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Machine heuristic in algorithm aversion: Perceived creativity and effort of output created by or with artificial intelligence
Published 2025-08-01“…Through two pre-registered experiments, we investigate how individuals evaluate creative content when it is labeled as created by AI, humans, or human-AI collaboration. While previous research has established algorithm aversion across various domains, our findings reveal nuanced patterns in creative contexts. …”
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Similarity measure for intuitionistic fuzzy sets and its applications in pattern recognition and multimodal medical image fusion
Published 2025-07-01“…Abstract Intuitionistic fuzzy similarity measures (IFSMs) play a significant role in applications involving complex decision-making, pattern recognition, and image processing. Several researchers have introduced different methods of IFSMs, yet these IFSMs fail to provide rational decisions. …”
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Artificial intelligence in automatic image segmentation system for exploring recurrence patterns in small cell carcinoma of the lung
Published 2025-05-01“…Utilizing imaging recurrence data, this study applies a recursive feature elimination algorithm to model and predict patient prognoses, aiming to enhance clinical guidance and prediction accuracy.Materials and MethodsThis research analyzed data from SCLC patients who received curative radiotherapy from January 1, 2010, to December 30, 2021, and had comprehensive follow-up records including pre- and post-treatment imaging. …”
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Evaluation of GLOCK 9 mm Firing Pin Aperture Shear Mark Individuality Based on 3,156 Different Pistols (Manufactured Over a 30 Year Period in Two Countries) Using Additional Patter...
Published 2024-07-01“…A total of 3156 GLOCK firearms were used to generate a sample of the same size. Our research hypothesis was that no cartridge cases fired from different 9 mm semiautomatic GLOCK pistols would be mistaken as coming from the same gun (a false match). …”
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Patterns of changing surface climate variability from the Last Glacial Maximum to present in transient model simulations
Published 2025-03-01“…A reanalysis of the LGM exhibits similar global mean variability to most of the ensemble, but spatial patterns vary. However, paleoclimate data assimilation combines model and proxy data information using a Kalman-filter-based algorithm. …”
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Deep Learning-Based Dzongkha Handwritten Digit Classification
Published 2024-03-01“…With the advancement in deep learning technology, many machine learning algorithms were developed to tackle the problem of pattern recognition. …”
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Hypertension Detection Using Passive-Aggressive Algorithm With The PA-I And PA-II Methods
Published 2023-03-01“…In this paper, the researchers used the Passive-Aggressive algorithm and the PA-I and PA-II methods to make a model for the diagnosis of hypertension. …”
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Weaponizing the Workplace: How Algorithmic Management Shaped Amazon’s Antiunion Campaign in Bessemer, Alabama
Published 2025-02-01“…The findings reveal that employers can weaponize elements or effects of algorithmic management against unions via repurposing devices that algorithmically control workers, engaging in “algorithmic slack-cutting,” and exploiting patterns of social media activity encouraged by algorithmic management. …”
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IoT-enhanced music therapy: Utilizing genetic algorithms for personalized violin instruction and mental health adjustment
Published 2025-08-01“…On the other hand, a genetic algorithm is an intelligent tool that reveals patterns in this information and identifies hidden relationships between instructional variables and the student’s mental health. …”
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Toward Sustainable Campus Energy Management: A Comprehensive Review of Energy Management, Predictive Algorithms, and Recommendations
Published 2025-06-01“…The paper states that to facilitate energy efficiency and manage consumption, it is important to extract patterns of energy consumption by data modelling and predictive algorithms to achieve the ultimate goal of consumption recommending and advising. …”
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A Comparative Study of Machine Learning Algorithms for Intrusion Detection Systems using the NSL-KDD Dataset
Published 2025-07-01“…In today’s digital era, cyberattacks are becoming increasingly complex, rendering traditional rule-based Intrusion Detection Systems (IDS) often ineffective in recognizing new attack patterns. The primary objective of this study is to design and implement a machine learning model for detecting network intrusions efficiently while minimizing latency, through a comparative analysis of several algorithms: Decision Tree, Random Forest, Support Vector Machine (SVM), and Boosting. …”
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Novel metrics and LSH algorithms for unsupervised, real-time anomaly detection in multi-aspect data streams
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