CORRELATION PROCESSING OF DIGITAL OPTICAL IMAGES FOR SOLVING CRIMINALISTIC PROBLEMS by V. L. Kozlov, A. S. Vasilchuk

“…It improves presentation and objectivity of tests, and also allows to reduce their carrying out terms. The technique of expert interpretation of correlation analysis results has been offered. …”
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Challenges and Opportunities of Assessing Efficiency of Digital Technology Introduction in Construction Projects by T. V. Vashchenko

“…Today for all countries of the world digitalization became not only possible but also a necessary tool of providing planned innovation growth in economy, a rise in production efficiency, competitiveness of products and services, increase in quality and standard of living of the population. …”
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Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective by Arshi Baig, Azhar Zafar

“…The image analysis by AI and deep-learning algorithms offers insight into the future of screening in diabetes. …”
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The Role of AI in On-Site Construction Robotics: A State-of-the-Art Review Using the Sense–Think–Act Framework by Zhihao Ren, Jung In Kim

“…The study also explores challenges such as environmental unpredictability, specialized task demands, and structural safety concerns. …”
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The Travel Visa as the Ubiquitous Legal Infrastructure of Everyday Global Mobility Arbitrariness by Frédéric Mégret

“…Adopting a global and comparative perspective, this Article seeks to analyze the politics of the visa as the indispensable sesame of international travel but also as the ultimate manifestation of that infrastructure’s arbitrariness. …”
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Review of Social Media Sentiment and Contextual Bandit Models in Stock Market Investment by Miao Ruicheng

“…Traditional strategies rely on historical data, but real-time sentiment provides valuable insights into market fluctuations.This paper examines the application of multi-armed bandit (MAB) algorithms, particularly their contextual variant, in financial decision-making. …”
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DeepBase: A Deep Learning-based Daily Baseflow Dataset across the United States by Parnian Ghaneei, Hamid Moradkhani

“…This study focuses on estimating baseflow using deep learning algorithms that enhance the estimation capabilities in both gauged and ungauged basins. …”
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A Survey of Noninteractive Zero Knowledge Proof System and Its Applications by Huixin Wu, Feng Wang

“…It is widely used in the construction of various types of cryptographic protocols and cryptographic algorithms because of its good privacy, authentication, and lower interactive complexity. …”
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Objective Feedback Recommendation in Multicriteria Large-Group Emergency Decision-Making by D. D. Orshella, N. A. Masruroh, H. M. Arini

“…LGEDM is often clustered into smaller subgroups using algorithms, such as k-means and hierarchical clustering, to manage this complexity and facilitate analysis. …”
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Karne prawo pracy a implementacja dyrektywy platformowej by Joanna Untrschuetz

“…The discussion also considers whether administrative penalties might provide a more robust framework for protecting platform workers’ rights. …”
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Deep Reinforcement Learning-Based Attention Decision Network for Agile Earth Observation Satellite Scheduling by Dongning Liu, Guanghui Zhou

“…Compared with other advanced algorithms, the proposed method obtained a better total profit in the test sets. …”
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Mass Collection of Workers’ Data in Warehouse Facilities: Reflections on Privacy and Workforce Well-being by Thomas De Lombaert, Arpan Rijal, Robert Costrasal, Michele Molè

“…Warehouses with complex monitoring and algorithmic management policies are rapidly expanding across the EU. …”
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Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology. by Fotios Drenos, Enzo Grossi, Massimo Buscema, Steve E Humphries

“…The constructed map suggests that most selected variables were related to CHD in a context dependent manner while only a small number of variables were related to a specific outcome. We also observed that loss of complexity in the network was linked to a future CHD event. …”
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Opportunities of Artificial Intelligence for Authentication and Assurance of Halal Products by Wayan Mahmudy, Diva Kurnianingtyas

“…With the help of high-speed computers, AI algorithms learn patterns in available data and perform assigned tasks with high accuracy and efficiency. …”
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Learning Fourier series with parametrized quantum circuits by Dirk Heimann, Hans Hohenfeld, Gunnar Schönhoff, Elie Mounzer, Frank Kirchner

“…Variational quantum algorithms (VQAs) and their applications in the field of quantum machine learning through parametrized quantum circuits (PQCs) are thought to be one major way of leveraging noisy intermediate-scale quantum computing devices. …”
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Reconstructing 3D Tree Models Using Motion Capture and Particle Flow by Jie Long, Michael D. Jones

“…Branch tips, as particles, are also generated within a bounding space defined by a stack of bounding boxes or a convex hull. …”
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The impacts of weak links on topology discovery process in large-scale wireless multi-hop networks by Liao Wenxing, Shi Xiaofei, Chen Xinying

“…Our previous research has studied the impacts of weak links on reactive routing protocols, which can also be considered as local topology discovery process. …”
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Challenges in Adopting Artificial Intelligence Technologies in Supply Chain Management in Romanian Companies by Radu RUGIUBEI, Valentin STOICA

“…Key challenges identified include high implementation costs, data quality issues, and ethical concerns related to data privacy and algorithmic transparency. The study also emphasizes the critical role of robust data governance and regulatory compliance in successful AI integration. …”
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Target Detection Label Assignment Method Based on Global Information by ZHANG Pei-pei, LU Zhen-yu

“…With the development of deep learning framework, new object detection algorithms have also been proposed, such as first-stage and two-stage detection models, which have improved the detection speed and solved the problem of object detection at different scales, but they have not yet been well solved for overlapping, occlusion and other issues. …”
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Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks by Rocco Restaino

“…Machine-learning-based algorithms designed for this task require an extensive optimization phase of network parameters, which must be performed using unsupervised learning techniques. …”
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