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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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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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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A De-Nesting Hybrid Reliability Analysis Method and Its Application in Marine Structure by Chenfeng Li, Tenglong Jin, Zequan Chen, Guanchen Wei

“…Traditional methods for hybrid reliability analysis usually require a nested optimization framework, which will lead to too many calls to the limit state function (LSF) and result in poor computational efficiency. …”
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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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Parameter Sensitivity Analysis and Algorithm Improvement of Optimization Scheduling Model for Cascade Pumping Stations by LIU Xiaolian, LI Zhenrong, WANG Xue-ni, ZHAI Yu, ZHANG Lei-ke, GUO Weiwei, TIAN Yu

“…Additionally, a Tent boundary mapping strategy was employed to regenerate the boundary value, resulting in improved the optimization efficiency of RUN. Six benchmark functions, including unimodal, multimodal and fixed dimension, were used to verify the performance and improvement strategies of TRUN. …”
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Deletion of genes linked to the C1-fixing gene cluster affects growth, by-products, and proteome of Clostridium autoethanogenum by Ugochi Jennifer Nwaokorie, Kristina Reinmets, Lorena Azevedo de Lima, Pratik Rajendra Pawar, Kurshedaktar Majibullah Shaikh, Audrey Harris, Michael Köpke, Kaspar Valgepea

“…However, our understanding of the functionalities of the genes involved in the C1-fixing gene cluster and its closely-linked genes is incomplete. …”
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Reconfiguration of dynamic brain networks in heart failure with preserved ejection fraction: Linking neurovascular coupling and cardiac dysfunction by Xiulin Liang, Qinghua Zhang, Chuanlong Zhang, Jingjing Liu, Pengcheng Sang, Qing Mao, Lei Wang

“…Results: (1) Static network topology properties exhibited significantly decreased local network efficiency among patients with HFpEF. The connectivity strength and information processing efficiency were diminished in the left parahippocampal gyrus, left cingulate gyrus, and right insular gyrus brain regions, and improved in the left thalamus, right fusiform gyrus, and right precuneus regions. (2) Dynamic network topology properties of patients with HFpEF showed decreased variability in critical nodes and brain subregions (e.g., the superior frontal gyrus, left amygdala, and left fusiform gyrus) and compensatory increases in the variability of specific regions (e.g., right insular gyrus, right postcentral gyrus, and right temporal gyrus). (3) In HFpEF, the static and dynamic functional brain network topology properties of the fusiform gyrus, cingulate gyrus, superior temporal gyrus, precuneus, parahippocampal gyrus, insular gyrus, and amygdala regions were significantly correlated with cardiac structural and functional indices, such as LVDd, LVMI, and E/e′ ratio. …”
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IRAQ'S AGRICULTURAL ECONOMY AND THE REALITY OF THE VARIABLRS AND THE RESULTS OBJECTIVE CURRICULUM AND QUANTITATIVE ANALYSIS FOR THE PERIOD (1990-2011) by Salim Al-Nuaimy, Mahasen. M Al-Jeboury

“…The research aims to formulate sober policies and practical actions contribute to adjust the course of the agricultural sector and to achieve its goals, which will make it easier to raise production and productivity, Variables of agricultural sector were agricultural work, capital accumulation agricultural, technical mechanism, technical chemical, agricultural loans, agricultural export, import of agricultural, national income, domestic consumption, the cultivatedareas, that have been expressed as (policies of productivity and investment, marketing and price) where its impact was deare on the growth of the agricultural sector and overall productivity during (1990-2010) and the development process and increase production and productivity in the agricultural sector associated with economic, social and institutional multiple and overlapping factors that effects the forms and varying proportions in its impact on agricultural output, which had been measured under function producing an aggregate of variables agricultural policy and its contribution to productivity growth as well as measuring productivity elements total (TFP) by using index (Malmaquist) depending on the (DEAP). …”
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Quality control of DEMs using check surfaces by Francisco Javier Ariza-López, José Rodríguez-Avi

“…Using the Kolmogorov–Smirnov statistic, the observed distribution functions of the results for different sample sizes (20, 50, 100) and different patch sizes (3 × 3, 5 × 5, 9 × 9, 11 × 11, 15 × 15, 19 × 19) and for a sample of points are compared against the true population distribution function. …”
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Neuroscience-informed nomogram model for early prediction of cognitive impairment in Parkinson's disease by Sudharshan Putha, Swaroop Reddy Gayam, Bhavani Prasad Kasaraneni, Krishna Kanth Kondapaka, Sateesh Kumar Nallamala, Praveen Thuniki

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to identify highly correlated clinical variables influencing cognitive function. Subsequently, these variables were integrated into a visualized nomogram model to facilitate early prediction of cognitive impairment (CI) risk. …”
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Path model explaining the association between fear of falling and health-related quality of life in (pre-)frail older adults by Tjard Sattler, Sophie Gottschalk, Hans-Helmut König, Tobias Braun, Gisela Büchele, Michael Denkinger, Tim Fleiner, Corinna Nerz, Kilian Rapp, Martina Schäufele, Christian Werner, Judith Dams

“…Unlike previous studies that examined only few mediating variables, this study aimed to develop a more comprehensive path model explaining the association between FoF and HrQoL. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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On the Nonlinear Forced Vibration of the Magnetostrictive Laminated Beam in a Complex Environment by Nicolae Herisanu, Bogdan Marinca, Vasile Marinca

“…The nonlinear differential equations were studied using an original, explicit, and very efficient technique, namely the optimal auxiliary functions method (OAFM). …”
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Characterization and treatment monitoring of ureagenesis disorders using stable isotopes by Gabriella Allegri, Martin Poms, Nadia Zürcher, Véronique Rüfenacht, Nicole Rimann, Déborah Mathis, Beat Thöny, Matthias Gautschi, Ralf A. Husain, Daniela Karall, Karolina Orchel-Szastak, Francesco Porta, Dominique Roland, Barbara Siri, Carlo Dionisi-Vici, René Santer, Johannes Häberle

“…Thus, the method proved to be safe and efficient to monitor UCD patients of variable severity pre- and post-therapy, being suitable as physiological endpoint for development of therapies.…”
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Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm by Vinoth Viswanathan, Sathiyamurthy Subbarayan, Ananthi Narayanaswamy, Devi Panneerselvam, Prabhakaran Jayasankar

“…A triangular membership function was employed to define all these variables. …”
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Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking by Jürgen Soom, Isabel Boavida, Renan Leite, Maria João Costa, Gert Toming, Mairo Leier, Jeffrey A. Tuhtan

“…Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under highly variable environmental conditions, which affect the ability to detect and assess fish size. …”
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Safety Prediction Using Vehicle Safety Evaluation Model Passing on Long-Span Bridge with Fully Connected Neural Network by Yang Yang, Lin Yang, Bo Wu, Gang Yao, Hang Li, Soltys Robert

“…Many research studies have been done to find convenience and efficiency measures. A vehicle safety evaluation model passing on a long-span bridge is presented in this paper based on fully connected neural network (FCN). …”
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Multiple metabolic requirements for size homeostasis and initiation of division in Saccharomyces cerevisiae by Shivatheja Soma, Kailu Yang, Maria I. Morales, Michael Polymenis

“…Furthermore, we show that adenylate kinase, encoded by ADK1, is a significant determinant of the efficiency of size control mechanisms. Finally, our data argue strongly that the cell size at division is not necessarily a function of the rate cells increase in size in the G1 phase of the cell cycle. …”
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