Navigating ethical minefields: a multi-stakeholder approach to assessing interconnected risks in generative AI using grey DEMATEL by Sridhar Jonnala, Sridhar Jonnala, Nisha Mary Thomas, Nisha Mary Thomas, Sarthak Mishra

“…The rapid advancement of generative artificial intelligence (AI) technologies has introduced unprecedented capabilities in content creation and human-AI interaction, while simultaneously raising significant ethical concerns. …”
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Combining Terrestrial Laser Scanning and Drone-Based Photogrammetry towards Improving Volume Calculations in Construction Projects by Sharafaddin Th. Muhammed, Fanar M. Abed

“…In contrast, Stonex X300 TLS device was used for laser data collection, while 3D Re-constructor software was used for data processing and analysis. …”
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Integrating Artificial Intelligence into Service Innovation, Business Development, and Legal Compliance: Insights from the Hainan Free Trade Port Era by Yincheng Li, Shumin Wang, Muhammad Bilawal Khaskheli

“…Hypothesis 3 state that HFTP enterprises comply with these laws while systemically assuring, in theory, and practice, the legal risks of artificial intelligence and its implications for legal regulation, which is a significant aspect of research, addressing legal risks related to data privacy, security, and algorithmic bias with many strategies being proposed. …”
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Ethics dumping in artificial intelligence by Jean-Christophe Bélisle-Pipon, Gavin Victor

“…Artificial Intelligence (AI) systems encode not just statistical models and complex algorithms designed to process and analyze data, but also significant normative baggage. …”
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Lightweight Stereo Matching for Real-Time Applications With 2D Cost Volume Aggregation by Thai la, Linh Tao, Dai Watanabe

“…Despite the significant advancements in learning-based stereo matching algorithms, a significant challenge remains: the high computational cost and memory demands of 3D convolutions, which hinder real-time deployment on resource-constrained platforms like edge devices. …”
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Evaluation and Classification of Accident-Inducing and Risk Propagation in Airport Apron Networks by Ruxin Wang, Hong Yan, Rui Kang, Xiaolei Feng

“…Results show that Tier 1 nodes (personnel and equipment) exhibit the highest accident-inducing potential, while Tier 2 nodes (management) play significant roles in risk propagation. …”
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A Comprehensive Review of Blockchain and Machine Learning Integration for Peer-to-Peer Energy Trading in Smart Grids by Sameen Fatima, Muhammad Junaid Arshad

“…A new architecture is proposed, integrating blockchain with ML algorithms to create resilient, secure, and efficient energy trading markets. …”
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Factors affecting frequency discrimination of vibrotactile stimuli: implications for cortical encoding. by Justin A Harris, Ehsan Arabzadeh, Adrienne L Fairhall, Claire Benito, Mathew E Diamond

“…<h4>Background</h4>Measuring perceptual judgments about stimuli while manipulating their physical characteristics can uncover the neural algorithms underlying sensory processing. …”
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Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression by Saad Alanazi, Rayan Alanazi

“…Also included in this plan is federated learning, allowing shared instruction across many medical institutions while protecting patient privacy and security.…”
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Generative Design-Driven Optimization for Effective Concrete Structural Systems by Hossam Wefki, Mona Salah, Emad Elbeltagi, Majed Alinizzi

“…This research introduces a parametric algorithmic model for the automated optimization of RC buildings with solid slab systems. …”
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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…We present a new model within the well-established field of multi-interface networks, designed to reduce battery consumption while maximizing network performance. Additionally, we examine the computational complexity of this model and propose two solution algorithms grounded in fixed-parameter tractability theory for specific network classes.…”
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Structure of associative heterarchical memory by R. V. Dushkin, V. A. Lelekova, V. Y. Stepankov, S. Fadeeva

“…Natural language recognition algorithms were used in conjunction with various artificial intelligence methods.Results. …”
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Simultaneous Classification of Objects with Unknown Rejection (SCOUR) Using Infra-Red Sensor Imagery by Adam Cuellar, Daniel Brignac, Abhijit Mahalanobis, Wasfy Mikhael

“…Towards this end, we train and test our method on a public domain medium-wave infra-red (MWIR) dataset provided by the US Army for the development of automatic target recognition (ATR) algorithms. The results of this experiment show that the proposed method outperforms other state-of-the-art methods in rejecting the unknown target types while accurately classifying the known ones.…”
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Computational and experimental study of thermal behavior in the oral cavity for biosensing applications by Yuanzhe Zhao, Jeroen H.M. Bergmann

“…Results reveal that anterior teeth exhibit greater thermal sensitivity and slower temperature recovery following cold exposure, while posterior regions maintain higher and more stable temperatures. …”
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AI-Driven Optimization of Breakwater Design: Predicting Wave Reflection and Structural Dimensions by Mohammed Loukili, Soufiane El Moumni, Kamila Kotrasova

“…Results demonstrated that Random Forest and Decision Tree balanced accuracy with computational efficiency, while the Gaussian Process closely matched analytical results but demanded higher computational resources. …”
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Evaluation of a Polarimetric Contrast Enhancement Technique as Preprocessing Step for Vessel Detection in SAR Images: Comparison of Frequency Bands and Polarimetric Modes by Alejandro Mestre-Quereda, Juan M. Lopez-Sanchez

“…A potential solution to this issue is to develop methodologies that suppress backscattered signals from the sea while preserving the radar returns from ships. In this work, we analyse a contrast enhancement method which is designed to suppress unwanted sea clutter while preserving signals from potential ships. …”
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Financing Mechanisms and Preferences of Technology-Driven Small- and Medium-Sized Enterprises in the Digitalization Context by Jing Hu, Lianming Huang, Weifu Li, Hongyi Xu

“…Additionally, six machine learning (ML) algorithms were employed to predict financing preferences. …”
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A redundant weight removal method inspired by specific immunotherapy for boosting transfer learning security by Qing Huang, Hongli Deng, Junxiang Wang, Tao Yang, Bochuan Zheng

“…Currently, redundant weights are removed mainly through pruning algorithms designed by correlating student data with teacher model nodes. …”
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ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution by Ahmed A. Al-Saedi, Veselka Boeva

“…Extensive experiments performed on time series electrocardiogram (ECG) databases (MITDB, SVDB, and INCARTDB) indicate that ADF-SL significantly outperforms the three existing algorithms that served as baselines. Compared to these baseline methods, ADF-SL accelerates model training on clients by up to 22.7%, 10.4%, and 5.8% compared to Vanilla SL, SplitFed, and FairFed, respectively, while maintaining model convergence and accuracy. …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…This enables the reduction of computational resources during detection processing while maintaining detection accuracy, even when using fewer features and lightweight machine learning algorithms. …”
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