Object Ontologies as a Priori Models for Logical-Probabilistic Machine Learning by D. N. Gavrilin, A.V. Mantsivoda

“…They are an expanded logical analog of object oriented programming models. While forming the core of the bSystem platform, object ontologies allow solving the applied problems of high complexity, in particular, in the field of management. …”
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SHRiMP: accurate mapping of short color-space reads. by Stephen M Rumble, Phil Lacroute, Adrian V Dalca, Marc Fiume, Arend Sidow, Michael Brudno

“…In this paper we present SHRiMP - the SHort Read Mapping Package: a set of algorithms and methods to map short reads to a genome, even in the presence of a large amount of polymorphism. …”
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Effect of Rotational Speed on Performance of Mixed Flow Pump as Turbine by Jun Chen, Tao Dai, Qing Yang

“…The k-ε turbulent model was used to simulate internal flow fields with three rotation speeds by SMPLEC algorithms. Subsequently, theoretical calculations and experiments were carried out to verify the precision of numerical simulation. …”
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Determinants of depressive symptoms in multinational middle-aged and older adults by Can Lu, Shenwei Wan, Zhiyong Liu

“…Evaluating six predictive algorithms, XGBoost demonstrated superior performance in four cohorts (AUC 0.7677–0.8771), while LightGBM excelled in ELSA (AUC 0.9011). …”
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Exploring Purchase Intention in Online Influencer Marketing Campaigns Through an Integrated Model by Shu Liu

“…This study aims to investigate the factors affecting consumers’ purchase intention in social media-based influencer marketing context, while simultaneously revealing the underlying mechanisms through an integrated model. …”
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Positive relationship between education level and risk perception and behavioral response: A machine learning approach. by Zhipeng Wei, Zhichun Zhang, Liping Guo, Wenjie Zhou, Kehu Yang

“…The findings indicate that, while the model's fit for preparatory behavior is 25.71% and its fit for behavioral intention is below 20%, the model effectively identifies key influencing factors. …”
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Teaching deep networks to see shape: Lessons from a simplified visual world. by Christian Jarvers, Heiko Neumann

“…Whereas humans base their judgements of category membership to a large extent on shape, deep networks rely much more strongly on other features such as color and texture. While this problem has been widely documented, the underlying reasons remain unclear. …”
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The State Preparation of Multivariate Normal Distributions using Tree Tensor Network by Hidetaka Manabe, Yuichi Sano

“…The numerical results suggest that our method can dramatically reduce the circuit depth and CNOT count while maintaining fidelity compared to existing approaches.…”
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SINGULAR VALUE VERSUS EIGENVALUE DECOMPOSITION EFFICIENCY IN COMPUTING PRINCIPAL COMPONENTS FOR DIMENSIONALITY REDUCTION OF LARGE DATASETS by Vadim Romanuke

“… Principal component analysis, being one of the best techniques for dimensionality reduction, is implemented by using one of the two high-accuracy algorithms: the singular value decomposition (SVD) and eigenvalue decomposition (EVD). …”
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Overview of Sign Language Translation Based on Natural Language Processing by Wang Hanmo

“…It highlights the critical need for high-quality, large-scale datasets to advance SLT research, while acknowledging challenges like data scarcity, annotation inconsistencies, and ethical concerns. …”
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Research on Functional Modularity and Health Monitoring Design of Home Fitness Equipment by Xinyue Song, Cuiyu Li

“…Multimodal sensors collect real-time physiological data, processed via Kalman filtering and adaptive algorithms to generate personalized fitness recommendations. …”
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Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. …”
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On Training Spiking Neural Networks by Means of a Novel Quantum Inspired Machine Learning Method by Jean Michel Sellier, Alexandre Martini

“…., temporal patterns), training them remains an open and complex problem. In practice, while in theory these networks are computationally as powerful as mainstream artificial neural networks, they have not reached the same accuracy levels yet. …”
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Re-Imagining a 'We' Beyond the Gathering of Reductions by Lila Athanasiadou, Goda Klumbyte, Antoinette Rouvroy

“… In this article Lila Athanasiadou and Goda Klumbytė engage in a conversation with Antoinette Rouvroy to revisit Guattari’s "Three Ecologies" and discuss their dynamics in and for the digital age. While a lot of the discourses on algorithms and digital future invoke catastrophic imaginaries of totalizing control, this conversation works with a propositional format, teasing out affirmative politics by pointing to spaces of potentiality within the environmental, the social and the mental realm. …”
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Integrating AI into neurosurgical decisions: a new Frontier in medicine by Kashif Munir

“…AI does best in the preoperative stage of planning where medical data depicted by MRI and CT scans are processed through machine learning and deep-learning algorithms that help improve diagnostic accuracy and prognosis. …”
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New worlds of logistical labour: Spaces, places, technologies, workers by Tom Barnes, Christopher O’Neill, Lauren Kelly

“…Third, it brings fresh perspectives to debates about continuity versus novelty in contemporary work, addressing issues such as labour displacement, labour augmentation, workplace regimes and algorithmic management. While reiterating the widespread and ongoing influence of despotic workplace practices in logistics globally, the collection challenges assumptions of geographical universalism that characterise much modern debate about logistical labour.…”
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Incremental GA-Based 3D Trajectory Optimization for Powered Parachute Aerial Delivery Systems by Hanafy M. Omar, Ayman Hamdy Kassem

“…This approach significantly reduces the computational time and CPU usage while maintaining cost-effectiveness for 3D trajectory planning. …”
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On Neutrosophy logic for Multiple Correlation Analysis in Fuzzy Uncertain Database by Samar Wazir, M.M. Sufyan Beg, Tanvir Ahmad, Shahab Saquib Sohail

“…While multiple correlation analysis highlights the relationships of interestingness and uninterestingness between items, the OWA operator enhances the results when combined with fuzzy means and probabilistic methods. …”
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Blockchain-Based Decentralized Identity Management System with AI and Merkle Trees by Hoang Viet Anh Le, Quoc Duy Nam Nguyen, Nakano Tadashi, Thi Hong Tran

“…The system’s efficiency in identifying and extracting information from identification cards is enhanced by the integration of artificial intelligence (AI) algorithms. These algorithms decompose the extracted fields into smaller units, facilitating optical character recognition (OCR) and user authentication processes. …”
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Navigating the Digital Maze: A Review of AI Bias, Social Media, and Mental Health in Generation Z by Jane Pei-Chen Chang, Szu-Wei Cheng, Steve Ming-Jang Chang, Kuan-Pin Su

“…The rapid adoption of artificial intelligence (AI) within social media platforms has fundamentally transformed the way Generation Z interacts with and navigates the digital landscape. While AI-driven algorithms enhance user experience through content personalization, they can also reinforce biases that affect the mental health and overall well-being of young individuals. …”
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