Environmental Science & Technology, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 26, 2025
Access to information about chemicals in products and articles is critical for supporting enforcement of chemical regulations, assessing risks from chemicals, allowing informed consumer choices, enabling product circularity. In this work, we identified evaluated available databases (DBs) on the literature using a defined protocol European national market surveillance authorities, nongovernmental agencies, industrial sector groups questionnaires. This first comprehensive review DBs that provide articles. A majority these are heterogeneous terms scope, ontologies, data structures. Among 57 DBs, 49 specific substances only 30 reported their concentration products. addition, 35 included hazard 27 provided safety or chemicals. The analysis highlights lack accessible most categories products/articles jurisdictions. limitations existing were attributed scattered regulatory requirements, unregulated substances, complexity supply chain communication, confidentiality issues. response challenges, opportunities improving transfer structures exploring alternative sources promote article
Language: Английский
Citations
1
Sci, Journal Year: 2024, Volume and Issue: 6(4), P. 60 - 60
Published: Oct. 3, 2024
This study explores the evolution and impact of research on challenges opportunities in implementation artificial intelligence (AI) manufacturing between 2019 August 2024. By addressing growing integration AI technologies sector, seeks to provide a comprehensive view how applications are transforming production processes, improving efficiency, opening new business opportunities. A bibliometric analysis was conducted, examining global scientific production, influential authors, key sources, thematic trends. Data were collected from Scopus, detailed review publications carried out identify knowledge gaps unresolved questions. The results reveal steady increase related manufacturing, with strong focus automation, predictive maintenance, supply chain optimization. also highlights dominance certain institutions authors driving this field research. Despite progress, significant remain, particularly regarding scalability solutions ethical considerations. findings suggest that while holds considerable potential for industry, more interdisciplinary is needed address existing maximize its benefits.
Language: Английский
Citations
6
Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 209, P. 123841 - 123841
Published: Oct. 25, 2024
Language: Английский
Citations
6
Decision Analytics Journal, Journal Year: 2024, Volume and Issue: 12, P. 100492 - 100492
Published: June 8, 2024
This study investigates the ensemble machine learning models to predict mechanical properties of 3D-printed Polylactic Acid (PLA) specimens. We studied effects five process parameters, including build orientation, infill angle, layer thickness, printing speed, and nozzle temperature, on printed parts tensile strength surface roughness. Machine are developed using experimental data collected from 27 Gradient Boosting Regression, Extreme Adaptive Random Forest Extremely Randomized Tree Regression were during modeling stage roughness parts. research demonstrates effectiveness model in providing accurate predictions with root mean square error (RMSE) 1.03, absolute (MAE) 0.82, percentage (MAPE) 2.20%. Similarly, shows better accuracy predicting having RMSE 0.408, MAE 0.31, MAPE 9.28%. Moreover, comparative confirms that techniques more useful than traditional support vector k-nearest neighbor for The results highlight a novel approach identifying complex correlations dataset, establishing foundation improved product design property optimization through adjustment parameters combination.
Language: Английский
Citations
5
Journal of Lifestyle and SDGs Review, Journal Year: 2025, Volume and Issue: 5(2), P. e03652 - e03652
Published: Jan. 7, 2025
Introduction: Technology integration in sales force management has become a vital catalyst for efficiency and competitiveness, especially the dynamic resource-limited contexts of growing markets. This research analyses influence technology adoption on efficacy teams these areas, emphasizing productivity, customer engagement, market growth. Emerging markets have distinct hurdles, including fragmented distribution networks, infrastructure constraints, varied client requirements, making intricate. utilizes primary data obtained from surveys interviews with professionals managers sectors such as agriculture, FMCG, pharmaceuticals, identifying essential technological tools, relationship (CRM) systems, mobile platforms, AI-driven analytics. The results indicate that significantly improves effectiveness by optimizing operations, enhancing decision-making using analytics, cultivating better connections. Nonetheless, obstacles insufficient digital literacy, poor infrastructure, opposition to change often impede successful adoption. study enhances literature connecting theoretical insights actual implementation setting developing Objective: examines how team reach economies. It explores effective identifies barriers adoption, suggests strategies overcoming challenges maximize technology's benefits. Theoretical Framework: impact performance regions, focusing characteristics. Rooted Resource-Based View (RBV) Acceptance Model (TAM), it analyzes tactics. Method: used mixed-methods approach, gather quantitative utilization measures, while semi-structured provide qualitative into problems. Regression analysis elucidates critical linkages, whereas secondary facilitates triangulation, hence providing strong enhance emerging countries. Results Discussion: indicates higher use frequency training sufficiency productivity retention. findings underscore need comprehensive strategies, prioritizing human involvement, leadership excellence, strategic application successfully improve performance. Research Implications: highlights reconsider dependence an independent booster In academics, incorporation real-world case studies courses is essential, companies must emphasize adaptable tactics correspond demands employee advancement. Originality/Value: paper addresses deficiencies comprehending intricate function economies, contesting established assumptions. By integrating scientific pragmatic suggestions, provides novel viewpoint, both academic discourse practical techniques boosting efficacy.
Language: Английский
Citations
0
Supply Chain Analytics, Journal Year: 2025, Volume and Issue: unknown, P. 100116 - 100116
Published: April 1, 2025
Language: Английский
Citations
0
Journal Of Big Data, Journal Year: 2025, Volume and Issue: 12(1)
Published: April 17, 2025
Language: Английский
Citations
0
Chemical Engineering Science, Journal Year: 2024, Volume and Issue: unknown, P. 121147 - 121147
Published: Dec. 1, 2024
Language: Английский
Citations
1
ACM Transactions on Asian and Low-Resource Language Information Processing, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 12, 2024
This day's quickly developing business landscape, supply chains have become more globalized, intricate, and multi-covering, making them crucial for companies to navigate through disruptions unpredictability. The major which are addressed in the chain process lack of transparency visibility network that's leads delay inefficiency process. In order overcome those drawbacks process, this article an enhanced intelligence is developed performs Unveiling Transformative Insights using learning like Cross-Modal Learning (CML) Natural Language Processing (NLP). implementation these techniques carried out software Python. analysis consists certain calculation called analysis, sales revenue Vs SKU various modes cost Lead time vs different supplier location. comparative performed among technique RF regression, SARIMA-LSTM-BP BiLSTM model. parameters involved performance MAE, MSE, RMSE R^2.
Language: Английский
Citations
0
Published: Feb. 22, 2024
Scavarda
Citations
0