CHILES. IX. Observational and Simulated H i Content and Star Formation of Blue Galaxies in Different Cosmic Web Environments by Nicholas M. Luber, Farhanul Hasan, J. H. van Gorkom, D. J. Pisano, Joseph N. Burchett, Julia Blue Bird, Hansung B. Gim, Kelley M. Hess, Lucas R. Hunt, David C. Koo, Sushma Kurapati, Danielle Lucero, Nir Mandelker, Martin Meyer, Emmanuel Momjian, Daisuke Nagai, Joel R. Primack, Min S. Yun

“…CHILES observes an increase in H i fraction at z  = 0.5 → 0 in the voids, while TNG predicts an increase in this time in all environments. …”
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Integrating Visual Cryptography for Efficient and Secure Image Sharing on Social Networks by Lijing Ren, Denghui Zhang

“…This prevalence poses challenges for secure image forwarding, as it is susceptible to privacy leaks when sharing data. While standard encryption algorithms can safeguard the privacy of textual data, image data entail larger volumes and significant redundancy. …”
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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…Vehicle detection algorithms constitute a fundamental pillar in intelligent driving systems and smart transportation infrastructure. …”
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Efficient scheduling of multiple software projects for work continuity and identical completion time by Abdulrahman Aldhubaiban, Ali AlMatouq

“…Our continuous variable model was solved in the cloud for optimality for large instances of upto 40 different software projects and 100 employees in less than 21 min using nonlinear programming algorithms. • A continuous variable nonlinear model is developed to efficiently schedule large-scale software projects. • The model enables scheduling for multiple projects with identical completion times while ensuring work continuity. • A cloud-based program architecture is designed to facilitate the testing of multiple solvers online.…”
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Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…As machine learning algorithms become increasingly accessible, a growing number of organizations and researchers are using these technologies to automate the process of exoplanet detection. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…The approach integrates quantum computing principles into classical control frameworks, creating a hybrid methodology that leverages quantum-inspired optimization while maintaining implementation feasibility on conventional hardware. …”
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The Impact of AI Software on Financial Transactions by Li Boyang

“…However, the integration of AI also raises significant concerns, including data security risks, algorithmic opacity, and increased market volatility, as evidenced by incidents like the 2010 “Flash Crash” and recent AI-driven stock fluctuations. …”
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CHIP: Clustering Hotspots in Layout Using Integer Programming by Rohit Reddy Takkala, Chris Chu

“…With several generic clustering algorithms at our disposal, hotspots can be clustered based on the distance metric defined while satisfying some tolerance conditions. …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…SBSP systems suffer from some serious challenges, such as beam angle error deviations, power transmission efficiency reduction, atmospheric disturbance, and space debris impact. While usual machine learning algorithms may predict the production of energy, they cannot respond sufficiently in real time to alter according to dynamic environmental conditions. …”
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基于IMU信号的人工智能上肢多关节运动状态识别系统构建——卒中后人工智能运动功能评估与检测系统建设前导研究 Construction of an Artificial Intelligence Upper Limb Multi-Joint Motion State Recognition System Based on IMU Signals—A Pre... by 程相鑫1，张烁1，杜松骏1，刘子阳1，周宏宇2，3，贾伟丽2，3，李子孝2，3，刘涛1 (CHENG Xiangxin1, ZHANG Shuo1, DU Songjun1, LIU Ziyang1, ZHOU Hongyu2,3, JIA Weili2,3, LI Zixiao2,3, LIU Tao1 )

“…., independently training single-joint classifiers and then merging the outputs) was constructed. At the algorithm level, traditional machine learning methods (time-frequency domain features+random forest) were compared with deep learning algorithms (long short-term memory-based end-to-end learning). …”
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A quantum random access memory (QRAM) using a polynomial encoding of binary strings by Priyanka Mukhopadhyay

“…Abstract Quantum algorithms claim significant speedup over their classical counterparts for solving many problems. …”
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Estimation of Ground-Level NO₂ Concentrations Over Megacities Using Sentinel-5P and Machine Learning Models: A Case Study of Istanbul by N. Yagmur Aydin, I. Aydin

“…Integration of ground and satellite data using machine learning (ML) algorithms enables more accurate regional analysis. …”
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Range and angle estimation with spiking neural resonators for FMCW radar by Nico Reeb, Javier Lopez-Randulfe, Robin Dietrich, Alois C Knoll

“…This research presents a novel spiking neuron model for signal processing of frequency-modulated continuous wave (FMCW) radars that outperforms the state-of-the-art spectrum analysis algorithms in latency and data bandwidth. These spiking neural resonators are based on the resonate-and-fire neuron model and optimized to dynamically process raw radar data while simultaneously emitting an output in the form of spikes. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. …”
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Review of eXplainable artificial intelligence for cybersecurity systems by Stéphane Reynaud, Ana Roxin

“…While most approaches investigated come from numeric AI, we conclude on the need for hybrid AI systems, combining the advantages of both AI sub-fields while maximising the protection provided against cyberattacks.…”
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Improving the Integrity of a Voting Process with Biometric Authentication and Data Encryption by Walter M. Molina, Lino R. Mac Kay, Daniel Subauste

“…Throughout the years, the voting process has under-gone a digital transformation, aiming to achieve greater control and optimize time while ensuring the integrity of each vote. While previous solutions have introduced changes in architecture and security processes, there hasn't been a defined secure model for voting. …”
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Statistical Prediction of Summer Rainfall and Vegetation in the Ethiopian Highlands by Mark R. Jury

“…After step-wise multivariate regression, the leading predictors are: surface temperature across Europe (cold-favourable), 850 mb zonal winds over the tropical Atlantic (easterly-favourable), and surface temperature in the tropical Indian Ocean (cold-favourable). Predictive algorithms for early and late rainfall exhibit a consistent r2 fit of ~0.50, while those for vegetation reach ~0.65 in late summer, indicating that fluctuations in food resources could be forewarned.…”
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A practical guide to optimizing industrial thermal spraying through comparative multi-objective optimization by Wolfgang Rannetbauer, Simon Hubmer, Carina Hambrock, Ronny Ramlau

“…Quality standards vary depending on the specific application, while cost-effectiveness remains a constant priority. …”
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Iteration Overlap and Dual-Sided LSOVA for Efficient Parallel Turbo Decoding Architectures by Stefan Weithoffer, Charbel Abdel Nour

“…At the algorithmic level, we introduce Dual-Sided Local-SOVA (DS-LSOVA), an enhanced variant of Local-SOVA that significantly lowers the complexity of extrinsic information computation while preserving decoding accuracy. …”
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FrameBoost: Advanced Video Analytics With Inference Trigger Frame Selection via Tracking Error Estimation by Jin Mo Yang, Sunwook Hwang, Jeongjun Park, Saewoong Bahk

“…Beyond selecting critical frames for system accuracy, a major requirement for ITF selection algorithms is efficiency. They must be able to extract informative frames while imposing minimal computational overhead on the analytics pipeline. …”
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