Creating a Newer and Improved Procedural Content Generation (PCG) Algorithm with Minimal Human Intervention for Computer Gaming Development by Lazaros Lazaridis, George F. Fragulis

“…Procedural content generation (PCG) algorithms have become increasingly vital in video games developed by small studios due to their ability to save time while creating diverse and engaging environments, significantly enhancing replayability by ensuring that each gameplay experience is distinct. …”
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Applying blood-derived epigenetic algorithms to saliva: cross-tissue similarity of DNA-methylation indices of aging, physiology, and cognition by Sepideh Zarandooz, Laurel Raffington

“…Abstract Background Epigenetic algorithms of aging, health, and cognition, based on DNA-methylation (DNAm) patterns, are prominent tools for measuring biological age and have been linked to age-related diseases, cognitive decline, and mortality. …”
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SSM-Net: Enhancing Compressed Sensing Image Reconstruction with Mamba Architecture and Fast Iterative Shrinking Threshold Algorithm Optimization by Xianwei Gao, Bi Chen, Xiang Yao, Ye Yuan

“…Compressed sensing (CS) is a powerful technique that can reduce data size while maintaining high reconstruction quality, which makes it particularly valuable in high-dimensional image applications. …”
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Optimal design of hollow conductor for high‐speed synchronous motor exploiting adaptive‐sampling radial basis function algorithm by Ruiye Li, Peng Cheng, Hai Lan

“…To address this, the paper proposes a multi‐objective optimisation method based on adaptive sampling radial basis function (ASRBF). The ASRBF algorithm adaptively adds sample points by estimating expected improvements at prediction points, enabling the surrogate model to rapidly approximate the global optimum while significantly reducing function evaluations. …”
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Unraveling Meteorological Dynamics: A Two-Level Clustering Algorithm for Time Series Pattern Recognition with Missing Data Handling by Ekaterini Skamnia, Eleni S. Bekri, Polychronis Economou

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A Novel Color Difference-Based Method for Palette Extraction and Evaluation Using Images of Birds by Melike Bektas Kosesoy, Seckin Yilmaz

“…In the literature, the success of color palettes is usually evaluated through questionnaires, while measurements are made without relying on numerical metrics. …”
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Hybridization and Optimization of Bio and Nature-Inspired Metaheuristic Techniques of Beacon Nodes Scheduling for Localization in Underwater IoT Networks by Umar Draz, Tariq Ali, Sana Yasin, Muhammad Hasanain Chaudary, Muhammad Ayaz, El-Hadi M. Aggoune, Isha Yasin

“…The hybridization techniques such as Elephant Herding Optimization (EHO) with Genetic Algorithm (GA), Firefly Algorithm (FA), Levy Firefly Algorithm (LFA), Bacterial Foraging Algorithm (BFA), and Binary Particle Swarm Optimization (BPSO) are used for optimization. …”
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Enhanced Heart Disease Classification Using Dual Attention Mechanisms and 3D-Echo Fusion Algorithm in Echocardiogram Videos by S Deepika, N. Jaisankar

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A Subimage Autofocus Bistatic Ground Cartesian Back-Projection Algorithm for Passive Bistatic SAR Based on GEO Satellites by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Xueming Song

“…SIAF-BGCBP reduces phase estimation’s complexity by 90% through subimage pixel density optimization while maintaining estimation accuracy. Further enhancement of SIAF-BGCBP via geometric inversion would enable the precise compensation of space-variant phase errors while remaining efficient. …”
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Grading of Traffic Interruptions in Highways to Tibet Based on the Entropy Weight-TOPSIS Method and Fuzzy C-Means Clustering Algorithm by Jian Tian, Zhiqiang Li, Suyan Zhuang, Jianfeng Xi, Min Li

“…The work proposed a model that integrated the entropy weight-TOPSIS method with the fuzzy C-means clustering algorithm to discuss the causes and characteristics of traffic interruptions on the four main highways to Tibet. …”
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CTL-YOLO: A Surface Defect Detection Algorithm for Lightweight Hot-Rolled Strip Steel Under Complex Backgrounds by Wenzheng Sun, Na Meng, Longfa Chen, Sen Yang, Yuguo Li, Shuo Tian

“…Additionally, it exhibits strong generalization capabilities on the public dataset GC10-DET. The algorithm can effectively improve detection accuracy while maintaining a lightweight design.…”
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Design and Implementation of Low-Complexity Multiple Symbol Detection Algorithm Using Hybrid Stochastic Computing in Aircraft Wireless Communications by Yukai Liu, Rongke Liu, Kairui Tian, Zheng Lu, Ling Zhao

“…Experimental results show that, compared to an 8-bit quantization MSD implementation, our proposed hybrid SC-based MSD architecture achieves a comparable bit error rate while reducing the hardware resources to 69%, 45%, and 36% of those required for the three-, five-, and seven-symbol MSD algorithms, respectively.…”
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Assessment of medication-related liver and kidney impairment in admitted patients in Depok, Indonesia: an observational study employing the Naranjo algorithm by Nadia Farhanah Syafhan, Ghea Shafa Aldora, Shinta Kamila

“…This study aimed to evaluate the prevalence of medication-related liver and kidney impairment among hospitalized patients, while also identifying the specific medication categories implicated. …”
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A Low Complexity Algorithm for 3D-HEVC Depth Map Intra Coding Based on MAD and ResNet by Erlin Tian, Jiabao Zhang, Qiuwen Zhang

“…To mitigate this challenge, the present paper proposes a deep learning-based encoding algorithm designed to replace the intricate coding unit (CU) partitioning process utilized in HTM. …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Convolutional Neural Networks are used to extract spatial features from agricultural data, while Long Short-Term Memory networks processed time series data. …”
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FECI-RTDETR a Lightweight Unmanned Aerial Vehicle Infrared Small Target Detector Algorithm Based on RT-DETR by Renzheng Xue, Shijie Hua, Haiqiang Xu

“…This paper proposes a lightweight UAV infrared small target detection algorithm, FECI-RTDETR. Initially, we introduce a lightweight RFConv-Block module that enhances spatial feature extraction capabilities while reducing computational redundancy. …”
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Evaluating machine leaning algorithms for accuracy, stability, and among-predictors discriminability in modeling species-richness across ten datasets by Yong Cao, Tyler E. Schartel, David C. Houghton, Jared Ross, Dana M. Infante

“…Global biodiversity is experiencing substantial declines, and mitigating this crisis requires analytical approaches that can accurately predict biodiversity in relation to natural conditions and human-induced stressors. While numerous machine learning (ML) algorithms for regression are available for such analyses, synthesizing outcomes across studies is challenging due to: (1) reliance on single datasets, limiting generalizability; (2) varying modeling processes; (3) inconsistent performance criteria; and (4) limited consideration of model stability and among-predictor discriminability.We addressed these issues by applying five ML algorithms—Random Forest (RF), Boosted Regression Tree (BRT), Extreme Gradient Boosting (XGB), Conditional Inference Forest (CIF), and Lasso—to ten large datasets on freshwater fish, mussels, and caddisflies. …”
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Collaborative Optimization on Both Weight and Fatigue Life of Fifth Wheel Based on Hybrid Random Forest with Improved BP Algorithm by Huan Xue, Chang Guo, Xiaojian Peng, Saiqing Xu, Kaixian Li, Jianwen Li

“…We proposed a prediction model combining a random forest algorithm with an optimized back propagation (BP) neural network. …”
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Collaborative Search Algorithm for Multi-UAVs Under Interference Conditions: A Multi-Agent Deep Reinforcement Learning Approach by Wei Wang, Yong Chen, Yu Zhang, Yong Chen, Yihang Du

“…The framework exhibits strong resilience to communication disruptions while maintaining stable search performance, validating its practical applicability in real-world interference scenarios.…”
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Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms. by Ayşenur Eser, Sinem Burcu Erdoğan

“…Three class classification performances of all algorithms were above 90% in terms of accuracy, sensitivity, specificity, F-1 score and precision metrics while two class accuracy performances of all algorithms were above 93% in terms of each performance metric. …”
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