This Person Does Exist by Matthias Schäfer

“…Finally, I argue that this artistic practice is a legitimate way of opening up a larger public discourse, although artists working with human data must be aware of ethical issues and responsibilities regarding privacy and consent. …”
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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. …”
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Generation of Vessel Track Characteristics Using a Conditional Generative Adversarial Network (CGAN) by Jessica N.A Campbell, Martha Dais Ferreira, Anthony W. Isenor

“…Machine learning (ML) models often require large volumes of data to learn a given task. However, access and existence of training data can be difficult to acquire due to privacy laws and availability. …”
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The impact of artificial intelligence on research efficiency by Mitra Madanchian, Hamed Taherdoost

“…However, challenges such as bias in algorithms, concerns about data privacy, and deficiencies in the infrastructure impede wide-scale application. …”
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Artificial Intelligence in Thoracic Surgery: Transforming Diagnostics, Treatment, and Patient Outcomes by Sara Lopes, Miguel Mascarenhas, João Fonseca, Maria Gabriela O. Fernandes, Adelino F. Leite-Moreira

“…AI-based tools can be employed in medicine, and by extracting useful information from big data, they allow for the early diagnosis of diseases like lung cancer. …”
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Acceptability of and Willingness to Use Virtual Reality Exergames for Weight Loss Among Young Adults With Overweight or Obesity in China: Qualitative Study by Yanya Chen, Bingsheng Guan, Yaqi Zhang, Suen Chow Lee, Jia-yu Liu, Sicun Li, Ming Liu, Xiaoshen Zhang, Wai-kit Ming

“…ResultsFour main themes and 8 subthemes emerged from the data. The main themes included perception of previous weight loss measures (regarded exercise and diet as the main measures for weight loss and difficulties in holding on to the weight loss methods), acceptability of virtual reality exergames (increasing opportunities for exercise, a powerful means for propelling doing exercise, positive impact on psychological well-being, and more appealing to office workers than students), willingness to use virtual reality exergames, and concerns (weight loss effect and other concerns). …”
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Securing the IoT System of Smart City against Cyber Threats Using Deep Learning by Tanzila Saba, Amjad Rehman Khan, Tariq Sadad, Seng-phil Hong

“…IoT enhances productivity and efficacy intelligently using remote management, but the risk of security and privacy increases. …”
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Trust-Based Consensus and ABAC for Blockchain Using Deep Learning to Secure Internet of Things by Arunkumar Muniswamy, R. Rathi

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A Novel Deep Learning Model for Human Skeleton Estimation Using FMCW Radar by Parma Hadi Rantelinggi, Xintong Shi, Mondher Bouazizi, Tomoaki Ohtsuki

“…Human skeleton estimation using Frequency-Modulated Continuous Wave (FMCW) radar is a promising approach for privacy-preserving motion analysis. …”
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Medical Photography in Dermatology: Quality and Safety in the Referral Process to Secondary Healthcare by Eduarda Castro Almeida, João Rocha-Neves, Ana Filipa Pedrosa, José Paulo Andrade

“…<b>Background:</b> Medical photography is widely used in dermatology referrals to secondary healthcare, yet concerns exist regarding image quality and data security. …”
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Edge-Assisted Label-Flipping Attack Detection in Federated Learning by Nourah S. AlOtaibi, Muhamad Felemban, Sajjad Mahmood

“…Federated Learning (FL) has transformed machine learning by facilitating decentralized, privacy-focused data processing. Despite its advantages, FL remains vulnerable to data poisoning attacks, particularly Label-Flipping Attacks (LFA). …”
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Adapting Classification Neural Network Architectures for Medical Image Segmentation Using Explainable AI by Arturs Nikulins, Edgars Edelmers, Kaspars Sudars, Inese Polaka

“…Despite their effectiveness, these networks face significant challenges, including the need for extensive annotated patient data, time-consuming manual segmentation processes and restricted data access due to privacy concerns. …”
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Depth-Based Intervention Detection in the Neonatal Intensive Care Unit Using Vision Transformers by Zein Hajj-Ali, Yasmina Souley Dosso, Kim Greenwood, JoAnn Harrold, James R. Green

“…An intervention detection method based solely on depth data was developed using a vision transformer (ViT) model utilizing real-world data from patients in the NICU. …”
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Adaptive Task Scheduling in Fog Computing Using Federated DQN and K-Means Clustering by Prashanth Choppara, S. Sudheer Mangalampalli

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Preliminary Electroencephalography-Based Assessment of Anxiety Using Machine Learning: A Pilot Study by Katarzyna Mróz, Kamil Jonak

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Securing and optimizing optical transmission in quantum wells using OAM and advanced modulation techniques by Muhammad Ahmad, Zhiping Wang, Ming Fang, Zhixiang Huang, Guoda Xie

“…However, current optical transmission methods encounter challenges in efficiently transmitting data due to limited OAM mode generation, reduced transmission privacy, and high atmospheric turbulence. …”
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Exploring assessment methods used by Grade Four English First Additional Language Teachers by Kofi Nkonkonya Mpuangnan, Gladys Phumzile Mngomezulu, Samantha Govender

“…The researchers opted for a thematic analysis approach, allowing for a thorough examination of the data while respecting the privacy and confidentiality of the participants. …”
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A New Ultralightweight RFID Mutual Authentication Protocol: SASI Using Recursive Hash by Umar Mujahid, M. Najam-ul-Islam, Atif Raza Jafri, Qurat-ul-Ain, M. Ali Shami

“…Nonline of sight capability makes RFID systems much better choice than its contended systems (such as barcode, magnetic tape, etc.). Since the RFID uses wireless channel for communication with its associated devices, there should be some optimal encryption methods to secure the communicating data from adversaries. …”
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Decentralized federated learning using validation loss for model sharing in crop disease classification by Denis Mamba Kabala, Adel Hafiane, Laurent Bobelin, Raphaël Canals

“…Several AI methods have been employed for this purpose, but despite achieving good results, many challenges remain, such as protecting farmers’ data, using machine learning on edge devices, and employing collaborative learning. …”
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How to Write Effective Prompts for Screening Biomedical Literature Using Large Language Models by Maria Teresa Colangelo, Stefano Guizzardi, Marco Meleti, Elena Calciolari, Carlo Galli

“…Finally, we explore emerging trends, including multi-stage screening pipelines and fine-tuning, while noting ethical considerations related to data privacy and transparency. By applying systematic prompt engineering and rigorous evaluation, researchers can optimize LLM-based screening processes, allowing for faster and more comprehensive evidence synthesis across biomedical disciplines.…”
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