Prototype Mobile Vision System for Automatic Length Estimation of Olive Flounder (<i>Paralichthys olivaceus</i>) in Indoor Aquaculture by Inyeong Kwon, Hang Thi Phuong Nguyen, Paththige Waruni Prasadini Fernando, Hieyong Jeong, Sungju Jung, Taeho Kim

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Leveraging the Power of Hybrid and Standalone Machine Learning for Enhanced FRP-Confined Concrete Columns Strength Prediction by Mehdi Ghasri, Mohammad Ghasemi, Abdolhamid Salarnia

“…The performance of these ML models was enhanced by optimizing them using the Marine Predators Algorithm (MPA). …”
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METAHEURISTIC-DRIVEN MULTI OBJECTIVE FIR FILTER DESIGN FOR ECG DENOISING by Mehmet Fatih Karakaş, Fatma Latifoğlu

“…The research employs advanced metaheuristic algorithms, including Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Genetic Algorithm (GA), Black Widow Optimization (BWO), Chaos Game Optimization (CGO), Harmony Search (HS), Squirrel Search Algorithm (SSA), and Atomic Orbital Search (AOS) to optimize multiple filter design parameters jointly. …”
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The Significant Effects of Threshold Selection for Advancing Nitrogen Use Efficiency in Whole Genome of Bread Wheat by Mohammad Bahman Sadeqi, Agim Ballvora, Said Dadshani, Md. Nurealam Siddiqui, Mohammad Kamruzzaman, Ahossi Patrice Koua, Jens Léon

“…By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.…”
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Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…Each target domain slice can deploy this estimator to predict its QoS and optimize slice resource allocation using the IDLA algorithm. …”
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A Two-Stage Robust Optimization Strategy for Long-Term Energy Storage and Cascaded Utilization of Cold and Heat Energy in Peer-to-Peer Electricity Energy Trading by Yun Chen, Yunhao Zhao, Xinghao Zhang, Ying Wang, Rongyao Mi, Junxiao Song, Zhiguo Hao, Chuanbo Xu

“…The strategy includes a UIES model with a photovoltaic (PV)–green roof, hydrogen storage, and cascading cold/heat energy subsystems. The first stage optimizes energy trading volume to maximize social welfare, while the second stage maximizes operational profit, considering uncertainties in PV generation and power prices. …”
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A dual layer secure and energy-efficient model for border surveillance using sea lion inspired strategy in wireless sensor networks by Jayachandran J, Vimaladevi K

“…This paper presents a Dual Layer Sea Lion Optimization algorithm (DL-SLnOA) model, a bio-inspired, clustering and routing that focuses on energy efficiency and security to enhance performance under challenging conditions. …”
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An Evolutionary Toolchain for Morphological Filter Mapping on Many-Core Architectures by Emerson C. Pedrino, Denis P. Lima, Igor F. Gallon, Valentin O. Roda, Naijia Liu, Gianluca Tempesti

“…The need to find a balance between performance and communication is a representative example of the general problem of mapping optimizations. The approach presented in this paper explores a two-phase design-time optimization toolchain based on evolutionary algorithms: a front-end single-objective algorithm decomposes a MM filter using smaller operators, while a back-end multi-objective (fault-tolerance, energy, and communication) algorithm searches for optimal mappings of the filter on a specific many-core system, taking into account the architectural parameters of the hardware. …”
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Predominance Preferential Selection for Minimizing Surplus Parts in the Selective Assembly of a Flow Production System by Kanghyeon Shin, Hyobin Son, Kyohong Jin

“…This paper presents the Predominance Preferential Selection (PPS) algorithm, an advanced approach to optimizing selective assembly in flow production systems. …”
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A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices by Hui Xiang, Xiao Liao, Yanjie Wang, Hui Cao, Xianjing Zhong, Qingshu Guan, Weiyun Ru

“…A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. …”
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Transformer based models with hierarchical graph representations for enhanced climate forecasting by T. Bhargava Ramu, Raviteja Kocherla, G. N. V. G. Sirisha, V. Lakshmi Chetana, P. Vidya Sagar, R. Balamurali, Nanditha Boddu

“…The model integrates three key components: Spatial-Temporal Fusion Module (STFM) to capture spatiotemporal dependencies, Hierarchical Graph Representation and Analysis (HGRA) to model structured climate relationships, and Dynamic Temporal Graph Attention Mechanism (DT-GAM) to enhance temporal feature extraction. To improve computational efficiency and feature selection, we introduce a hybrid optimization approach (HWOA-TTA) that combines the Whale Optimization Algorithm (WOA) and Tiki-Taka Algorithm (TTA). …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Finally, machine learning algorithms such as random forest and XGBoost are used to predict vehicle speed based on onboard data and weather sensor data. …”
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Bayesian Time-Domain Ringing Suppression Approach in Impulse Ultrawideband Synthetic Aperture Radar by Xinhao Xu, Wenjie Li, Haibo Tang, Longyong Chen, Chengwei Zhang, Tao Jiang, Jie Liu, Xingdong Liang

“…Building on this analysis, we propose a Bayesian ringing suppression algorithm based on sparse optimization. The method effectively enhances imaging quality while balancing the trade-off between ringing suppression and image fidelity. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…However, we challenged this assumption by initiating the inverse problem at different locations in the parameter space using a robust variant of a gradient-based method, which ultimately resulted in a better fit than global methods.We tested four different optimization algorithms available in the PEST and PEST++ suites. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Construction and Application Analysis of an Intelligent Distribution Network Identification System Based on Deep Neural Networks by Yu Ma

“…In addition, the Cross-Validation Grid Search Algorithm (GSA) was used to optimize the hyperparameters to ensure that the model can achieve the optimal performance on different data sets. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…From the results, it produces two metrics, TKN and coliform, that are higher than WHO guidelines while maintaining the optimal level of DO throughout the duration of the study. …”
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An Innovative Priority-Aware Mission Planning Framework for an Agile Earth Observation Satellite by Guangtong Zhu, Zixuan Zheng, Chenhao Ouyang, Yufei Guo, Pengyu Sun

“…The proposed approach effectively maintains satellite maneuver constraints while achieving significant improvements in priority-based target acquisition and computational efficiency. …”
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