Peyman Baghershahi, Sourav Medya et al.

Temporal information extraction from unstructured text is essential for contextualizing events and deriving actionable insights, particularly in the medical domain. We address the task of extracting clinical events and their temporal relations using the well-studied I2B2 2012 Temporal Relations Challenge corpus. This task is inherently challenging due to complex clinical language, long documents, and sparse annotations. We introduce GRAPHTREX, a novel method integrating span-based entity-relation extraction, clinical large pre-trained language models (LPLMs), and Heterogeneous Graph Transformers (HGT) to capture local and global dependencies. Our HGT component facilitates information propagation across the document through innovative global landmarks that bridge distant entities. Our method improves the state-of-the-art with 5.5% improvement in the tempeval $F_1$ score over the previous best and up to 8.9% improvement on long-range relations, which presents a formidable challenge. We further demonstrate generalizability by establishing a strong baseline on the E3C corpus. This work not only advances temporal information extraction but also lays the groundwork for improved diagnostic and prognostic models through enhanced temporal reasoning.

Roberto Miranda Pimentel Fully, Danilo Soares Monte-Mor, Neyla Tardin

Contexto: a regulação constitui um campo analítico de elevada complexidade, no qual persistem controvérsias na literatura econômica acerca de seus determinantes, mecanismos e efeitos. Com o propósito de ampliar a compreensão das múltiplas perspectivas sobre o tema, transcendendo a abordagem estritamente econômica, este estudo propõe um método de mensuração do efeito regulatório sobre firmas de capital aberto no Brasil. O método culmina na formulação de um índice que viabiliza a comparação do peso relativo da regulação entre empresas pertencentes a distintos setores da economia nacional. Objetivo: o objetivo deste artigo é propor e aplicar um conjunto de indicadores que mensurem, de forma comparativa, o peso relativo da regulação sobre empresas de capital aberto no Brasil, considerando a intensidade regulatória por firma, indústria e mercado. Embora não constitua uma métrica direta de impacto econômico ou concorrencial, o índice fornece subsídios para estudos posteriores sobre a relação entre regulação, estratégia corporativa e desempenho setorial, podendo também contribuir para análises acerca dos reflexos regulatórios sobre a dinâmica concorrencial em diferentes segmentos da economia. Método: para identificar tal comportamento que distancia o efeito da regulação sobre a empresa em relação à indústria em que ela informa operar, utilizou-se o conceito de Nível de Distanciamento da Indústria (NDI), no qual se avalia o quanto a empresa está próxima ou distante do índice da sua indústria. Conclusões: o trabalho identificou clusters de comportamento das empresas frente ao peso da regulação estatal, o que permite auxiliar na compreensão das estratégias das empresas na adaptação aos aspectos regulatórios no Brasil.

Tiago Brandão

The Innovation Delusion: How Our Obsession with the New Has Disrupted the Work That Matters Most (2020), by Lee Vinsel and Andrew L. Russell, presents a blistering critique of the contemporary ideology of innovation, exposing what the authors call «innovation-speak» – a hegemonic discourse that glorifies disruptive change and marginalises the essential work of maintenance. The Innovation Delusion, by Lee Vinsel and Andrew L. Russell, published not many years ago (2020), is among the scholar books one must read, especially for younger generations and policymakers around the world. Many years ago, Steven Shapin (1989) unearthed the role of the technician in modern science. Innovation Delusion does the same for hidden activities in innovation — i.e., activities related to technology and engineering. Maintenance, upkeep and care is the motto behind Vinsel and Russell’s book.

Jin Hu, Hong Zhang

Wenbo Sui, Daniel Lichau, Josselin Lefèvre et al.

Recent studies of multimodal industrial anomaly detection (IAD) based on 3D point clouds and RGB images have highlighted the importance of exploiting the redundancy and complementarity among modalities for accurate classification and segmentation. However, achieving multimodal IAD in practical production lines remains a work in progress. It is essential to consider the trade-offs between the costs and benefits associated with the introduction of new modalities while ensuring compatibility with current processes. Existing quality control processes combine rapid in-line inspections, such as optical and infrared imaging with high-resolution but time-consuming near-line characterization techniques, including industrial CT and electron microscopy to manually or semi-automatically locate and analyze defects in the production of Li-ion batteries and composite materials. Given the cost and time limitations, only a subset of the samples can be inspected by all in-line and near-line methods, and the remaining samples are only evaluated through one or two forms of in-line inspection. To fully exploit data for deep learning-driven automatic defect detection, the models must have the ability to leverage multimodal training and handle incomplete modalities during inference. In this paper, we propose CMDIAD, a Cross-Modal Distillation framework for IAD to demonstrate the feasibility of a Multi-modal Training, Few-modal Inference (MTFI) pipeline. Our findings show that the MTFI pipeline can more effectively utilize incomplete multimodal information compared to applying only a single modality for training and inference. Moreover, we investigate the reasons behind the asymmetric performance improvement using point clouds or RGB images as the main modality of inference. This provides a foundation for our future multimodal dataset construction with additional modalities from manufacturing scenarios.

Ergin Kükrer, Nurdil Eskin

This study aims to provide insights into the intricate interactions between gas and liquid phases within flow components, which are pivotal in various industrial sectors such as nuclear reactors, oil and gas pipelines, and thermal management systems. Employing the Eulerian–Eulerian approach, our computational model incorporates interphase relations, including drag and non-drag forces, to analyze phase distribution and velocities within a complex U-bend system. Comprising two horizontal-to-vertical bends and one vertical 180-degree elbow, the U-bend system’s behavior concerning bend geometry and airflow rates is scrutinized, highlighting their significant impact on multiphase flow dynamics. The study not only presents a detailed exposition of the numerical modeling techniques tailored for this complex geometry but also discusses the results obtained. Detailed analyses of local void fraction and phase velocities for each phase are provided. Furthermore, experimental validation enhances the reliability of our computational findings, with close agreement observed between computational and experimental results. Overall, the study underscores the efficacy of the Eulerian approach with interphase relations in capturing the complex behavior of the multiphase flow in U-bend systems, offering valuable insights for hydraulic system design and optimization in industrial applications.

A. Benavides-Moran, S. Lain

Modeling efforts on turbulent gas-solid flows have mainly focused on studying particle-laden flows in channels and pipes. Despite its significance for industrial applications, the study of gas-solid flows in sudden or gradual expansions is less common in the literature. This paper challenges current two-phase flow models to compute the dilute turbulent gas-solid flow in a vertically oriented 12° conical diffuser. The solids phase is modeled in two ways: the Two-Fluid Model approach that incorporates closure relations derived from the kinetic theory of granular flow, and the Euler-Lagrange particle tracking model with two-way coupling. In both cases, turbulence in the gas phase is estimated by the Reynolds stress model with additional modulation terms that account for the effect of the particles on the gas-phase turbulence. Simulation results are validated versus experimental benchmark data not only for gas axial velocity but also for streamwise and radial turbulence intensity, as comparison with such turbulent variables has not been detailed in previous studies. Nevertheless, due to the lack of experimental data for validation, profiles of solids axial velocity are only compared numerically. Contours of turbulence kinetic energy and granular temperature in the diffuser region reveal a high shear area responsible for the production of turbulence in both phases. Moreover, results obtained from the Euler-Lagrange model show an intense particle fluctuating velocity in the streamwise direction downstream of the diffuser.

Çağlar Akar, Doğa Başar Sarıipek, Gökçe Cerev

Poverty is widely acknowledged as a significant factor in the outbreak of armed conflicts, particularly fueling armed conflict within national borders. There is a compelling argument positing that poverty is a primary catalyst for intrastate armed conflicts; reciprocally, these conflicts exacerbate poverty. This article introduces a statistical model to forecast the likelihood of armed conflict within a country by scrutinizing the intricate relationship between intrastate armed conflicts and various facets of poverty. Poverty, arising from factors such as gender inequality and limited access to education and public services, profoundly affects social cohesion. Armed conflicts, a significant cause of poverty, result in migration, economic devastation, and adverse effects on social unity, particularly affecting disadvantaged and marginal groups. Forecasting and receiving early warnings for intrastate armed conflicts are crucial for international policymakers to take precautionary measures. Anticipating and proactively addressing potential conflicts can mitigate adverse consequences and prevent escalation. Hence, forecasting intrastate armed conflicts is vital, prompting policymakers to prioritize the development of effective strategies to mitigate their impact. While not guaranteeing absolute certainty in forecasting future armed conflicts, the model shows a high degree of accuracy in assessing security risks related to intrastate conflicts. It utilizes a machine‐learning algorithm and annually published fragility data to forecast future intrastate armed conflicts. Despite the widespread use of machine‐learning algorithms in engineering, their application in social sciences still needs to be improved. This article introduces an innovative approach to examining the correlation between various dimensions of poverty and armed conflict using machine‐learning algorithms.

Zachary Carlini

We give a new, conceptual proof of the $\imath$Serre and Serre-Lusztig relations for $\imath$quantum groups. The key to our approach is a new formula for the comultiplication of the $\imath$-divided powers, which allows us to reformulate the relations in terms of the adjoint action. We then obtain a proof using properties of the adjoint representation. The flexibility of this approach allows us to establish a more general family of relations which seem difficult to establish otherwise.

Anupam Bhardwaj

Classical pulsating stars such as Cepheid and RR Lyrae variables exhibit well-defined Period-Luminosity relations at near-infrared wavelengths. Despite their extensive use as stellar standard candles, the effects of metallicity on Period-Luminosity relations for these pulsating variables, and in turn, on possible biases in distance determinations, are not well understood. We present ongoing efforts in determining accurate and precise metallicity coefficients of Period-Luminosity-Metallicity relations for classical pulsators at near-infrared wavelengths. For Cepheids, it is crucial to obtain a homogeneous sample of photometric light curves and high-resolution spectra for a wide range of metallicities to empirically determine metallicity coefficient and reconcile differences with the predictions of the theoretical models. For RR Lyrae variables, using their host globular clusters covering a wide range of metallicities, we determined the most precise metallicity coefficient at near-infrared wavelengths, which is in excellent agreement with the predictions of the horizontal branch evolution and stellar pulsation models.

Gadzhi Magomedkamilovich Guseynov

The study of reforms in Dagestan which contributed to the involvement of its peoples in the economic, political and cultural space of the Russian Empire using archival materials, first introduced into scientific circulation seems to be relevant. The problem is to study some previously unknown features of economic development, such as road construction; building bridges, construction of a seaport in Petrovsk on the Caspian Sea, laying of a railway linking Dagestan with Russia and the South Caucasus through the North Caucasus, which had both transport and industrial value. The attention is focused on the cities of Temir-Khan-Shura, Petrovsk, Derbent and Kizlyar, as well as the settlement of Khasavyurt, which played a large role in the socio-economic, political and cultural development of post-reform Dagestan. The aim of the study was to analyze main economic, political and cultural changes in the cities of Dagestan, which were conditioned by their integration into the capitalist path of development of Russia and colonial interests of autocracy. Cities, which made up an insignificant part of the oblast population in the post-reform time, played an increasing role in the socio-economic, political and cultural development of Dagestan. The problems set in the article were solved with the application of general scientific research methods within the framework of historical, comparative and statistical analysis. The results of the research allow for the conclusion that the post-reform period was a turning point in the history of Dagestan in many respects and, above all, that its entry into the Russian Empire determined the further economic progress of the entire North Caucasus. Gradually, the settled for centuries economic structure of the highlanders took the path of transformation under the influence of Russian market relations of the second half of the 19th century.

Tien-Chin Wang, Hsiu-Chin Hsieh, Xuan-Huynh Nguyen et al.

This study applies consistent fuzzy preference relations (CFPR) to evaluate the influential criteria of revitalization strategies (RS) for the hospitality industry in the post-pandemic (COVID-19) era in Taiwan. A real case applies CFPR in order to analyze the relationship between governmental implementation and industrial expectations in Taiwan. The results indicate that “market revitalization”, such as the Taiwanese government’s implementation of various stimulus vouchers and coupons to encourage market consumption and revitalize the overall economy, is considered the most essential/important criteria for RS. This study strengthens the government sector by evaluating the heterogeneity of revitalization strategies best used to formulate the actions to pilot industries as a global contribution to fight the COVID-19 pandemic within a global crisis.

Tuğçe Acar, Derya Topdağ

Identifying the growth in health expenditures and the factors affecting expenditure is a global problem. Accordingly, based on the recent developments in the economic growth literature, the determinants of health expenditures in Organisation for Economic Co-operation and Development (OECD) countries with similar economic development levels were analyzed within the framework of misery index and economic development. This study considers the data set and accessibility of the variables in the analysis, conducted for 34 OECD countries covering 2001–2019. In addition to the real gross domestic product per capita, the economic development indicator of the countries, this study analyzed the misery index, which is the macroeconomic performance indicator, the effects of the urban population, life expectancy at birth, household expenditures, and political stability as a state-institutional factor on health expenditures with the non-additive fixed-effect panel quantile regression method. According to the findings, the effect of the misery index and gross domestic product per capita on health expenditures at each quantile level was positive. In line with the findings, for governments to suppress growth in health expenditures, revising the health system would potentially be more effective than improving macroeconomic conditions.

Juan Manuel Cano Sanchiz

This article proposes some potential contributions of contemporary art to industrial and technological heritage discussions. The paper analyses the relations among art, industrial ruins, technological trash, heritage, and society from an archaeological perspective, although this standpoint is compared to and complemented with those of art and art history. First, the text presents how industrial sites and technological artefacts from the recent past are transformed for/by the artists. In doing so, it offers a preliminary basic typology of art-obsolescence relations illustrated with cases from Europe, Asia and the Americas. Four major kinds of interactions are introduced: the conversion of abandoned industrial buildings into art galleries and museums; the transformation of larger obsolete industrial/technological areas into creative hubs; the intervention of artists in industrial ruins; and the creative recycling of technological waste. Second, the text infers from the examples provided in the typology three possible functions of art regarding heritage: revelation/addition of value; mediation between the public and dark heritages; and recognition in technological and industrial history. In the end, the paper defends the role of art in the making of industrial and technological heritages, as well as in reconnecting them to society.

G. Gall

Barry Dowdeswell, Roopak Sinha, Stephen G. MacDonell

Integrating the design and creation of fault identification and diagnostic capabilities into Model-Driven Development methodologies is one approach to enhancing the resilience of Industrial Cyber-Physical Systems. We present a Fault Diagnostic Engine designed to recognise and diagnose faults in IEC 61499 Function Block Applications. Using diagnostic agents that interact directly with the target application, we demonstrate fault monitoring and analysis techniques and as well as failure scenario intervention. By designing and building fault diagnostic resources during early phases of Model-Driven Development, both iterative testing and long-term fault management capabilities can be created. While applying and refining appropriate model artifacts, we demonstrate that the concurrent development of function blocks alongside fault management capabilities is both feasible and worthwhile.

Seemann Peter, Stofkova Zuzana

Research background: The concept of globalization is interpreted by various authors in terms of its importance or content. Globalization refers to the process of gradually erasing the borders of nation-states, and economic globalization is the culmination of this process. The proof is the interconnectedness of economies around the world, where each economy reacts sensitively to fluctuations and changes in other economies. Purpose of the article: The paper deals with the examination of conflicts in the work environment of selected companies and the subsequent formulation of suggestions and recommendations for improvement. Methods: Nowadays, conflicts in industrial relations and failure to manage conflict situations are one of the biggest problems in companies. A quantitative questionnaire survey was used to find out the current situation in companies in terms of conflicts, specific causes of conflicts, the impact of conflicts on work performance, how employees resolve work conflicts, and their awareness of alternative conflict resolution, with whom employees most often come into conflict. The questionnaire was anonymous; therefore, the specific company names are not given. The numbers of 190 selected companies were contacted, and 93 of them were replied to the questionnaire, which forms a survey sample. Findings & Value added: The conclusion contains recommendations for individual respondent’s businesses to successfully resolve and prevent conflicts in the workplace, and thus strive to build a peaceful working atmosphere without extra costs incurred ineffective conflict resolution. Furthermore, there is an evaluation of the economic aspect and demonstration of the benefits of acquiring and using the skills of alternative conflict resolution in the form of elimination of losses.

S. Wood, L. D. Menezes