Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Characterizing Crop Distribution and the Impact on Forest Conservation in Central Africa by Mohammed S. Ozigis, Serge Wich, Mahsa Abdolshahnejad, Adrià Descals, Zoltan Szantoi, Douglas Sheil, Erik Meijaard

“…While the role of expanding agriculture in deforestation and the loss of other natural ecosystems is well known, the specific drivers in the context of small- and large-scale agriculture remain poorly understood. …”
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Assessing the risk of pedestrian crossing behavior on suburban roads using structural equation model by Shahrbanoo Kavianpour, Farshidreza Haghighi, Abbas Sheykhfard, Subasish Das, Grigorios Fountas, Mohammad Mehdi Oshanreh

“…While pedestrian crashes on suburban roads have received more attention over recent years, the role of pedestrian crossing risk in areas adjacent to pedestrian crossing facilities, such as pedestrian overpasses, has been neglected. …”
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Satellite Remote Sensing Techniques and Limitations for Identifying Bare Soil by Beth Delaney, Kevin Tansey, Mick Whelan

“…From 191 papers, this review synthesises advancements in BS detection methodologies, such as threshold masking and classification algorithms, while highlighting persistent challenges such as spectral confusion and inconsistent validation practices. …”
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Optimization of Pertamax Fuel Distribution Using Clarke-Wright Savings, Nearest Neighbour, and Goal Programming (Case Study: Malang City) by Tharisa Melani, Sobri Abusini, Marjono Marjono

“…The CWS is applied to group routes efficiently by reducing travel distances, while NN determined the delivery sequence within each route. …”
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Machine Learning-Based Seismic Damage Assessment of a Bridge Portfolio in Cohesive Soil by Burak Ozturk, Ahmed Fouad Hussein, Mohamed Hesham El Naggar

“…This study investigates the application of machine learning (ML) algorithms for seismic damage classification of bridges supported by helical pile foundations in cohesive soils. …”
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The evolving role of programming and LLMs in the development of self-driving laboratories by John R. Kitchin

“…We discuss strategies to mitigate these risks while leveraging LLMs for enhanced efficiency in self-driving laboratories. …”
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Deep Space Insights: Machine Learning Revolutionizing Astrophysical Discoveries by Dutta Samya, Paul Prithwineel

“…Autoencoders and RNNs are used for anomaly detection and time-series analysis, respectively, while GANs enhance the resolution of cosmological simulations. …”
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A Novel Approach for Rapid Detection of Forest Degradation and Diseases Through Anomaly Analysis of Sentinel-2 Spectral Data by Sofiia Drozd, Nataliia Kussul, Hanna Yailymova

“…The aim of this study was to develop an accessible and reliable technique that could match the performance of more complex algorithms while using minimal computational resources. …”
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A Knee Rehabilitation Exercises Dataset for Postural Assessment using Wearable Devices by Panagiotis Kasnesis, Theodora Plavoukou, Amalia Contiero Syropoulou, Lazaros Toumanidis, George Georgoudis

“…The goal of KneE-PAD is to be used for training machine learning algorithms for automatic postural assessment using only wearable sensors (sEMG and IMU), which could become a vital part of a virtual coach to supervise the patients and provide useful feedback to them while executing their prescribed rehabilitation exercises remotely.…”
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Artificial intelligence in academic research: Benefits, challenges, and ethical dimensions in doctoral studies by Zaki EL HANI, Jaouad KARROUM, Abdelmajid ELOUADI, Aniss MOUMEN

“…However, this transformation is accompanied by challenges, including ethical concerns such as algorithmic bias, risks to data privacy, and over-reliance on automation, which may erode critical thinking and human judgment. …”
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AI IN CYBER DEFENSE: PRIVACY RISKS, PUBLIC TRUST, AND POLICY CHALLENGES by Abdullah Azizi, Mohammad Qias Mohammadi, Abdul Wahid Samadzai

“…The results reveal that while AI-based systems improve threat detection and response times, they also raise significant concerns about data privacy, surveillance, and the potential for algorithmic bias. …”
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Balancing tech and humanity by Linda Cottone

“…As threats like cyber insecurity and AI-based decision-making rise, the role of both state and non-state actors becomes essential in safeguarding rights while managing migration. While technology can enhance efficiency, as shown in Lebanon's response to the Tripoli bomb attack, it must adhere to international legal standards, especially privacy protections in the ICCPR and UDHR. …”
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Generation of Genuine Multipartite Entangled States via Indistinguishability of Identical Particles by Kobra Mahdavipour, Farzam Nosrati, Stefania Sciara, Roberto Morandotti, Rosario Lo Franco

“…The presented theoretical approach, while already implementable with current linear optics architectures, has the potential to bring clear advantages over existing technologies, such as in quantum computing search algorithms and in the design of new experiments in quantum optics or other platforms.…”
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The Double-Edged Sword of Social Media in the European Union Crisis Management: A Literature Review by Tănase Tasențe

“…Key themes include the paradoxical nature of social media as a “double-edged sword”: enabling real-time updates and grassroots mobilization while also fueling polarized discourse and disinformation. …”
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Immune-Mediated Adverse Events Associated with Ipilimumab CTLA-4 Blockade Therapy: The Underlying Mechanisms and Clinical Management by Ahmad Tarhini

“…The skin and gastrointestinal tract are most frequently affected, while hepatic, endocrine, and neurologic events are less common. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…Time series forecasting often faces challenges in producing reliable predictions due to inherent uncertainty in dynamic systems. While point predictions are commonly used, they may not adequately capture this uncertainty, especially in financial systems where forecasting accuracy directly impacts decision-making. …”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…SVM achieved the highest predictive accuracy (R2 = 0.98), while KNN and ANN showed lower performance (R2 = 0.69 and 0.71, respectively). …”
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DREFNet: Deep Residual Enhanced Feature GAN for VVC Compressed Video Quality Improvement by Tanni Das, Kiho Choi

“…Different compression tools in modern video codecs are vital for minimizing artifacts that arise during the encoding and decoding processes. While the advanced algorithms used by these modern codecs can effectively decrease file sizes and enhance compression efficiency, they frequently find it challenging to eliminate artifacts entirely. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Leveraging a comprehensive dataset from KAGGLE containing 35,126 retinal fundus images representing one healthy (normal) stage and four DR stages, our proposed model demonstrates superior accuracy compared to existing deep learning algorithms. Data augmentation techniques address class imbalance, while SAEs facilitate accurate classification through layer-wise unsupervised pre-training and supervised fine-tuning. …”
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