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  1. 41

    Last digit tendency: Lucky numbers and psychological rounding in mobile transactions by Hai Wang, Tian Lu, Yingjie Zhang, Yue Wu, Yiheng Sun, Jingran Dong, Wen Huang

    Published 2025-01-01
    “…These findings are key for understanding the last digit tendency and its psychological and emotional mechanisms, which could be used as an indicator of public sentiment or in methods of detecting fraudulent business activity.…”
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    Article
  2. 42

    Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

    Published 2024-01-01
    “…The proposed algorithm combines the artificial hummingbird algorithm exploration phase with the genetic algorithm’s mutation and crossover operators, to optimize the support vector machine’s hyperparameters and categorize users as fraudulent or nonfraudulent. It utilizes 7,270 rows of labeled historical electricity consumption data from the Liberia Electricity Corporation over 15 independent runs. …”
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  3. 43

    Asking an AI for salary negotiation advice is a matter of concern: Controlled experimental perturbation of ChatGPT for protected and non-protected group discrimination on a context... by R Stuart Geiger, Flynn O'Sullivan, Elsie Wang, Jonathan Lo

    Published 2025-01-01
    “…We also tested for fictional and fraudulent universities and found wildly inconsistent results across different cases and model versions. …”
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  4. 44

    Penerapan Library AR.js pada Aplikasi e-Label Batik untuk Mendukung Kejelasan dan Kecepatan Tampilnya Informasi Keaslian Batik by Paminto Agung Christianto, Restyandito Restyandito, Eko Budi Susanto, Moh. Reza Maulana

    Published 2019-05-01
    “…The ignorance of the community in distinguishing between original batik and textile products with batik motifs, has caused the community to be vulnerable to fraudulent attempts from the sellers of batik and led to the tendency to buy batik-patterned textile products at a lower price. …”
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    Article
  5. 45

    A universal DNA microarray for rapid fish species authentication by Patrizia Bade, Sebastian Stix, Kristina Kappel, Jan Fritsche, Ilka Haase, Andrew Torda, Nils Wax, Markus Fischer, Dirk Brandis, Ute Schröder

    Published 2025-06-01
    “…This new screening method shows potential to authenticate specimens from all fish species and by this could play an important role in fighting fraudulent practices and adulteration in the seafood sector.…”
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    Article
  6. 46

    Providing an Anti-Marketing Model to Prevent Criminal Behaviors in Online and Digital Businesses by Ghasem Zarei, Younes Nikkhah

    Published 2024-06-01
    “…Certain profit-driven individuals exploit this expansive environment for fraudulent and unethical business practices. To curb criminal activities in the marketing sector, this study aims to introduce an anti-marketing model tailored for online and digital businesses and provide practical solutions. …”
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    Article
  7. 47

    Intersectional Analysis of Urban Land Corruption in Harare, Zimbabwe by Manase Kudzai, Praise Karuma, Tanaka Mutume, Primrose Hove

    Published 2025-01-01
    “…Urban land corruption manifests through bribery, fraudulent allocations, and exploitation, disproportionately affecting vulnerable groups, especially women. …”
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    Article
  8. 48

    Adversarial measurements for convolutional neural network-based energy theft detection model in smart grid by Santosh Nirmal, Pramod Patil, Sagar Shinde

    Published 2025-03-01
    “…Its goal is to reduce electricity costs by deceiving the model into recognizing a fraudulent customer as legitimate.In this paper, four different experiments are conducted in which we check the performance of Convolutional Neural Network and adaboost (CNN-Adaboost) ETD system. …”
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    Article
  9. 49

    A Small Tamper-Resistant Anti-Recycling IC Sensor With a Reused I/O Interface and DC Signalling by Alexandros Dimopoulos, Mihai Sima, Stephen W. Neville

    Published 2024-01-01
    “…Combining this sensor with a random sample-based testing strategy allows for low-cost and time efficient detection of fraudulently recycled batches of ICs. Through simulation-based validation using process-accurate models of a 65 nm technology we show that employing a random sample size as small as 130 is sufficient for identifying such batches with a statistical significance level of 0.01.…”
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