Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…For data analysis, a genetic algorithm, particle accumulation optimization, and MATLAB software were employed. …”
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Random Natural Gradient by Ioannis Kolotouros, Petros Wallden

“…In this work we propose two methods that reduce the resources/state preparations required for QNG, while keeping the advantages and performance of the QNG-based optimization. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Quantitative radiomic features of white matter, gray matter, and cerebrospinal fluid were extracted from whole-brain structural MRI images. Feature reduction was performed on the training set data to construct radiomics signatures. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…A ratio greater than 1.1 indicates a good probability of lower 3rd molar eruption, while a below 0.8 indicates no eruption. The algorithm development process demonstrated the effectiveness of our hybrid approach in dental health analytics. …”
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Medical care costs of cancer in the last year of life using national health insurance data in Korea. by Mihai Park, Inmyung Song

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MRD: A Linear-Complexity Encoder for Real-Time Vehicle Detection by Kaijie Li, Xiaoci Huang

“…To address these limitations, this study introduces Mamba RT-DETR (MRD), an optimized architecture featuring three principal innovations: (1) We devise an efficient vehicle detection Mamba (EVDMamba) network that strategically integrates a linear-complexity state space model (SSM) to substantially mitigate computational overhead while preserving feature extraction efficacy. (2) To counteract the constrained receptive fields and suboptimal spatial localization associated with conventional SSM sequence modeling, we implement a multi-branch collaborative learning framework that synergistically optimizes channel dimension processing, thereby augmenting the model’s capacity to capture critical spatial dependencies. (3) Comprehensive evaluations on the BDD100K benchmark demonstrate that MRD architecture achieves a 3.1% enhancement in mean average precision (mAP) relative to state-of-the-art RT-DETR variants, while concurrently reducing parameter count by 55.7%—a dual optimization of accuracy and efficiency.…”
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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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CHIP: Clustering Hotspots in Layout Using Integer Programming by Rohit Reddy Takkala, Chris Chu

“…However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. …”
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Engineering and Technological Advancements in Repetitive Transcranial Magnetic Stimulation (rTMS): A Five-Year Review by Abigail Tubbs, Enrique Alvarez Vazquez

“…A structured review of peer-reviewed studies from 2019 to 2024 focused on technological and clinical advancements in rTMS, including AI-driven personalized treatments, portable devices, and integrated BCIs. AI algorithms have optimized patient-specific protocols, while portable devices have expanded access. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…These advancements also make education more inclusive, helping to bridge accessibility gaps for underserved communities. However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The study explores the comparative advantages and limitations of different blockchain architectures and evaluates emerging optimization techniques such as hybrid consensus algorithms and artificial intelligence-based enhancements. …”
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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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Urban monitoring, evaluation and application of COVID-19 listed vaccine effectiveness: a health code blockchain study by Tao Wang, Hongyan Li, Chaoqun Li, Zheheng Li

“…Based on population mobility, the algorithm principle of urban optimal vaccination strategy is given. …”
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Immune Microenvironment Characterization and Machine Learning-Guided Identification of Diagnostic Biomarkers for Ulcerative Colitis by Zheng Q, Wang L, Zhang Y, Peng J, Hou J, Wang H, Ma Y, Tang P, Li Y, Li H, Chen Y, Li J, Chen Y

“…Immune cell infiltration was assessed via the ImmuCellAI algorithm, while differential expression analysis and WGCNA were performed to identify key immune-related genes. …”
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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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The Impact of AI Software on Financial Transactions by Li Boyang

“…The rapid advancement of artificial intelligence (AI) has profoundly transformed financial trading, enhanced efficiency, accuracy, and customer service while introducing new challenges. This paper explores AI’s applications in quantitative trading, risk forecasting, and intelligent customer interactions, demonstrating its ability to optimize decision-making and reduce operational costs. …”
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Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…A brute-force heuristic optimization approach is applied to determine the hyperparameters that maximize classification accuracy across different M-ELM configurations while avoiding excessive training times. …”
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An efficient detection of Sinkhole attacks using machine learning: Impact on energy and security. by Muhammad Zulkifl Hasan, Zurina Mohd Hanapi, Zuriati Ahmad Zukarnain, Fahrul Hakim Huyop, Muhammad Daniel Hafiz Abdullah

“…This paper introduces SFlexCrypt, an innovative approach tailored to address these security challenges while optimizing energy consumption in WSNs. SFlexCrypt stands out by seamlessly integrating advanced machine learning algorithms to achieve high-precision detection and effective mitigation of sinkhole attacks. …”
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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. …”
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