Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

“…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
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Flexible Reconfiguration for Optimal Operation of Distribution Network Under Renewable Generation and Load Uncertainty by Behzad Esmaeilnezhad, Hossein Amini, Reza Noroozian, Saeid Jalilzadeh

“…Minimizing the operational costs is difficult when there is a high penetration of renewable resources and variability of loads, which introduces uncertainty. …”
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Load frequency control in isolated island city microgrids using deep graph reinforcement learning considering extensive scenarios by Ping He, Xiongwei Huang, Ruobing He, Linkun Yuan

“…Demonstrated effectively in China Southern Grid’s island microgrid setup, LE-LFC emerges as an advanced solution for modern grid variability, offering superior robustness, adaptability, and learning speed, thus enabling flexible and efficient energy system management.…”
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A robust optimization model for allocation-routing problems under uncertain conditions. by Tingting Zhang, Yanqiu Liu

“…Temporary hospital capacity significantly influences the objective function more than general hospitals. As the problem size increases, the robust optimization model performs better than the deterministic model. …”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…This paper proposes a novel hybrid technique, termed Decision Tree with Hill Climbing (DTHC), for efficient spectrum hole detection in CRNs. The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. …”
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Energy‐maximising moment‐based constrained optimal control of ocean wave energy farms by Nicolás Faedo, Giordano Scarciotti, Alessandro Astolfi, John V. Ringwood

“…The authors develop a framework under which the objective function (and system variables) can be mapped to a finite‐dimensional tractable quadratic program (QP), which can be efficiently solved using state‐of‐the‐art solvers. …”
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Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…A five-dimensional objective system—comprising energy efficiency, spatial quality, economic cost, ecological benefits, and cultural expression—was established, alongside the identification and standardization of 29 key variables to construct mapping relationships among objective functions. …”
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Semantic ECG hash similarity graph by Yixian Fang, Shilin Zhang, Yuwei Ren

“…Subsequently, a lightweight linear hash function is utilized to produce a hash representation for the unseen signal. …”
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Structural strength analysis and optimization of converter lug based on Kriging model by HE Guanqiang, LIU Yongjiang, LI Hua, CHEN Liming

“…In this paper, machine learning methods were considered to approximate the functional relationships between design variables and responses. …”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. The minimum manufacturing cost of ship hull shell plates (SHSPs) is the objective function, the rules and requirements for the seam position and the size of a single shell plate are the constraints, and the position and shape of the seam are the design variables. …”
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Neuro-Evolution of Augmenting Topologies for Dynamic Scheduling of Flexible Job Shop Problem by Jian Huang, Yarong Chen, Jabir Mumtaz, Liuyan Zhong

“…This study introduces a neuro-evolution of augmenting topologies (NEAT) algorithm aimed at optimizing the scheduling efficiency in flexible job shops by minimizing both maximum completion and average lag times, taking into account variables like sporadic job arrivals, variable machining durations, tool wear, preventive maintenance, and equipment failures. …”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Ionospheric Correction Based on Ingestion of Global Ionospheric Maps into the NeQuick 2 Model by Xiao Yu, Chengli She, Weimin Zhen, Nava Bruno, Dun Liu, Xinan Yue, Ming Ou, Jisheng Xu

“…The accuracy of TEC prediction can be improved further through performing a four-coefficient function expression of Az versus MODIP. …”
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Torsional Vibration Suppression During Mode Transition Process in a Parallel Hybrid Electric Vehicle Based on Multiple Model Predictive Control by Cheng Huang, Changqing Du, Longjian Li, Xiangyu Gongye, Yifan Zhao

“…At the same time, the influence of the cost function, the weight coefficient, and the predictive time domain on the torsional vibration suppression effect during the mode transition process are explored in the mMPC strategy design, and the solution time is controlled within 10ms, which meet the real-time requirements. …”
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XPolypNet: A U-Net-Based Model for Semantic Segmentation of Gastrointestinal Polyps With Explainable AI by Arjun Kumar Bose Arnob, Muhammad Mostafa Monowar, Md. Abdul Hamid, M. F. Mridha

“…The presented model was evaluated on five benchmark datasets, achieving a Dice Coefficient of 0.8378 and a Mean Intersection over Union (mIoU) of 0.8427. …”
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Specific nature of the integrative (complex) effect of environmental factors on hazelnut cultivars in the Russian humid subtropics by T. D. Besedina, A. P. Boyko, Ts. V. Tutberidze, N. S. Kiseleva

“…The expediency of the crop’s large-scale cultivation calls for measuring the parameters of agroclimatic indicators, ranging in variability, intensity, and duration of their impact. …”
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Automatic detection of optic canal fractures and recognition and segmentation of anatomical structures in the orbital apex based on artificial intelligence by Yu-Lin Li, Yu-Hao Li, Mu-Yang Wei, Guang-Yu Li

“…Timely and accurate diagnosis and treatment are crucial for preserving visual function. However, diagnosing OCF can be challenging for inexperienced clinicians due to atypical OCF changes in imaging studies and variability in optic canal anatomy. …”
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Examining the Factors Affecting the Use of Crypto Assets as Foreign Payment and Investment Instruments: A Quantitative Study by Güneş Yılmaz, Tayfur Süleyman Koç

“…Along with path coefficients, f² and q² effect sizes were also analyzed to examine the interaction between the variables. …”
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Measuring and estimation of suspended sediment variation using sediment rating curve approach in Mereg River by Sohila Aghabeigi Amin, Heidar Mirzaei

“…As a major component of hydrological, geomorphological, and ecological functioning of rivers, suspended sediment has been identified as the leading direct cause of river instabilities. …”
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THE TEMPERATURE DEPENDENCE OF UNSTEADY HEAT CONDUCTION IN SOLIDS by L. M. Ozherelkova, E. S. Savin

“…Both in the case of high and low temperatures, the temperature dependences of the heat capacity and the thermal conductivity coefficient are power-law, which allows us to bring the original heat conduction equation to a form that allows the use of the classical method of variable separation in solving the corresponding boundary value problems for the heat conduction equation. …”
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